feat:统一API格式为Gemini

plugins/AIChat/main.py

@@ -488,7 +488,7 @@ class AIChat(PluginBase):
 
     async def _generate_image_description(self, image_base64: str, prompt: str, config: dict) -> str:
         """
-        使用 AI 生成图片描述
+        使用 Gemini API 生成图片描述
 
         Args:
             image_base64: 图片的 base64 数据
@@ -498,26 +498,39 @@ class AIChat(PluginBase):
         Returns:
             图片描述文本，失败返回空字符串
         """
+        import json
         try:
             api_config = self.config["api"]
             description_model = config.get("model", api_config["model"])
+            api_url = api_config.get("gemini_url", "https://api.functen.cn/v1beta/models")
 
-            # 构建消息
-            messages = [
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": prompt},
-                        {"type": "image_url", "image_url": {"url": image_base64}}
-                    ]
-                }
-            ]
+            # 处理 base64 数据
+            image_data = image_base64
+            mime_type = "image/jpeg"
+            if image_data.startswith("data:"):
+                mime_type = image_data.split(";")[0].split(":")[1]
+                image_data = image_data.split(",", 1)[1]
+
+            # 构建 Gemini 格式请求
+            full_url = f"{api_url}/{description_model}:streamGenerateContent?alt=sse"
 
             payload = {
-                "model": description_model,
-                "messages": messages,
-                "max_tokens": config.get("max_tokens", 1000),
-                "stream": True
+                "contents": [
+                    {
+                        "parts": [
+                            {"text": prompt},
+                            {
+                                "inline_data": {
+                                    "mime_type": mime_type,
+                                    "data": image_data
+                                }
+                            }
+                        ]
+                    }
+                ],
+                "generationConfig": {
+                    "maxOutputTokens": config.get("max_tokens", 1000)
+                }
             }
 
             headers = {
@@ -525,12 +538,12 @@ class AIChat(PluginBase):
                 "Authorization": f"Bearer {api_config['api_key']}"
             }
 
-            timeout = aiohttp.ClientTimeout(total=api_config["timeout"])
+            timeout = aiohttp.ClientTimeout(total=api_config.get("timeout", 120))
 
             # 配置代理
             connector = None
             proxy_config = self.config.get("proxy", {})
-            if proxy_config.get("enabled", False):
+            if proxy_config.get("enabled", False) and PROXY_SUPPORT:
                 proxy_type = proxy_config.get("type", "socks5").upper()
                 proxy_host = proxy_config.get("host", "127.0.0.1")
                 proxy_port = proxy_config.get("port", 7890)
@@ -542,43 +555,37 @@ class AIChat(PluginBase):
                 else:
                     proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
 
-                if PROXY_SUPPORT:
-                    try:
-                        connector = ProxyConnector.from_url(proxy_url)
-                    except Exception as e:
-                        logger.warning(f"代理配置失败，将直连: {e}")
-                        connector = None
+                try:
+                    connector = ProxyConnector.from_url(proxy_url)
+                except Exception as e:
+                    logger.warning(f"代理配置失败，将直连: {e}")
 
             async with aiohttp.ClientSession(timeout=timeout, connector=connector) as session:
-                async with session.post(
-                    api_config["url"],
-                    json=payload,
-                    headers=headers
-                ) as resp:
+                async with session.post(full_url, json=payload, headers=headers) as resp:
                     if resp.status != 200:
                         error_text = await resp.text()
                         logger.error(f"图片描述 API 返回错误: {resp.status}, {error_text[:200]}")
                         return ""
 
-                    # 流式接收响应
-                    import json
+                    # 流式接收 Gemini 响应
                     description = ""
                     async for line in resp.content:
                         line = line.decode('utf-8').strip()
-                        if not line or line == "data: [DONE]":
+                        if not line or not line.startswith("data: "):
                             continue
 
-                        if line.startswith("data: "):
-                            try:
-                                data = json.loads(line[6:])
-                                delta = data.get("choices", [{}])[0].get("delta", {})
-                                content = delta.get("content", "")
-                                if content:
-                                    description += content
-                            except:
-                                pass
+                        try:
+                            data = json.loads(line[6:])
+                            candidates = data.get("candidates", [])
+                            if candidates:
+                                parts = candidates[0].get("content", {}).get("parts", [])
+                                for part in parts:
+                                    if "text" in part:
+                                        description += part["text"]
+                        except:
+                            pass
 
-                    logger.debug(f"图片描述生成成功: {description}")
+                    logger.debug(f"图片描述生成成功: {description[:100]}...")
                     return description.strip()
 
         except Exception as e:
@@ -788,6 +795,7 @@ class AIChat(PluginBase):
         Gemini 格式: {"functionCall": {"name": "...", "args": {...}}}
         转换为内部格式: {"id": "...", "function": {"name": "...", "arguments": "..."}}
         """
+        import json
         tool_calls = []
         for i, part in enumerate(response_parts):
             if "functionCall" in part:
@@ -812,6 +820,7 @@ class AIChat(PluginBase):
             tool_calls: 工具调用列表
             tool_results: 工具执行结果列表
         """
+        import json
         new_contents = contents.copy()
 
         # 添加 model 的工具调用响应