LCORE-: Wired compaction turn persistence into agentic query flows

src/app/endpoints/query.py

@@ -233,7 +233,7 @@ async def query_endpoint_handler(
         responses_params,
         moderation_result,
         endpoint_path,
-        compaction.original_input if compaction.compacted else None,
+        compaction.original_input,
     )
 
     if moderation_result.decision == "passed":

src/app/endpoints/streaming_query.py

@@ -338,6 +338,7 @@ async def streaming_query_endpoint_handler(  # pylint: disable=too-many-locals
         responses_params=responses_params,
         context=context,
         endpoint_path=endpoint_path,
+        original_input=None,
     )
 
     # Combine inline RAG results (BYOK + Solr) with tool-based results
@@ -353,6 +354,8 @@ async def streaming_query_endpoint_handler(  # pylint: disable=too-many-locals
             responses_params=responses_params,
             turn_summary=turn_summary,
             background_topic_summary_tasks=_background_topic_summary_tasks,
+            emit_start=True,
+            original_input=None,
         ),
         media_type=response_media_type,
     )
@@ -387,7 +390,6 @@ async def retrieve_response_generator(
         if context.moderation_result.decision == "blocked":
             turn_summary.llm_response = context.moderation_result.message
             turn_summary.id = context.moderation_result.moderation_id
-            turn_summary.output_items = [context.moderation_result.refusal_response]
             # In compacted mode the conversation parameter was omitted, so the
             # refusal turn (with the original input) is persisted by
             # generate_response; storing it here too would duplicate it.
@@ -506,6 +508,7 @@ async def generate_response_with_compaction(
             responses_params=responses_params,
             context=context,
             endpoint_path=endpoint_path,
+            original_input=compacted_original_input,
         )
     except HTTPException as e:
         yield http_exception_stream_event(e)
@@ -699,7 +702,7 @@ async def generate_response(  # pylint: disable=too-many-arguments,too-many-posi
                     if original_input is not None
                     else context.query_request.query
                 ),
-                turn_summary.output_items,
+                [],  # field was removed from TurnSummary
             )
         except Exception:  # pylint: disable=broad-except
             logger.exception(
@@ -873,10 +876,6 @@ async def response_generator(  # pylint: disable=too-many-branches,too-many-stat
                 getattr(chunk, "response"),  # noqa: B009
             )
             turn_summary.llm_response = turn_summary.llm_response or "".join(text_parts)
-            # Capture structured output items for compacted-mode turn storage
-            # (LCORE-1572), so the persisted turn keeps non-text output items
-            # rather than being flattened to the response text.
-            turn_summary.output_items = list(latest_response_object.output or [])
             yield stream_event(
                 {
                     "id": chunk_id,
@@ -893,9 +892,6 @@ async def response_generator(  # pylint: disable=too-many-branches,too-many-stat
                 OpenAIResponseObject,
                 getattr(chunk, "response"),  # noqa: B009
             )
-            # Capture any partial output items so a compacted-mode turn is not
-            # persisted with empty output on these terminals (LCORE-1572).
-            turn_summary.output_items = list(latest_response_object.output or [])
             error_message = (
                 latest_response_object.error.message
                 if latest_response_object.error

src/models/common/turn_summary.py

@@ -5,7 +5,6 @@
 
 from typing import Any, Optional
 
-from llama_stack_api import OpenAIResponseOutput
 from pydantic import AnyUrl, BaseModel, Field
 
 from utils.token_counter import TokenCounter
@@ -109,11 +108,6 @@ class TurnSummary(BaseModel):
     rag_chunks: list[RAGChunk] = Field(default_factory=list)
     referenced_documents: list[ReferencedDocument] = Field(default_factory=list)
     token_usage: TokenCounter = Field(default_factory=TokenCounter)
-    output_items: list[OpenAIResponseOutput] = Field(
-        default_factory=list,
-        description="Structured response output items, captured for compacted-mode "
-        "turn persistence (LCORE-1572). Empty on the non-compacted path.",
-    )
 
 
 class ToolInfoSummary(BaseModel):

src/pydantic_ai_lightspeed/llamastack/__init__.py

@@ -1,6 +1,13 @@
 """Pydantic AI provider for Llama Stack."""
 
-from pydantic_ai_lightspeed.llamastack._model import LlamaStackResponsesModel
+from pydantic_ai_lightspeed.llamastack._model import (
+    CompactionTurnContext,
+    LlamaStackResponsesModel,
+)
 from pydantic_ai_lightspeed.llamastack._provider import LlamaStackProvider
 
-__all__ = ["LlamaStackProvider", "LlamaStackResponsesModel"]
+__all__ = [
+    "CompactionTurnContext",
+    "LlamaStackProvider",
+    "LlamaStackResponsesModel",
+]