AI_Data_Analysis.json

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        "data": {
          "description": "Create a prompt template with dynamic variables.",
          "display_name": "Prompt",
          "id": "Prompt-qO6pf",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {
              "template": [
                "sample_data",
                "previous_response"
              ]
            },
            "description": "Create a prompt template with dynamic variables.",
            "display_name": "InsightPrompt",
            "documentation": "",
            "edited": false,
            "error": null,
            "field_order": [
              "template"
            ],
            "frozen": false,
            "full_path": null,
            "icon": "prompts",
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            "is_input": null,
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            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "name": "",
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Prompt Message",
                "hidden": false,
                "method": "build_prompt",
                "name": "prompt",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "priority": null,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
              },
              "previous_response": {
                "advanced": false,
                "display_name": "previous_response",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "previous_response",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "sample_data": {
                "advanced": false,
                "display_name": "sample_data",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "sample_data",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "template": {
                "_input_type": "PromptInput",
                "advanced": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "",
                "list": false,
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "prompt",
                "value": "You are an expert insight researcher.\n\nSample Data: {sample_data}\nRecommended Machine Learning Model: {previous_response}\n\nUse Tavily Search to investigate the queries and analyze the findings.\nFocus on industry case studies and marketing strategy with sample data.\n\nSteps:\n1. Search using provided queries\n2. Analyze search results\n3. Verify source credibility\n4. Extract key findings\n\nFormat findings as:\n\nSEARCH RESULTS:\n[Key findings from searches]\n\nSOURCE ANALYSIS:\n[Credibility assessment]\n\nMAIN INSIGHTS:\n[Critical discoveries]\n\nEVIDENCE QUALITY:\n[Evaluation of findings]"
              },
              "tool_placeholder": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tool Placeholder",
                "dynamic": false,
                "info": "A placeholder input for tool mode.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "tool_placeholder",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "type": "Prompt"
        },
        "dragging": false,
        "height": 347,
        "id": "Prompt-qO6pf",
        "measured": {
          "height": 347,
          "width": 320
        },
        "position": {
          "x": 3075.492617540369,
          "y": -1383.3803349578236
        },
        "positionAbsolute": {
          "x": 1803.2315476328304,
          "y": 839.0423490089254
        },
        "selected": false,
        "type": "genericNode",
        "width": 320
      },
      {
        "data": {
          "id": "ChatInput-iZffQ",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "inputs",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Get chat inputs from the Playground.",
            "display_name": "Chat Input",
            "documentation": "",
            "edited": false,
            "field_order": [
              "input_value",
              "should_store_message",
              "sender",
              "sender_name",
              "session_id",
              "files",
              "background_color",
              "chat_icon",
              "text_color"
            ],
            "frozen": false,
            "icon": "MessagesSquare",
            "key": "ChatInput",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "hidden": false,
                "method": "message_response",
                "name": "message",
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "template": {
              "_type": "Component",
              "background_color": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Background Color",
                "dynamic": false,
                "info": "The background color of the icon.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "background_color",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "chat_icon": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Icon",
                "dynamic": false,
                "info": "The icon of the message.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "chat_icon",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.data.utils import IMG_FILE_TYPES, TEXT_FILE_TYPES\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.io import (\n    DropdownInput,\n    FileInput,\n    MessageTextInput,\n    MultilineInput,\n    Output,\n)\nfrom langflow.schema.message import Message\nfrom langflow.utils.constants import (\n    MESSAGE_SENDER_AI,\n    MESSAGE_SENDER_NAME_USER,\n    MESSAGE_SENDER_USER,\n)\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Get chat inputs from the Playground.\"\n    icon = \"MessagesSquare\"\n    name = \"ChatInput\"\n    minimized = True\n\n    inputs = [\n        MultilineInput(\n            name=\"input_value\",\n            display_name=\"Text\",\n            value=\"\",\n            info=\"Message to be passed as input.\",\n            input_types=[],\n        ),\n        BoolInput(\n            name=\"should_store_message\",\n            display_name=\"Store Messages\",\n            info=\"Store the message in the history.\",\n            value=True,\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n            value=MESSAGE_SENDER_USER,\n            info=\"Type of sender.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Name of the sender.\",\n            value=MESSAGE_SENDER_NAME_USER,\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        FileInput(\n            name=\"files\",\n            display_name=\"Files\",\n            file_types=TEXT_FILE_TYPES + IMG_FILE_TYPES,\n            info=\"Files to be sent with the message.\",\n            advanced=True,\n            is_list=True,\n            temp_file=True,\n        ),\n        MessageTextInput(\n            name=\"background_color\",\n            display_name=\"Background Color\",\n            info=\"The background color of the icon.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"chat_icon\",\n            display_name=\"Icon\",\n            info=\"The icon of the message.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"text_color\",\n            display_name=\"Text Color\",\n            info=\"The text color of the name\",\n            advanced=True,\n        ),\n    ]\n    outputs = [\n        Output(display_name=\"Message\", name=\"message\", method=\"message_response\"),\n    ]\n\n    async def message_response(self) -> Message:\n        background_color = self.background_color\n        text_color = self.text_color\n        icon = self.chat_icon\n\n        message = await Message.create(\n            text=self.input_value,\n            sender=self.sender,\n            sender_name=self.sender_name,\n            session_id=self.session_id,\n            files=self.files,\n            properties={\n                \"background_color\": background_color,\n                \"text_color\": text_color,\n                \"icon\": icon,\n            },\n        )\n        if self.session_id and isinstance(message, Message) and self.should_store_message:\n            stored_message = await self.send_message(\n                message,\n            )\n            self.message.value = stored_message\n            message = stored_message\n\n        self.status = message\n        return message\n"
              },
              "files": {
                "_input_type": "FileInput",
                "advanced": true,
                "display_name": "Files",
                "dynamic": false,
                "fileTypes": [
                  "txt",
                  "md",
                  "mdx",
                  "csv",
                  "json",
                  "yaml",
                  "yml",
                  "xml",
                  "html",
                  "htm",
                  "pdf",
                  "docx",
                  "py",
                  "sh",
                  "sql",
                  "js",
                  "ts",
                  "tsx",
                  "jpg",
                  "jpeg",
                  "png",
                  "bmp",
                  "image"
                ],
                "file_path": "",
                "info": "Files to be sent with the message.",
                "list": true,
                "name": "files",
                "placeholder": "",
                "required": false,
                "show": true,
                "temp_file": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "file",
                "value": ""
              },
              "input_value": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "display_name": "Text",
                "dynamic": false,
                "info": "Message to be passed as input.",
                "input_types": [],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Research the effectiveness of different prompt engineering techniques in controlling AI hallucinations, with focus on real-world applications and empirical studies."
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Type of sender.",
                "name": "sender",
                "options": [
                  "Machine",
                  "User"
                ],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "User"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Name of the sender.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "User"
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "should_store_message": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Store Messages",
                "dynamic": false,
                "info": "Store the message in the history.",
                "list": false,
                "name": "should_store_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "text_color": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Text Color",
                "dynamic": false,
                "info": "The text color of the name",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "text_color",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            }
          },
          "type": "ChatInput"
        },
        "dragging": false,
        "height": 234,
        "id": "ChatInput-iZffQ",
        "measured": {
          "height": 234,
          "width": 320
        },
        "position": {
          "x": 609.1602019398908,
          "y": -1046.4200931736812
        },
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          "x": 756.0075981758582,
          "y": 756.7423476254241
        },
        "selected": false,
        "type": "genericNode",
        "width": 320
      },
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          "description": "Create a prompt template with dynamic variables.",
          "display_name": "Prompt",
          "id": "Prompt-DbV1b",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {
              "template": [
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              ]
            },
            "description": "Create a prompt template with dynamic variables.",
            "display_name": "Prompt",
            "documentation": "",
            "edited": false,
            "error": null,
            "field_order": [
              "template"
            ],
            "frozen": false,
            "full_path": null,
            "icon": "prompts",
            "is_composition": null,
            "is_input": null,
            "is_output": null,
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "name": "",
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Prompt Message",
                "hidden": false,
                "method": "build_prompt",
                "name": "prompt",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
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              }
            ],
            "pinned": false,
            "priority": null,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
              },
              "models": {
                "advanced": false,
                "display_name": "models",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "models",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "sample_code": {
                "advanced": false,
                "display_name": "sample_code",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "sample_code",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "search_results": {
                "advanced": false,
                "display_name": "search_results",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "search_results",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "template": {
                "_input_type": "PromptInput",
                "advanced": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "",
                "list": false,
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "prompt",
                "value": "RESEARCH FINDINGS: {search_results}\nSample Code: {sample_code}\nRecommended Machine Learning Models: {models}\n"
              },
              "tool_placeholder": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tool Placeholder",
                "dynamic": false,
                "info": "A placeholder input for tool mode.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "tool_placeholder",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "type": "Prompt"
        },
        "dragging": false,
        "height": 433,
        "id": "Prompt-DbV1b",
        "measured": {
          "height": 433,
          "width": 320
        },
        "position": {
          "x": 4225.01941556787,
          "y": -757.9025971045164
        },
        "positionAbsolute": {
          "x": 2504.138359606453,
          "y": 434.061360540584
        },
        "selected": false,
        "type": "genericNode",
        "width": 320
      },
      {
        "data": {
          "description": "Create a prompt template with dynamic variables.",
          "display_name": "Prompt",
          "id": "Prompt-rqNod",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {
              "template": []
            },
            "description": "Create a prompt template with dynamic variables.",
            "display_name": "Prompt",
            "documentation": "",
            "edited": false,
            "error": null,
            "field_order": [
              "template"
            ],
            "frozen": false,
            "full_path": null,
            "icon": "prompts",
            "is_composition": null,
            "is_input": null,
            "is_output": null,
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "name": "",
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Prompt Message",
                "hidden": false,
                "method": "build_prompt",
                "name": "prompt",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "priority": null,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
              },
              "template": {
                "_input_type": "PromptInput",
                "advanced": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "",
                "list": false,
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "prompt",
                "value": "You are a reporter expert.\n\nCreate a comprehensive synthesis and report of our findings and include sample python code and recommended machine learning model from input.\n\nFormat your response as:\n\nEXECUTIVE SUMMARY:\n[Key findings and implications]\n\nMETHODOLOGY:\n- Search Strategy Used\n- Sources Analyzed\n- Quality Assessment\n\nFINDINGS & ANALYSIS:\n[Detailed discussion of discoveries]\n\nCONCLUSIONS:\n[Main takeaways and insights]\n\nFUTURE DIRECTIONS:\n[Suggested next steps]\n\nSAMPLE CODE:\n[sample code]\n\nRecommended Machine Learning Models: [models]\n\nIMPORTANT: For each major point or finding, include the relevant source link in square brackets at the end of the sentence or paragraph. For example: \"Harvard has developed a solid-state battery that charges in minutes. [Source: https://example.com/article]\"\n\n"
              },
              "tool_placeholder": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tool Placeholder",
                "dynamic": false,
                "info": "A placeholder input for tool mode.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "name": "tool_placeholder",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "type": "Prompt"
        },
        "dragging": false,
        "height": 260,
        "id": "Prompt-rqNod",
        "measured": {
          "height": 260,
          "width": 320
        },
        "position": {
          "x": 4174.116116770179,
          "y": -1287.4308592959974
        },
        "positionAbsolute": {
          "x": 2498.9482347755306,
          "y": 889.7491088138673
        },
        "selected": false,
        "type": "genericNode",
        "width": 320
      },
      {
        "data": {
          "id": "TavilySearchComponent-weKTf",
          "node": {
            "base_classes": [
              "Data",
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {},
            "description": "**Tavily Search** is a search engine optimized for LLMs and RAG,         aimed at efficient, quick, and persistent search results.",
            "display_name": "Tavily AI Search",
            "documentation": "",
            "edited": false,
            "field_order": [
              "api_key",
              "query",
              "search_depth",
              "topic",
              "time_range",
              "max_results",
              "include_images",
              "include_answer"
            ],
            "frozen": false,
            "icon": "TavilyIcon",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Toolset",
                "hidden": null,
                "method": "to_toolkit",
                "name": "component_as_tool",
                "options": null,
                "required_inputs": null,
                "selected": "Tool",
                "tool_mode": true,
                "types": [
                  "Tool"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "template": {
              "_type": "Component",
              "api_key": {
                "_input_type": "SecretStrInput",
                "advanced": false,
                "display_name": "Tavily API Key",
                "dynamic": false,
                "info": "Your Tavily API Key.",
                "input_types": [],
                "load_from_db": false,
                "name": "api_key",
                "password": true,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "chunks_per_source": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Chunks Per Source",
                "dynamic": false,
                "info": "The number of content chunks to retrieve from each source (1-3). Only works with advanced search.",
                "list": false,
                "list_add_label": "Add More",
                "name": "chunks_per_source",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 3
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import httpx\nfrom loguru import logger\n\nfrom langflow.custom import Component\nfrom langflow.helpers.data import data_to_text\nfrom langflow.io import BoolInput, DropdownInput, IntInput, MessageTextInput, Output, SecretStrInput\nfrom langflow.schema import Data\nfrom langflow.schema.message import Message\n\n\nclass TavilySearchComponent(Component):\n    display_name = \"Tavily Search API\"\n    description = \"\"\"**Tavily Search** is a search engine optimized for LLMs and RAG, \\\n        aimed at efficient, quick, and persistent search results.\"\"\"\n    icon = \"TavilyIcon\"\n\n    inputs = [\n        SecretStrInput(\n            name=\"api_key\",\n            display_name=\"Tavily API Key\",\n            required=True,\n            info=\"Your Tavily API Key.\",\n        ),\n        MessageTextInput(\n            name=\"query\",\n            display_name=\"Search Query\",\n            info=\"The search query you want to execute with Tavily.\",\n            tool_mode=True,\n        ),\n        DropdownInput(\n            name=\"search_depth\",\n            display_name=\"Search Depth\",\n            info=\"The depth of the search.\",\n            options=[\"basic\", \"advanced\"],\n            value=\"advanced\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"chunks_per_source\",\n            display_name=\"Chunks Per Source\",\n            info=(\"The number of content chunks to retrieve from each source (1-3). Only works with advanced search.\"),\n            value=3,\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"topic\",\n            display_name=\"Search Topic\",\n            info=\"The category of the search.\",\n            options=[\"general\", \"news\"],\n            value=\"general\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"days\",\n            display_name=\"Days\",\n            info=\"Number of days back from current date to include. Only available with news topic.\",\n            value=7,\n            advanced=True,\n        ),\n        IntInput(\n            name=\"max_results\",\n            display_name=\"Max Results\",\n            info=\"The maximum number of search results to return.\",\n            value=5,\n            advanced=True,\n        ),\n        BoolInput(\n            name=\"include_answer\",\n            display_name=\"Include Answer\",\n            info=\"Include a short answer to original query.\",\n            value=True,\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"time_range\",\n            display_name=\"Time Range\",\n            info=\"The time range back from the current date to filter results.\",\n            options=[\"day\", \"week\", \"month\", \"year\"],\n            value=None,  # Default to None to make it optional\n            advanced=True,\n        ),\n        BoolInput(\n            name=\"include_images\",\n            display_name=\"Include Images\",\n            info=\"Include a list of query-related images in the response.\",\n            value=True,\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"include_domains\",\n            display_name=\"Include Domains\",\n            info=\"Comma-separated list of domains to include in the search results.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"exclude_domains\",\n            display_name=\"Exclude Domains\",\n            info=\"Comma-separated list of domains to exclude from the search results.\",\n            advanced=True,\n        ),\n        BoolInput(\n            name=\"include_raw_content\",\n            display_name=\"Include Raw Content\",\n            info=\"Include the cleaned and parsed HTML content of each search result.\",\n            value=False,\n            advanced=True,\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Data\", name=\"data\", method=\"fetch_content\"),\n        Output(display_name=\"Text\", name=\"text\", method=\"fetch_content_text\"),\n    ]\n\n    def fetch_content(self) -> list[Data]:\n        try:\n            # Only process domains if they're provided\n            include_domains = None\n            exclude_domains = None\n\n            if self.include_domains:\n                include_domains = [domain.strip() for domain in self.include_domains.split(\",\") if domain.strip()]\n\n            if self.exclude_domains:\n                exclude_domains = [domain.strip() for domain in self.exclude_domains.split(\",\") if domain.strip()]\n\n            url = \"https://api.tavily.com/search\"\n            headers = {\n                \"content-type\": \"application/json\",\n                \"accept\": \"application/json\",\n            }\n\n            payload = {\n                \"api_key\": self.api_key,\n                \"query\": self.query,\n                \"search_depth\": self.search_depth,\n                \"topic\": self.topic,\n                \"max_results\": self.max_results,\n                \"include_images\": self.include_images,\n                \"include_answer\": self.include_answer,\n                \"include_raw_content\": self.include_raw_content,\n                \"days\": self.days,\n                \"time_range\": self.time_range,\n            }\n\n            # Only add domains to payload if they exist and have values\n            if include_domains:\n                payload[\"include_domains\"] = include_domains\n            if exclude_domains:\n                payload[\"exclude_domains\"] = exclude_domains\n\n            # Add conditional parameters only if they should be included\n            if self.search_depth == \"advanced\" and self.chunks_per_source:\n                payload[\"chunks_per_source\"] = self.chunks_per_source\n\n            if self.topic == \"news\" and self.days:\n                payload[\"days\"] = int(self.days)  # Ensure days is an integer\n\n            # Add time_range if it's set\n            if hasattr(self, \"time_range\") and self.time_range:\n                payload[\"time_range\"] = self.time_range\n\n            # Add timeout handling\n            with httpx.Client(timeout=90.0) as client:\n                response = client.post(url, json=payload, headers=headers)\n\n            response.raise_for_status()\n            search_results = response.json()\n\n            data_results = []\n\n            if self.include_answer and search_results.get(\"answer\"):\n                data_results.append(Data(text=search_results[\"answer\"]))\n\n            for result in search_results.get(\"results\", []):\n                content = result.get(\"content\", \"\")\n                result_data = {\n                    \"title\": result.get(\"title\"),\n                    \"url\": result.get(\"url\"),\n                    \"content\": content,\n                    \"score\": result.get(\"score\"),\n                }\n                if self.include_raw_content:\n                    result_data[\"raw_content\"] = result.get(\"raw_content\")\n\n                data_results.append(Data(text=content, data=result_data))\n\n            if self.include_images and search_results.get(\"images\"):\n                data_results.append(Data(text=\"Images found\", data={\"images\": search_results[\"images\"]}))\n\n        except httpx.TimeoutException:\n            error_message = \"Request timed out (90s). Please try again or adjust parameters.\"\n            logger.error(error_message)\n            return [Data(text=error_message, data={\"error\": error_message})]\n        except httpx.HTTPStatusError as exc:\n            error_message = f\"HTTP error occurred: {exc.response.status_code} - {exc.response.text}\"\n            logger.error(error_message)\n            return [Data(text=error_message, data={\"error\": error_message})]\n        except httpx.RequestError as exc:\n            error_message = f\"Request error occurred: {exc}\"\n            logger.error(error_message)\n            return [Data(text=error_message, data={\"error\": error_message})]\n        except ValueError as exc:\n            error_message = f\"Invalid response format: {exc}\"\n            logger.error(error_message)\n            return [Data(text=error_message, data={\"error\": error_message})]\n        else:\n            self.status = data_results\n            return data_results\n\n    def fetch_content_text(self) -> Message:\n        data = self.fetch_content()\n        result_string = data_to_text(\"{text}\", data)\n        self.status = result_string\n        return Message(text=result_string)\n"
              },
              "days": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Days",
                "dynamic": false,
                "info": "Number of days back from current date to include. Only available with news topic.",
                "list": false,
                "list_add_label": "Add More",
                "name": "days",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 7
              },
              "exclude_domains": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Exclude Domains",
                "dynamic": false,
                "info": "Comma-separated list of domains to exclude from the search results.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "exclude_domains",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "include_answer": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Include Answer",
                "dynamic": false,
                "info": "Include a short answer to original query.",
                "list": false,
                "list_add_label": "Add More",
                "name": "include_answer",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "include_domains": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Include Domains",
                "dynamic": false,
                "info": "Comma-separated list of domains to include in the search results.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "include_domains",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "include_images": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Include Images",
                "dynamic": false,
                "info": "Include a list of query-related images in the response.",
                "list": false,
                "list_add_label": "Add More",
                "name": "include_images",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "include_raw_content": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Include Raw Content",
                "dynamic": false,
                "info": "Include the cleaned and parsed HTML content of each search result.",
                "list": false,
                "list_add_label": "Add More",
                "name": "include_raw_content",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "max_results": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Max Results",
                "dynamic": false,
                "info": "The maximum number of search results to return.",
                "list": false,
                "list_add_label": "Add More",
                "name": "max_results",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 5
              },
              "query": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Search Query",
                "dynamic": false,
                "info": "The search query you want to execute with Tavily.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "query",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "search_depth": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Search Depth",
                "dynamic": false,
                "info": "The depth of the search.",
                "name": "search_depth",
                "options": [
                  "basic",
                  "advanced"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "advanced"
              },
              "time_range": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Time Range",
                "dynamic": false,
                "info": "The time range back from the current date to filter results.",
                "name": "time_range",
                "options": [
                  "day",
                  "week",
                  "month",
                  "year"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str"
              },
              "tools_metadata": {
                "_input_type": "ToolsInput",
                "advanced": false,
                "display_name": "Actions",
                "dynamic": false,
                "info": "Modify tool names and descriptions to help agents understand when to use each tool.",
                "is_list": true,
                "list_add_label": "Add More",
                "name": "tools_metadata",
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "tools",
                "value": [
                  {
                    "args": {
                      "query": {
                        "default": "",
                        "description": "The search query you want to execute with Tavily.",
                        "title": "Query",
                        "type": "string"
                      }
                    },
                    "description": "TavilySearchComponent. fetch_content - **Tavily Search** is a search engine optimized for LLMs and RAG,         aimed at efficient, quick, and persistent search results.",
                    "display_description": "TavilySearchComponent. fetch_content - **Tavily Search** is a search engine optimized for LLMs and RAG,         aimed at efficient, quick, and persistent search results.",
                    "display_name": "fetch_content",
                    "name": "fetch_content",
                    "readonly": false,
                    "status": true,
                    "tags": [
                      "fetch_content"
                    ]
                  },
                  {
                    "args": {
                      "query": {
                        "default": "",
                        "description": "The search query you want to execute with Tavily.",
                        "title": "Query",
                        "type": "string"
                      }
                    },
                    "description": "TavilySearchComponent. fetch_content_text - **Tavily Search** is a search engine optimized for LLMs and RAG,         aimed at efficient, quick, and persistent search results.",
                    "display_description": "TavilySearchComponent. fetch_content_text - **Tavily Search** is a search engine optimized for LLMs and RAG,         aimed at efficient, quick, and persistent search results.",
                    "display_name": "fetch_content_text",
                    "name": "fetch_content_text",
                    "readonly": false,
                    "status": true,
                    "tags": [
                      "fetch_content_text"
                    ]
                  }
                ]
              },
              "topic": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Search Topic",
                "dynamic": false,
                "info": "The category of the search.",
                "name": "topic",
                "options": [
                  "general",
                  "news"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "general"
              }
            },
            "tool_mode": true
          },
          "showNode": true,
          "type": "TavilySearchComponent"
        },
        "dragging": false,
        "id": "TavilySearchComponent-weKTf",
        "measured": {
          "height": 350,
          "width": 320
        },
        "position": {
          "x": 3217.159334766486,
          "y": -654.862913060193
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Agent-AH0XX",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "agents",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Define the agent's instructions, then enter a task to complete using tools.",
            "display_name": "InsightAgnet",
            "documentation": "",
            "edited": false,
            "field_order": [
              "agent_llm",
              "max_tokens",
              "model_kwargs",
              "json_mode",
              "model_name",
              "openai_api_base",
              "api_key",
              "temperature",
              "seed",
              "max_retries",
              "timeout",
              "system_prompt",
              "tools",
              "input_value",
              "handle_parsing_errors",
              "verbose",
              "max_iterations",
              "agent_description",
              "memory",
              "sender",
              "sender_name",
              "n_messages",
              "session_id",
              "order",
              "template",
              "add_current_date_tool"
            ],
            "frozen": false,
            "icon": "bot",
            "key": "Agent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Response",
                "hidden": false,
                "method": "message_response",
                "name": "response",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 1.1732828199964098e-19,
            "template": {
              "_type": "Component",
              "add_current_date_tool": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Current Date",
                "dynamic": false,
                "info": "If true, will add a tool to the agent that returns the current date.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "add_current_date_tool",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "agent_description": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Agent Description [Deprecated]",
                "dynamic": false,
                "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically. This feature is deprecated and will be removed in future versions.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "agent_description",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "A helpful assistant with access to the following tools:"
              },
              "agent_llm": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Language Model",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "LanguageModel"
                ],
                "name": "agent_llm",
                "options": [
                  "Amazon Bedrock",
                  "Anthropic",
                  "Azure OpenAI",
                  "Google Generative AI",
                  "Groq",
                  "NVIDIA",
                  "OpenAI",
                  "SambaNova",
                  "Custom"
                ],
                "options_metadata": [
                  {
                    "icon": "Amazon"
                  },
                  {
                    "icon": "Anthropic"
                  },
                  {
                    "icon": "Azure"
                  },
                  {
                    "icon": "GoogleGenerativeAI"
                  },
                  {
                    "icon": "Groq"
                  },
                  {
                    "icon": "NVIDIA"
                  },
                  {
                    "icon": "OpenAI"
                  },
                  {
                    "icon": "SambaNova"
                  },
                  {
                    "icon": "brain"
                  }
                ],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.agents.events import ExceptionWithMessageError\nfrom langflow.base.models.model_input_constants import (\n    ALL_PROVIDER_FIELDS,\n    MODEL_DYNAMIC_UPDATE_FIELDS,\n    MODEL_PROVIDERS_DICT,\n    MODELS_METADATA,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.custom.utils import update_component_build_config\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.logging import logger\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n    component_input.advanced = True\n    return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n    display_name: str = \"Agent\"\n    description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n    icon = \"bot\"\n    beta = False\n    name = \"Agent\"\n\n    memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n    inputs = [\n        DropdownInput(\n            name=\"agent_llm\",\n            display_name=\"Model Provider\",\n            info=\"The provider of the language model that the agent will use to generate responses.\",\n            options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n            value=\"OpenAI\",\n            real_time_refresh=True,\n            input_types=[],\n            options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())] + [{\"icon\": \"brain\"}],\n        ),\n        *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n        MultilineInput(\n            name=\"system_prompt\",\n            display_name=\"Agent Instructions\",\n            info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n            value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n            advanced=False,\n        ),\n        *LCToolsAgentComponent._base_inputs,\n        *memory_inputs,\n        BoolInput(\n            name=\"add_current_date_tool\",\n            display_name=\"Current Date\",\n            advanced=True,\n            info=\"If true, will add a tool to the agent that returns the current date.\",\n            value=True,\n        ),\n    ]\n    outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n    async def message_response(self) -> Message:\n        try:\n            # Get LLM model and validate\n            llm_model, display_name = self.get_llm()\n            if llm_model is None:\n                msg = \"No language model selected. Please choose a model to proceed.\"\n                raise ValueError(msg)\n            self.model_name = get_model_name(llm_model, display_name=display_name)\n\n            # Get memory data\n            self.chat_history = await self.get_memory_data()\n\n            # Add current date tool if enabled\n            if self.add_current_date_tool:\n                if not isinstance(self.tools, list):  # type: ignore[has-type]\n                    self.tools = []\n                current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)\n                if not isinstance(current_date_tool, StructuredTool):\n                    msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n                    raise TypeError(msg)\n                self.tools.append(current_date_tool)\n\n            # Validate tools\n            if not self.tools:\n                msg = \"Tools are required to run the agent. Please add at least one tool.\"\n                raise ValueError(msg)\n\n            # Set up and run agent\n            self.set(\n                llm=llm_model,\n                tools=self.tools,\n                chat_history=self.chat_history,\n                input_value=self.input_value,\n                system_prompt=self.system_prompt,\n            )\n            agent = self.create_agent_runnable()\n            return await self.run_agent(agent)\n\n        except (ValueError, TypeError, KeyError) as e:\n            logger.error(f\"{type(e).__name__}: {e!s}\")\n            raise\n        except ExceptionWithMessageError as e:\n            logger.error(f\"ExceptionWithMessageError occurred: {e}\")\n            raise\n        except Exception as e:\n            logger.error(f\"Unexpected error: {e!s}\")\n            raise\n\n    async def get_memory_data(self):\n        memory_kwargs = {\n            component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n        }\n        # filter out empty values\n        memory_kwargs = {k: v for k, v in memory_kwargs.items() if v is not None}\n\n        return await MemoryComponent(**self.get_base_args()).set(**memory_kwargs).retrieve_messages()\n\n    def get_llm(self):\n        if not isinstance(self.agent_llm, str):\n            return self.agent_llm, None\n\n        try:\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if not provider_info:\n                msg = f\"Invalid model provider: {self.agent_llm}\"\n                raise ValueError(msg)\n\n            component_class = provider_info.get(\"component_class\")\n            display_name = component_class.display_name\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\", \"\")\n\n            return self._build_llm_model(component_class, inputs, prefix), display_name\n\n        except Exception as e:\n            logger.error(f\"Error building {self.agent_llm} language model: {e!s}\")\n            msg = f\"Failed to initialize language model: {e!s}\"\n            raise ValueError(msg) from e\n\n    def _build_llm_model(self, component, inputs, prefix=\"\"):\n        model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n        return component.set(**model_kwargs).build_model()\n\n    def set_component_params(self, component):\n        provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n        if provider_info:\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\")\n            model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n\n            return component.set(**model_kwargs)\n        return component\n\n    def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n        \"\"\"Delete specified fields from build_config.\"\"\"\n        for field in fields:\n            build_config.pop(field, None)\n\n    def update_input_types(self, build_config: dotdict) -> dotdict:\n        \"\"\"Update input types for all fields in build_config.\"\"\"\n        for key, value in build_config.items():\n            if isinstance(value, dict):\n                if value.get(\"input_types\") is None:\n                    build_config[key][\"input_types\"] = []\n            elif hasattr(value, \"input_types\") and value.input_types is None:\n                value.input_types = []\n        return build_config\n\n    async def update_build_config(\n        self, build_config: dotdict, field_value: str, field_name: str | None = None\n    ) -> dotdict:\n        # Iterate over all providers in the MODEL_PROVIDERS_DICT\n        # Existing logic for updating build_config\n        if field_name in (\"agent_llm\",):\n            build_config[\"agent_llm\"][\"value\"] = field_value\n            provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call the component class's update_build_config method\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n\n            provider_configs: dict[str, tuple[dict, list[dict]]] = {\n                provider: (\n                    MODEL_PROVIDERS_DICT[provider][\"fields\"],\n                    [\n                        MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n                        for other_provider in MODEL_PROVIDERS_DICT\n                        if other_provider != provider\n                    ],\n                )\n                for provider in MODEL_PROVIDERS_DICT\n            }\n            if field_value in provider_configs:\n                fields_to_add, fields_to_delete = provider_configs[field_value]\n\n                # Delete fields from other providers\n                for fields in fields_to_delete:\n                    self.delete_fields(build_config, fields)\n\n                # Add provider-specific fields\n                if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n                    build_config.update(fields_to_add)\n                else:\n                    build_config.update(fields_to_add)\n                # Reset input types for agent_llm\n                build_config[\"agent_llm\"][\"input_types\"] = []\n            elif field_value == \"Custom\":\n                # Delete all provider fields\n                self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n                # Update with custom component\n                custom_component = DropdownInput(\n                    name=\"agent_llm\",\n                    display_name=\"Language Model\",\n                    options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n                    value=\"Custom\",\n                    real_time_refresh=True,\n                    input_types=[\"LanguageModel\"],\n                    options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())]\n                    + [{\"icon\": \"brain\"}],\n                )\n                build_config.update({\"agent_llm\": custom_component.to_dict()})\n            # Update input types for all fields\n            build_config = self.update_input_types(build_config)\n\n            # Validate required keys\n            default_keys = [\n                \"code\",\n                \"_type\",\n                \"agent_llm\",\n                \"tools\",\n                \"input_value\",\n                \"add_current_date_tool\",\n                \"system_prompt\",\n                \"agent_description\",\n                \"max_iterations\",\n                \"handle_parsing_errors\",\n                \"verbose\",\n            ]\n            missing_keys = [key for key in default_keys if key not in build_config]\n            if missing_keys:\n                msg = f\"Missing required keys in build_config: {missing_keys}\"\n                raise ValueError(msg)\n        if (\n            isinstance(self.agent_llm, str)\n            and self.agent_llm in MODEL_PROVIDERS_DICT\n            and field_name in MODEL_DYNAMIC_UPDATE_FIELDS\n        ):\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                component_class = self.set_component_params(component_class)\n                prefix = provider_info.get(\"prefix\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call each component class's update_build_config method\n                    # remove the prefix from the field_name\n                    if isinstance(field_name, str) and isinstance(prefix, str):\n                        field_name = field_name.replace(prefix, \"\")\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n        return dotdict({k: v.to_dict() if hasattr(v, \"to_dict\") else v for k, v in build_config.items()})\n"
              },
              "handle_parsing_errors": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Handle Parse Errors",
                "dynamic": false,
                "info": "Should the Agent fix errors when reading user input for better processing?",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "handle_parsing_errors",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "input_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "The input provided by the user for the agent to process.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "max_iterations": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Max Iterations",
                "dynamic": false,
                "info": "The maximum number of attempts the agent can make to complete its task before it stops.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "max_iterations",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 15
              },
              "memory": {
                "_input_type": "HandleInput",
                "advanced": true,
                "display_name": "External Memory",
                "dynamic": false,
                "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                "input_types": [
                  "Memory"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "memory",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "n_messages": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Messages",
                "dynamic": false,
                "info": "Number of messages to retrieve.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "n_messages",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 100
              },
              "order": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Order",
                "dynamic": false,
                "info": "Order of the messages.",
                "input_types": [],
                "name": "order",
                "options": [
                  "Ascending",
                  "Descending"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Ascending"
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Filter by sender type.",
                "input_types": [],
                "name": "sender",
                "options": [
                  "Machine",
                  "User",
                  "Machine and User"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Machine and User"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Filter by sender name.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_prompt": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "Agent Instructions",
                "dynamic": false,
                "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_prompt",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "You are a helpful assistant that can use tools to answer questions and perform tasks."
              },
              "template": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "{sender_name}: {text}"
              },
              "tools": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Tools",
                "dynamic": false,
                "info": "These are the tools that the agent can use to help with tasks.",
                "input_types": [
                  "Tool"
                ],
                "list": true,
                "list_add_label": "Add More",
                "name": "tools",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Agent"
        },
        "dragging": false,
        "id": "Agent-AH0XX",
        "measured": {
          "height": 459,
          "width": 320
        },
        "position": {
          "x": 3631.1575464435923,
          "y": -1360.5120154366896
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "OllamaModel-3aggd",
          "node": {
            "base_classes": [
              "LanguageModel",
              "Message"
            ],
            "beta": false,
            "category": "models",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Generate text using Ollama Local LLMs.",
            "display_name": "InsightModel",
            "documentation": "",
            "edited": false,
            "field_order": [
              "base_url",
              "model_name",
              "temperature",
              "format",
              "metadata",
              "mirostat",
              "mirostat_eta",
              "mirostat_tau",
              "num_ctx",
              "num_gpu",
              "num_thread",
              "repeat_last_n",
              "repeat_penalty",
              "tfs_z",
              "timeout",
              "top_k",
              "top_p",
              "verbose",
              "tags",
              "stop_tokens",
              "system",
              "tool_model_enabled",
              "template",
              "input_value",
              "system_message",
              "stream"
            ],
            "frozen": false,
            "icon": "Ollama",
            "key": "OllamaModel",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "text_response",
                "name": "text_output",
                "options": null,
                "required_inputs": [],
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Language Model",
                "hidden": false,
                "method": "build_model",
                "name": "model_output",
                "options": null,
                "required_inputs": [],
                "selected": "LanguageModel",
                "tool_mode": true,
                "types": [
                  "LanguageModel"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.0005185853433287903,
            "template": {
              "_type": "Component",
              "base_url": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Base URL",
                "dynamic": false,
                "info": "Endpoint of the Ollama API.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "base_url",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "http://localhost:11434"
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import asyncio\nfrom typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import ChatOllama\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.ollama_constants import OLLAMA_TOOL_MODELS_BASE, URL_LIST\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SliderInput\nfrom langflow.logging import logger\n\nHTTP_STATUS_OK = 200\n\n\nclass ChatOllamaComponent(LCModelComponent):\n    display_name = \"Ollama\"\n    description = \"Generate text using Ollama Local LLMs.\"\n    icon = \"Ollama\"\n    name = \"OllamaModel\"\n\n    # Define constants for JSON keys\n    JSON_MODELS_KEY = \"models\"\n    JSON_NAME_KEY = \"name\"\n    JSON_CAPABILITIES_KEY = \"capabilities\"\n    DESIRED_CAPABILITY = \"completion\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Base URL\",\n            info=\"Endpoint of the Ollama API.\",\n            value=\"\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=[],\n            info=\"Refer to https://ollama.com/library for more models.\",\n            refresh_button=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"format\", display_name=\"Format\", info=\"Specify the format of the output (e.g., json).\", advanced=True\n        ),\n        DictInput(name=\"metadata\", display_name=\"Metadata\", info=\"Metadata to add to the run trace.\", advanced=True),\n        DropdownInput(\n            name=\"mirostat\",\n            display_name=\"Mirostat\",\n            options=[\"Disabled\", \"Mirostat\", \"Mirostat 2.0\"],\n            info=\"Enable/disable Mirostat sampling for controlling perplexity.\",\n            value=\"Disabled\",\n            advanced=True,\n            real_time_refresh=True,\n        ),\n        FloatInput(\n            name=\"mirostat_eta\",\n            display_name=\"Mirostat Eta\",\n            info=\"Learning rate for Mirostat algorithm. (Default: 0.1)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"mirostat_tau\",\n            display_name=\"Mirostat Tau\",\n            info=\"Controls the balance between coherence and diversity of the output. (Default: 5.0)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_ctx\",\n            display_name=\"Context Window Size\",\n            info=\"Size of the context window for generating tokens. (Default: 2048)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_gpu\",\n            display_name=\"Number of GPUs\",\n            info=\"Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_thread\",\n            display_name=\"Number of Threads\",\n            info=\"Number of threads to use during computation. (Default: detected for optimal performance)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"repeat_last_n\",\n            display_name=\"Repeat Last N\",\n            info=\"How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"repeat_penalty\",\n            display_name=\"Repeat Penalty\",\n            info=\"Penalty for repetitions in generated text. (Default: 1.1)\",\n            advanced=True,\n        ),\n        FloatInput(name=\"tfs_z\", display_name=\"TFS Z\", info=\"Tail free sampling value. (Default: 1)\", advanced=True),\n        IntInput(name=\"timeout\", display_name=\"Timeout\", info=\"Timeout for the request stream.\", advanced=True),\n        IntInput(\n            name=\"top_k\", display_name=\"Top K\", info=\"Limits token selection to top K. (Default: 40)\", advanced=True\n        ),\n        FloatInput(name=\"top_p\", display_name=\"Top P\", info=\"Works together with top-k. (Default: 0.9)\", advanced=True),\n        BoolInput(name=\"verbose\", display_name=\"Verbose\", info=\"Whether to print out response text.\", advanced=True),\n        MessageTextInput(\n            name=\"tags\",\n            display_name=\"Tags\",\n            info=\"Comma-separated list of tags to add to the run trace.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"stop_tokens\",\n            display_name=\"Stop Tokens\",\n            info=\"Comma-separated list of tokens to signal the model to stop generating text.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"system\", display_name=\"System\", info=\"System to use for generating text.\", advanced=True\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Tool Model Enabled\",\n            info=\"Whether to enable tool calling in the model.\",\n            value=False,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"template\", display_name=\"Template\", info=\"Template to use for generating text.\", advanced=True\n        ),\n        *LCModelComponent._base_inputs,\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        # Mapping mirostat settings to their corresponding values\n        mirostat_options = {\"Mirostat\": 1, \"Mirostat 2.0\": 2}\n\n        # Default to 0 for 'Disabled'\n        mirostat_value = mirostat_options.get(self.mirostat, 0)\n\n        # Set mirostat_eta and mirostat_tau to None if mirostat is disabled\n        if mirostat_value == 0:\n            mirostat_eta = None\n            mirostat_tau = None\n        else:\n            mirostat_eta = self.mirostat_eta\n            mirostat_tau = self.mirostat_tau\n\n        # Mapping system settings to their corresponding values\n        llm_params = {\n            \"base_url\": self.base_url,\n            \"model\": self.model_name,\n            \"mirostat\": mirostat_value,\n            \"format\": self.format,\n            \"metadata\": self.metadata,\n            \"tags\": self.tags.split(\",\") if self.tags else None,\n            \"mirostat_eta\": mirostat_eta,\n            \"mirostat_tau\": mirostat_tau,\n            \"num_ctx\": self.num_ctx or None,\n            \"num_gpu\": self.num_gpu or None,\n            \"num_thread\": self.num_thread or None,\n            \"repeat_last_n\": self.repeat_last_n or None,\n            \"repeat_penalty\": self.repeat_penalty or None,\n            \"temperature\": self.temperature or None,\n            \"stop\": self.stop_tokens.split(\",\") if self.stop_tokens else None,\n            \"system\": self.system,\n            \"tfs_z\": self.tfs_z or None,\n            \"timeout\": self.timeout or None,\n            \"top_k\": self.top_k or None,\n            \"top_p\": self.top_p or None,\n            \"verbose\": self.verbose,\n            \"template\": self.template,\n        }\n\n        # Remove parameters with None values\n        llm_params = {k: v for k, v in llm_params.items() if v is not None}\n\n        try:\n            output = ChatOllama(**llm_params)\n        except Exception as e:\n            msg = (\n                \"Unable to connect to the Ollama API. \",\n                \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n            )\n            raise ValueError(msg) from e\n\n        return output\n\n    async def is_valid_ollama_url(self, url: str) -> bool:\n        try:\n            async with httpx.AsyncClient() as client:\n                return (await client.get(urljoin(url, \"api/tags\"))).status_code == HTTP_STATUS_OK\n        except httpx.RequestError:\n            return False\n\n    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n        if field_name == \"mirostat\":\n            if field_value == \"Disabled\":\n                build_config[\"mirostat_eta\"][\"advanced\"] = True\n                build_config[\"mirostat_tau\"][\"advanced\"] = True\n                build_config[\"mirostat_eta\"][\"value\"] = None\n                build_config[\"mirostat_tau\"][\"value\"] = None\n\n            else:\n                build_config[\"mirostat_eta\"][\"advanced\"] = False\n                build_config[\"mirostat_tau\"][\"advanced\"] = False\n\n                if field_value == \"Mirostat 2.0\":\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.2\n                    build_config[\"mirostat_tau\"][\"value\"] = 10\n                else:\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.1\n                    build_config[\"mirostat_tau\"][\"value\"] = 5\n\n        if field_name in {\"base_url\", \"model_name\"}:\n            if build_config[\"base_url\"].get(\"load_from_db\", False):\n                base_url_value = await self.get_variables(build_config[\"base_url\"].get(\"value\", \"\"), \"base_url\")\n            else:\n                base_url_value = build_config[\"base_url\"].get(\"value\", \"\")\n\n            if not await self.is_valid_ollama_url(base_url_value):\n                # Check if any URL in the list is valid\n                valid_url = \"\"\n                check_urls = URL_LIST\n                if self.base_url:\n                    check_urls = [self.base_url, *URL_LIST]\n                for url in check_urls:\n                    if await self.is_valid_ollama_url(url):\n                        valid_url = url\n                        break\n                if valid_url != \"\":\n                    build_config[\"base_url\"][\"value\"] = valid_url\n                else:\n                    msg = \"No valid Ollama URL found.\"\n                    raise ValueError(msg)\n        if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n            if await self.is_valid_ollama_url(self.base_url):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(self.base_url, tool_model_enabled)\n            elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(\n                    build_config[\"base_url\"].get(\"value\", \"\"), tool_model_enabled\n                )\n            else:\n                build_config[\"model_name\"][\"options\"] = []\n        if field_name == \"keep_alive_flag\":\n            if field_value == \"Keep\":\n                build_config[\"keep_alive\"][\"value\"] = \"-1\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            elif field_value == \"Immediately\":\n                build_config[\"keep_alive\"][\"value\"] = \"0\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            else:\n                build_config[\"keep_alive\"][\"advanced\"] = False\n\n        return build_config\n\n    async def get_models(self, base_url_value: str, tool_model_enabled: bool | None = None) -> list[str]:\n        \"\"\"Fetches a list of models from the Ollama API that do not have the \"embedding\" capability.\n\n        Args:\n            base_url_value (str): The base URL of the Ollama API.\n            tool_model_enabled (bool | None, optional): If True, filters the models further to include\n                only those that support tool calling. Defaults to None.\n\n        Returns:\n            list[str]: A list of model names that do not have the \"embedding\" capability. If\n                `tool_model_enabled` is True, only models supporting tool calling are included.\n\n        Raises:\n            ValueError: If there is an issue with the API request or response, or if the model\n                names cannot be retrieved.\n        \"\"\"\n        try:\n            # Normalize the base URL to avoid the repeated \"/\" at the end\n            base_url = base_url_value.rstrip(\"/\") + \"/\"\n\n            # Ollama REST API to return models\n            tags_url = urljoin(base_url, \"api/tags\")\n\n            # Ollama REST API to return model capabilities\n            show_url = urljoin(base_url, \"api/show\")\n\n            async with httpx.AsyncClient() as client:\n                # Fetch available models\n                tags_response = await client.get(tags_url)\n                tags_response.raise_for_status()\n                models = tags_response.json()\n                if asyncio.iscoroutine(models):\n                    models = await models\n                logger.debug(f\"Available models: {models}\")\n\n                # Filter models that are NOT embedding models\n                model_ids = []\n                for model in models[self.JSON_MODELS_KEY]:\n                    model_name = model[self.JSON_NAME_KEY]\n                    logger.debug(f\"Checking model: {model_name}\")\n\n                    payload = {\"model\": model_name}\n                    show_response = await client.post(show_url, json=payload)\n                    show_response.raise_for_status()\n                    json_data = show_response.json()\n                    if asyncio.iscoroutine(json_data):\n                        json_data = await json_data\n                    capabilities = json_data.get(self.JSON_CAPABILITIES_KEY, [])\n                    logger.debug(f\"Model: {model_name}, Capabilities: {capabilities}\")\n\n                    if self.DESIRED_CAPABILITY in capabilities:\n                        model_ids.append(model_name)\n\n        except (httpx.RequestError, ValueError) as e:\n            msg = \"Could not get model names from Ollama.\"\n            raise ValueError(msg) from e\n\n        return (\n            model_ids if not tool_model_enabled else [model for model in model_ids if self.supports_tool_calling(model)]\n        )\n\n    def supports_tool_calling(self, model: str) -> bool:\n        \"\"\"Check if model name is in the base of any models example llama3.3 can have 1b and 2b.\"\"\"\n        return any(model.startswith(f\"{tool_model}\") for tool_model in OLLAMA_TOOL_MODELS_BASE)\n"
              },
              "format": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Format",
                "dynamic": false,
                "info": "Specify the format of the output (e.g., json).",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "format",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "input_value": {
                "_input_type": "MessageInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "metadata": {
                "_input_type": "DictInput",
                "advanced": true,
                "display_name": "Metadata",
                "dynamic": false,
                "info": "Metadata to add to the run trace.",
                "list": false,
                "list_add_label": "Add More",
                "name": "metadata",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "dict",
                "value": {}
              },
              "mirostat": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Mirostat",
                "dynamic": false,
                "info": "Enable/disable Mirostat sampling for controlling perplexity.",
                "name": "mirostat",
                "options": [
                  "Disabled",
                  "Mirostat",
                  "Mirostat 2.0"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Disabled"
              },
              "mirostat_eta": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Eta",
                "dynamic": false,
                "info": "Learning rate for Mirostat algorithm. (Default: 0.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_eta",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "mirostat_tau": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Tau",
                "dynamic": false,
                "info": "Controls the balance between coherence and diversity of the output. (Default: 5.0)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_tau",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "model_name": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Model Name",
                "dynamic": false,
                "info": "Refer to https://ollama.com/library for more models.",
                "name": "model_name",
                "options": [
                  "mistral:latest",
                  "llama3.2:latest",
                  "qwen2.5-coder:7b",
                  "qwen2.5:32b",
                  "llama3.2:1b",
                  "qwen2.5-coder:3b"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "refresh_button": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "mistral:latest"
              },
              "num_ctx": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Context Window Size",
                "dynamic": false,
                "info": "Size of the context window for generating tokens. (Default: 2048)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_ctx",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_gpu": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of GPUs",
                "dynamic": false,
                "info": "Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_gpu",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_thread": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Threads",
                "dynamic": false,
                "info": "Number of threads to use during computation. (Default: detected for optimal performance)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_thread",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_last_n": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Repeat Last N",
                "dynamic": false,
                "info": "How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_last_n",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_penalty": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Repeat Penalty",
                "dynamic": false,
                "info": "Penalty for repetitions in generated text. (Default: 1.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_penalty",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "stop_tokens": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Stop Tokens",
                "dynamic": false,
                "info": "Comma-separated list of tokens to signal the model to stop generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "stop_tokens",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "stream": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Stream",
                "dynamic": false,
                "info": "Stream the response from the model. Streaming works only in Chat.",
                "list": false,
                "list_add_label": "Add More",
                "name": "stream",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "system": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "System",
                "dynamic": false,
                "info": "System to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "system",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_message": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "System Message",
                "dynamic": false,
                "info": "System message to pass to the model.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tags": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tags",
                "dynamic": false,
                "info": "Comma-separated list of tags to add to the run trace.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tags",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "temperature": {
                "_input_type": "SliderInput",
                "advanced": true,
                "display_name": "Temperature",
                "dynamic": false,
                "info": "",
                "max_label": "",
                "max_label_icon": "",
                "min_label": "",
                "min_label_icon": "",
                "name": "temperature",
                "placeholder": "",
                "range_spec": {
                  "max": 1,
                  "min": 0,
                  "step": 0.01,
                  "step_type": "float"
                },
                "required": false,
                "show": true,
                "slider_buttons": false,
                "slider_buttons_options": [],
                "slider_input": false,
                "title_case": false,
                "tool_mode": false,
                "type": "slider",
                "value": 0.1
              },
              "template": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Template",
                "dynamic": false,
                "info": "Template to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tfs_z": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "TFS Z",
                "dynamic": false,
                "info": "Tail free sampling value. (Default: 1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "tfs_z",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "timeout": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Timeout",
                "dynamic": false,
                "info": "Timeout for the request stream.",
                "list": false,
                "list_add_label": "Add More",
                "name": "timeout",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "tool_model_enabled": {
                "_input_type": "BoolInput",
                "advanced": false,
                "display_name": "Tool Model Enabled",
                "dynamic": false,
                "info": "Whether to enable tool calling in the model.",
                "list": false,
                "list_add_label": "Add More",
                "name": "tool_model_enabled",
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "top_k": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Top K",
                "dynamic": false,
                "info": "Limits token selection to top K. (Default: 40)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_k",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "top_p": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Top P",
                "dynamic": false,
                "info": "Works together with top-k. (Default: 0.9)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_p",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "Whether to print out response text.",
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "OllamaModel"
        },
        "dragging": false,
        "id": "OllamaModel-3aggd",
        "measured": {
          "height": 568,
          "width": 320
        },
        "position": {
          "x": 3055.822894638568,
          "y": -2064.5096564550977
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "OllamaModel-gCTC1",
          "node": {
            "base_classes": [
              "LanguageModel",
              "Message"
            ],
            "beta": false,
            "category": "models",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Generate text using Ollama Local LLMs.",
            "display_name": "ReporterModel",
            "documentation": "",
            "edited": false,
            "field_order": [
              "base_url",
              "model_name",
              "temperature",
              "format",
              "metadata",
              "mirostat",
              "mirostat_eta",
              "mirostat_tau",
              "num_ctx",
              "num_gpu",
              "num_thread",
              "repeat_last_n",
              "repeat_penalty",
              "tfs_z",
              "timeout",
              "top_k",
              "top_p",
              "verbose",
              "tags",
              "stop_tokens",
              "system",
              "tool_model_enabled",
              "template",
              "input_value",
              "system_message",
              "stream"
            ],
            "frozen": false,
            "icon": "Ollama",
            "key": "OllamaModel",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "text_response",
                "name": "text_output",
                "options": null,
                "required_inputs": [],
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Language Model",
                "hidden": false,
                "method": "build_model",
                "name": "model_output",
                "options": null,
                "required_inputs": [],
                "selected": "LanguageModel",
                "tool_mode": true,
                "types": [
                  "LanguageModel"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.0005185853433287903,
            "template": {
              "_type": "Component",
              "base_url": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Base URL",
                "dynamic": false,
                "info": "Endpoint of the Ollama API.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "base_url",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "http://localhost:11434"
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import asyncio\nfrom typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import ChatOllama\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.ollama_constants import OLLAMA_TOOL_MODELS_BASE, URL_LIST\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SliderInput\nfrom langflow.logging import logger\n\nHTTP_STATUS_OK = 200\n\n\nclass ChatOllamaComponent(LCModelComponent):\n    display_name = \"Ollama\"\n    description = \"Generate text using Ollama Local LLMs.\"\n    icon = \"Ollama\"\n    name = \"OllamaModel\"\n\n    # Define constants for JSON keys\n    JSON_MODELS_KEY = \"models\"\n    JSON_NAME_KEY = \"name\"\n    JSON_CAPABILITIES_KEY = \"capabilities\"\n    DESIRED_CAPABILITY = \"completion\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Base URL\",\n            info=\"Endpoint of the Ollama API.\",\n            value=\"\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=[],\n            info=\"Refer to https://ollama.com/library for more models.\",\n            refresh_button=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"format\", display_name=\"Format\", info=\"Specify the format of the output (e.g., json).\", advanced=True\n        ),\n        DictInput(name=\"metadata\", display_name=\"Metadata\", info=\"Metadata to add to the run trace.\", advanced=True),\n        DropdownInput(\n            name=\"mirostat\",\n            display_name=\"Mirostat\",\n            options=[\"Disabled\", \"Mirostat\", \"Mirostat 2.0\"],\n            info=\"Enable/disable Mirostat sampling for controlling perplexity.\",\n            value=\"Disabled\",\n            advanced=True,\n            real_time_refresh=True,\n        ),\n        FloatInput(\n            name=\"mirostat_eta\",\n            display_name=\"Mirostat Eta\",\n            info=\"Learning rate for Mirostat algorithm. (Default: 0.1)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"mirostat_tau\",\n            display_name=\"Mirostat Tau\",\n            info=\"Controls the balance between coherence and diversity of the output. (Default: 5.0)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_ctx\",\n            display_name=\"Context Window Size\",\n            info=\"Size of the context window for generating tokens. (Default: 2048)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_gpu\",\n            display_name=\"Number of GPUs\",\n            info=\"Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_thread\",\n            display_name=\"Number of Threads\",\n            info=\"Number of threads to use during computation. (Default: detected for optimal performance)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"repeat_last_n\",\n            display_name=\"Repeat Last N\",\n            info=\"How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"repeat_penalty\",\n            display_name=\"Repeat Penalty\",\n            info=\"Penalty for repetitions in generated text. (Default: 1.1)\",\n            advanced=True,\n        ),\n        FloatInput(name=\"tfs_z\", display_name=\"TFS Z\", info=\"Tail free sampling value. (Default: 1)\", advanced=True),\n        IntInput(name=\"timeout\", display_name=\"Timeout\", info=\"Timeout for the request stream.\", advanced=True),\n        IntInput(\n            name=\"top_k\", display_name=\"Top K\", info=\"Limits token selection to top K. (Default: 40)\", advanced=True\n        ),\n        FloatInput(name=\"top_p\", display_name=\"Top P\", info=\"Works together with top-k. (Default: 0.9)\", advanced=True),\n        BoolInput(name=\"verbose\", display_name=\"Verbose\", info=\"Whether to print out response text.\", advanced=True),\n        MessageTextInput(\n            name=\"tags\",\n            display_name=\"Tags\",\n            info=\"Comma-separated list of tags to add to the run trace.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"stop_tokens\",\n            display_name=\"Stop Tokens\",\n            info=\"Comma-separated list of tokens to signal the model to stop generating text.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"system\", display_name=\"System\", info=\"System to use for generating text.\", advanced=True\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Tool Model Enabled\",\n            info=\"Whether to enable tool calling in the model.\",\n            value=False,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"template\", display_name=\"Template\", info=\"Template to use for generating text.\", advanced=True\n        ),\n        *LCModelComponent._base_inputs,\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        # Mapping mirostat settings to their corresponding values\n        mirostat_options = {\"Mirostat\": 1, \"Mirostat 2.0\": 2}\n\n        # Default to 0 for 'Disabled'\n        mirostat_value = mirostat_options.get(self.mirostat, 0)\n\n        # Set mirostat_eta and mirostat_tau to None if mirostat is disabled\n        if mirostat_value == 0:\n            mirostat_eta = None\n            mirostat_tau = None\n        else:\n            mirostat_eta = self.mirostat_eta\n            mirostat_tau = self.mirostat_tau\n\n        # Mapping system settings to their corresponding values\n        llm_params = {\n            \"base_url\": self.base_url,\n            \"model\": self.model_name,\n            \"mirostat\": mirostat_value,\n            \"format\": self.format,\n            \"metadata\": self.metadata,\n            \"tags\": self.tags.split(\",\") if self.tags else None,\n            \"mirostat_eta\": mirostat_eta,\n            \"mirostat_tau\": mirostat_tau,\n            \"num_ctx\": self.num_ctx or None,\n            \"num_gpu\": self.num_gpu or None,\n            \"num_thread\": self.num_thread or None,\n            \"repeat_last_n\": self.repeat_last_n or None,\n            \"repeat_penalty\": self.repeat_penalty or None,\n            \"temperature\": self.temperature or None,\n            \"stop\": self.stop_tokens.split(\",\") if self.stop_tokens else None,\n            \"system\": self.system,\n            \"tfs_z\": self.tfs_z or None,\n            \"timeout\": self.timeout or None,\n            \"top_k\": self.top_k or None,\n            \"top_p\": self.top_p or None,\n            \"verbose\": self.verbose,\n            \"template\": self.template,\n        }\n\n        # Remove parameters with None values\n        llm_params = {k: v for k, v in llm_params.items() if v is not None}\n\n        try:\n            output = ChatOllama(**llm_params)\n        except Exception as e:\n            msg = (\n                \"Unable to connect to the Ollama API. \",\n                \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n            )\n            raise ValueError(msg) from e\n\n        return output\n\n    async def is_valid_ollama_url(self, url: str) -> bool:\n        try:\n            async with httpx.AsyncClient() as client:\n                return (await client.get(urljoin(url, \"api/tags\"))).status_code == HTTP_STATUS_OK\n        except httpx.RequestError:\n            return False\n\n    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n        if field_name == \"mirostat\":\n            if field_value == \"Disabled\":\n                build_config[\"mirostat_eta\"][\"advanced\"] = True\n                build_config[\"mirostat_tau\"][\"advanced\"] = True\n                build_config[\"mirostat_eta\"][\"value\"] = None\n                build_config[\"mirostat_tau\"][\"value\"] = None\n\n            else:\n                build_config[\"mirostat_eta\"][\"advanced\"] = False\n                build_config[\"mirostat_tau\"][\"advanced\"] = False\n\n                if field_value == \"Mirostat 2.0\":\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.2\n                    build_config[\"mirostat_tau\"][\"value\"] = 10\n                else:\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.1\n                    build_config[\"mirostat_tau\"][\"value\"] = 5\n\n        if field_name in {\"base_url\", \"model_name\"}:\n            if build_config[\"base_url\"].get(\"load_from_db\", False):\n                base_url_value = await self.get_variables(build_config[\"base_url\"].get(\"value\", \"\"), \"base_url\")\n            else:\n                base_url_value = build_config[\"base_url\"].get(\"value\", \"\")\n\n            if not await self.is_valid_ollama_url(base_url_value):\n                # Check if any URL in the list is valid\n                valid_url = \"\"\n                check_urls = URL_LIST\n                if self.base_url:\n                    check_urls = [self.base_url, *URL_LIST]\n                for url in check_urls:\n                    if await self.is_valid_ollama_url(url):\n                        valid_url = url\n                        break\n                if valid_url != \"\":\n                    build_config[\"base_url\"][\"value\"] = valid_url\n                else:\n                    msg = \"No valid Ollama URL found.\"\n                    raise ValueError(msg)\n        if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n            if await self.is_valid_ollama_url(self.base_url):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(self.base_url, tool_model_enabled)\n            elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(\n                    build_config[\"base_url\"].get(\"value\", \"\"), tool_model_enabled\n                )\n            else:\n                build_config[\"model_name\"][\"options\"] = []\n        if field_name == \"keep_alive_flag\":\n            if field_value == \"Keep\":\n                build_config[\"keep_alive\"][\"value\"] = \"-1\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            elif field_value == \"Immediately\":\n                build_config[\"keep_alive\"][\"value\"] = \"0\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            else:\n                build_config[\"keep_alive\"][\"advanced\"] = False\n\n        return build_config\n\n    async def get_models(self, base_url_value: str, tool_model_enabled: bool | None = None) -> list[str]:\n        \"\"\"Fetches a list of models from the Ollama API that do not have the \"embedding\" capability.\n\n        Args:\n            base_url_value (str): The base URL of the Ollama API.\n            tool_model_enabled (bool | None, optional): If True, filters the models further to include\n                only those that support tool calling. Defaults to None.\n\n        Returns:\n            list[str]: A list of model names that do not have the \"embedding\" capability. If\n                `tool_model_enabled` is True, only models supporting tool calling are included.\n\n        Raises:\n            ValueError: If there is an issue with the API request or response, or if the model\n                names cannot be retrieved.\n        \"\"\"\n        try:\n            # Normalize the base URL to avoid the repeated \"/\" at the end\n            base_url = base_url_value.rstrip(\"/\") + \"/\"\n\n            # Ollama REST API to return models\n            tags_url = urljoin(base_url, \"api/tags\")\n\n            # Ollama REST API to return model capabilities\n            show_url = urljoin(base_url, \"api/show\")\n\n            async with httpx.AsyncClient() as client:\n                # Fetch available models\n                tags_response = await client.get(tags_url)\n                tags_response.raise_for_status()\n                models = tags_response.json()\n                if asyncio.iscoroutine(models):\n                    models = await models\n                logger.debug(f\"Available models: {models}\")\n\n                # Filter models that are NOT embedding models\n                model_ids = []\n                for model in models[self.JSON_MODELS_KEY]:\n                    model_name = model[self.JSON_NAME_KEY]\n                    logger.debug(f\"Checking model: {model_name}\")\n\n                    payload = {\"model\": model_name}\n                    show_response = await client.post(show_url, json=payload)\n                    show_response.raise_for_status()\n                    json_data = show_response.json()\n                    if asyncio.iscoroutine(json_data):\n                        json_data = await json_data\n                    capabilities = json_data.get(self.JSON_CAPABILITIES_KEY, [])\n                    logger.debug(f\"Model: {model_name}, Capabilities: {capabilities}\")\n\n                    if self.DESIRED_CAPABILITY in capabilities:\n                        model_ids.append(model_name)\n\n        except (httpx.RequestError, ValueError) as e:\n            msg = \"Could not get model names from Ollama.\"\n            raise ValueError(msg) from e\n\n        return (\n            model_ids if not tool_model_enabled else [model for model in model_ids if self.supports_tool_calling(model)]\n        )\n\n    def supports_tool_calling(self, model: str) -> bool:\n        \"\"\"Check if model name is in the base of any models example llama3.3 can have 1b and 2b.\"\"\"\n        return any(model.startswith(f\"{tool_model}\") for tool_model in OLLAMA_TOOL_MODELS_BASE)\n"
              },
              "format": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Format",
                "dynamic": false,
                "info": "Specify the format of the output (e.g., json).",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "format",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "input_value": {
                "_input_type": "MessageInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "metadata": {
                "_input_type": "DictInput",
                "advanced": true,
                "display_name": "Metadata",
                "dynamic": false,
                "info": "Metadata to add to the run trace.",
                "list": false,
                "list_add_label": "Add More",
                "name": "metadata",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "dict",
                "value": {}
              },
              "mirostat": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Mirostat",
                "dynamic": false,
                "info": "Enable/disable Mirostat sampling for controlling perplexity.",
                "name": "mirostat",
                "options": [
                  "Disabled",
                  "Mirostat",
                  "Mirostat 2.0"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Disabled"
              },
              "mirostat_eta": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Eta",
                "dynamic": false,
                "info": "Learning rate for Mirostat algorithm. (Default: 0.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_eta",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "mirostat_tau": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Tau",
                "dynamic": false,
                "info": "Controls the balance between coherence and diversity of the output. (Default: 5.0)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_tau",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "model_name": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Model Name",
                "dynamic": false,
                "info": "Refer to https://ollama.com/library for more models.",
                "name": "model_name",
                "options": [
                  "mistral-nemo:latest",
                  "mistral:latest",
                  "llama3.2:latest",
                  "qwen2.5-coder:7b",
                  "qwen2.5:32b",
                  "llama3.2:1b",
                  "qwen2.5-coder:3b"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "refresh_button": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "mistral-nemo:latest"
              },
              "num_ctx": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Context Window Size",
                "dynamic": false,
                "info": "Size of the context window for generating tokens. (Default: 2048)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_ctx",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_gpu": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of GPUs",
                "dynamic": false,
                "info": "Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_gpu",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_thread": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Threads",
                "dynamic": false,
                "info": "Number of threads to use during computation. (Default: detected for optimal performance)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_thread",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_last_n": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Repeat Last N",
                "dynamic": false,
                "info": "How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_last_n",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_penalty": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Repeat Penalty",
                "dynamic": false,
                "info": "Penalty for repetitions in generated text. (Default: 1.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_penalty",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "stop_tokens": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Stop Tokens",
                "dynamic": false,
                "info": "Comma-separated list of tokens to signal the model to stop generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "stop_tokens",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "stream": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Stream",
                "dynamic": false,
                "info": "Stream the response from the model. Streaming works only in Chat.",
                "list": false,
                "list_add_label": "Add More",
                "name": "stream",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "system": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "System",
                "dynamic": false,
                "info": "System to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "system",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_message": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "System Message",
                "dynamic": false,
                "info": "System message to pass to the model.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tags": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tags",
                "dynamic": false,
                "info": "Comma-separated list of tags to add to the run trace.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tags",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "temperature": {
                "_input_type": "SliderInput",
                "advanced": true,
                "display_name": "Temperature",
                "dynamic": false,
                "info": "",
                "max_label": "",
                "max_label_icon": "",
                "min_label": "",
                "min_label_icon": "",
                "name": "temperature",
                "placeholder": "",
                "range_spec": {
                  "max": 1,
                  "min": 0,
                  "step": 0.01,
                  "step_type": "float"
                },
                "required": false,
                "show": true,
                "slider_buttons": false,
                "slider_buttons_options": [],
                "slider_input": false,
                "title_case": false,
                "tool_mode": false,
                "type": "slider",
                "value": 0.1
              },
              "template": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Template",
                "dynamic": false,
                "info": "Template to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tfs_z": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "TFS Z",
                "dynamic": false,
                "info": "Tail free sampling value. (Default: 1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "tfs_z",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "timeout": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Timeout",
                "dynamic": false,
                "info": "Timeout for the request stream.",
                "list": false,
                "list_add_label": "Add More",
                "name": "timeout",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "tool_model_enabled": {
                "_input_type": "BoolInput",
                "advanced": false,
                "display_name": "Tool Model Enabled",
                "dynamic": false,
                "info": "Whether to enable tool calling in the model.",
                "list": false,
                "list_add_label": "Add More",
                "name": "tool_model_enabled",
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "top_k": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Top K",
                "dynamic": false,
                "info": "Limits token selection to top K. (Default: 40)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_k",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "top_p": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Top P",
                "dynamic": false,
                "info": "Works together with top-k. (Default: 0.9)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_p",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "Whether to print out response text.",
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "OllamaModel"
        },
        "dragging": false,
        "id": "OllamaModel-gCTC1",
        "measured": {
          "height": 568,
          "width": 320
        },
        "position": {
          "x": 4192.453267974375,
          "y": -2078.384196629341
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Agent-AGDrR",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "agents",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Define the agent's instructions, then enter a task to complete using tools.",
            "display_name": "ReporterAgent",
            "documentation": "",
            "edited": false,
            "field_order": [
              "agent_llm",
              "max_tokens",
              "model_kwargs",
              "json_mode",
              "model_name",
              "openai_api_base",
              "api_key",
              "temperature",
              "seed",
              "max_retries",
              "timeout",
              "system_prompt",
              "tools",
              "input_value",
              "handle_parsing_errors",
              "verbose",
              "max_iterations",
              "agent_description",
              "memory",
              "sender",
              "sender_name",
              "n_messages",
              "session_id",
              "order",
              "template",
              "add_current_date_tool"
            ],
            "frozen": false,
            "icon": "bot",
            "key": "Agent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Response",
                "hidden": false,
                "method": "message_response",
                "name": "response",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 1.1732828199964098e-19,
            "template": {
              "_type": "Component",
              "add_current_date_tool": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Current Date",
                "dynamic": false,
                "info": "If true, will add a tool to the agent that returns the current date.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "add_current_date_tool",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "agent_description": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Agent Description [Deprecated]",
                "dynamic": false,
                "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically. This feature is deprecated and will be removed in future versions.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "agent_description",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "A helpful assistant with access to the following tools:"
              },
              "agent_llm": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Language Model",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "LanguageModel"
                ],
                "name": "agent_llm",
                "options": [
                  "Amazon Bedrock",
                  "Anthropic",
                  "Azure OpenAI",
                  "Google Generative AI",
                  "Groq",
                  "NVIDIA",
                  "OpenAI",
                  "SambaNova",
                  "Custom"
                ],
                "options_metadata": [
                  {
                    "icon": "Amazon"
                  },
                  {
                    "icon": "Anthropic"
                  },
                  {
                    "icon": "Azure"
                  },
                  {
                    "icon": "GoogleGenerativeAI"
                  },
                  {
                    "icon": "Groq"
                  },
                  {
                    "icon": "NVIDIA"
                  },
                  {
                    "icon": "OpenAI"
                  },
                  {
                    "icon": "SambaNova"
                  },
                  {
                    "icon": "brain"
                  }
                ],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.agents.events import ExceptionWithMessageError\nfrom langflow.base.models.model_input_constants import (\n    ALL_PROVIDER_FIELDS,\n    MODEL_DYNAMIC_UPDATE_FIELDS,\n    MODEL_PROVIDERS_DICT,\n    MODELS_METADATA,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.custom.utils import update_component_build_config\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.logging import logger\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n    component_input.advanced = True\n    return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n    display_name: str = \"Agent\"\n    description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n    icon = \"bot\"\n    beta = False\n    name = \"Agent\"\n\n    memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n    inputs = [\n        DropdownInput(\n            name=\"agent_llm\",\n            display_name=\"Model Provider\",\n            info=\"The provider of the language model that the agent will use to generate responses.\",\n            options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n            value=\"OpenAI\",\n            real_time_refresh=True,\n            input_types=[],\n            options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())] + [{\"icon\": \"brain\"}],\n        ),\n        *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n        MultilineInput(\n            name=\"system_prompt\",\n            display_name=\"Agent Instructions\",\n            info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n            value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n            advanced=False,\n        ),\n        *LCToolsAgentComponent._base_inputs,\n        *memory_inputs,\n        BoolInput(\n            name=\"add_current_date_tool\",\n            display_name=\"Current Date\",\n            advanced=True,\n            info=\"If true, will add a tool to the agent that returns the current date.\",\n            value=True,\n        ),\n    ]\n    outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n    async def message_response(self) -> Message:\n        try:\n            # Get LLM model and validate\n            llm_model, display_name = self.get_llm()\n            if llm_model is None:\n                msg = \"No language model selected. Please choose a model to proceed.\"\n                raise ValueError(msg)\n            self.model_name = get_model_name(llm_model, display_name=display_name)\n\n            # Get memory data\n            self.chat_history = await self.get_memory_data()\n\n            # Add current date tool if enabled\n            if self.add_current_date_tool:\n                if not isinstance(self.tools, list):  # type: ignore[has-type]\n                    self.tools = []\n                current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)\n                if not isinstance(current_date_tool, StructuredTool):\n                    msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n                    raise TypeError(msg)\n                self.tools.append(current_date_tool)\n\n            # Validate tools\n            if not self.tools:\n                msg = \"Tools are required to run the agent. Please add at least one tool.\"\n                raise ValueError(msg)\n\n            # Set up and run agent\n            self.set(\n                llm=llm_model,\n                tools=self.tools,\n                chat_history=self.chat_history,\n                input_value=self.input_value,\n                system_prompt=self.system_prompt,\n            )\n            agent = self.create_agent_runnable()\n            return await self.run_agent(agent)\n\n        except (ValueError, TypeError, KeyError) as e:\n            logger.error(f\"{type(e).__name__}: {e!s}\")\n            raise\n        except ExceptionWithMessageError as e:\n            logger.error(f\"ExceptionWithMessageError occurred: {e}\")\n            raise\n        except Exception as e:\n            logger.error(f\"Unexpected error: {e!s}\")\n            raise\n\n    async def get_memory_data(self):\n        memory_kwargs = {\n            component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n        }\n        # filter out empty values\n        memory_kwargs = {k: v for k, v in memory_kwargs.items() if v is not None}\n\n        return await MemoryComponent(**self.get_base_args()).set(**memory_kwargs).retrieve_messages()\n\n    def get_llm(self):\n        if not isinstance(self.agent_llm, str):\n            return self.agent_llm, None\n\n        try:\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if not provider_info:\n                msg = f\"Invalid model provider: {self.agent_llm}\"\n                raise ValueError(msg)\n\n            component_class = provider_info.get(\"component_class\")\n            display_name = component_class.display_name\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\", \"\")\n\n            return self._build_llm_model(component_class, inputs, prefix), display_name\n\n        except Exception as e:\n            logger.error(f\"Error building {self.agent_llm} language model: {e!s}\")\n            msg = f\"Failed to initialize language model: {e!s}\"\n            raise ValueError(msg) from e\n\n    def _build_llm_model(self, component, inputs, prefix=\"\"):\n        model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n        return component.set(**model_kwargs).build_model()\n\n    def set_component_params(self, component):\n        provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n        if provider_info:\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\")\n            model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n\n            return component.set(**model_kwargs)\n        return component\n\n    def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n        \"\"\"Delete specified fields from build_config.\"\"\"\n        for field in fields:\n            build_config.pop(field, None)\n\n    def update_input_types(self, build_config: dotdict) -> dotdict:\n        \"\"\"Update input types for all fields in build_config.\"\"\"\n        for key, value in build_config.items():\n            if isinstance(value, dict):\n                if value.get(\"input_types\") is None:\n                    build_config[key][\"input_types\"] = []\n            elif hasattr(value, \"input_types\") and value.input_types is None:\n                value.input_types = []\n        return build_config\n\n    async def update_build_config(\n        self, build_config: dotdict, field_value: str, field_name: str | None = None\n    ) -> dotdict:\n        # Iterate over all providers in the MODEL_PROVIDERS_DICT\n        # Existing logic for updating build_config\n        if field_name in (\"agent_llm\",):\n            build_config[\"agent_llm\"][\"value\"] = field_value\n            provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call the component class's update_build_config method\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n\n            provider_configs: dict[str, tuple[dict, list[dict]]] = {\n                provider: (\n                    MODEL_PROVIDERS_DICT[provider][\"fields\"],\n                    [\n                        MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n                        for other_provider in MODEL_PROVIDERS_DICT\n                        if other_provider != provider\n                    ],\n                )\n                for provider in MODEL_PROVIDERS_DICT\n            }\n            if field_value in provider_configs:\n                fields_to_add, fields_to_delete = provider_configs[field_value]\n\n                # Delete fields from other providers\n                for fields in fields_to_delete:\n                    self.delete_fields(build_config, fields)\n\n                # Add provider-specific fields\n                if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n                    build_config.update(fields_to_add)\n                else:\n                    build_config.update(fields_to_add)\n                # Reset input types for agent_llm\n                build_config[\"agent_llm\"][\"input_types\"] = []\n            elif field_value == \"Custom\":\n                # Delete all provider fields\n                self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n                # Update with custom component\n                custom_component = DropdownInput(\n                    name=\"agent_llm\",\n                    display_name=\"Language Model\",\n                    options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n                    value=\"Custom\",\n                    real_time_refresh=True,\n                    input_types=[\"LanguageModel\"],\n                    options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())]\n                    + [{\"icon\": \"brain\"}],\n                )\n                build_config.update({\"agent_llm\": custom_component.to_dict()})\n            # Update input types for all fields\n            build_config = self.update_input_types(build_config)\n\n            # Validate required keys\n            default_keys = [\n                \"code\",\n                \"_type\",\n                \"agent_llm\",\n                \"tools\",\n                \"input_value\",\n                \"add_current_date_tool\",\n                \"system_prompt\",\n                \"agent_description\",\n                \"max_iterations\",\n                \"handle_parsing_errors\",\n                \"verbose\",\n            ]\n            missing_keys = [key for key in default_keys if key not in build_config]\n            if missing_keys:\n                msg = f\"Missing required keys in build_config: {missing_keys}\"\n                raise ValueError(msg)\n        if (\n            isinstance(self.agent_llm, str)\n            and self.agent_llm in MODEL_PROVIDERS_DICT\n            and field_name in MODEL_DYNAMIC_UPDATE_FIELDS\n        ):\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                component_class = self.set_component_params(component_class)\n                prefix = provider_info.get(\"prefix\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call each component class's update_build_config method\n                    # remove the prefix from the field_name\n                    if isinstance(field_name, str) and isinstance(prefix, str):\n                        field_name = field_name.replace(prefix, \"\")\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n        return dotdict({k: v.to_dict() if hasattr(v, \"to_dict\") else v for k, v in build_config.items()})\n"
              },
              "handle_parsing_errors": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Handle Parse Errors",
                "dynamic": false,
                "info": "Should the Agent fix errors when reading user input for better processing?",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "handle_parsing_errors",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "input_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "The input provided by the user for the agent to process.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "max_iterations": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Max Iterations",
                "dynamic": false,
                "info": "The maximum number of attempts the agent can make to complete its task before it stops.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "max_iterations",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 15
              },
              "memory": {
                "_input_type": "HandleInput",
                "advanced": true,
                "display_name": "External Memory",
                "dynamic": false,
                "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                "input_types": [
                  "Memory"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "memory",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "n_messages": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Messages",
                "dynamic": false,
                "info": "Number of messages to retrieve.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "n_messages",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 100
              },
              "order": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Order",
                "dynamic": false,
                "info": "Order of the messages.",
                "input_types": [],
                "name": "order",
                "options": [
                  "Ascending",
                  "Descending"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Ascending"
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Filter by sender type.",
                "input_types": [],
                "name": "sender",
                "options": [
                  "Machine",
                  "User",
                  "Machine and User"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Machine and User"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Filter by sender name.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_prompt": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "Agent Instructions",
                "dynamic": false,
                "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_prompt",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "You are a helpful assistant that can use tools to answer questions and perform tasks."
              },
              "template": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "{sender_name}: {text}"
              },
              "tools": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Tools",
                "dynamic": false,
                "info": "These are the tools that the agent can use to help with tasks.",
                "input_types": [
                  "Tool"
                ],
                "list": true,
                "list_add_label": "Add More",
                "name": "tools",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Agent"
        },
        "dragging": false,
        "id": "Agent-AGDrR",
        "measured": {
          "height": 459,
          "width": 320
        },
        "position": {
          "x": 4686.650661741705,
          "y": -1269.8525602290226
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "File-8gQuL",
          "node": {
            "base_classes": [
              "Data",
              "DataFrame",
              "Message"
            ],
            "beta": false,
            "category": "data",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Load a file to be used in your project.",
            "display_name": "File",
            "documentation": "",
            "edited": false,
            "field_order": [
              "path",
              "file_path",
              "separator",
              "silent_errors",
              "delete_server_file_after_processing",
              "ignore_unsupported_extensions",
              "ignore_unspecified_files",
              "use_multithreading",
              "concurrency_multithreading"
            ],
            "frozen": false,
            "icon": "file-text",
            "key": "File",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Data",
                "method": "load_files",
                "name": "data",
                "required_inputs": [],
                "selected": "Data",
                "tool_mode": true,
                "types": [
                  "Data"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "DataFrame",
                "hidden": false,
                "method": "load_dataframe",
                "name": "dataframe",
                "required_inputs": [],
                "selected": "DataFrame",
                "tool_mode": true,
                "types": [
                  "DataFrame"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "load_message",
                "name": "message",
                "required_inputs": [],
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 9.159206968830713e-17,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.data import BaseFileComponent\nfrom langflow.base.data.utils import TEXT_FILE_TYPES, parallel_load_data, parse_text_file_to_data\nfrom langflow.io import BoolInput, IntInput\nfrom langflow.schema import Data\n\n\nclass FileComponent(BaseFileComponent):\n    \"\"\"Handles loading and processing of individual or zipped text files.\n\n    This component supports processing multiple valid files within a zip archive,\n    resolving paths, validating file types, and optionally using multithreading for processing.\n    \"\"\"\n\n    display_name = \"File\"\n    description = \"Load a file to be used in your project.\"\n    icon = \"file-text\"\n    name = \"File\"\n\n    VALID_EXTENSIONS = TEXT_FILE_TYPES\n\n    inputs = [\n        *BaseFileComponent._base_inputs,\n        BoolInput(\n            name=\"use_multithreading\",\n            display_name=\"[Deprecated] Use Multithreading\",\n            advanced=True,\n            value=True,\n            info=\"Set 'Processing Concurrency' greater than 1 to enable multithreading.\",\n        ),\n        IntInput(\n            name=\"concurrency_multithreading\",\n            display_name=\"Processing Concurrency\",\n            advanced=True,\n            info=\"When multiple files are being processed, the number of files to process concurrently.\",\n            value=1,\n        ),\n    ]\n\n    outputs = [\n        *BaseFileComponent._base_outputs,\n    ]\n\n    def process_files(self, file_list: list[BaseFileComponent.BaseFile]) -> list[BaseFileComponent.BaseFile]:\n        \"\"\"Processes files either sequentially or in parallel, depending on concurrency settings.\n\n        Args:\n            file_list (list[BaseFileComponent.BaseFile]): List of files to process.\n\n        Returns:\n            list[BaseFileComponent.BaseFile]: Updated list of files with merged data.\n        \"\"\"\n\n        def process_file(file_path: str, *, silent_errors: bool = False) -> Data | None:\n            \"\"\"Processes a single file and returns its Data object.\"\"\"\n            try:\n                return parse_text_file_to_data(file_path, silent_errors=silent_errors)\n            except FileNotFoundError as e:\n                msg = f\"File not found: {file_path}. Error: {e}\"\n                self.log(msg)\n                if not silent_errors:\n                    raise\n                return None\n            except Exception as e:\n                msg = f\"Unexpected error processing {file_path}: {e}\"\n                self.log(msg)\n                if not silent_errors:\n                    raise\n                return None\n\n        if not file_list:\n            msg = \"No files to process.\"\n            raise ValueError(msg)\n\n        concurrency = 1 if not self.use_multithreading else max(1, self.concurrency_multithreading)\n        file_count = len(file_list)\n\n        parallel_processing_threshold = 2\n        if concurrency < parallel_processing_threshold or file_count < parallel_processing_threshold:\n            if file_count > 1:\n                self.log(f\"Processing {file_count} files sequentially.\")\n            processed_data = [process_file(str(file.path), silent_errors=self.silent_errors) for file in file_list]\n        else:\n            self.log(f\"Starting parallel processing of {file_count} files with concurrency: {concurrency}.\")\n            file_paths = [str(file.path) for file in file_list]\n            processed_data = parallel_load_data(\n                file_paths,\n                silent_errors=self.silent_errors,\n                load_function=process_file,\n                max_concurrency=concurrency,\n            )\n\n        # Use rollup_basefile_data to merge processed data with BaseFile objects\n        return self.rollup_data(file_list, processed_data)\n"
              },
              "concurrency_multithreading": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Processing Concurrency",
                "dynamic": false,
                "info": "When multiple files are being processed, the number of files to process concurrently.",
                "list": false,
                "list_add_label": "Add More",
                "name": "concurrency_multithreading",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 1
              },
              "delete_server_file_after_processing": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Delete Server File After Processing",
                "dynamic": false,
                "info": "If true, the Server File Path will be deleted after processing.",
                "list": false,
                "list_add_label": "Add More",
                "name": "delete_server_file_after_processing",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "file_path": {
                "_input_type": "HandleInput",
                "advanced": true,
                "display_name": "Server File Path",
                "dynamic": false,
                "info": "Data object with a 'file_path' property pointing to server file or a Message object with a path to the file. Supercedes 'Path' but supports same file types.",
                "input_types": [
                  "Data",
                  "Message"
                ],
                "list": true,
                "list_add_label": "Add More",
                "name": "file_path",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "ignore_unspecified_files": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Ignore Unspecified Files",
                "dynamic": false,
                "info": "If true, Data with no 'file_path' property will be ignored.",
                "list": false,
                "list_add_label": "Add More",
                "name": "ignore_unspecified_files",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "ignore_unsupported_extensions": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Ignore Unsupported Extensions",
                "dynamic": false,
                "info": "If true, files with unsupported extensions will not be processed.",
                "list": false,
                "list_add_label": "Add More",
                "name": "ignore_unsupported_extensions",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "path": {
                "_input_type": "FileInput",
                "advanced": false,
                "display_name": "Files",
                "dynamic": false,
                "fileTypes": [
                  "txt",
                  "md",
                  "mdx",
                  "csv",
                  "json",
                  "yaml",
                  "yml",
                  "xml",
                  "html",
                  "htm",
                  "pdf",
                  "docx",
                  "py",
                  "sh",
                  "sql",
                  "js",
                  "ts",
                  "tsx",
                  "zip",
                  "tar",
                  "tgz",
                  "bz2",
                  "gz"
                ],
                "file_path": [
                  "9d0099b1-a77d-47a6-add8-91abafc6ba5d/de956d5c-66ef-4888-98bb-815fc46faed6.csv"
                ],
                "info": "Supported file extensions: txt, md, mdx, csv, json, yaml, yml, xml, html, htm, pdf, docx, py, sh, sql, js, ts, tsx; optionally bundled in file extensions: zip, tar, tgz, bz2, gz",
                "list": true,
                "list_add_label": "Add More",
                "name": "path",
                "placeholder": "",
                "required": false,
                "show": true,
                "temp_file": false,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "file",
                "value": ""
              },
              "separator": {
                "_input_type": "StrInput",
                "advanced": true,
                "display_name": "Separator",
                "dynamic": false,
                "info": "Specify the separator to use between multiple outputs in Message format.",
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "separator",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "\n\n"
              },
              "silent_errors": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Silent Errors",
                "dynamic": false,
                "info": "If true, errors will not raise an exception.",
                "list": false,
                "list_add_label": "Add More",
                "name": "silent_errors",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "use_multithreading": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "[Deprecated] Use Multithreading",
                "dynamic": false,
                "info": "Set 'Processing Concurrency' greater than 1 to enable multithreading.",
                "list": false,
                "list_add_label": "Add More",
                "name": "use_multithreading",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "File"
        },
        "dragging": false,
        "id": "File-8gQuL",
        "measured": {
          "height": 340,
          "width": 320
        },
        "position": {
          "x": -497.04913086508054,
          "y": -631.6170491193668
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "DataFrameOperationsComponent-iVb8k",
          "node": {
            "base_classes": [
              "DataFrame"
            ],
            "beta": false,
            "category": "processing",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Perform various operations on a DataFrame.",
            "display_name": "DataFrame Operations",
            "documentation": "",
            "edited": false,
            "field_order": [
              "df",
              "operation",
              "column_name",
              "filter_value",
              "ascending",
              "new_column_name",
              "new_column_value",
              "columns_to_select",
              "num_rows",
              "replace_value",
              "replacement_value"
            ],
            "frozen": false,
            "icon": "table",
            "key": "DataFrameOperationsComponent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "DataFrame",
                "hidden": false,
                "method": "perform_operation",
                "name": "output",
                "options": null,
                "required_inputs": null,
                "selected": "DataFrame",
                "tool_mode": true,
                "types": [
                  "DataFrame"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.007568328950209746,
            "template": {
              "_type": "Component",
              "ascending": {
                "_input_type": "BoolInput",
                "advanced": false,
                "display_name": "Sort Ascending",
                "dynamic": true,
                "info": "Whether to sort in ascending order.",
                "list": false,
                "list_add_label": "Add More",
                "name": "ascending",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.custom import Component\nfrom langflow.io import BoolInput, DataFrameInput, DropdownInput, IntInput, MessageTextInput, Output, StrInput\nfrom langflow.schema import DataFrame\n\n\nclass DataFrameOperationsComponent(Component):\n    display_name = \"DataFrame Operations\"\n    description = \"Perform various operations on a DataFrame.\"\n    icon = \"table\"\n\n    # Available operations\n    OPERATION_CHOICES = [\n        \"Add Column\",\n        \"Drop Column\",\n        \"Filter\",\n        \"Head\",\n        \"Rename Column\",\n        \"Replace Value\",\n        \"Select Columns\",\n        \"Sort\",\n        \"Tail\",\n    ]\n\n    inputs = [\n        DataFrameInput(\n            name=\"df\",\n            display_name=\"DataFrame\",\n            info=\"The input DataFrame to operate on.\",\n        ),\n        DropdownInput(\n            name=\"operation\",\n            display_name=\"Operation\",\n            options=OPERATION_CHOICES,\n            info=\"Select the DataFrame operation to perform.\",\n            real_time_refresh=True,\n        ),\n        StrInput(\n            name=\"column_name\",\n            display_name=\"Column Name\",\n            info=\"The column name to use for the operation.\",\n            dynamic=True,\n            show=False,\n        ),\n        MessageTextInput(\n            name=\"filter_value\",\n            display_name=\"Filter Value\",\n            info=\"The value to filter rows by.\",\n            dynamic=True,\n            show=False,\n        ),\n        BoolInput(\n            name=\"ascending\",\n            display_name=\"Sort Ascending\",\n            info=\"Whether to sort in ascending order.\",\n            dynamic=True,\n            show=False,\n            value=True,\n        ),\n        StrInput(\n            name=\"new_column_name\",\n            display_name=\"New Column Name\",\n            info=\"The new column name when renaming or adding a column.\",\n            dynamic=True,\n            show=False,\n        ),\n        MessageTextInput(\n            name=\"new_column_value\",\n            display_name=\"New Column Value\",\n            info=\"The value to populate the new column with.\",\n            dynamic=True,\n            show=False,\n        ),\n        StrInput(\n            name=\"columns_to_select\",\n            display_name=\"Columns to Select\",\n            dynamic=True,\n            is_list=True,\n            show=False,\n        ),\n        IntInput(\n            name=\"num_rows\",\n            display_name=\"Number of Rows\",\n            info=\"Number of rows to return (for head/tail).\",\n            dynamic=True,\n            show=False,\n            value=5,\n        ),\n        MessageTextInput(\n            name=\"replace_value\",\n            display_name=\"Value to Replace\",\n            info=\"The value to replace in the column.\",\n            dynamic=True,\n            show=False,\n        ),\n        MessageTextInput(\n            name=\"replacement_value\",\n            display_name=\"Replacement Value\",\n            info=\"The value to replace with.\",\n            dynamic=True,\n            show=False,\n        ),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"DataFrame\",\n            name=\"output\",\n            method=\"perform_operation\",\n            info=\"The resulting DataFrame after the operation.\",\n        )\n    ]\n\n    def update_build_config(self, build_config, field_value, field_name=None):\n        # Hide all dynamic fields by default\n        dynamic_fields = [\n            \"column_name\",\n            \"filter_value\",\n            \"ascending\",\n            \"new_column_name\",\n            \"new_column_value\",\n            \"columns_to_select\",\n            \"num_rows\",\n            \"replace_value\",\n            \"replacement_value\",\n        ]\n        for field in dynamic_fields:\n            build_config[field][\"show\"] = False\n\n        # Show relevant fields based on the selected operation\n        if field_name == \"operation\":\n            if field_value == \"Filter\":\n                build_config[\"column_name\"][\"show\"] = True\n                build_config[\"filter_value\"][\"show\"] = True\n            elif field_value == \"Sort\":\n                build_config[\"column_name\"][\"show\"] = True\n                build_config[\"ascending\"][\"show\"] = True\n            elif field_value == \"Drop Column\":\n                build_config[\"column_name\"][\"show\"] = True\n            elif field_value == \"Rename Column\":\n                build_config[\"column_name\"][\"show\"] = True\n                build_config[\"new_column_name\"][\"show\"] = True\n            elif field_value == \"Add Column\":\n                build_config[\"new_column_name\"][\"show\"] = True\n                build_config[\"new_column_value\"][\"show\"] = True\n            elif field_value == \"Select Columns\":\n                build_config[\"columns_to_select\"][\"show\"] = True\n            elif field_value in {\"Head\", \"Tail\"}:\n                build_config[\"num_rows\"][\"show\"] = True\n            elif field_value == \"Replace Value\":\n                build_config[\"column_name\"][\"show\"] = True\n                build_config[\"replace_value\"][\"show\"] = True\n                build_config[\"replacement_value\"][\"show\"] = True\n\n        return build_config\n\n    def perform_operation(self) -> DataFrame:\n        dataframe_copy = self.df.copy()\n        operation = self.operation\n\n        if operation == \"Filter\":\n            return self.filter_rows_by_value(dataframe_copy)\n        if operation == \"Sort\":\n            return self.sort_by_column(dataframe_copy)\n        if operation == \"Drop Column\":\n            return self.drop_column(dataframe_copy)\n        if operation == \"Rename Column\":\n            return self.rename_column(dataframe_copy)\n        if operation == \"Add Column\":\n            return self.add_column(dataframe_copy)\n        if operation == \"Select Columns\":\n            return self.select_columns(dataframe_copy)\n        if operation == \"Head\":\n            return self.head(dataframe_copy)\n        if operation == \"Tail\":\n            return self.tail(dataframe_copy)\n        if operation == \"Replace Value\":\n            return self.replace_values(dataframe_copy)\n        msg = f\"Unsupported operation: {operation}\"\n\n        raise ValueError(msg)\n\n    # Existing methods\n    def filter_rows_by_value(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df[df[self.column_name] == self.filter_value])\n\n    def sort_by_column(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df.sort_values(by=self.column_name, ascending=self.ascending))\n\n    def drop_column(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df.drop(columns=[self.column_name]))\n\n    def rename_column(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df.rename(columns={self.column_name: self.new_column_name}))\n\n    def add_column(self, df: DataFrame) -> DataFrame:\n        df[self.new_column_name] = [self.new_column_value] * len(df)\n        return DataFrame(df)\n\n    def select_columns(self, df: DataFrame) -> DataFrame:\n        columns = [col.strip() for col in self.columns_to_select]\n        return DataFrame(df[columns])\n\n    # New methods\n    def head(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df.head(self.num_rows))\n\n    def tail(self, df: DataFrame) -> DataFrame:\n        return DataFrame(df.tail(self.num_rows))\n\n    def replace_values(self, df: DataFrame) -> DataFrame:\n        df[self.column_name] = df[self.column_name].replace(self.replace_value, self.replacement_value)\n        return DataFrame(df)\n"
              },
              "column_name": {
                "_input_type": "StrInput",
                "advanced": false,
                "display_name": "Column Name",
                "dynamic": true,
                "info": "The column name to use for the operation.",
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "column_name",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "columns_to_select": {
                "_input_type": "StrInput",
                "advanced": false,
                "display_name": "Columns to Select",
                "dynamic": true,
                "info": "",
                "list": true,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "columns_to_select",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "df": {
                "_input_type": "DataFrameInput",
                "advanced": false,
                "display_name": "DataFrame",
                "dynamic": false,
                "info": "The input DataFrame to operate on.",
                "input_types": [
                  "DataFrame"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "df",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "filter_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Filter Value",
                "dynamic": true,
                "info": "The value to filter rows by.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "filter_value",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "new_column_name": {
                "_input_type": "StrInput",
                "advanced": false,
                "display_name": "New Column Name",
                "dynamic": true,
                "info": "The new column name when renaming or adding a column.",
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "new_column_name",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "new_column_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "New Column Value",
                "dynamic": true,
                "info": "The value to populate the new column with.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "new_column_value",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "num_rows": {
                "_input_type": "IntInput",
                "advanced": false,
                "display_name": "Number of Rows",
                "dynamic": true,
                "info": "Number of rows to return (for head/tail).",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_rows",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 5
              },
              "operation": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Operation",
                "dynamic": false,
                "info": "Select the DataFrame operation to perform.",
                "name": "operation",
                "options": [
                  "Add Column",
                  "Drop Column",
                  "Filter",
                  "Head",
                  "Rename Column",
                  "Replace Value",
                  "Select Columns",
                  "Sort",
                  "Tail"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Head"
              },
              "replace_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Value to Replace",
                "dynamic": true,
                "info": "The value to replace in the column.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "replace_value",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "replacement_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Replacement Value",
                "dynamic": true,
                "info": "The value to replace with.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "replacement_value",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "DataFrameOperationsComponent"
        },
        "dragging": false,
        "id": "DataFrameOperationsComponent-iVb8k",
        "measured": {
          "height": 357,
          "width": 320
        },
        "position": {
          "x": -88.07132386375883,
          "y": -766.2247788885181
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "ParserComponent-gE82G",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "processing",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Format a DataFrame or Data object into text using a template. Enable 'Stringify' to convert input into a readable string instead.",
            "display_name": "Parser",
            "documentation": "",
            "edited": false,
            "field_order": [
              "mode",
              "pattern",
              "input_data",
              "sep"
            ],
            "frozen": false,
            "icon": "braces",
            "key": "ParserComponent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Parsed Text",
                "hidden": false,
                "method": "parse_combined_text",
                "name": "parsed_text",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.5915955070868325,
            "template": {
              "_type": "Component",
              "clean_data": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Clean Data",
                "dynamic": false,
                "info": "Enable to clean the data by removing empty rows and lines in each cell of the DataFrame/ Data object.",
                "list": false,
                "list_add_label": "Add More",
                "name": "clean_data",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import json\nfrom typing import Any\n\nfrom langflow.custom import Component\nfrom langflow.io import (\n    BoolInput,\n    HandleInput,\n    MessageTextInput,\n    MultilineInput,\n    Output,\n    TabInput,\n)\nfrom langflow.schema import Data, DataFrame\nfrom langflow.schema.message import Message\n\n\nclass ParserComponent(Component):\n    display_name = \"Parser\"\n    description = (\n        \"Format a DataFrame or Data object into text using a template. \"\n        \"Enable 'Stringify' to convert input into a readable string instead.\"\n    )\n    icon = \"braces\"\n\n    inputs = [\n        TabInput(\n            name=\"mode\",\n            display_name=\"Mode\",\n            options=[\"Parser\", \"Stringify\"],\n            value=\"Parser\",\n            info=\"Convert into raw string instead of using a template.\",\n            real_time_refresh=True,\n        ),\n        MultilineInput(\n            name=\"pattern\",\n            display_name=\"Template\",\n            info=(\n                \"Use variables within curly brackets to extract column values for DataFrames \"\n                \"or key values for Data.\"\n                \"For example: `Name: {Name}, Age: {Age}, Country: {Country}`\"\n            ),\n            value=\"Text: {text}\",  # Example default\n            dynamic=True,\n            show=True,\n            required=True,\n        ),\n        HandleInput(\n            name=\"input_data\",\n            display_name=\"Data or DataFrame\",\n            input_types=[\"DataFrame\", \"Data\"],\n            info=\"Accepts either a DataFrame or a Data object.\",\n            required=True,\n        ),\n        MessageTextInput(\n            name=\"sep\",\n            display_name=\"Separator\",\n            advanced=True,\n            value=\"\\n\",\n            info=\"String used to separate rows/items.\",\n        ),\n    ]\n\n    outputs = [\n        Output(\n            display_name=\"Parsed Text\",\n            name=\"parsed_text\",\n            info=\"Formatted text output.\",\n            method=\"parse_combined_text\",\n        ),\n    ]\n\n    def update_build_config(self, build_config, field_value, field_name=None):\n        \"\"\"Dynamically hide/show `template` and enforce requirement based on `stringify`.\"\"\"\n        if field_name == \"mode\":\n            build_config[\"pattern\"][\"show\"] = self.mode == \"Parser\"\n            build_config[\"pattern\"][\"required\"] = self.mode == \"Parser\"\n            if field_value:\n                clean_data = BoolInput(\n                    name=\"clean_data\",\n                    display_name=\"Clean Data\",\n                    info=(\n                        \"Enable to clean the data by removing empty rows and lines \"\n                        \"in each cell of the DataFrame/ Data object.\"\n                    ),\n                    value=True,\n                    advanced=True,\n                    required=False,\n                )\n                build_config[\"clean_data\"] = clean_data.to_dict()\n            else:\n                build_config.pop(\"clean_data\", None)\n\n        return build_config\n\n    def _clean_args(self):\n        \"\"\"Prepare arguments based on input type.\"\"\"\n        input_data = self.input_data\n\n        match input_data:\n            case list() if all(isinstance(item, Data) for item in input_data):\n                msg = \"List of Data objects is not supported.\"\n                raise ValueError(msg)\n            case DataFrame():\n                return input_data, None\n            case Data():\n                return None, input_data\n            case dict() if \"data\" in input_data:\n                try:\n                    if \"columns\" in input_data:  # Likely a DataFrame\n                        return DataFrame.from_dict(input_data), None\n                    # Likely a Data object\n                    return None, Data(**input_data)\n                except (TypeError, ValueError, KeyError) as e:\n                    msg = f\"Invalid structured input provided: {e!s}\"\n                    raise ValueError(msg) from e\n            case _:\n                msg = f\"Unsupported input type: {type(input_data)}. Expected DataFrame or Data.\"\n                raise ValueError(msg)\n\n    def parse_combined_text(self) -> Message:\n        \"\"\"Parse all rows/items into a single text or convert input to string if `stringify` is enabled.\"\"\"\n        # Early return for stringify option\n        if self.mode == \"Stringify\":\n            return self.convert_to_string()\n\n        df, data = self._clean_args()\n\n        lines = []\n        if df is not None:\n            for _, row in df.iterrows():\n                formatted_text = self.pattern.format(**row.to_dict())\n                lines.append(formatted_text)\n        elif data is not None:\n            formatted_text = self.pattern.format(**data.data)\n            lines.append(formatted_text)\n\n        combined_text = self.sep.join(lines)\n        self.status = combined_text\n        return Message(text=combined_text)\n\n    def _safe_convert(self, data: Any) -> str:\n        \"\"\"Safely convert input data to string.\"\"\"\n        try:\n            if isinstance(data, str):\n                return data\n            if isinstance(data, Message):\n                return data.get_text()\n            if isinstance(data, Data):\n                return json.dumps(data.data)\n            if isinstance(data, DataFrame):\n                if hasattr(self, \"clean_data\") and self.clean_data:\n                    # Remove empty rows\n                    data = data.dropna(how=\"all\")\n                    # Remove empty lines in each cell\n                    data = data.replace(r\"^\\s*$\", \"\", regex=True)\n                    # Replace multiple newlines with a single newline\n                    data = data.replace(r\"\\n+\", \"\\n\", regex=True)\n                return data.to_markdown(index=False)\n            return str(data)\n        except (ValueError, TypeError, AttributeError) as e:\n            msg = f\"Error converting data: {e!s}\"\n            raise ValueError(msg) from e\n\n    def convert_to_string(self) -> Message:\n        \"\"\"Convert input data to string with proper error handling.\"\"\"\n        result = \"\"\n        if isinstance(self.input_data, list):\n            result = \"\\n\".join([self._safe_convert(item) for item in self.input_data])\n        else:\n            result = self._safe_convert(self.input_data)\n        self.log(f\"Converted to string with length: {len(result)}\")\n\n        message = Message(text=result)\n        self.status = message\n        return message\n"
              },
              "input_data": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Data or DataFrame",
                "dynamic": false,
                "info": "Accepts either a DataFrame or a Data object.",
                "input_types": [
                  "DataFrame",
                  "Data"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "input_data",
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "mode": {
                "_input_type": "TabInput",
                "advanced": false,
                "display_name": "Mode",
                "dynamic": false,
                "info": "Convert into raw string instead of using a template.",
                "name": "mode",
                "options": [
                  "Parser",
                  "Stringify"
                ],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "tab",
                "value": "Stringify"
              },
              "pattern": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "Template",
                "dynamic": true,
                "info": "Use variables within curly brackets to extract column values for DataFrames or key values for Data.For example: `Name: {Name}, Age: {Age}, Country: {Country}`",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "pattern",
                "placeholder": "",
                "required": false,
                "show": false,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Text: {text}"
              },
              "sep": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Separator",
                "dynamic": false,
                "info": "String used to separate rows/items.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sep",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "\n"
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "ParserComponent"
        },
        "dragging": false,
        "id": "ParserComponent-gE82G",
        "measured": {
          "height": 312,
          "width": 320
        },
        "position": {
          "x": 263.07612731224384,
          "y": -562.8745131720065
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "OllamaModel-KJfnQ",
          "node": {
            "base_classes": [
              "LanguageModel",
              "Message"
            ],
            "beta": false,
            "category": "models",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Generate text using Ollama Local LLMs.",
            "display_name": "AanalyzerModel",
            "documentation": "",
            "edited": false,
            "field_order": [
              "base_url",
              "model_name",
              "temperature",
              "format",
              "metadata",
              "mirostat",
              "mirostat_eta",
              "mirostat_tau",
              "num_ctx",
              "num_gpu",
              "num_thread",
              "repeat_last_n",
              "repeat_penalty",
              "tfs_z",
              "timeout",
              "top_k",
              "top_p",
              "verbose",
              "tags",
              "stop_tokens",
              "system",
              "tool_model_enabled",
              "template",
              "input_value",
              "system_message",
              "stream"
            ],
            "frozen": false,
            "icon": "Ollama",
            "key": "OllamaModel",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "text_response",
                "name": "text_output",
                "options": null,
                "required_inputs": [],
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Language Model",
                "hidden": false,
                "method": "build_model",
                "name": "model_output",
                "options": null,
                "required_inputs": [],
                "selected": "LanguageModel",
                "tool_mode": true,
                "types": [
                  "LanguageModel"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 1.1514907767935298e-16,
            "template": {
              "_type": "Component",
              "base_url": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Base URL",
                "dynamic": false,
                "info": "Endpoint of the Ollama API.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "base_url",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "http://localhost:11434"
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import asyncio\nfrom typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import ChatOllama\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.ollama_constants import OLLAMA_TOOL_MODELS_BASE, URL_LIST\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SliderInput\nfrom langflow.logging import logger\n\nHTTP_STATUS_OK = 200\n\n\nclass ChatOllamaComponent(LCModelComponent):\n    display_name = \"Ollama\"\n    description = \"Generate text using Ollama Local LLMs.\"\n    icon = \"Ollama\"\n    name = \"OllamaModel\"\n\n    # Define constants for JSON keys\n    JSON_MODELS_KEY = \"models\"\n    JSON_NAME_KEY = \"name\"\n    JSON_CAPABILITIES_KEY = \"capabilities\"\n    DESIRED_CAPABILITY = \"completion\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Base URL\",\n            info=\"Endpoint of the Ollama API.\",\n            value=\"\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=[],\n            info=\"Refer to https://ollama.com/library for more models.\",\n            refresh_button=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"format\", display_name=\"Format\", info=\"Specify the format of the output (e.g., json).\", advanced=True\n        ),\n        DictInput(name=\"metadata\", display_name=\"Metadata\", info=\"Metadata to add to the run trace.\", advanced=True),\n        DropdownInput(\n            name=\"mirostat\",\n            display_name=\"Mirostat\",\n            options=[\"Disabled\", \"Mirostat\", \"Mirostat 2.0\"],\n            info=\"Enable/disable Mirostat sampling for controlling perplexity.\",\n            value=\"Disabled\",\n            advanced=True,\n            real_time_refresh=True,\n        ),\n        FloatInput(\n            name=\"mirostat_eta\",\n            display_name=\"Mirostat Eta\",\n            info=\"Learning rate for Mirostat algorithm. (Default: 0.1)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"mirostat_tau\",\n            display_name=\"Mirostat Tau\",\n            info=\"Controls the balance between coherence and diversity of the output. (Default: 5.0)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_ctx\",\n            display_name=\"Context Window Size\",\n            info=\"Size of the context window for generating tokens. (Default: 2048)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_gpu\",\n            display_name=\"Number of GPUs\",\n            info=\"Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_thread\",\n            display_name=\"Number of Threads\",\n            info=\"Number of threads to use during computation. (Default: detected for optimal performance)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"repeat_last_n\",\n            display_name=\"Repeat Last N\",\n            info=\"How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"repeat_penalty\",\n            display_name=\"Repeat Penalty\",\n            info=\"Penalty for repetitions in generated text. (Default: 1.1)\",\n            advanced=True,\n        ),\n        FloatInput(name=\"tfs_z\", display_name=\"TFS Z\", info=\"Tail free sampling value. (Default: 1)\", advanced=True),\n        IntInput(name=\"timeout\", display_name=\"Timeout\", info=\"Timeout for the request stream.\", advanced=True),\n        IntInput(\n            name=\"top_k\", display_name=\"Top K\", info=\"Limits token selection to top K. (Default: 40)\", advanced=True\n        ),\n        FloatInput(name=\"top_p\", display_name=\"Top P\", info=\"Works together with top-k. (Default: 0.9)\", advanced=True),\n        BoolInput(name=\"verbose\", display_name=\"Verbose\", info=\"Whether to print out response text.\", advanced=True),\n        MessageTextInput(\n            name=\"tags\",\n            display_name=\"Tags\",\n            info=\"Comma-separated list of tags to add to the run trace.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"stop_tokens\",\n            display_name=\"Stop Tokens\",\n            info=\"Comma-separated list of tokens to signal the model to stop generating text.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"system\", display_name=\"System\", info=\"System to use for generating text.\", advanced=True\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Tool Model Enabled\",\n            info=\"Whether to enable tool calling in the model.\",\n            value=False,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"template\", display_name=\"Template\", info=\"Template to use for generating text.\", advanced=True\n        ),\n        *LCModelComponent._base_inputs,\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        # Mapping mirostat settings to their corresponding values\n        mirostat_options = {\"Mirostat\": 1, \"Mirostat 2.0\": 2}\n\n        # Default to 0 for 'Disabled'\n        mirostat_value = mirostat_options.get(self.mirostat, 0)\n\n        # Set mirostat_eta and mirostat_tau to None if mirostat is disabled\n        if mirostat_value == 0:\n            mirostat_eta = None\n            mirostat_tau = None\n        else:\n            mirostat_eta = self.mirostat_eta\n            mirostat_tau = self.mirostat_tau\n\n        # Mapping system settings to their corresponding values\n        llm_params = {\n            \"base_url\": self.base_url,\n            \"model\": self.model_name,\n            \"mirostat\": mirostat_value,\n            \"format\": self.format,\n            \"metadata\": self.metadata,\n            \"tags\": self.tags.split(\",\") if self.tags else None,\n            \"mirostat_eta\": mirostat_eta,\n            \"mirostat_tau\": mirostat_tau,\n            \"num_ctx\": self.num_ctx or None,\n            \"num_gpu\": self.num_gpu or None,\n            \"num_thread\": self.num_thread or None,\n            \"repeat_last_n\": self.repeat_last_n or None,\n            \"repeat_penalty\": self.repeat_penalty or None,\n            \"temperature\": self.temperature or None,\n            \"stop\": self.stop_tokens.split(\",\") if self.stop_tokens else None,\n            \"system\": self.system,\n            \"tfs_z\": self.tfs_z or None,\n            \"timeout\": self.timeout or None,\n            \"top_k\": self.top_k or None,\n            \"top_p\": self.top_p or None,\n            \"verbose\": self.verbose,\n            \"template\": self.template,\n        }\n\n        # Remove parameters with None values\n        llm_params = {k: v for k, v in llm_params.items() if v is not None}\n\n        try:\n            output = ChatOllama(**llm_params)\n        except Exception as e:\n            msg = (\n                \"Unable to connect to the Ollama API. \",\n                \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n            )\n            raise ValueError(msg) from e\n\n        return output\n\n    async def is_valid_ollama_url(self, url: str) -> bool:\n        try:\n            async with httpx.AsyncClient() as client:\n                return (await client.get(urljoin(url, \"api/tags\"))).status_code == HTTP_STATUS_OK\n        except httpx.RequestError:\n            return False\n\n    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n        if field_name == \"mirostat\":\n            if field_value == \"Disabled\":\n                build_config[\"mirostat_eta\"][\"advanced\"] = True\n                build_config[\"mirostat_tau\"][\"advanced\"] = True\n                build_config[\"mirostat_eta\"][\"value\"] = None\n                build_config[\"mirostat_tau\"][\"value\"] = None\n\n            else:\n                build_config[\"mirostat_eta\"][\"advanced\"] = False\n                build_config[\"mirostat_tau\"][\"advanced\"] = False\n\n                if field_value == \"Mirostat 2.0\":\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.2\n                    build_config[\"mirostat_tau\"][\"value\"] = 10\n                else:\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.1\n                    build_config[\"mirostat_tau\"][\"value\"] = 5\n\n        if field_name in {\"base_url\", \"model_name\"}:\n            if build_config[\"base_url\"].get(\"load_from_db\", False):\n                base_url_value = await self.get_variables(build_config[\"base_url\"].get(\"value\", \"\"), \"base_url\")\n            else:\n                base_url_value = build_config[\"base_url\"].get(\"value\", \"\")\n\n            if not await self.is_valid_ollama_url(base_url_value):\n                # Check if any URL in the list is valid\n                valid_url = \"\"\n                check_urls = URL_LIST\n                if self.base_url:\n                    check_urls = [self.base_url, *URL_LIST]\n                for url in check_urls:\n                    if await self.is_valid_ollama_url(url):\n                        valid_url = url\n                        break\n                if valid_url != \"\":\n                    build_config[\"base_url\"][\"value\"] = valid_url\n                else:\n                    msg = \"No valid Ollama URL found.\"\n                    raise ValueError(msg)\n        if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n            if await self.is_valid_ollama_url(self.base_url):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(self.base_url, tool_model_enabled)\n            elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(\n                    build_config[\"base_url\"].get(\"value\", \"\"), tool_model_enabled\n                )\n            else:\n                build_config[\"model_name\"][\"options\"] = []\n        if field_name == \"keep_alive_flag\":\n            if field_value == \"Keep\":\n                build_config[\"keep_alive\"][\"value\"] = \"-1\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            elif field_value == \"Immediately\":\n                build_config[\"keep_alive\"][\"value\"] = \"0\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            else:\n                build_config[\"keep_alive\"][\"advanced\"] = False\n\n        return build_config\n\n    async def get_models(self, base_url_value: str, tool_model_enabled: bool | None = None) -> list[str]:\n        \"\"\"Fetches a list of models from the Ollama API that do not have the \"embedding\" capability.\n\n        Args:\n            base_url_value (str): The base URL of the Ollama API.\n            tool_model_enabled (bool | None, optional): If True, filters the models further to include\n                only those that support tool calling. Defaults to None.\n\n        Returns:\n            list[str]: A list of model names that do not have the \"embedding\" capability. If\n                `tool_model_enabled` is True, only models supporting tool calling are included.\n\n        Raises:\n            ValueError: If there is an issue with the API request or response, or if the model\n                names cannot be retrieved.\n        \"\"\"\n        try:\n            # Normalize the base URL to avoid the repeated \"/\" at the end\n            base_url = base_url_value.rstrip(\"/\") + \"/\"\n\n            # Ollama REST API to return models\n            tags_url = urljoin(base_url, \"api/tags\")\n\n            # Ollama REST API to return model capabilities\n            show_url = urljoin(base_url, \"api/show\")\n\n            async with httpx.AsyncClient() as client:\n                # Fetch available models\n                tags_response = await client.get(tags_url)\n                tags_response.raise_for_status()\n                models = tags_response.json()\n                if asyncio.iscoroutine(models):\n                    models = await models\n                logger.debug(f\"Available models: {models}\")\n\n                # Filter models that are NOT embedding models\n                model_ids = []\n                for model in models[self.JSON_MODELS_KEY]:\n                    model_name = model[self.JSON_NAME_KEY]\n                    logger.debug(f\"Checking model: {model_name}\")\n\n                    payload = {\"model\": model_name}\n                    show_response = await client.post(show_url, json=payload)\n                    show_response.raise_for_status()\n                    json_data = show_response.json()\n                    if asyncio.iscoroutine(json_data):\n                        json_data = await json_data\n                    capabilities = json_data.get(self.JSON_CAPABILITIES_KEY, [])\n                    logger.debug(f\"Model: {model_name}, Capabilities: {capabilities}\")\n\n                    if self.DESIRED_CAPABILITY in capabilities:\n                        model_ids.append(model_name)\n\n        except (httpx.RequestError, ValueError) as e:\n            msg = \"Could not get model names from Ollama.\"\n            raise ValueError(msg) from e\n\n        return (\n            model_ids if not tool_model_enabled else [model for model in model_ids if self.supports_tool_calling(model)]\n        )\n\n    def supports_tool_calling(self, model: str) -> bool:\n        \"\"\"Check if model name is in the base of any models example llama3.3 can have 1b and 2b.\"\"\"\n        return any(model.startswith(f\"{tool_model}\") for tool_model in OLLAMA_TOOL_MODELS_BASE)\n"
              },
              "format": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Format",
                "dynamic": false,
                "info": "Specify the format of the output (e.g., json).",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "format",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "input_value": {
                "_input_type": "MessageInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "metadata": {
                "_input_type": "DictInput",
                "advanced": true,
                "display_name": "Metadata",
                "dynamic": false,
                "info": "Metadata to add to the run trace.",
                "list": false,
                "list_add_label": "Add More",
                "name": "metadata",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "dict",
                "value": {}
              },
              "mirostat": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Mirostat",
                "dynamic": false,
                "info": "Enable/disable Mirostat sampling for controlling perplexity.",
                "name": "mirostat",
                "options": [
                  "Disabled",
                  "Mirostat",
                  "Mirostat 2.0"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Disabled"
              },
              "mirostat_eta": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Eta",
                "dynamic": false,
                "info": "Learning rate for Mirostat algorithm. (Default: 0.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_eta",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "mirostat_tau": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Tau",
                "dynamic": false,
                "info": "Controls the balance between coherence and diversity of the output. (Default: 5.0)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_tau",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "model_name": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Model Name",
                "dynamic": false,
                "info": "Refer to https://ollama.com/library for more models.",
                "name": "model_name",
                "options": [
                  "mistral:latest",
                  "llama3.2:latest",
                  "qwen2.5-coder:7b",
                  "qwen2.5:32b",
                  "llama3.2:1b",
                  "qwen2.5-coder:3b"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "refresh_button": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "llama3.2:latest"
              },
              "num_ctx": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Context Window Size",
                "dynamic": false,
                "info": "Size of the context window for generating tokens. (Default: 2048)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_ctx",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_gpu": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of GPUs",
                "dynamic": false,
                "info": "Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_gpu",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_thread": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Threads",
                "dynamic": false,
                "info": "Number of threads to use during computation. (Default: detected for optimal performance)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_thread",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_last_n": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Repeat Last N",
                "dynamic": false,
                "info": "How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_last_n",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_penalty": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Repeat Penalty",
                "dynamic": false,
                "info": "Penalty for repetitions in generated text. (Default: 1.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_penalty",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "stop_tokens": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Stop Tokens",
                "dynamic": false,
                "info": "Comma-separated list of tokens to signal the model to stop generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "stop_tokens",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "stream": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Stream",
                "dynamic": false,
                "info": "Stream the response from the model. Streaming works only in Chat.",
                "list": false,
                "list_add_label": "Add More",
                "name": "stream",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "system": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "System",
                "dynamic": false,
                "info": "System to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "system",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_message": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "System Message",
                "dynamic": false,
                "info": "System message to pass to the model.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tags": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tags",
                "dynamic": false,
                "info": "Comma-separated list of tags to add to the run trace.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tags",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "temperature": {
                "_input_type": "SliderInput",
                "advanced": true,
                "display_name": "Temperature",
                "dynamic": false,
                "info": "",
                "max_label": "",
                "max_label_icon": "",
                "min_label": "",
                "min_label_icon": "",
                "name": "temperature",
                "placeholder": "",
                "range_spec": {
                  "max": 1,
                  "min": 0,
                  "step": 0.01,
                  "step_type": "float"
                },
                "required": false,
                "show": true,
                "slider_buttons": false,
                "slider_buttons_options": [],
                "slider_input": false,
                "title_case": false,
                "tool_mode": false,
                "type": "slider",
                "value": 0.1
              },
              "template": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Template",
                "dynamic": false,
                "info": "Template to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tfs_z": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "TFS Z",
                "dynamic": false,
                "info": "Tail free sampling value. (Default: 1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "tfs_z",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "timeout": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Timeout",
                "dynamic": false,
                "info": "Timeout for the request stream.",
                "list": false,
                "list_add_label": "Add More",
                "name": "timeout",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "tool_model_enabled": {
                "_input_type": "BoolInput",
                "advanced": false,
                "display_name": "Tool Model Enabled",
                "dynamic": false,
                "info": "Whether to enable tool calling in the model.",
                "list": false,
                "list_add_label": "Add More",
                "name": "tool_model_enabled",
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "top_k": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Top K",
                "dynamic": false,
                "info": "Limits token selection to top K. (Default: 40)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_k",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "top_p": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Top P",
                "dynamic": false,
                "info": "Works together with top-k. (Default: 0.9)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_p",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "Whether to print out response text.",
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "OllamaModel"
        },
        "dragging": false,
        "id": "OllamaModel-KJfnQ",
        "measured": {
          "height": 568,
          "width": 320
        },
        "position": {
          "x": 914.7742796945215,
          "y": -1845.070959443508
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Agent-qKLwT",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "agents",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Define the agent's instructions, then enter a task to complete using tools.",
            "display_name": "AnalyzerAgent",
            "documentation": "",
            "edited": false,
            "field_order": [
              "agent_llm",
              "max_tokens",
              "model_kwargs",
              "json_mode",
              "model_name",
              "openai_api_base",
              "api_key",
              "temperature",
              "seed",
              "max_retries",
              "timeout",
              "system_prompt",
              "tools",
              "input_value",
              "handle_parsing_errors",
              "verbose",
              "max_iterations",
              "agent_description",
              "memory",
              "sender",
              "sender_name",
              "n_messages",
              "session_id",
              "order",
              "template",
              "add_current_date_tool"
            ],
            "frozen": false,
            "icon": "bot",
            "key": "Agent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Response",
                "hidden": false,
                "method": "message_response",
                "name": "response",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 1.1732828199964098e-19,
            "template": {
              "_type": "Component",
              "add_current_date_tool": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Current Date",
                "dynamic": false,
                "info": "If true, will add a tool to the agent that returns the current date.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "add_current_date_tool",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "agent_description": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Agent Description [Deprecated]",
                "dynamic": false,
                "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically. This feature is deprecated and will be removed in future versions.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "agent_description",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "A helpful assistant with access to the following tools:"
              },
              "agent_llm": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Language Model",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "LanguageModel"
                ],
                "name": "agent_llm",
                "options": [
                  "Amazon Bedrock",
                  "Anthropic",
                  "Azure OpenAI",
                  "Google Generative AI",
                  "Groq",
                  "NVIDIA",
                  "OpenAI",
                  "SambaNova",
                  "Custom"
                ],
                "options_metadata": [
                  {
                    "icon": "Amazon"
                  },
                  {
                    "icon": "Anthropic"
                  },
                  {
                    "icon": "Azure"
                  },
                  {
                    "icon": "GoogleGenerativeAI"
                  },
                  {
                    "icon": "Groq"
                  },
                  {
                    "icon": "NVIDIA"
                  },
                  {
                    "icon": "OpenAI"
                  },
                  {
                    "icon": "SambaNova"
                  },
                  {
                    "icon": "brain"
                  }
                ],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.agents.events import ExceptionWithMessageError\nfrom langflow.base.models.model_input_constants import (\n    ALL_PROVIDER_FIELDS,\n    MODEL_DYNAMIC_UPDATE_FIELDS,\n    MODEL_PROVIDERS_DICT,\n    MODELS_METADATA,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.custom.utils import update_component_build_config\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.logging import logger\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n    component_input.advanced = True\n    return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n    display_name: str = \"Agent\"\n    description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n    icon = \"bot\"\n    beta = False\n    name = \"Agent\"\n\n    memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n    inputs = [\n        DropdownInput(\n            name=\"agent_llm\",\n            display_name=\"Model Provider\",\n            info=\"The provider of the language model that the agent will use to generate responses.\",\n            options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n            value=\"OpenAI\",\n            real_time_refresh=True,\n            input_types=[],\n            options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())] + [{\"icon\": \"brain\"}],\n        ),\n        *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n        MultilineInput(\n            name=\"system_prompt\",\n            display_name=\"Agent Instructions\",\n            info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n            value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n            advanced=False,\n        ),\n        *LCToolsAgentComponent._base_inputs,\n        *memory_inputs,\n        BoolInput(\n            name=\"add_current_date_tool\",\n            display_name=\"Current Date\",\n            advanced=True,\n            info=\"If true, will add a tool to the agent that returns the current date.\",\n            value=True,\n        ),\n    ]\n    outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n    async def message_response(self) -> Message:\n        try:\n            # Get LLM model and validate\n            llm_model, display_name = self.get_llm()\n            if llm_model is None:\n                msg = \"No language model selected. Please choose a model to proceed.\"\n                raise ValueError(msg)\n            self.model_name = get_model_name(llm_model, display_name=display_name)\n\n            # Get memory data\n            self.chat_history = await self.get_memory_data()\n\n            # Add current date tool if enabled\n            if self.add_current_date_tool:\n                if not isinstance(self.tools, list):  # type: ignore[has-type]\n                    self.tools = []\n                current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)\n                if not isinstance(current_date_tool, StructuredTool):\n                    msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n                    raise TypeError(msg)\n                self.tools.append(current_date_tool)\n\n            # Validate tools\n            if not self.tools:\n                msg = \"Tools are required to run the agent. Please add at least one tool.\"\n                raise ValueError(msg)\n\n            # Set up and run agent\n            self.set(\n                llm=llm_model,\n                tools=self.tools,\n                chat_history=self.chat_history,\n                input_value=self.input_value,\n                system_prompt=self.system_prompt,\n            )\n            agent = self.create_agent_runnable()\n            return await self.run_agent(agent)\n\n        except (ValueError, TypeError, KeyError) as e:\n            logger.error(f\"{type(e).__name__}: {e!s}\")\n            raise\n        except ExceptionWithMessageError as e:\n            logger.error(f\"ExceptionWithMessageError occurred: {e}\")\n            raise\n        except Exception as e:\n            logger.error(f\"Unexpected error: {e!s}\")\n            raise\n\n    async def get_memory_data(self):\n        memory_kwargs = {\n            component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n        }\n        # filter out empty values\n        memory_kwargs = {k: v for k, v in memory_kwargs.items() if v is not None}\n\n        return await MemoryComponent(**self.get_base_args()).set(**memory_kwargs).retrieve_messages()\n\n    def get_llm(self):\n        if not isinstance(self.agent_llm, str):\n            return self.agent_llm, None\n\n        try:\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if not provider_info:\n                msg = f\"Invalid model provider: {self.agent_llm}\"\n                raise ValueError(msg)\n\n            component_class = provider_info.get(\"component_class\")\n            display_name = component_class.display_name\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\", \"\")\n\n            return self._build_llm_model(component_class, inputs, prefix), display_name\n\n        except Exception as e:\n            logger.error(f\"Error building {self.agent_llm} language model: {e!s}\")\n            msg = f\"Failed to initialize language model: {e!s}\"\n            raise ValueError(msg) from e\n\n    def _build_llm_model(self, component, inputs, prefix=\"\"):\n        model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n        return component.set(**model_kwargs).build_model()\n\n    def set_component_params(self, component):\n        provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n        if provider_info:\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\")\n            model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n\n            return component.set(**model_kwargs)\n        return component\n\n    def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n        \"\"\"Delete specified fields from build_config.\"\"\"\n        for field in fields:\n            build_config.pop(field, None)\n\n    def update_input_types(self, build_config: dotdict) -> dotdict:\n        \"\"\"Update input types for all fields in build_config.\"\"\"\n        for key, value in build_config.items():\n            if isinstance(value, dict):\n                if value.get(\"input_types\") is None:\n                    build_config[key][\"input_types\"] = []\n            elif hasattr(value, \"input_types\") and value.input_types is None:\n                value.input_types = []\n        return build_config\n\n    async def update_build_config(\n        self, build_config: dotdict, field_value: str, field_name: str | None = None\n    ) -> dotdict:\n        # Iterate over all providers in the MODEL_PROVIDERS_DICT\n        # Existing logic for updating build_config\n        if field_name in (\"agent_llm\",):\n            build_config[\"agent_llm\"][\"value\"] = field_value\n            provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call the component class's update_build_config method\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n\n            provider_configs: dict[str, tuple[dict, list[dict]]] = {\n                provider: (\n                    MODEL_PROVIDERS_DICT[provider][\"fields\"],\n                    [\n                        MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n                        for other_provider in MODEL_PROVIDERS_DICT\n                        if other_provider != provider\n                    ],\n                )\n                for provider in MODEL_PROVIDERS_DICT\n            }\n            if field_value in provider_configs:\n                fields_to_add, fields_to_delete = provider_configs[field_value]\n\n                # Delete fields from other providers\n                for fields in fields_to_delete:\n                    self.delete_fields(build_config, fields)\n\n                # Add provider-specific fields\n                if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n                    build_config.update(fields_to_add)\n                else:\n                    build_config.update(fields_to_add)\n                # Reset input types for agent_llm\n                build_config[\"agent_llm\"][\"input_types\"] = []\n            elif field_value == \"Custom\":\n                # Delete all provider fields\n                self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n                # Update with custom component\n                custom_component = DropdownInput(\n                    name=\"agent_llm\",\n                    display_name=\"Language Model\",\n                    options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n                    value=\"Custom\",\n                    real_time_refresh=True,\n                    input_types=[\"LanguageModel\"],\n                    options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())]\n                    + [{\"icon\": \"brain\"}],\n                )\n                build_config.update({\"agent_llm\": custom_component.to_dict()})\n            # Update input types for all fields\n            build_config = self.update_input_types(build_config)\n\n            # Validate required keys\n            default_keys = [\n                \"code\",\n                \"_type\",\n                \"agent_llm\",\n                \"tools\",\n                \"input_value\",\n                \"add_current_date_tool\",\n                \"system_prompt\",\n                \"agent_description\",\n                \"max_iterations\",\n                \"handle_parsing_errors\",\n                \"verbose\",\n            ]\n            missing_keys = [key for key in default_keys if key not in build_config]\n            if missing_keys:\n                msg = f\"Missing required keys in build_config: {missing_keys}\"\n                raise ValueError(msg)\n        if (\n            isinstance(self.agent_llm, str)\n            and self.agent_llm in MODEL_PROVIDERS_DICT\n            and field_name in MODEL_DYNAMIC_UPDATE_FIELDS\n        ):\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                component_class = self.set_component_params(component_class)\n                prefix = provider_info.get(\"prefix\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call each component class's update_build_config method\n                    # remove the prefix from the field_name\n                    if isinstance(field_name, str) and isinstance(prefix, str):\n                        field_name = field_name.replace(prefix, \"\")\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n        return dotdict({k: v.to_dict() if hasattr(v, \"to_dict\") else v for k, v in build_config.items()})\n"
              },
              "handle_parsing_errors": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Handle Parse Errors",
                "dynamic": false,
                "info": "Should the Agent fix errors when reading user input for better processing?",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "handle_parsing_errors",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "input_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "The input provided by the user for the agent to process.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "max_iterations": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Max Iterations",
                "dynamic": false,
                "info": "The maximum number of attempts the agent can make to complete its task before it stops.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "max_iterations",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 15
              },
              "memory": {
                "_input_type": "HandleInput",
                "advanced": true,
                "display_name": "External Memory",
                "dynamic": false,
                "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                "input_types": [
                  "Memory"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "memory",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "n_messages": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Messages",
                "dynamic": false,
                "info": "Number of messages to retrieve.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "n_messages",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 100
              },
              "order": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Order",
                "dynamic": false,
                "info": "Order of the messages.",
                "input_types": [],
                "name": "order",
                "options": [
                  "Ascending",
                  "Descending"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Ascending"
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Filter by sender type.",
                "input_types": [],
                "name": "sender",
                "options": [
                  "Machine",
                  "User",
                  "Machine and User"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Machine and User"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Filter by sender name.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_prompt": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "Agent Instructions",
                "dynamic": false,
                "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_prompt",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "You are a helpful assistant that can use tools to answer questions and perform tasks."
              },
              "template": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "{sender_name}: {text}"
              },
              "tools": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Tools",
                "dynamic": false,
                "info": "These are the tools that the agent can use to help with tasks.",
                "input_types": [
                  "Tool"
                ],
                "list": true,
                "list_add_label": "Add More",
                "name": "tools",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Agent"
        },
        "dragging": false,
        "id": "Agent-qKLwT",
        "measured": {
          "height": 459,
          "width": 320
        },
        "position": {
          "x": 1507.6907443931707,
          "y": -1073.9262160600986
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Prompt-DNozc",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {
              "template": [
                "user_input",
                "data"
              ]
            },
            "description": "Create a prompt template with dynamic variables.",
            "display_name": "Prompt",
            "documentation": "",
            "edited": false,
            "error": null,
            "field_order": [
              "template",
              "tool_placeholder"
            ],
            "frozen": false,
            "full_path": null,
            "icon": "prompts",
            "is_composition": null,
            "is_input": null,
            "is_output": null,
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "name": "",
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Prompt Message",
                "hidden": false,
                "method": "build_prompt",
                "name": "prompt",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "priority": null,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
              },
              "data": {
                "advanced": false,
                "display_name": "data",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "data",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "template": {
                "_input_type": "PromptInput",
                "advanced": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "",
                "list": false,
                "list_add_label": "Add More",
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "prompt",
                "value": "User Input: {user_input}\nSampe Data: {data}\n\n\nMachin Learning Models:\n\nModel Name 1:\nPros:\nCons:\n\n"
              },
              "tool_placeholder": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tool Placeholder",
                "dynamic": false,
                "info": "A placeholder input for tool mode.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tool_placeholder",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "user_input": {
                "advanced": false,
                "display_name": "user_input",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "user_input",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Prompt"
        },
        "dragging": false,
        "id": "Prompt-DNozc",
        "measured": {
          "height": 495,
          "width": 320
        },
        "position": {
          "x": 1053.3554900965362,
          "y": -1089.2325533460896
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "OllamaModel-FeVHc",
          "node": {
            "base_classes": [
              "LanguageModel",
              "Message"
            ],
            "beta": false,
            "category": "models",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Generate text using Ollama Local LLMs.",
            "display_name": "CoderModel",
            "documentation": "",
            "edited": false,
            "field_order": [
              "base_url",
              "model_name",
              "temperature",
              "format",
              "metadata",
              "mirostat",
              "mirostat_eta",
              "mirostat_tau",
              "num_ctx",
              "num_gpu",
              "num_thread",
              "repeat_last_n",
              "repeat_penalty",
              "tfs_z",
              "timeout",
              "top_k",
              "top_p",
              "verbose",
              "tags",
              "stop_tokens",
              "system",
              "tool_model_enabled",
              "template",
              "input_value",
              "system_message",
              "stream"
            ],
            "frozen": false,
            "icon": "Ollama",
            "key": "OllamaModel",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "text_response",
                "name": "text_output",
                "options": null,
                "required_inputs": [],
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              },
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Language Model",
                "hidden": false,
                "method": "build_model",
                "name": "model_output",
                "options": null,
                "required_inputs": [],
                "selected": "LanguageModel",
                "tool_mode": true,
                "types": [
                  "LanguageModel"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.001,
            "template": {
              "_type": "Component",
              "base_url": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Base URL",
                "dynamic": false,
                "info": "Endpoint of the Ollama API.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "base_url",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "http://localhost:11434"
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "import asyncio\nfrom typing import Any\nfrom urllib.parse import urljoin\n\nimport httpx\nfrom langchain_ollama import ChatOllama\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.base.models.ollama_constants import OLLAMA_TOOL_MODELS_BASE, URL_LIST\nfrom langflow.field_typing import LanguageModel\nfrom langflow.field_typing.range_spec import RangeSpec\nfrom langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SliderInput\nfrom langflow.logging import logger\n\nHTTP_STATUS_OK = 200\n\n\nclass ChatOllamaComponent(LCModelComponent):\n    display_name = \"Ollama\"\n    description = \"Generate text using Ollama Local LLMs.\"\n    icon = \"Ollama\"\n    name = \"OllamaModel\"\n\n    # Define constants for JSON keys\n    JSON_MODELS_KEY = \"models\"\n    JSON_NAME_KEY = \"name\"\n    JSON_CAPABILITIES_KEY = \"capabilities\"\n    DESIRED_CAPABILITY = \"completion\"\n\n    inputs = [\n        MessageTextInput(\n            name=\"base_url\",\n            display_name=\"Base URL\",\n            info=\"Endpoint of the Ollama API.\",\n            value=\"\",\n        ),\n        DropdownInput(\n            name=\"model_name\",\n            display_name=\"Model Name\",\n            options=[],\n            info=\"Refer to https://ollama.com/library for more models.\",\n            refresh_button=True,\n            real_time_refresh=True,\n        ),\n        SliderInput(\n            name=\"temperature\",\n            display_name=\"Temperature\",\n            value=0.1,\n            range_spec=RangeSpec(min=0, max=1, step=0.01),\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"format\", display_name=\"Format\", info=\"Specify the format of the output (e.g., json).\", advanced=True\n        ),\n        DictInput(name=\"metadata\", display_name=\"Metadata\", info=\"Metadata to add to the run trace.\", advanced=True),\n        DropdownInput(\n            name=\"mirostat\",\n            display_name=\"Mirostat\",\n            options=[\"Disabled\", \"Mirostat\", \"Mirostat 2.0\"],\n            info=\"Enable/disable Mirostat sampling for controlling perplexity.\",\n            value=\"Disabled\",\n            advanced=True,\n            real_time_refresh=True,\n        ),\n        FloatInput(\n            name=\"mirostat_eta\",\n            display_name=\"Mirostat Eta\",\n            info=\"Learning rate for Mirostat algorithm. (Default: 0.1)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"mirostat_tau\",\n            display_name=\"Mirostat Tau\",\n            info=\"Controls the balance between coherence and diversity of the output. (Default: 5.0)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_ctx\",\n            display_name=\"Context Window Size\",\n            info=\"Size of the context window for generating tokens. (Default: 2048)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_gpu\",\n            display_name=\"Number of GPUs\",\n            info=\"Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"num_thread\",\n            display_name=\"Number of Threads\",\n            info=\"Number of threads to use during computation. (Default: detected for optimal performance)\",\n            advanced=True,\n        ),\n        IntInput(\n            name=\"repeat_last_n\",\n            display_name=\"Repeat Last N\",\n            info=\"How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)\",\n            advanced=True,\n        ),\n        FloatInput(\n            name=\"repeat_penalty\",\n            display_name=\"Repeat Penalty\",\n            info=\"Penalty for repetitions in generated text. (Default: 1.1)\",\n            advanced=True,\n        ),\n        FloatInput(name=\"tfs_z\", display_name=\"TFS Z\", info=\"Tail free sampling value. (Default: 1)\", advanced=True),\n        IntInput(name=\"timeout\", display_name=\"Timeout\", info=\"Timeout for the request stream.\", advanced=True),\n        IntInput(\n            name=\"top_k\", display_name=\"Top K\", info=\"Limits token selection to top K. (Default: 40)\", advanced=True\n        ),\n        FloatInput(name=\"top_p\", display_name=\"Top P\", info=\"Works together with top-k. (Default: 0.9)\", advanced=True),\n        BoolInput(name=\"verbose\", display_name=\"Verbose\", info=\"Whether to print out response text.\", advanced=True),\n        MessageTextInput(\n            name=\"tags\",\n            display_name=\"Tags\",\n            info=\"Comma-separated list of tags to add to the run trace.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"stop_tokens\",\n            display_name=\"Stop Tokens\",\n            info=\"Comma-separated list of tokens to signal the model to stop generating text.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"system\", display_name=\"System\", info=\"System to use for generating text.\", advanced=True\n        ),\n        BoolInput(\n            name=\"tool_model_enabled\",\n            display_name=\"Tool Model Enabled\",\n            info=\"Whether to enable tool calling in the model.\",\n            value=False,\n            real_time_refresh=True,\n        ),\n        MessageTextInput(\n            name=\"template\", display_name=\"Template\", info=\"Template to use for generating text.\", advanced=True\n        ),\n        *LCModelComponent._base_inputs,\n    ]\n\n    def build_model(self) -> LanguageModel:  # type: ignore[type-var]\n        # Mapping mirostat settings to their corresponding values\n        mirostat_options = {\"Mirostat\": 1, \"Mirostat 2.0\": 2}\n\n        # Default to 0 for 'Disabled'\n        mirostat_value = mirostat_options.get(self.mirostat, 0)\n\n        # Set mirostat_eta and mirostat_tau to None if mirostat is disabled\n        if mirostat_value == 0:\n            mirostat_eta = None\n            mirostat_tau = None\n        else:\n            mirostat_eta = self.mirostat_eta\n            mirostat_tau = self.mirostat_tau\n\n        # Mapping system settings to their corresponding values\n        llm_params = {\n            \"base_url\": self.base_url,\n            \"model\": self.model_name,\n            \"mirostat\": mirostat_value,\n            \"format\": self.format,\n            \"metadata\": self.metadata,\n            \"tags\": self.tags.split(\",\") if self.tags else None,\n            \"mirostat_eta\": mirostat_eta,\n            \"mirostat_tau\": mirostat_tau,\n            \"num_ctx\": self.num_ctx or None,\n            \"num_gpu\": self.num_gpu or None,\n            \"num_thread\": self.num_thread or None,\n            \"repeat_last_n\": self.repeat_last_n or None,\n            \"repeat_penalty\": self.repeat_penalty or None,\n            \"temperature\": self.temperature or None,\n            \"stop\": self.stop_tokens.split(\",\") if self.stop_tokens else None,\n            \"system\": self.system,\n            \"tfs_z\": self.tfs_z or None,\n            \"timeout\": self.timeout or None,\n            \"top_k\": self.top_k or None,\n            \"top_p\": self.top_p or None,\n            \"verbose\": self.verbose,\n            \"template\": self.template,\n        }\n\n        # Remove parameters with None values\n        llm_params = {k: v for k, v in llm_params.items() if v is not None}\n\n        try:\n            output = ChatOllama(**llm_params)\n        except Exception as e:\n            msg = (\n                \"Unable to connect to the Ollama API. \",\n                \"Please verify the base URL, ensure the relevant Ollama model is pulled, and try again.\",\n            )\n            raise ValueError(msg) from e\n\n        return output\n\n    async def is_valid_ollama_url(self, url: str) -> bool:\n        try:\n            async with httpx.AsyncClient() as client:\n                return (await client.get(urljoin(url, \"api/tags\"))).status_code == HTTP_STATUS_OK\n        except httpx.RequestError:\n            return False\n\n    async def update_build_config(self, build_config: dict, field_value: Any, field_name: str | None = None):\n        if field_name == \"mirostat\":\n            if field_value == \"Disabled\":\n                build_config[\"mirostat_eta\"][\"advanced\"] = True\n                build_config[\"mirostat_tau\"][\"advanced\"] = True\n                build_config[\"mirostat_eta\"][\"value\"] = None\n                build_config[\"mirostat_tau\"][\"value\"] = None\n\n            else:\n                build_config[\"mirostat_eta\"][\"advanced\"] = False\n                build_config[\"mirostat_tau\"][\"advanced\"] = False\n\n                if field_value == \"Mirostat 2.0\":\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.2\n                    build_config[\"mirostat_tau\"][\"value\"] = 10\n                else:\n                    build_config[\"mirostat_eta\"][\"value\"] = 0.1\n                    build_config[\"mirostat_tau\"][\"value\"] = 5\n\n        if field_name in {\"base_url\", \"model_name\"}:\n            if build_config[\"base_url\"].get(\"load_from_db\", False):\n                base_url_value = await self.get_variables(build_config[\"base_url\"].get(\"value\", \"\"), \"base_url\")\n            else:\n                base_url_value = build_config[\"base_url\"].get(\"value\", \"\")\n\n            if not await self.is_valid_ollama_url(base_url_value):\n                # Check if any URL in the list is valid\n                valid_url = \"\"\n                check_urls = URL_LIST\n                if self.base_url:\n                    check_urls = [self.base_url, *URL_LIST]\n                for url in check_urls:\n                    if await self.is_valid_ollama_url(url):\n                        valid_url = url\n                        break\n                if valid_url != \"\":\n                    build_config[\"base_url\"][\"value\"] = valid_url\n                else:\n                    msg = \"No valid Ollama URL found.\"\n                    raise ValueError(msg)\n        if field_name in {\"model_name\", \"base_url\", \"tool_model_enabled\"}:\n            if await self.is_valid_ollama_url(self.base_url):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(self.base_url, tool_model_enabled)\n            elif await self.is_valid_ollama_url(build_config[\"base_url\"].get(\"value\", \"\")):\n                tool_model_enabled = build_config[\"tool_model_enabled\"].get(\"value\", False) or self.tool_model_enabled\n                build_config[\"model_name\"][\"options\"] = await self.get_models(\n                    build_config[\"base_url\"].get(\"value\", \"\"), tool_model_enabled\n                )\n            else:\n                build_config[\"model_name\"][\"options\"] = []\n        if field_name == \"keep_alive_flag\":\n            if field_value == \"Keep\":\n                build_config[\"keep_alive\"][\"value\"] = \"-1\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            elif field_value == \"Immediately\":\n                build_config[\"keep_alive\"][\"value\"] = \"0\"\n                build_config[\"keep_alive\"][\"advanced\"] = True\n            else:\n                build_config[\"keep_alive\"][\"advanced\"] = False\n\n        return build_config\n\n    async def get_models(self, base_url_value: str, tool_model_enabled: bool | None = None) -> list[str]:\n        \"\"\"Fetches a list of models from the Ollama API that do not have the \"embedding\" capability.\n\n        Args:\n            base_url_value (str): The base URL of the Ollama API.\n            tool_model_enabled (bool | None, optional): If True, filters the models further to include\n                only those that support tool calling. Defaults to None.\n\n        Returns:\n            list[str]: A list of model names that do not have the \"embedding\" capability. If\n                `tool_model_enabled` is True, only models supporting tool calling are included.\n\n        Raises:\n            ValueError: If there is an issue with the API request or response, or if the model\n                names cannot be retrieved.\n        \"\"\"\n        try:\n            # Normalize the base URL to avoid the repeated \"/\" at the end\n            base_url = base_url_value.rstrip(\"/\") + \"/\"\n\n            # Ollama REST API to return models\n            tags_url = urljoin(base_url, \"api/tags\")\n\n            # Ollama REST API to return model capabilities\n            show_url = urljoin(base_url, \"api/show\")\n\n            async with httpx.AsyncClient() as client:\n                # Fetch available models\n                tags_response = await client.get(tags_url)\n                tags_response.raise_for_status()\n                models = tags_response.json()\n                if asyncio.iscoroutine(models):\n                    models = await models\n                logger.debug(f\"Available models: {models}\")\n\n                # Filter models that are NOT embedding models\n                model_ids = []\n                for model in models[self.JSON_MODELS_KEY]:\n                    model_name = model[self.JSON_NAME_KEY]\n                    logger.debug(f\"Checking model: {model_name}\")\n\n                    payload = {\"model\": model_name}\n                    show_response = await client.post(show_url, json=payload)\n                    show_response.raise_for_status()\n                    json_data = show_response.json()\n                    if asyncio.iscoroutine(json_data):\n                        json_data = await json_data\n                    capabilities = json_data.get(self.JSON_CAPABILITIES_KEY, [])\n                    logger.debug(f\"Model: {model_name}, Capabilities: {capabilities}\")\n\n                    if self.DESIRED_CAPABILITY in capabilities:\n                        model_ids.append(model_name)\n\n        except (httpx.RequestError, ValueError) as e:\n            msg = \"Could not get model names from Ollama.\"\n            raise ValueError(msg) from e\n\n        return (\n            model_ids if not tool_model_enabled else [model for model in model_ids if self.supports_tool_calling(model)]\n        )\n\n    def supports_tool_calling(self, model: str) -> bool:\n        \"\"\"Check if model name is in the base of any models example llama3.3 can have 1b and 2b.\"\"\"\n        return any(model.startswith(f\"{tool_model}\") for tool_model in OLLAMA_TOOL_MODELS_BASE)\n"
              },
              "format": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Format",
                "dynamic": false,
                "info": "Specify the format of the output (e.g., json).",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "format",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "input_value": {
                "_input_type": "MessageInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "metadata": {
                "_input_type": "DictInput",
                "advanced": true,
                "display_name": "Metadata",
                "dynamic": false,
                "info": "Metadata to add to the run trace.",
                "list": false,
                "list_add_label": "Add More",
                "name": "metadata",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "dict",
                "value": {}
              },
              "mirostat": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Mirostat",
                "dynamic": false,
                "info": "Enable/disable Mirostat sampling for controlling perplexity.",
                "name": "mirostat",
                "options": [
                  "Disabled",
                  "Mirostat",
                  "Mirostat 2.0"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Disabled"
              },
              "mirostat_eta": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Eta",
                "dynamic": false,
                "info": "Learning rate for Mirostat algorithm. (Default: 0.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_eta",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "mirostat_tau": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Mirostat Tau",
                "dynamic": false,
                "info": "Controls the balance between coherence and diversity of the output. (Default: 5.0)",
                "list": false,
                "list_add_label": "Add More",
                "name": "mirostat_tau",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "model_name": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Model Name",
                "dynamic": false,
                "info": "Refer to https://ollama.com/library for more models.",
                "name": "model_name",
                "options": [
                  "mistral:latest",
                  "llama3.2:latest",
                  "qwen2.5-coder:7b",
                  "qwen2.5:32b",
                  "llama3.2:1b",
                  "qwen2.5-coder:3b"
                ],
                "options_metadata": [],
                "placeholder": "",
                "real_time_refresh": true,
                "refresh_button": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "qwen2.5-coder:7b"
              },
              "num_ctx": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Context Window Size",
                "dynamic": false,
                "info": "Size of the context window for generating tokens. (Default: 2048)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_ctx",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_gpu": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of GPUs",
                "dynamic": false,
                "info": "Number of GPUs to use for computation. (Default: 1 on macOS, 0 to disable)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_gpu",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "num_thread": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Threads",
                "dynamic": false,
                "info": "Number of threads to use during computation. (Default: detected for optimal performance)",
                "list": false,
                "list_add_label": "Add More",
                "name": "num_thread",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_last_n": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Repeat Last N",
                "dynamic": false,
                "info": "How far back the model looks to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_last_n",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "repeat_penalty": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Repeat Penalty",
                "dynamic": false,
                "info": "Penalty for repetitions in generated text. (Default: 1.1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "repeat_penalty",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "stop_tokens": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Stop Tokens",
                "dynamic": false,
                "info": "Comma-separated list of tokens to signal the model to stop generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "stop_tokens",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "stream": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Stream",
                "dynamic": false,
                "info": "Stream the response from the model. Streaming works only in Chat.",
                "list": false,
                "list_add_label": "Add More",
                "name": "stream",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              },
              "system": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "System",
                "dynamic": false,
                "info": "System to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "system",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_message": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "System Message",
                "dynamic": false,
                "info": "System message to pass to the model.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tags": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tags",
                "dynamic": false,
                "info": "Comma-separated list of tags to add to the run trace.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tags",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "temperature": {
                "_input_type": "SliderInput",
                "advanced": true,
                "display_name": "Temperature",
                "dynamic": false,
                "info": "",
                "max_label": "",
                "max_label_icon": "",
                "min_label": "",
                "min_label_icon": "",
                "name": "temperature",
                "placeholder": "",
                "range_spec": {
                  "max": 1,
                  "min": 0,
                  "step": 0.01,
                  "step_type": "float"
                },
                "required": false,
                "show": true,
                "slider_buttons": false,
                "slider_buttons_options": [],
                "slider_input": false,
                "title_case": false,
                "tool_mode": false,
                "type": "slider",
                "value": 0.1
              },
              "template": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Template",
                "dynamic": false,
                "info": "Template to use for generating text.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "tfs_z": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "TFS Z",
                "dynamic": false,
                "info": "Tail free sampling value. (Default: 1)",
                "list": false,
                "list_add_label": "Add More",
                "name": "tfs_z",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "timeout": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Timeout",
                "dynamic": false,
                "info": "Timeout for the request stream.",
                "list": false,
                "list_add_label": "Add More",
                "name": "timeout",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "tool_model_enabled": {
                "_input_type": "BoolInput",
                "advanced": false,
                "display_name": "Tool Model Enabled",
                "dynamic": false,
                "info": "Whether to enable tool calling in the model.",
                "list": false,
                "list_add_label": "Add More",
                "name": "tool_model_enabled",
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "top_k": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Top K",
                "dynamic": false,
                "info": "Limits token selection to top K. (Default: 40)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_k",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": ""
              },
              "top_p": {
                "_input_type": "FloatInput",
                "advanced": true,
                "display_name": "Top P",
                "dynamic": false,
                "info": "Works together with top-k. (Default: 0.9)",
                "list": false,
                "list_add_label": "Add More",
                "name": "top_p",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "float",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "Whether to print out response text.",
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": false
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "OllamaModel"
        },
        "dragging": false,
        "id": "OllamaModel-FeVHc",
        "measured": {
          "height": 568,
          "width": 320
        },
        "position": {
          "x": 2140.3222441417042,
          "y": -1806.2739782284027
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Agent-K8pt3",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "agents",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Define the agent's instructions, then enter a task to complete using tools.",
            "display_name": "CoderAgent",
            "documentation": "",
            "edited": false,
            "field_order": [
              "agent_llm",
              "max_tokens",
              "model_kwargs",
              "json_mode",
              "model_name",
              "openai_api_base",
              "api_key",
              "temperature",
              "seed",
              "max_retries",
              "timeout",
              "system_prompt",
              "tools",
              "input_value",
              "handle_parsing_errors",
              "verbose",
              "max_iterations",
              "agent_description",
              "memory",
              "sender",
              "sender_name",
              "n_messages",
              "session_id",
              "order",
              "template",
              "add_current_date_tool"
            ],
            "frozen": false,
            "icon": "bot",
            "key": "Agent",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Response",
                "hidden": false,
                "method": "message_response",
                "name": "response",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 5.283996070936036e-7,
            "template": {
              "_type": "Component",
              "add_current_date_tool": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Current Date",
                "dynamic": false,
                "info": "If true, will add a tool to the agent that returns the current date.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "add_current_date_tool",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "agent_description": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Agent Description [Deprecated]",
                "dynamic": false,
                "info": "The description of the agent. This is only used when in Tool Mode. Defaults to 'A helpful assistant with access to the following tools:' and tools are added dynamically. This feature is deprecated and will be removed in future versions.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "agent_description",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "A helpful assistant with access to the following tools:"
              },
              "agent_llm": {
                "_input_type": "DropdownInput",
                "advanced": false,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Language Model",
                "dynamic": false,
                "info": "",
                "input_types": [
                  "LanguageModel"
                ],
                "name": "agent_llm",
                "options": [
                  "Amazon Bedrock",
                  "Anthropic",
                  "Azure OpenAI",
                  "Google Generative AI",
                  "Groq",
                  "NVIDIA",
                  "OpenAI",
                  "SambaNova",
                  "Custom"
                ],
                "options_metadata": [
                  {
                    "icon": "Amazon"
                  },
                  {
                    "icon": "Anthropic"
                  },
                  {
                    "icon": "Azure"
                  },
                  {
                    "icon": "GoogleGenerativeAI"
                  },
                  {
                    "icon": "Groq"
                  },
                  {
                    "icon": "NVIDIA"
                  },
                  {
                    "icon": "OpenAI"
                  },
                  {
                    "icon": "SambaNova"
                  },
                  {
                    "icon": "brain"
                  }
                ],
                "placeholder": "",
                "real_time_refresh": true,
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langchain_core.tools import StructuredTool\n\nfrom langflow.base.agents.agent import LCToolsAgentComponent\nfrom langflow.base.agents.events import ExceptionWithMessageError\nfrom langflow.base.models.model_input_constants import (\n    ALL_PROVIDER_FIELDS,\n    MODEL_DYNAMIC_UPDATE_FIELDS,\n    MODEL_PROVIDERS_DICT,\n    MODELS_METADATA,\n)\nfrom langflow.base.models.model_utils import get_model_name\nfrom langflow.components.helpers import CurrentDateComponent\nfrom langflow.components.helpers.memory import MemoryComponent\nfrom langflow.components.langchain_utilities.tool_calling import ToolCallingAgentComponent\nfrom langflow.custom.utils import update_component_build_config\nfrom langflow.io import BoolInput, DropdownInput, MultilineInput, Output\nfrom langflow.logging import logger\nfrom langflow.schema.dotdict import dotdict\nfrom langflow.schema.message import Message\n\n\ndef set_advanced_true(component_input):\n    component_input.advanced = True\n    return component_input\n\n\nclass AgentComponent(ToolCallingAgentComponent):\n    display_name: str = \"Agent\"\n    description: str = \"Define the agent's instructions, then enter a task to complete using tools.\"\n    icon = \"bot\"\n    beta = False\n    name = \"Agent\"\n\n    memory_inputs = [set_advanced_true(component_input) for component_input in MemoryComponent().inputs]\n\n    inputs = [\n        DropdownInput(\n            name=\"agent_llm\",\n            display_name=\"Model Provider\",\n            info=\"The provider of the language model that the agent will use to generate responses.\",\n            options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n            value=\"OpenAI\",\n            real_time_refresh=True,\n            input_types=[],\n            options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())] + [{\"icon\": \"brain\"}],\n        ),\n        *MODEL_PROVIDERS_DICT[\"OpenAI\"][\"inputs\"],\n        MultilineInput(\n            name=\"system_prompt\",\n            display_name=\"Agent Instructions\",\n            info=\"System Prompt: Initial instructions and context provided to guide the agent's behavior.\",\n            value=\"You are a helpful assistant that can use tools to answer questions and perform tasks.\",\n            advanced=False,\n        ),\n        *LCToolsAgentComponent._base_inputs,\n        *memory_inputs,\n        BoolInput(\n            name=\"add_current_date_tool\",\n            display_name=\"Current Date\",\n            advanced=True,\n            info=\"If true, will add a tool to the agent that returns the current date.\",\n            value=True,\n        ),\n    ]\n    outputs = [Output(name=\"response\", display_name=\"Response\", method=\"message_response\")]\n\n    async def message_response(self) -> Message:\n        try:\n            # Get LLM model and validate\n            llm_model, display_name = self.get_llm()\n            if llm_model is None:\n                msg = \"No language model selected. Please choose a model to proceed.\"\n                raise ValueError(msg)\n            self.model_name = get_model_name(llm_model, display_name=display_name)\n\n            # Get memory data\n            self.chat_history = await self.get_memory_data()\n\n            # Add current date tool if enabled\n            if self.add_current_date_tool:\n                if not isinstance(self.tools, list):  # type: ignore[has-type]\n                    self.tools = []\n                current_date_tool = (await CurrentDateComponent(**self.get_base_args()).to_toolkit()).pop(0)\n                if not isinstance(current_date_tool, StructuredTool):\n                    msg = \"CurrentDateComponent must be converted to a StructuredTool\"\n                    raise TypeError(msg)\n                self.tools.append(current_date_tool)\n\n            # Validate tools\n            if not self.tools:\n                msg = \"Tools are required to run the agent. Please add at least one tool.\"\n                raise ValueError(msg)\n\n            # Set up and run agent\n            self.set(\n                llm=llm_model,\n                tools=self.tools,\n                chat_history=self.chat_history,\n                input_value=self.input_value,\n                system_prompt=self.system_prompt,\n            )\n            agent = self.create_agent_runnable()\n            return await self.run_agent(agent)\n\n        except (ValueError, TypeError, KeyError) as e:\n            logger.error(f\"{type(e).__name__}: {e!s}\")\n            raise\n        except ExceptionWithMessageError as e:\n            logger.error(f\"ExceptionWithMessageError occurred: {e}\")\n            raise\n        except Exception as e:\n            logger.error(f\"Unexpected error: {e!s}\")\n            raise\n\n    async def get_memory_data(self):\n        memory_kwargs = {\n            component_input.name: getattr(self, f\"{component_input.name}\") for component_input in self.memory_inputs\n        }\n        # filter out empty values\n        memory_kwargs = {k: v for k, v in memory_kwargs.items() if v is not None}\n\n        return await MemoryComponent(**self.get_base_args()).set(**memory_kwargs).retrieve_messages()\n\n    def get_llm(self):\n        if not isinstance(self.agent_llm, str):\n            return self.agent_llm, None\n\n        try:\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if not provider_info:\n                msg = f\"Invalid model provider: {self.agent_llm}\"\n                raise ValueError(msg)\n\n            component_class = provider_info.get(\"component_class\")\n            display_name = component_class.display_name\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\", \"\")\n\n            return self._build_llm_model(component_class, inputs, prefix), display_name\n\n        except Exception as e:\n            logger.error(f\"Error building {self.agent_llm} language model: {e!s}\")\n            msg = f\"Failed to initialize language model: {e!s}\"\n            raise ValueError(msg) from e\n\n    def _build_llm_model(self, component, inputs, prefix=\"\"):\n        model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n        return component.set(**model_kwargs).build_model()\n\n    def set_component_params(self, component):\n        provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n        if provider_info:\n            inputs = provider_info.get(\"inputs\")\n            prefix = provider_info.get(\"prefix\")\n            model_kwargs = {input_.name: getattr(self, f\"{prefix}{input_.name}\") for input_ in inputs}\n\n            return component.set(**model_kwargs)\n        return component\n\n    def delete_fields(self, build_config: dotdict, fields: dict | list[str]) -> None:\n        \"\"\"Delete specified fields from build_config.\"\"\"\n        for field in fields:\n            build_config.pop(field, None)\n\n    def update_input_types(self, build_config: dotdict) -> dotdict:\n        \"\"\"Update input types for all fields in build_config.\"\"\"\n        for key, value in build_config.items():\n            if isinstance(value, dict):\n                if value.get(\"input_types\") is None:\n                    build_config[key][\"input_types\"] = []\n            elif hasattr(value, \"input_types\") and value.input_types is None:\n                value.input_types = []\n        return build_config\n\n    async def update_build_config(\n        self, build_config: dotdict, field_value: str, field_name: str | None = None\n    ) -> dotdict:\n        # Iterate over all providers in the MODEL_PROVIDERS_DICT\n        # Existing logic for updating build_config\n        if field_name in (\"agent_llm\",):\n            build_config[\"agent_llm\"][\"value\"] = field_value\n            provider_info = MODEL_PROVIDERS_DICT.get(field_value)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call the component class's update_build_config method\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n\n            provider_configs: dict[str, tuple[dict, list[dict]]] = {\n                provider: (\n                    MODEL_PROVIDERS_DICT[provider][\"fields\"],\n                    [\n                        MODEL_PROVIDERS_DICT[other_provider][\"fields\"]\n                        for other_provider in MODEL_PROVIDERS_DICT\n                        if other_provider != provider\n                    ],\n                )\n                for provider in MODEL_PROVIDERS_DICT\n            }\n            if field_value in provider_configs:\n                fields_to_add, fields_to_delete = provider_configs[field_value]\n\n                # Delete fields from other providers\n                for fields in fields_to_delete:\n                    self.delete_fields(build_config, fields)\n\n                # Add provider-specific fields\n                if field_value == \"OpenAI\" and not any(field in build_config for field in fields_to_add):\n                    build_config.update(fields_to_add)\n                else:\n                    build_config.update(fields_to_add)\n                # Reset input types for agent_llm\n                build_config[\"agent_llm\"][\"input_types\"] = []\n            elif field_value == \"Custom\":\n                # Delete all provider fields\n                self.delete_fields(build_config, ALL_PROVIDER_FIELDS)\n                # Update with custom component\n                custom_component = DropdownInput(\n                    name=\"agent_llm\",\n                    display_name=\"Language Model\",\n                    options=[*sorted(MODEL_PROVIDERS_DICT.keys()), \"Custom\"],\n                    value=\"Custom\",\n                    real_time_refresh=True,\n                    input_types=[\"LanguageModel\"],\n                    options_metadata=[MODELS_METADATA[key] for key in sorted(MODELS_METADATA.keys())]\n                    + [{\"icon\": \"brain\"}],\n                )\n                build_config.update({\"agent_llm\": custom_component.to_dict()})\n            # Update input types for all fields\n            build_config = self.update_input_types(build_config)\n\n            # Validate required keys\n            default_keys = [\n                \"code\",\n                \"_type\",\n                \"agent_llm\",\n                \"tools\",\n                \"input_value\",\n                \"add_current_date_tool\",\n                \"system_prompt\",\n                \"agent_description\",\n                \"max_iterations\",\n                \"handle_parsing_errors\",\n                \"verbose\",\n            ]\n            missing_keys = [key for key in default_keys if key not in build_config]\n            if missing_keys:\n                msg = f\"Missing required keys in build_config: {missing_keys}\"\n                raise ValueError(msg)\n        if (\n            isinstance(self.agent_llm, str)\n            and self.agent_llm in MODEL_PROVIDERS_DICT\n            and field_name in MODEL_DYNAMIC_UPDATE_FIELDS\n        ):\n            provider_info = MODEL_PROVIDERS_DICT.get(self.agent_llm)\n            if provider_info:\n                component_class = provider_info.get(\"component_class\")\n                component_class = self.set_component_params(component_class)\n                prefix = provider_info.get(\"prefix\")\n                if component_class and hasattr(component_class, \"update_build_config\"):\n                    # Call each component class's update_build_config method\n                    # remove the prefix from the field_name\n                    if isinstance(field_name, str) and isinstance(prefix, str):\n                        field_name = field_name.replace(prefix, \"\")\n                    build_config = await update_component_build_config(\n                        component_class, build_config, field_value, \"model_name\"\n                    )\n        return dotdict({k: v.to_dict() if hasattr(v, \"to_dict\") else v for k, v in build_config.items()})\n"
              },
              "handle_parsing_errors": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Handle Parse Errors",
                "dynamic": false,
                "info": "Should the Agent fix errors when reading user input for better processing?",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "handle_parsing_errors",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "input_value": {
                "_input_type": "MessageTextInput",
                "advanced": false,
                "display_name": "Input",
                "dynamic": false,
                "info": "The input provided by the user for the agent to process.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "input_value",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "max_iterations": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Max Iterations",
                "dynamic": false,
                "info": "The maximum number of attempts the agent can make to complete its task before it stops.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "max_iterations",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 15
              },
              "memory": {
                "_input_type": "HandleInput",
                "advanced": true,
                "display_name": "External Memory",
                "dynamic": false,
                "info": "Retrieve messages from an external memory. If empty, it will use the Langflow tables.",
                "input_types": [
                  "Memory"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "memory",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "n_messages": {
                "_input_type": "IntInput",
                "advanced": true,
                "display_name": "Number of Messages",
                "dynamic": false,
                "info": "Number of messages to retrieve.",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "n_messages",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "int",
                "value": 100
              },
              "order": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Order",
                "dynamic": false,
                "info": "Order of the messages.",
                "input_types": [],
                "name": "order",
                "options": [
                  "Ascending",
                  "Descending"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Ascending"
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Filter by sender type.",
                "input_types": [],
                "name": "sender",
                "options": [
                  "Machine",
                  "User",
                  "Machine and User"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Machine and User"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Filter by sender name.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "system_prompt": {
                "_input_type": "MultilineInput",
                "advanced": false,
                "copy_field": false,
                "display_name": "Agent Instructions",
                "dynamic": false,
                "info": "System Prompt: Initial instructions and context provided to guide the agent's behavior.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "system_prompt",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "You are a helpful assistant that can use tools to answer questions and perform tasks."
              },
              "template": {
                "_input_type": "MultilineInput",
                "advanced": true,
                "copy_field": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "The template to use for formatting the data. It can contain the keys {text}, {sender} or any other key in the message data.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "multiline": true,
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "{sender_name}: {text}"
              },
              "tools": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Tools",
                "dynamic": false,
                "info": "These are the tools that the agent can use to help with tasks.",
                "input_types": [
                  "Tool"
                ],
                "list": true,
                "list_add_label": "Add More",
                "name": "tools",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "verbose": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Verbose",
                "dynamic": false,
                "info": "",
                "input_types": [],
                "list": false,
                "list_add_label": "Add More",
                "name": "verbose",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Agent"
        },
        "dragging": false,
        "id": "Agent-K8pt3",
        "measured": {
          "height": 459,
          "width": 320
        },
        "position": {
          "x": 2616.2306869877048,
          "y": -1505.151042769277
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "Prompt-KCJ8a",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "conditional_paths": [],
            "custom_fields": {
              "template": [
                "data",
                "previous_response"
              ]
            },
            "description": "Create a prompt template with dynamic variables.",
            "display_name": "CoderPrompt",
            "documentation": "",
            "edited": false,
            "error": null,
            "field_order": [
              "template",
              "tool_placeholder"
            ],
            "frozen": false,
            "full_path": null,
            "icon": "prompts",
            "is_composition": null,
            "is_input": null,
            "is_output": null,
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": false,
            "name": "",
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Prompt Message",
                "hidden": false,
                "method": "build_prompt",
                "name": "prompt",
                "options": null,
                "required_inputs": null,
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "priority": null,
            "template": {
              "_type": "Component",
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from langflow.base.prompts.api_utils import process_prompt_template\nfrom langflow.custom import Component\nfrom langflow.inputs.inputs import DefaultPromptField\nfrom langflow.io import MessageTextInput, Output, PromptInput\nfrom langflow.schema.message import Message\nfrom langflow.template.utils import update_template_values\n\n\nclass PromptComponent(Component):\n    display_name: str = \"Prompt\"\n    description: str = \"Create a prompt template with dynamic variables.\"\n    icon = \"prompts\"\n    trace_type = \"prompt\"\n    name = \"Prompt\"\n\n    inputs = [\n        PromptInput(name=\"template\", display_name=\"Template\"),\n        MessageTextInput(\n            name=\"tool_placeholder\",\n            display_name=\"Tool Placeholder\",\n            tool_mode=True,\n            advanced=True,\n            info=\"A placeholder input for tool mode.\",\n        ),\n    ]\n\n    outputs = [\n        Output(display_name=\"Prompt Message\", name=\"prompt\", method=\"build_prompt\"),\n    ]\n\n    async def build_prompt(self) -> Message:\n        prompt = Message.from_template(**self._attributes)\n        self.status = prompt.text\n        return prompt\n\n    def _update_template(self, frontend_node: dict):\n        prompt_template = frontend_node[\"template\"][\"template\"][\"value\"]\n        custom_fields = frontend_node[\"custom_fields\"]\n        frontend_node_template = frontend_node[\"template\"]\n        _ = process_prompt_template(\n            template=prompt_template,\n            name=\"template\",\n            custom_fields=custom_fields,\n            frontend_node_template=frontend_node_template,\n        )\n        return frontend_node\n\n    async def update_frontend_node(self, new_frontend_node: dict, current_frontend_node: dict):\n        \"\"\"This function is called after the code validation is done.\"\"\"\n        frontend_node = await super().update_frontend_node(new_frontend_node, current_frontend_node)\n        template = frontend_node[\"template\"][\"template\"][\"value\"]\n        # Kept it duplicated for backwards compatibility\n        _ = process_prompt_template(\n            template=template,\n            name=\"template\",\n            custom_fields=frontend_node[\"custom_fields\"],\n            frontend_node_template=frontend_node[\"template\"],\n        )\n        # Now that template is updated, we need to grab any values that were set in the current_frontend_node\n        # and update the frontend_node with those values\n        update_template_values(new_template=frontend_node, previous_template=current_frontend_node[\"template\"])\n        return frontend_node\n\n    def _get_fallback_input(self, **kwargs):\n        return DefaultPromptField(**kwargs)\n"
              },
              "data": {
                "advanced": false,
                "display_name": "data",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "data",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "previous_response": {
                "advanced": false,
                "display_name": "previous_response",
                "dynamic": false,
                "field_type": "str",
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "previous_response",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "type": "str",
                "value": ""
              },
              "template": {
                "_input_type": "PromptInput",
                "advanced": false,
                "display_name": "Template",
                "dynamic": false,
                "info": "",
                "list": false,
                "list_add_label": "Add More",
                "name": "template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "type": "prompt",
                "value": "Sample Data: {data}\nRecommended Machine Learning Models: {previous_response}\n\nGenerate Python code for the first model."
              },
              "tool_placeholder": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Tool Placeholder",
                "dynamic": false,
                "info": "A placeholder input for tool mode.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "tool_placeholder",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": true,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "showNode": true,
          "type": "Prompt"
        },
        "dragging": false,
        "id": "Prompt-KCJ8a",
        "measured": {
          "height": 481,
          "width": 320
        },
        "position": {
          "x": 2050.7900362649802,
          "y": -1124.5164152252878
        },
        "selected": false,
        "type": "genericNode"
      },
      {
        "data": {
          "id": "ChatOutput-4yaIs",
          "node": {
            "base_classes": [
              "Message"
            ],
            "beta": false,
            "category": "outputs",
            "conditional_paths": [],
            "custom_fields": {},
            "description": "Display a chat message in the Playground.",
            "display_name": "Chat Output",
            "documentation": "",
            "edited": false,
            "field_order": [
              "input_value",
              "should_store_message",
              "sender",
              "sender_name",
              "session_id",
              "data_template",
              "background_color",
              "chat_icon",
              "text_color",
              "clean_data"
            ],
            "frozen": false,
            "icon": "MessagesSquare",
            "key": "ChatOutput",
            "legacy": false,
            "lf_version": "1.4.2",
            "metadata": {},
            "minimized": true,
            "output_types": [],
            "outputs": [
              {
                "allows_loop": false,
                "cache": true,
                "display_name": "Message",
                "method": "message_response",
                "name": "message",
                "selected": "Message",
                "tool_mode": true,
                "types": [
                  "Message"
                ],
                "value": "__UNDEFINED__"
              }
            ],
            "pinned": false,
            "score": 0.003169567463043492,
            "template": {
              "_type": "Component",
              "background_color": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Background Color",
                "dynamic": false,
                "info": "The background color of the icon.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "background_color",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "chat_icon": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Icon",
                "dynamic": false,
                "info": "The icon of the message.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "chat_icon",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "clean_data": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Basic Clean Data",
                "dynamic": false,
                "info": "Whether to clean the data",
                "list": false,
                "list_add_label": "Add More",
                "name": "clean_data",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "code": {
                "advanced": true,
                "dynamic": true,
                "fileTypes": [],
                "file_path": "",
                "info": "",
                "list": false,
                "load_from_db": false,
                "multiline": true,
                "name": "code",
                "password": false,
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "type": "code",
                "value": "from collections.abc import Generator\nfrom typing import Any\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.inputs import BoolInput\nfrom langflow.inputs.inputs import HandleInput\nfrom langflow.io import DropdownInput, MessageTextInput, Output\nfrom langflow.schema.data import Data\nfrom langflow.schema.dataframe import DataFrame\nfrom langflow.schema.message import Message\nfrom langflow.schema.properties import Source\nfrom langflow.utils.constants import (\n    MESSAGE_SENDER_AI,\n    MESSAGE_SENDER_NAME_AI,\n    MESSAGE_SENDER_USER,\n)\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Display a chat message in the Playground.\"\n    icon = \"MessagesSquare\"\n    name = \"ChatOutput\"\n    minimized = True\n\n    inputs = [\n        HandleInput(\n            name=\"input_value\",\n            display_name=\"Text\",\n            info=\"Message to be passed as output.\",\n            input_types=[\"Data\", \"DataFrame\", \"Message\"],\n            required=True,\n        ),\n        BoolInput(\n            name=\"should_store_message\",\n            display_name=\"Store Messages\",\n            info=\"Store the message in the history.\",\n            value=True,\n            advanced=True,\n        ),\n        DropdownInput(\n            name=\"sender\",\n            display_name=\"Sender Type\",\n            options=[MESSAGE_SENDER_AI, MESSAGE_SENDER_USER],\n            value=MESSAGE_SENDER_AI,\n            advanced=True,\n            info=\"Type of sender.\",\n        ),\n        MessageTextInput(\n            name=\"sender_name\",\n            display_name=\"Sender Name\",\n            info=\"Name of the sender.\",\n            value=MESSAGE_SENDER_NAME_AI,\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"session_id\",\n            display_name=\"Session ID\",\n            info=\"The session ID of the chat. If empty, the current session ID parameter will be used.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"data_template\",\n            display_name=\"Data Template\",\n            value=\"{text}\",\n            advanced=True,\n            info=\"Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.\",\n        ),\n        MessageTextInput(\n            name=\"background_color\",\n            display_name=\"Background Color\",\n            info=\"The background color of the icon.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"chat_icon\",\n            display_name=\"Icon\",\n            info=\"The icon of the message.\",\n            advanced=True,\n        ),\n        MessageTextInput(\n            name=\"text_color\",\n            display_name=\"Text Color\",\n            info=\"The text color of the name\",\n            advanced=True,\n        ),\n        BoolInput(\n            name=\"clean_data\",\n            display_name=\"Basic Clean Data\",\n            value=True,\n            info=\"Whether to clean the data\",\n            advanced=True,\n        ),\n    ]\n    outputs = [\n        Output(\n            display_name=\"Message\",\n            name=\"message\",\n            method=\"message_response\",\n        ),\n    ]\n\n    def _build_source(self, id_: str | None, display_name: str | None, source: str | None) -> Source:\n        source_dict = {}\n        if id_:\n            source_dict[\"id\"] = id_\n        if display_name:\n            source_dict[\"display_name\"] = display_name\n        if source:\n            # Handle case where source is a ChatOpenAI object\n            if hasattr(source, \"model_name\"):\n                source_dict[\"source\"] = source.model_name\n            elif hasattr(source, \"model\"):\n                source_dict[\"source\"] = str(source.model)\n            else:\n                source_dict[\"source\"] = str(source)\n        return Source(**source_dict)\n\n    async def message_response(self) -> Message:\n        # First convert the input to string if needed\n        text = self.convert_to_string()\n        # Get source properties\n        source, icon, display_name, source_id = self.get_properties_from_source_component()\n        background_color = self.background_color\n        text_color = self.text_color\n        if self.chat_icon:\n            icon = self.chat_icon\n\n        # Create or use existing Message object\n        if isinstance(self.input_value, Message):\n            message = self.input_value\n            # Update message properties\n            message.text = text\n        else:\n            message = Message(text=text)\n\n        # Set message properties\n        message.sender = self.sender\n        message.sender_name = self.sender_name\n        message.session_id = self.session_id\n        message.flow_id = self.graph.flow_id if hasattr(self, \"graph\") else None\n        message.properties.source = self._build_source(source_id, display_name, source)\n        message.properties.icon = icon\n        message.properties.background_color = background_color\n        message.properties.text_color = text_color\n\n        # Store message if needed\n        if self.session_id and self.should_store_message:\n            stored_message = await self.send_message(message)\n            self.message.value = stored_message\n            message = stored_message\n\n        self.status = message\n        return message\n\n    def _validate_input(self) -> None:\n        \"\"\"Validate the input data and raise ValueError if invalid.\"\"\"\n        if self.input_value is None:\n            msg = \"Input data cannot be None\"\n            raise ValueError(msg)\n        if isinstance(self.input_value, list) and not all(\n            isinstance(item, Message | Data | DataFrame | str) for item in self.input_value\n        ):\n            invalid_types = [\n                type(item).__name__\n                for item in self.input_value\n                if not isinstance(item, Message | Data | DataFrame | str)\n            ]\n            msg = f\"Expected Data or DataFrame or Message or str, got {invalid_types}\"\n            raise TypeError(msg)\n        if not isinstance(\n            self.input_value,\n            Message | Data | DataFrame | str | list | Generator | type(None),\n        ):\n            type_name = type(self.input_value).__name__\n            msg = f\"Expected Data or DataFrame or Message or str, Generator or None, got {type_name}\"\n            raise TypeError(msg)\n\n    def _safe_convert(self, data: Any) -> str:\n        \"\"\"Safely convert input data to string.\"\"\"\n        try:\n            if isinstance(data, str):\n                return data\n            if isinstance(data, Message):\n                return data.get_text()\n            if isinstance(data, Data):\n                if data.get_text() is None:\n                    msg = \"Empty Data object\"\n                    raise ValueError(msg)\n                return data.get_text()\n            if isinstance(data, DataFrame):\n                if self.clean_data:\n                    # Remove empty rows\n                    data = data.dropna(how=\"all\")\n                    # Remove empty lines in each cell\n                    data = data.replace(r\"^\\s*$\", \"\", regex=True)\n                    # Replace multiple newlines with a single newline\n                    data = data.replace(r\"\\n+\", \"\\n\", regex=True)\n\n                # Replace pipe characters to avoid markdown table issues\n                processed_data = data.replace(r\"\\|\", r\"\\\\|\", regex=True)\n\n                processed_data = processed_data.map(\n                    lambda x: str(x).replace(\"\\n\", \"<br/>\") if isinstance(x, str) else x\n                )\n\n                return processed_data.to_markdown(index=False)\n            return str(data)\n        except (ValueError, TypeError, AttributeError) as e:\n            msg = f\"Error converting data: {e!s}\"\n            raise ValueError(msg) from e\n\n    def convert_to_string(self) -> str | Generator[Any, None, None]:\n        \"\"\"Convert input data to string with proper error handling.\"\"\"\n        self._validate_input()\n        if isinstance(self.input_value, list):\n            return \"\\n\".join([self._safe_convert(item) for item in self.input_value])\n        if isinstance(self.input_value, Generator):\n            return self.input_value\n        return self._safe_convert(self.input_value)\n"
              },
              "data_template": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Data Template",
                "dynamic": false,
                "info": "Template to convert Data to Text. If left empty, it will be dynamically set to the Data's text key.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "data_template",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "{text}"
              },
              "input_value": {
                "_input_type": "HandleInput",
                "advanced": false,
                "display_name": "Text",
                "dynamic": false,
                "info": "Message to be passed as output.",
                "input_types": [
                  "Data",
                  "DataFrame",
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "name": "input_value",
                "placeholder": "",
                "required": true,
                "show": true,
                "title_case": false,
                "trace_as_metadata": true,
                "type": "other",
                "value": ""
              },
              "sender": {
                "_input_type": "DropdownInput",
                "advanced": true,
                "combobox": false,
                "dialog_inputs": {},
                "display_name": "Sender Type",
                "dynamic": false,
                "info": "Type of sender.",
                "name": "sender",
                "options": [
                  "Machine",
                  "User"
                ],
                "options_metadata": [],
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "toggle": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "str",
                "value": "Machine"
              },
              "sender_name": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Sender Name",
                "dynamic": false,
                "info": "Name of the sender.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "sender_name",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": "AI"
              },
              "session_id": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Session ID",
                "dynamic": false,
                "info": "The session ID of the chat. If empty, the current session ID parameter will be used.",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "session_id",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              },
              "should_store_message": {
                "_input_type": "BoolInput",
                "advanced": true,
                "display_name": "Store Messages",
                "dynamic": false,
                "info": "Store the message in the history.",
                "list": false,
                "list_add_label": "Add More",
                "name": "should_store_message",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_metadata": true,
                "type": "bool",
                "value": true
              },
              "text_color": {
                "_input_type": "MessageTextInput",
                "advanced": true,
                "display_name": "Text Color",
                "dynamic": false,
                "info": "The text color of the name",
                "input_types": [
                  "Message"
                ],
                "list": false,
                "list_add_label": "Add More",
                "load_from_db": false,
                "name": "text_color",
                "placeholder": "",
                "required": false,
                "show": true,
                "title_case": false,
                "tool_mode": false,
                "trace_as_input": true,
                "trace_as_metadata": true,
                "type": "str",
                "value": ""
              }
            },
            "tool_mode": false
          },
          "showNode": false,
          "type": "ChatOutput"
        },
        "dragging": false,
        "id": "ChatOutput-4yaIs",
        "measured": {
          "height": 66,
          "width": 192
        },
        "position": {
          "x": 5140.980897955954,
          "y": -787.5399535496285
        },
        "selected": false,
        "type": "genericNode"
      }
    ],
    "viewport": {
      "x": -9.949177490308784,
      "y": 752.8968289869533,
      "zoom": 0.35357101242547034
    }
  },
  "description": "Agent that generates focused plans, conducts web searches, and synthesizes findings into comprehensive reports.",
  "endpoint_name": null,
  "id": "9008aead-354e-4430-a258-a9858108ae28",
  "is_component": false,
  "last_tested_version": "1.4.2",
  "name": "AI Data Analysis",
  "tags": [
    "assistants",
    "agents"
  ]
}