refactor: centralize llm backend configuration

plugins/message_summary/main.py

@@ -6,8 +6,6 @@ from datetime import datetime, timedelta
 from pathlib import Path
 from typing import Dict, Any, Tuple, Optional, List
 
-import aiohttp
-from aiohttp import ClientTimeout
 from loguru import logger
 
 from base.plugin_common.message_plugin_interface import MessagePluginInterface
@@ -22,6 +20,7 @@ from utils.markdown_to_image import convert_md_str_to_image
 from utils.revoke.message_auto_revoke import MessageAutoRevoke
 from utils.robot_cmd.robot_command import GroupBotManager, PermissionStatus
 from utils.string_utils import remove_reasoning_content, remove_trailing_content
+from utils.ai.unified_llm import UnifiedLLMClient
 from utils.wechat.contact_manager import ContactManager
 from utils.wechat.message_to_db import MessageStorage
 from wechat_ipad import WechatAPIClient
@@ -93,6 +92,10 @@ class MessageSummaryPlugin(MessagePluginInterface):
             self._connect_timeout_seconds = int(api_config.get("connect_timeout_seconds", 10))
             self._request_timeout_seconds = int(api_config.get("request_timeout_seconds", 180))
             self._retry_delays_seconds = api_config.get("retry_delays_seconds", [10, 20])
+            self.llm_client = UnifiedLLMClient(api_config)
+            self._api_mode = self.llm_client.mode or self._api_mode
+            self._response_mode = self.llm_client.response_mode or self._response_mode
+            self._workflow_output_key = self.llm_client.workflow_output_key or self._workflow_output_key
             self.message_storage = MessageStorage()
             db_manager = context.get("db_manager")
             if db_manager:
@@ -221,81 +224,6 @@ class MessageSummaryPlugin(MessagePluginInterface):
             sanitized_name = "群聊"
         return sanitized_name
 
-    async def _parse_streaming_response(self, response: aiohttp.ClientResponse) -> Dict[str, Any]:
-        """解析 Dify 的 SSE 流式响应"""
-        answer_parts: List[str] = []
-        metadata: Dict[str, Any] = {}
-        final_payload: Dict[str, Any] = {}
-        buffer = ""
-
-        async for chunk in response.content.iter_any():
-            if not chunk:
-                continue
-
-            buffer += chunk.decode("utf-8", errors="ignore")
-
-            while "\n\n" in buffer:
-                raw_event, buffer = buffer.split("\n\n", 1)
-                raw_event = raw_event.strip()
-                if not raw_event:
-                    continue
-
-                data_lines = []
-                for line in raw_event.splitlines():
-                    line = line.strip()
-                    if line.startswith("data:"):
-                        data_lines.append(line[5:].strip())
-
-                if not data_lines:
-                    continue
-
-                payload_text = "\n".join(data_lines).strip()
-                if not payload_text or payload_text == "[DONE]":
-                    continue
-
-                try:
-                    payload = json.loads(payload_text)
-                except json.JSONDecodeError:
-                    self.LOG.warning(f"无法解析流式响应片段: {payload_text[:200]}")
-                    continue
-
-                event_name = str(payload.get("event", "")).strip()
-                if event_name in {"message", "agent_message"}:
-                    chunk_text = payload.get("answer", "")
-                    if chunk_text:
-                        answer_parts.append(chunk_text)
-                elif event_name in {"message_end", "workflow_finished"}:
-                    final_payload = payload
-                    if self._api_mode == "workflow":
-                        payload_data = payload.get("data", {}) if isinstance(payload.get("data"), dict) else {}
-                        outputs = payload_data.get("outputs", {}) if isinstance(payload_data.get("outputs"), dict) else {}
-                        if outputs:
-                            for key in filter(None, [self._workflow_output_key, "text", "answer", "result_json", "result"]):
-                                if outputs.get(key) is not None:
-                                    answer_parts = [self._stringify_output(outputs.get(key))]
-                                    break
-                    metadata = payload.get("metadata", {}) or payload.get("data", {}).get("metadata", {}) or metadata
-                elif event_name == "error":
-                    raise RuntimeError(payload.get("message") or payload.get("error") or "流式总结生成失败")
-                else:
-                    if self._api_mode == "workflow":
-                        payload_data = payload.get("data", {}) if isinstance(payload.get("data"), dict) else {}
-                        outputs = payload_data.get("outputs", {}) if isinstance(payload_data.get("outputs"), dict) else {}
-                        for key in filter(None, [self._workflow_output_key, "text", "answer", "result_json", "result"]):
-                            if outputs.get(key) is not None:
-                                chunk_text = self._stringify_output(outputs.get(key))
-                                if chunk_text:
-                                    answer_parts.append(chunk_text)
-                                break
-
-        answer = "".join(answer_parts)
-        return {
-            "answer": answer,
-            "metadata": metadata,
-            "data": final_payload.get("data", {}) if isinstance(final_payload, dict) else {},
-            "event": final_payload.get("event", "") if isinstance(final_payload, dict) else "",
-        }
-
     def _append_usage_info(self, answer: str, metadata: Dict[str, Any]) -> str:
         """把 token 统计追加到总结文本末尾"""
         if not answer or not answer.strip():
@@ -440,7 +368,6 @@ class MessageSummaryPlugin(MessagePluginInterface):
 
     async def _generate_summary(self, chat_content: str, group_name: str) -> Tuple[str, Optional[str]]:
         """生成总结"""
-        # Dify API配置
         content_compress = chat_content
         try:
             content_compress = compress_chat_data(chat_content)
@@ -449,96 +376,50 @@ class MessageSummaryPlugin(MessagePluginInterface):
             self.LOG.error(f"压缩内容失败：{e}")
 
         prompt = f"请根据[{group_name}]群的群聊记录生成一份总结：\n\n{content_compress}"
-        if self._api_mode == "workflow":
-            data = {
-                "inputs": {
-                    "query": prompt,
-                    "group_name": group_name,
-                    "chat_content": content_compress,
-                },
-                "response_mode": self._response_mode,
-                "user": group_name if group_name is not None else "message_summary_bot",
-            }
-        else:
-            data = {
-                "inputs": {},
-                "query": prompt,
-                "response_mode": self._response_mode,
-                "conversation_id": "",
-                "user": group_name if group_name is not None else "message_summary_bot",
-                "files": []
-            }
-
-        self.LOG.info(f"群聊总结内容：{data}")
-        # 设置请求头
-        headers = {
-            "Authorization": f"Bearer {self._api_key}",
-            "Content-Type": "application/json",
-            "Accept": "text/event-stream" if self._response_mode == "streaming" else "application/json"
+        inputs = {
+            "query": prompt,
+            "group_name": group_name,
+            "chat_content": content_compress,
         }
+        self.LOG.info(f"群聊总结请求准备: group={group_name}, mode={self._api_mode}, response_mode={self._response_mode}")
 
         max_retries = len(self._retry_delays_seconds) + 1
 
         for attempt in range(1, max_retries + 1):
             try:
-                custom_timeout = ClientTimeout(
-                    total=None,
-                    connect=self._connect_timeout_seconds,
-                    sock_read=self._request_timeout_seconds
+                response = await asyncio.to_thread(
+                    self.llm_client.run,
+                    prompt,
+                    group_name if group_name is not None else "message_summary_bot",
+                    inputs,
+                    f"message_summary:{group_name}",
                 )
-                conn = aiohttp.TCPConnector(keepalive_timeout=60)  # 保持连接活跃
-                async with aiohttp.ClientSession(connector=conn, timeout=custom_timeout) as session:
-                    async with session.post(self._api_url, headers=headers, json=data) as response:
-                        response.raise_for_status()  # 检查请求是否成功
-                        if self._response_mode == "streaming":
-                            response_data = await self._parse_streaming_response(response)
-                        else:
-                            response_data = await response.json()
+                if not response or not response.get("text"):
+                    raise RuntimeError(self.llm_client.last_error or "LLM 未返回有效总结内容")
 
-                        self.LOG.info(f"Dify API响应状态码: {response.status}, attempt={attempt}")
-                        self.LOG.debug(f"响应数据: {json.dumps(response_data, ensure_ascii=False, indent=2)}")
+                answer = self._clean_summary_output(response.get("text", ""))
+                metadata = {"usage": response.get("usage", {}) or {}}
+                spath = ""
+                answer = self._append_usage_info(answer, metadata)
 
-                        if self._api_mode == "workflow":
-                            answer, metadata = self._parse_workflow_response(response_data)
-                        else:
-                            answer = response_data.get("answer", "")
-                            metadata = response_data.get("metadata", {})
+                if answer and len(answer.strip()) > 0:
+                    try:
+                        timestamp = int(time.time())
+                        output_path = f"summary_{timestamp}.png"
+                        self.LOG.info(f"开始生成图片: {output_path}")
+                        spath = await convert_md_str_to_image(answer, output_path)
+                        self.LOG.info(f"成功生成图片: {spath}")
+                    except Exception as e:
+                        self.LOG.error(f"生成图片失败: {e}", exc_info=True)
+                        max_length = 2000
+                        if len(answer) > max_length:
+                            answer = answer[:max_length] + "\n\n... (内容过长，已截断)"
+                        self.LOG.info("图片生成失败，将发送文本消息作为备选方案")
+                        spath = None
+                else:
+                    spath = None
+                return answer, spath
 
-                        if not answer or not answer.strip():
-                            raise RuntimeError("Dify 未返回有效总结内容")
-
-                        answer = self._clean_summary_output(answer)
-                        spath = ""
-                        answer = self._append_usage_info(answer, metadata)
-
-                        if answer and len(answer.strip()) > 0:
-                            try:
-                                # 使用唯一文件名并指定完整路径
-                                timestamp = int(time.time())
-                                output_path = f"summary_{timestamp}.png"
-                                self.LOG.info(f"开始生成图片: {output_path}")
-                                spath = await convert_md_str_to_image(answer, output_path)
-                                self.LOG.info(f"成功生成图片: {spath}")
-                            except Exception as e:
-                                self.LOG.error(f"生成图片失败: {e}", exc_info=True)
-                                try:
-                                    max_length = 2000
-                                    if len(answer) > max_length:
-                                        answer = answer[:max_length] + "\n\n... (内容过长，已截断)"
-                                    self.LOG.info("图片生成失败，将发送文本消息作为备选方案")
-                                    spath = None
-                                except Exception as fallback_error:
-                                    self.LOG.error(f"备选文本发送也失败: {fallback_error}")
-                                    spath = None
-                        else:
-                            spath = None
-                        # 返回文本内容和图片路径
-                        return answer, spath
-
-            except aiohttp.ClientError as e:
-                self.LOG.error(f"请求Dify API时出错: attempt={attempt}/{max_retries}, error={e}")
-            except json.JSONDecodeError as e:
-                self.LOG.error(f"解析Dify API响应时出错: attempt={attempt}/{max_retries}, error={e}")
             except Exception as e:
                 self.LOG.error(f"处理总结时出现未知错误: attempt={attempt}/{max_retries}, error={e}")