Merge branch 'feat/openai-compatible'

.gitignore

@@ -16,6 +16,7 @@ uploads
 .venv
 __pycache__
 .claude
+*.db
 
 # Editor directories and files
 .vscode/*
@@ -27,3 +28,10 @@ __pycache__
 *.njsproj
 *.sln
 *.sw?
+
+# Skills
+.skills
+.agent
+.agents
+.trae
+skills-lock.json

server/api/chat_routes_glm.py

@@ -1,150 +0,0 @@
-"""
-GLM-4.6V 平台路由处理器（zai-sdk）
-所有智谱 GLM 相关逻辑均集中在此文件，main.py 无感知任何平台细节。
-"""
-
-import json
-import os
-import sys
-from pathlib import Path
-
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse, StreamingResponse
-
-from utils.helpers import generate_unique_id, get_current_timestamp
-from utils.logger import log_info
-
-
-def init():
-    """
-    初始化 GLM 后端：验证 API Key 是否配置。
-    由 main.py 在启动时调用（若 LLM_BACKEND=glm）。
-    """
-    api_key = os.getenv("ZHIPU_API_KEY") or os.getenv("GLM_API_KEY")
-    if not api_key:
-        raise ValueError(
-            "GLM 模式需要设置环境变量 ZHIPU_API_KEY（在 https://open.bigmodel.cn 申请）"
-        )
-    log_info(f"[GLM] 初始化完成，ZHIPU_API_KEY 已配置")
-
-
-async def chat_handler(body: dict):
-    """
-    GLM 聊天处理器（对外接口与百炼 chat_endpoint_handler 完全兼容）。
-    流式/非流式自动适配，支持图像、文档附件、联网搜索、深度思考。
-    """
-    from utils.glm_adapter import glm_chat_sync, glm_stream_generator
-
-    if not isinstance(body, dict):
-        raise HTTPException(status_code=400, detail="请求体必须是 JSON 对象")
-
-    messages = body.get("messages", [])
-    model = body.get("model", "glm-4.6v")
-    stream = body.get("stream", True)
-    temperature = body.get("temperature", 0.7)
-    max_tokens = body.get("max_tokens", body.get("maxTokens", 2000))
-    # 区分搜索模式：深度搜索 > 简单搜索 > 不搜索
-    if body.get("deepSearch", False):
-        web_search = "deep"
-    elif body.get("webSearch", False):
-        web_search = "simple"
-    else:
-        web_search = False
-    deep_think = body.get("deepThinking", False)
-    files = body.get("files", [])
-
-    # 兼容前端简化格式（非 messages 结构）
-    if not messages:
-        msg_text = body.get("message", "")
-        sys_prompt = body.get("systemPrompt", "你是一个智能助手。")
-        user_content = (
-            msg_text
-            if isinstance(msg_text, list)
-            else [{"type": "text", "text": msg_text}]
-        )
-        messages = [
-            {"role": "system", "content": sys_prompt},
-            {"role": "user", "content": user_content},
-        ]
-
-    log_info(
-        f"[GLM] model={model} stream={stream} web_search={web_search} "
-        f"thinking={deep_think} files={len(files)} msgs={len(messages)}"
-    )
-
-    if stream:
-        return StreamingResponse(
-            glm_stream_generator(
-                messages=messages,
-                model=model,
-                temperature=temperature,
-                max_tokens=max_tokens,
-                files=files or None,
-                web_search=web_search,
-                deep_thinking=deep_think,
-            ),
-            media_type="text/event-stream",
-        )
-
-    result = glm_chat_sync(
-        messages=messages,
-        model=model,
-        temperature=temperature,
-        max_tokens=max_tokens,
-        files=files or None,
-        web_search=web_search,
-        deep_thinking=deep_think,
-    )
-    resp = {
-        "id": f"chatcmpl-{generate_unique_id()}",
-        "object": "chat.completion",
-        "created": get_current_timestamp(),
-        "model": result["model"],
-        "choices": [
-            {
-                "index": 0,
-                "message": {"role": "assistant", "content": result["content"]},
-                "finish_reason": "stop",
-            }
-        ],
-    }
-    if result.get("usage"):
-        resp["usage"] = result["usage"]
-    return JSONResponse(content=resp)
-
-
-def models_handler():
-    """返回 GLM 可用模型列表"""
-    return {
-        "data": [
-            {
-                "id": "glm-4.6v",
-                "name": "GLM-4.6V（推荐）",
-                "description": "最新旗舰模型，支持文本/图像/文档/深度思考",
-                "maxTokens": 128000,
-                "provider": "ZhipuAI",
-            },
-            {
-                "id": "glm-4-flash",
-                "name": "GLM-4 Flash",
-                "description": "高性价比文本模型（0.2元/千token）",
-                "maxTokens": 128000,
-                "provider": "ZhipuAI",
-            },
-            {
-                "id": "glm-4v-plus-0111",
-                "name": "GLM-4V Plus",
-                "description": "图像 + PDF/DOCX 原生多模态",
-                "maxTokens": 128000,
-                "provider": "ZhipuAI",
-            },
-            {
-                "id": "glm-z1-flash",
-                "name": "GLM-Z1 Flash",
-                "description": "深度思考推理模型",
-                "maxTokens": 128000,
-                "provider": "ZhipuAI",
-            },
-        ],
-        "object": "list",
-    }

server/api/conversation_routes.py

@@ -0,0 +1,200 @@
+"""
+会话管理路由 - 对话 CRUD 和文件上传
+
+与平台无关的通用功能，不涉及任何 LLM 平台细节。
+"""
+
+import json
+import os
+from datetime import datetime
+from pathlib import Path
+from typing import Dict
+
+from fastapi import File, HTTPException, UploadFile
+from fastapi.responses import FileResponse
+
+import sys
+sys.path.append(str(Path(__file__).parent.parent))
+
+from database import get_db
+from utils.helpers import generate_unique_id
+from utils.logger import log_error, log_exception, log_info
+
+# 配置上传目录
+upload_dir = Path(__file__).parent.parent / "uploads"
+upload_dir.mkdir(exist_ok=True)
+
+
+# ── 会话管理 ─────────────────────────────────────────────────────
+
+
+async def get_conversations_handler():
+    """获取所有对话处理器"""
+    db = get_db()
+    return db.list_conversations()
+
+
+async def get_conversation_handler(conversation_id: str):
+    """获取特定对话处理器"""
+    db = get_db()
+    conversation = db.get_conversation(conversation_id)
+    if not conversation:
+        raise HTTPException(status_code=404, detail="对话不存在")
+    return conversation
+
+
+async def save_conversation_handler(data: dict):
+    """保存或更新对话处理器"""
+    try:
+        db = get_db()
+        conversation_id = data.get("id")
+
+        # 检查是否已存在
+        existing = db.get_conversation(conversation_id) if conversation_id else None
+
+        if existing:
+            # 更新现有会话
+            return db.update_conversation(conversation_id, data)
+        else:
+            # 创建新会话
+            return db.create_conversation(data)
+
+    except Exception as e:
+        log_error(f"Error saving conversation: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+async def delete_conversation_handler(conversation_id: str):
+    """删除对话处理器"""
+    db = get_db()
+    success = db.delete_conversation(conversation_id)
+    if success:
+        return {"success": True, "message": "删除成功"}
+    else:
+        raise HTTPException(status_code=404, detail="对话不存在")
+
+
+# ── 文件上传 ─────────────────────────────────────────────────────
+
+
+async def upload_file_handler(file: UploadFile = File(...)):
+    """文件上传处理器"""
+    try:
+        # 允许的 MIME 类型（宽松策略）
+        allowed_types = {
+            # 图片
+            "image/jpeg",
+            "image/png",
+            "image/gif",
+            "image/webp",
+            "image/bmp",
+            "image/svg+xml",
+            # 文本类
+            "text/plain",
+            "text/csv",
+            "text/markdown",
+            "text/html",
+            "text/xml",
+            "application/json",
+            "application/xml",
+            # PDF
+            "application/pdf",
+            # Office 文档
+            "application/msword",
+            "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+            "application/vnd.ms-excel",
+            "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+            "application/vnd.ms-powerpoint",
+            "application/vnd.openxmlformats-officedocument.presentationml.presentation",
+        }
+
+        # 允许的扩展名（兜底：MIME 类型可能被浏览器误判）
+        allowed_extensions = {
+            ".jpg",
+            ".jpeg",
+            ".png",
+            ".gif",
+            ".webp",
+            ".bmp",
+            ".txt",
+            ".md",
+            ".csv",
+            ".json",
+            ".xml",
+            ".yaml",
+            ".yml",
+            ".log",
+            ".pdf",
+            ".doc",
+            ".docx",
+            ".xls",
+            ".xlsx",
+            ".ppt",
+            ".pptx",
+            ".py",
+            ".js",
+            ".ts",
+            ".html",
+            ".css",
+        }
+
+        file_extension = Path(file.filename).suffix.lower()
+
+        if (
+            file.content_type not in allowed_types
+            and file_extension not in allowed_extensions
+        ):
+            raise HTTPException(
+                status_code=400,
+                detail=f"不支持的文件类型: {file.content_type}（{file_extension}）",
+            )
+
+        # 生成唯一文件名
+        unique_filename = f"{int(datetime.utcnow().timestamp())}_{generate_unique_id()}{file_extension}"
+        file_path = upload_dir / unique_filename
+
+        # 保存文件到本地（临时缓存）
+        content = await file.read()
+        with open(file_path, "wb") as f:
+            f.write(content)
+
+        # 文件关闭后再上传到 OSS
+        from utils.oss_uploader import upload_file as oss_upload
+
+        oss_result = oss_upload(str(file_path))
+        file_url = oss_result["url"]
+
+        # 返回文件信息
+        result = {
+            "url": file_url,
+            "name": file.filename,
+            "size": len(content),
+            "mimeType": file.content_type,
+        }
+
+        log_info(f"File uploaded: {result}")
+        return result
+
+    except Exception as e:
+        log_error(f"Upload error: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"上传失败: {str(e)}")
+
+
+def serve_upload_handler(filename: str):
+    """提供上传文件访问处理器"""
+    file_path = upload_dir / filename
+    if not file_path.exists():
+        raise HTTPException(status_code=404, detail="文件不存在")
+
+    return FileResponse(str(file_path))
+
+
+# ── 停止生成 ─────────────────────────────────────────────────────
+
+
+async def stop_generation_handler(message_id: str = None):
+    """停止生成处理器"""
+    message = (
+        f"已发出停止指令，消息ID: {message_id}" if message_id else "已发出停止指令"
+    )
+    return {"success": True, "message": message}

server/main.py

@@ -45,28 +45,22 @@ from utils.logger import get_logger
 
 logger = get_logger()
 
+# ── 初始化数据库 ───────────────────────────────────────────────────────
+from database import init_db
+
+init_db()
+
 # ── 加载环境变量 ──────────────────────────────────────────────────────
 load_dotenv()
 
-LLM_BACKEND = os.getenv("LLM_BACKEND", "dashscope").lower().strip()
+# ── 会话管理路由处理器 ────────────────────────────────────────────────
-if LLM_BACKEND not in {"dashscope", "glm"}:
+from api.conversation_routes import (delete_conversation_handler,
-    logger.warning(f"未知的 LLM_BACKEND='{LLM_BACKEND}'，回退到 dashscope")
-    LLM_BACKEND = "dashscope"
-
-# ── 动态加载平台模块 ──────────────────────────────────────────────────
-if LLM_BACKEND == "glm":
-    import api.chat_routes_glm as _platform
-else:
-    import api.chat_routes as _platform
-
-_platform.init()  # 各平台自行完成初始化（API Key 校验等）
-
-# 通用路由处理器（文件上传、会话管理等，与平台无关，统一用百炼路由中的实现）
-from api.chat_routes import (delete_conversation_handler,
                                      get_conversation_handler,
                                      get_conversations_handler,
-                             save_conversation_handler, serve_upload_handler,
+                                     save_conversation_handler,
-                             stop_generation_handler, upload_file_handler)
+                                     serve_upload_handler,
+                                     stop_generation_handler,
+                                     upload_file_handler)
 
 # ── OpenAI 兼容网关初始化 ───────────────────────────────────────────────
 from api.openai_gateway import init_adapters, router as openai_router
@@ -110,12 +104,11 @@ async def health_check():
     return {
         "status": "healthy",
         "version": "4.0.0",
-        "default_backend": LLM_BACKEND,
         "available_providers": get_available_providers(),
         "endpoints": {
             "openai_compatible": "/v1/chat/completions",
-            "legacy": "/api/chat-ui/chat",
             "models": "/v1/models",
+            "conversations": "/api/chat-ui/conversations",
         },
         "timestamp": datetime.now(timezone.utc).isoformat(),
     }
@@ -234,7 +227,6 @@ if __name__ == "__main__":
     print(f"  模型列表       : http://localhost:{port}/v1/models")
     print("-" * 60)
     print(f"  可用平台       : {', '.join(available) or '无（请配置 API Key）'}")
-    print(f"  默认平台       : {LLM_BACKEND} (向后兼容模式)")
     print("-" * 60)
     print("  使用方法:")
     print("  curl -X POST http://localhost:8000/v1/chat/completions \\")