feat(ollama): shared stdlib-only Ollama HTTP client

core/ollama_client.py

@@ -0,0 +1,265 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""共享 Ollama 接入层 — 统一 4 个模块的 Ollama HTTP 调用。
+
+收敛对象 (此前各自重复实现):
+  - cerebellum_core.py      小脑: /api/embed 批处理 + /api/generate + /api/tags (urllib)
+  - router_cascade.py       路由: /api/embed + /api/generate + /api/tags (urllib)
+  - token_saver_mcp_server  压缩: /api/chat + /api/tags (httpx)
+  - mcp-servers/ollama-mcp  桥接: /api/generate|chat 流式 + 旧版 /api/embeddings (urllib)
+
+设计原则:
+  - 零第三方依赖: 仅标准库 urllib (统一原 httpx 路径)
+  - 低层接入: 只做 HTTP 封装 + 数据提取; 异常向上抛, 由调用方保持各自的降级策略
+  - 不动配置: 各模块保留自己的 env 前缀与默认模型, 本模块只收"怎么调"
+  - 兼容双接口: /api/generate (补全式) 与 /api/chat (聊天式) 都支持; 流式/非流式都支持
+"""
+
+from __future__ import annotations
+
+import json
+import urllib.request
+from typing import Any, Dict, List, Optional
+
+
+# ═══════════════════════════════════════════
+# 底层 HTTP (urllib, 零第三方依赖)
+# ═══════════════════════════════════════════
+
+
+def _url(host: str, path: str) -> str:
+    return f"{host.rstrip('/')}{path}"
+
+
+def post_json(
+    host: str, path: str, payload: Dict[str, Any], timeout: int = 120
+) -> Dict[str, Any]:
+    """POST JSON → JSON。网络/解析异常向上抛, 由调用方决定降级。"""
+    req = urllib.request.Request(
+        _url(host, path),
+        data=json.dumps(payload).encode("utf-8"),
+        headers={"Content-Type": "application/json"},
+        method="POST",
+    )
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        return json.loads(resp.read().decode("utf-8"))
+
+
+def get_json(host: str, path: str, timeout: int = 30) -> Dict[str, Any]:
+    """GET → JSON。异常向上抛。"""
+    req = urllib.request.Request(_url(host, path), method="GET")
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        return json.loads(resp.read().decode("utf-8"))
+
+
+def _stream_lines(
+    host: str, path: str, payload: Dict[str, Any], timeout: int = 120
+) -> List[Dict[str, Any]]:
+    """流式 POST, 逐行解析 JSON 对象 (Ollama NDJSON)。异常向上抛。"""
+    req = urllib.request.Request(
+        _url(host, path),
+        data=json.dumps(payload).encode("utf-8"),
+        headers={"Content-Type": "application/json"},
+        method="POST",
+    )
+    chunks: List[Dict[str, Any]] = []
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        for line in resp:
+            line = line.decode("utf-8", errors="replace").strip()
+            if not line:
+                continue
+            try:
+                chunks.append(json.loads(line))
+            except json.JSONDecodeError:
+                continue
+    return chunks
+
+
+# ═══════════════════════════════════════════
+# 健康检查
+# ═══════════════════════════════════════════
+
+
+def status(host: str) -> Dict[str, Any]:
+    """Ollama 健康检查 (GET /api/tags)。失败自带降级: {"ok": False, "error": ...}"""
+    try:
+        tags = get_json(host, "/api/tags", timeout=5)
+        models = [m["name"] for m in tags.get("models", [])]
+        return {"ok": True, "host": host, "models": models}
+    except Exception as e:
+        return {"ok": False, "host": host, "error": str(e)}
+
+
+# ═══════════════════════════════════════════
+# 向量嵌入 (新版 /api/embed, 支持批处理)
+# ═══════════════════════════════════════════
+
+
+def embed(
+    host: str, model: str, texts: List[str], timeout: int = 60
+) -> List[List[float]]:
+    """批量向量化, 返回 embeddings 列表 (与 texts 顺序一致)。异常向上抛。"""
+    resp = post_json(
+        host, "/api/embed", {"model": model, "input": texts}, timeout=timeout
+    )
+    return resp.get("embeddings", [])
+
+
+# ═══════════════════════════════════════════
+# 补全式生成 (/api/generate, 非流式)
+# ═══════════════════════════════════════════
+
+
+def generate(
+    host: str,
+    model: str,
+    prompt: str,
+    system: str = "",
+    temperature: float = 0.3,
+    max_tokens: int = 512,
+    timeout: int = 120,
+    think: Optional[bool] = None,
+) -> str:
+    """补全式生成, 返回正文文本。异常向上抛。
+
+    think: qwen3 等思考模型的控制开关; None=不控制, False=关闭思考
+           (摘要/分类任务建议 False, 避免思考过程吃掉 token 预算)。
+    兜底: 某些模型 response 为空但 thinking 有内容时, 取 thinking 末尾 200 字符。
+    """
+    payload: Dict[str, Any] = {
+        "model": model,
+        "prompt": prompt,
+        "system": system,
+        "stream": False,
+        "options": {"temperature": temperature, "num_predict": max_tokens},
+    }
+    if think is not None:
+        # qwen3 顶层 think 参数 (options 内不生效)
+        payload["think"] = think
+    resp = post_json(host, "/api/generate", payload, timeout=timeout)
+    out = (resp.get("response") or "").strip()
+    if not out and resp.get("thinking"):
+        out = (resp.get("thinking") or "").strip()[-200:]
+    return out
+
+
+def generate_stream(
+    host: str,
+    model: str,
+    prompt: str,
+    system: str = "",
+    temperature: float = 0.7,
+    max_tokens: int = 2048,
+    timeout: int = 120,
+) -> str:
+    """流式补全生成 (逐行 NDJSON), 拼接 response 返回。异常向上抛。"""
+    payload: Dict[str, Any] = {
+        "model": model,
+        "prompt": prompt,
+        "system": system,
+        "stream": True,
+        "options": {"temperature": temperature, "num_predict": max_tokens},
+    }
+    parts: List[str] = []
+    for chunk in _stream_lines(host, "/api/generate", payload, timeout=timeout):
+        text = chunk.get("response") or ""
+        if text:
+            parts.append(text)
+        if chunk.get("done"):
+            break
+    return "".join(parts)
+
+
+# ═══════════════════════════════════════════
+# 聊天式生成 (/api/chat)
+# ═══════════════════════════════════════════
+
+
+def chat(
+    host: str,
+    model: str,
+    messages: List[Dict[str, Any]],
+    temperature: float = 0.2,
+    max_tokens: int = 512,
+    timeout: int = 180,
+    keep_alive: str = "30m",
+) -> Dict[str, Any]:
+    """聊天式生成 (非流式), 返回 Ollama 原始 JSON
+    (含 message.content / prompt_eval_count / eval_count)。异常向上抛。
+    """
+    payload: Dict[str, Any] = {
+        "model": model,
+        "messages": messages,
+        "stream": False,
+        "options": {"temperature": temperature, "num_predict": max_tokens},
+        "keep_alive": keep_alive,
+    }
+    return post_json(host, "/api/chat", payload, timeout=timeout)
+
+
+def chat_stream(
+    host: str,
+    model: str,
+    messages: List[Dict[str, Any]],
+    temperature: float = 0.7,
+    max_tokens: int = 2048,
+    timeout: int = 120,
+) -> str:
+    """流式聊天 (逐行 NDJSON), 拼接 message.content 返回。异常向上抛。"""
+    payload: Dict[str, Any] = {
+        "model": model,
+        "messages": messages,
+        "stream": True,
+        "options": {"temperature": temperature, "num_predict": max_tokens},
+    }
+    parts: List[str] = []
+    for chunk in _stream_lines(host, "/api/chat", payload, timeout=timeout):
+        msg = chunk.get("message") or {}
+        text = msg.get("content") or ""
+        if text:
+            parts.append(text)
+        if chunk.get("done"):
+            break
+    return "".join(parts)
+
+
+# ═══════════════════════════════════════════
+# 模型管理
+# ═══════════════════════════════════════════
+
+
+def list_models(host: str, timeout: int = 30) -> List[str]:
+    """列出已安装模型名。异常向上抛。"""
+    tags = get_json(host, "/api/tags", timeout=timeout)
+    return [m["name"] for m in tags.get("models", [])]
+
+
+def pull_model(host: str, model: str, timeout: int = 300) -> Dict[str, Any]:
+    """拉取模型 (POST /api/pull)。异常向上抛。"""
+    return post_json(
+        host, "/api/pull", {"model": model, "stream": False}, timeout=timeout
+    )
+
+
+def delete_model(host: str, model: str, timeout: int = 60) -> Dict[str, Any]:
+    """删除模型 (DELETE /api/delete)。异常向上抛。"""
+    req = urllib.request.Request(
+        _url(host, "/api/delete"),
+        data=json.dumps({"model": model}).encode("utf-8"),
+        headers={"Content-Type": "application/json"},
+        method="DELETE",
+    )
+    with urllib.request.urlopen(req, timeout=timeout) as resp:
+        return json.loads(resp.read().decode("utf-8"))
+
+
+# ═══════════════════════════════════════════
+# 自检 (smoke test)
+# ═══════════════════════════════════════════
+
+if __name__ == "__main__":
+    import sys
+
+    host = sys.argv[1] if len(sys.argv) > 1 else "http://127.0.0.1:11434"
+    print("status:", status(host))
+    print("models:", list_models(host) if status(host).get("ok") else [])