feat: QYLAW 法律法规知识库

- 语义检索(FAISS + embedding)+ 精确查找(法规名+条号) - RAG 问答(SSE 流式,支持 thinking 折叠显示) - 法规浏览(原文阅读) - 历史记录(检索+对话持久化到 SQLite) - 设置页(系统提示词/模板/LLM 参数可配置) - 检索质量评估脚本 Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
2026-08-07 14:55:25 +08:00
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+"""LLM 客户端 — 调用 114:7000 Qwen3.5-35B 服务(流式)"""
+import json
+import logging
+from typing import AsyncGenerator
+
+import httpx
+
+from app.config import LLM_URL, LLM_MODEL
+
+logger = logging.getLogger(__name__)
+
+_client: httpx.AsyncClient | None = None
+
+
+def _get_client() -> httpx.AsyncClient:
+    global _client
+    if _client is None or _client.is_closed:
+        _client = httpx.AsyncClient(timeout=120)
+    return _client
+
+
+DEFAULT_SYSTEM_PROMPT = "你是法律助手,根据提供的法规条文回答问题,必须引用法规名和条号。"
+
+
+async def stream_chat(
+    prompt: str,
+    system: str | None = None,
+    temperature: float = 0.3,
+    max_tokens: int = 2048,
+    thinking_enabled: bool = True,
+    thinking_budget: int = 2048,
+) -> AsyncGenerator[tuple[str, str], None]:
+    """流式对话,区分 thinking 和 answer
+
+    模型输出格式:thinking 内容以 "Here's a thinking process:" 开头,
+    以 </thinking> 结尾,之后是正式回答。
+
+    Args:
+        prompt: 用户 prompt(已含 context)
+        system: system prompt
+        temperature: 温度
+        max_tokens: 最大生成 token(含 thinking)
+        thinking_enabled: 是否启用 thinking
+        thinking_budget: thinking 预算(thinking 最大 token 数)
+
+    Yields:
+        (type, content) 元组,type 为 "thinking" 或 "answer"
+
+    Raises:
+        RuntimeError: LLM 服务不可用
+    """
+    client = _get_client()
+    sys_content = system if system else DEFAULT_SYSTEM_PROMPT
+
+    # thinking 关闭时,通过 system prompt 补充指示
+    if not thinking_enabled:
+        sys_content += "\n\n注意:不要输出思考过程,直接给出答案。"
+
+    # payload:使用 chat_template_kwargs.enable_thinking 控制 thinking 开关
+    # 这是 Qwen3.5 vLLM 的原生参数,比 system prompt 更可靠
+    payload = {
+        "model": LLM_MODEL,
+        "messages": [
+            {"role": "system", "content": sys_content},
+            {"role": "user", "content": prompt},
+        ],
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+        "stream": True,
+        "chat_template_kwargs": {"enable_thinking": thinking_enabled},
+    }
+
+    # 状态机:跟踪当前是否在 thinking 区域
+    in_thinking = thinking_enabled  # thinking 开启时,输出通常以 thinking 开头
+    # 小缓冲:仅用于检测跨块的 thinking 结束标记
+    tail_buffer = ""
+    # Qwen3.5 的 thinking 结束标记: </think>
+    THINKING_END_TAG = "</think>"
+
+    last_err = None
+    for attempt in range(2):  # 重试 1 次
+        try:
+            async with client.stream(
+                "POST",
+                f"{LLM_URL}/chat/completions",
+                json=payload,
+                timeout=120,
+            ) as resp:
+                resp.raise_for_status()
+                async for line in resp.aiter_lines():
+                    if not line or not line.startswith("data: "):
+                        continue
+                    data_str = line[6:]
+                    if data_str.strip() == "[DONE]":
+                        return
+                    try:
+                        chunk = json.loads(data_str)
+                        delta = chunk["choices"][0].get("delta", {})
+                        content = delta.get("content", "")
+                        if not content:
+                            continue
+
+                        if not thinking_enabled:
+                            # thinking 关闭,全部作为 answer
+                            yield ("answer", content)
+                        else:
+                            # thinking 开启,需要解析 THINKING_END_TAG 标记
+                            if in_thinking:
+                                if THINKING_END_TAG in content:
+                                    # 分割:前面是 thinking,后面是 answer
+                                    parts = content.split(THINKING_END_TAG, 1)
+                                    thinking_part = parts[0]
+                                    answer_part = parts[1] if len(parts) > 1 else ""
+                                    if thinking_part:
+                                        yield ("thinking", thinking_part)
+                                    if answer_part:
+                                        yield ("answer", answer_part.lstrip())
+                                    in_thinking = False
+                                    tail_buffer = ""
+                                else:
+                                    # 检查是否是 THINKING_END_TAG 的前缀(跨块情况)
+                                    tail_buffer = (tail_buffer + content)[-12:]
+                                    # 检查 tail_buffer 是否是 THINKING_END_TAG 的前缀
+                                    is_prefix = any(
+                                        tail_buffer.endswith(THINKING_END_TAG[:k])
+                                        for k in range(1, len(THINKING_END_TAG))
+                                    )
+                                    if is_prefix:
+                                        continue
+                                    yield ("thinking", content)
+                            else:
+                                yield ("answer", content)
+                    except (json.JSONDecodeError, KeyError, IndexError):
+                        continue
+            return
+        except Exception as e:
+            last_err = e
+            logger.warning(f"LLM 流式调用第 {attempt+1} 次失败: {e}")
+
+    raise RuntimeError(f"LLM 服务调用失败: {last_err}")