Update app.py

app.py

@@ -1,7 +1,11 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import StreamingResponse, JSONResponse
 import os
 from dotenv import load_dotenv
+import requests
+from typing import Dict, Any, List
+from pydantic import BaseModel
 
 load_dotenv()
 
@@ -14,6 +18,90 @@ app.add_middleware(
     allow_headers=["*"]
 )
 
+# Получаем переменные окружения
+FLOWISE_API_BASE_URL = os.getenv("FLOWISE_API_BASE_URL")
+FLOWISE_CHATFLOW_ID = os.getenv("FLOWISE_CHATFLOW_ID")
+
+class ChatMessage(BaseModel):
+    role: str
+    content: str
+
+class ChatCompletionRequest(BaseModel):
+    model: str
+    messages: List[ChatMessage]
+    temperature: float = 0.7
+
 @app.get("/")
 async def root():
-    return {"status": "FastFlowWrapper is running"} 
+    return {"status": "FastFlowWrapper is running"}
+
+@app.get("/v1/models")
+async def get_models():
+    try:
+        # Запрашиваем список чатфлоу из Flowise
+        response = requests.get(f"{FLOWISE_API_BASE_URL}/chatflows")
+        response.raise_for_status()
+        chatflows = response.json()
+        
+        # Преобразуем в формат OpenAI API
+        models = []
+        for chatflow in chatflows:
+            models.append({
+                "id": chatflow.get("id"),
+                "object": "model",
+                "created": 1677610602,  # Фиксированная дата для примера
+                "owned_by": "flowise",
+                "permission": [],
+                "root": "flowise",
+                "parent": None
+            })
+        
+        return {"object": "list", "data": models}
+    except requests.RequestException as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/v1/chat/completions")
+async def create_chat_completion(request: ChatCompletionRequest):
+    try:
+        # Получаем последнее сообщение из диалога
+        last_message = request.messages[-1]
+        if last_message.role != "user":
+            raise HTTPException(status_code=400, detail="Last message must be from user")
+        
+        # Формируем запрос к Flowise
+        flowise_request = {
+            "question": last_message.content
+        }
+        
+        # Отправляем запрос к Flowise
+        response = requests.post(
+            f"{FLOWISE_API_BASE_URL}/prediction/{FLOWISE_CHATFLOW_ID}",
+            json=flowise_request
+        )
+        response.raise_for_status()
+        
+        # Преобразуем ответ в формат OpenAI API
+        flowise_response = response.json()
+        return {
+            "id": "chatcmpl-" + os.urandom(12).hex(),
+            "object": "chat.completion",
+            "created": int(response.elapsed.total_seconds()),
+            "model": request.model,
+            "choices": [
+                {
+                    "index": 0,
+                    "message": {
+                        "role": "assistant",
+                        "content": flowise_response.get("text", "")
+                    },
+                    "finish_reason": "stop"
+                }
+            ],
+            "usage": {
+                "prompt_tokens": len(last_message.content),
+                "completion_tokens": len(str(flowise_response.get("text", ""))),
+                "total_tokens": len(last_message.content) + len(str(flowise_response.get("text", "")))
+            }
+        }
+    except requests.RequestException as e:
+        raise HTTPException(status_code=500, detail=str(e))