feat: 集成 Brave Search 工具调用（ReAct 循环）

image_daemon.py

@@ -14,6 +14,7 @@ APP_SECRET = os.environ.get("FEISHU_APP_SECRET", "")
 API_BASE_URL = os.environ.get("API_BASE_URL", "https://asem12345-cliproxyapi.hf.space/v1")
 API_KEY = os.environ.get("API_KEY", "")
 MODEL_NAME = os.environ.get("MODEL_NAME", "gemini-3-flash")
+BRAVE_API_KEY = os.environ.get("BRAVE_API_KEY", "")
 
 # OpenClaw Gateway (本地)
 OPENCLAW_GATEWAY = "http://127.0.0.1:18789/v1"
@@ -317,46 +318,117 @@ def check_openclaw_gateway():
     except Exception as e:
         log(f"⚠️ Gateway 不可用 ({e})，使用外部 LLM + SOUL 人设")
 
+# ---------- Brave Search ----------
+def search_brave(query, count=5):
+    """Brave Search API 一次搜索。返回整理得到的摘要字符串。"""
+    if not BRAVE_API_KEY:
+        return "搜索失败：BRAVE_API_KEY 未配置"
+    try:
+        resp = requests.get(
+            "https://api.search.brave.com/res/v1/web/search",
+            headers={"Accept": "application/json", "X-Subscription-Token": BRAVE_API_KEY},
+            params={"q": query, "count": count, "text_decorations": False, "extra_snippets": True},
+            timeout=10
+        )
+        if resp.status_code != 200:
+            return f"搜索失败 ({resp.status_code})"
+        results = resp.json().get("web", {}).get("results", [])
+        if not results:
+            return "未找到相关结果"
+        lines = []
+        for r in results[:count]:
+            title = r.get("title", "无标题")
+            url = r.get("url", "")
+            desc = r.get("description") or (r.get("extra_snippets") or [""])[0]
+            lines.append(f"- **{title}**\n  {desc}\n  {url}")
+        log(f"🔍 Brave 搜索「{query}」得到 {len(results)} 条")
+        return "\n".join(lines)
+    except Exception as e:
+        log(f"⚠️ Brave 搜索异常: {e}")
+        return f"搜索异常: {e}"
+
+# Brave Search 的 OpenAI tools 定义
+BRAVE_TOOL_DEF = [{
+    "type": "function",
+    "function": {
+        "name": "brave_search",
+        "description": "当需要查找实时信息、最新数据、公司信息、行业报告等时，调用此工具进行网页搜索",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "query": {
+                    "type": "string",
+                    "description": "搜索关键词，英文搜索通常效果更好"
+                }
+            },
+            "required": ["query"]
+        }
+    }
+}]
+
 # ---------- LLM 对话 ----------
 def chat_with_llm(user_text, history=None):
-    """优先转发给本地 OpenClaw Gateway（带人设+插件），Fallback 到外部 LLM+SOUL"""
+    """带 Brave Search 工具的 ReAct 循环（最多搜 3 次）"""
     try:
         if _use_gateway:
-            # 走 OpenClaw Gateway：人设和工具由它处理
             resp = requests.post(
                 f"{OPENCLAW_GATEWAY}/chat/completions",
                 json={"model": "default", "messages": (history or []) + [{"role": "user", "content": user_text}], "stream": False},
                 timeout=120
             )
             if resp.status_code == 200:
-                data = resp.json()
-                reply = data["choices"][0]["message"]["content"]
+                reply = resp.json()["choices"][0]["message"]["content"]
                 log(f"🤖 Gateway 回复: {reply[:60]}...")
                 return reply
             log(f"⚠️ Gateway 失败 ({resp.status_code})，Fallback到外部 LLM")
 
-        # Fallback：外部 LLM + SOUL.md 人设
         if not API_KEY:
             return "抱歉，我的大脑连接中断了 (API_KEY missing)"
+
+        import json as _json
         soul = _soul_prompt or "You are a helpful assistant."
+        headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
         messages = [{"role": "system", "content": soul}] + (history or []) + [{"role": "user", "content": user_text}]
-        payload = {"model": MODEL_NAME, "messages": messages, "stream": False}
-        log(f"🤖 外部 LLM ({MODEL_NAME}): {user_text[:50]}...")
-        resp = requests.post(
-            f"{API_BASE_URL}/chat/completions",
-            headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
-            json=payload, timeout=60
-        )
-        if resp.status_code == 200:
-            reply = resp.json()["choices"][0]["message"]["content"]
-            log(f"🤖 LLM 回复: {reply[:60]}...")
-            return reply
-        log(f"❌ 外部 LLM 错误 {resp.status_code}: {resp.text[:100]}")
-        return f"思考时遇到错误 ({resp.status_code})"
+
+        for _ in range(4):  # 最多 3 次工具调用 + 1 次最终回复
+            log(f"🤖 外部 LLM ({MODEL_NAME}): {user_text[:50]}...")
+            payload = {
+                "model": MODEL_NAME,
+                "messages": messages,
+                "stream": False
+            }
+            if BRAVE_API_KEY:
+                payload["tools"] = BRAVE_TOOL_DEF
+            resp = requests.post(f"{API_BASE_URL}/chat/completions", headers=headers, json=payload, timeout=60)
+            if resp.status_code != 200:
+                log(f"❌ 外部 LLM 错误 {resp.status_code}: {resp.text[:100]}")
+                return f"思考时遇到错误 ({resp.status_code})"
+
+            msg = resp.json()["choices"][0]["message"]
+            tool_calls = msg.get("tool_calls") or []
+
+            if not tool_calls:
+                reply = msg.get("content", "")
+                log(f"🤖 LLM 回复: {reply[:60]}...")
+                return reply
+
+            # 执行工具调用
+            messages.append(msg)
+            for tc in tool_calls:
+                fn = tc["function"]["name"]
+                args = _json.loads(tc["function"]["arguments"])
+                if fn == "brave_search":
+                    result = search_brave(args.get("query", ""))
+                else:
+                    result = f"未知工具: {fn}"
+                messages.append({"role": "tool", "tool_call_id": tc["id"], "content": result})
+
+        return "思考超时，请稍后再试"
     except Exception as e:
         log(f"❌ chat_with_llm 异常: {e}")
         return f"大脑短路了: {e}"
 
+
 # ---------- 处理文本消息 ----------
 def handle_text_message(message_id, chat_id, text):
     """LLM (带历史) -> 发送，如有待处理图片则做针对 Vision"""