Update app.py

app.py

@@ -1,28 +1,39 @@
 from fastapi import FastAPI, Request
 from pydantic import BaseModel
+import os
+
 
 app = FastAPI()
 
-# Определяем модель для запроса
-class Message(BaseModel):
-    role: str
-    content: str
 
 class RequestBody(BaseModel):
     model: str
-    messages: list[Message]
-    temperature: float
-    top_p: float
-    max_tokens: int
+    key_body: str
+    text: str
 
 
 @app.post("/api/v1")
 async def generate_response(request_body: RequestBody):
-    # Извлечение и подготовка сообщений
-    input_text = "\n".join([f"{msg.role}: {msg.content}" for msg in request_body.messages])
-
+    input_text = request_body.text
+    model = request_body.model
+    key_true = os.environ['key']
+    key_body = request_body.key_body
+    if key_body == key_true:
+        if model == "gemini":
+            key_gemini = os.environ['key_gemini']
+            headers = {'Content-Type': 'application/json',}
+            params = {'key': key_gemini}
+            json_data = {'contents': [{'parts': [{'text': promt}]}]}
+            response = requests.post('https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent',params=params,headers=headers,json=json_data,)
+            all_chunk = response.json()['candidates'][0]['content']['parts'][0]['text']
     
-    response = input_text
-
-    # Возвращаем ответ в формате JSON
-    return {"response": response}
+        if model == 'groq':
+            key_groq = os.environ['key_groq']
+            headers = {'Authorization': f'Bearer {key_groq}','Content-Type': 'application/json'}
+            json_data = {'messages': [{'role': 'user','content': promt}],'model': 'llama-3.1-70b-versatile',}
+            response = requests.post('https://api.groq.com/openai/v1/chat/completions', headers=headers, json=json_data)
+            all_chunk = response.json()["choices"][0]["message"]["content"]
+            
+    if key_body != key_true:
+        all_chunk = "How's the hack going?"
+    return {"response": all_chunk}