Update app.py

app.py

@@ -1,20 +1,18 @@
-from fastapi import FastAPI, HTTPException, Request
+from fastapi import FastAPI, HTTPException
 from fastapi.responses import StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
 import aiohttp
 import json
 import time
-import random
-import ast
-import urllib.parse
-from apscheduler.schedulers.background import BackgroundScheduler
 import os
 from pydantic import BaseModel
-
-OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY", None)
+from apscheduler.schedulers.background import BackgroundScheduler
 
 app = FastAPI()
 
+# Enable CORS
+app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
+
 # Time-Limited Infinite Cache
 cache = {}
 CACHE_DURATION = 120
@@ -47,47 +45,47 @@ async def stream_text(request: StreamTextRequest):
         cached_response, timestamp = cache[cache_key]
         return StreamingResponse(iter([f"{cached_response}"]), media_type='text/event-stream')
 
-    # Model selection logic
-    fmodel = "gpt-4" if "gpt-4" in request.model else "gpt-3.5-turbo"
+    # Use the API specified by the user
+    api_url = "https://api.pawan.krd/unfiltered/v1"
+    api_key = request.api_key if request.api_key != 'none' else os.environ.get("OPENAI_API_KEY")
 
     system_message = """You are an AI language assistant. Your sole task is to correct the grammar, spelling, and structure of the sentences provided to you. You must not change the meaning of the sentences, and you should focus only on making them grammatically correct, concise, and clear. Do not add any additional information or provide explanations unless specifically asked. Your responses should be limited to the corrected version of the sentence."""
 
     messages = [{'role': 'system', 'content': system_message}]
-    messages.extend(ast.literal_eval(request.history))
+    messages.extend(json.loads(request.history))
     messages.append({'role': 'user', 'content': request.query})
-    
-    data = {'messages': messages, 'model': fmodel, 'stream': True}
 
-    api_key = request.api_key if request.api_key != 'none' else OPENAI_API_KEY
+    data = {
+        'messages': messages,
+        'model': request.model,
+        'stream': True
+    }
 
     async def stream_response():
         async with aiohttp.ClientSession() as session:
             async with session.post(
-                'https://api.openai.com/v1/chat/completions',
+                api_url,
                 headers={'Authorization': f'Bearer {api_key}', 'Content-Type': 'application/json'},
                 json=data
             ) as response:
                 if response.status != 200:
                     raise HTTPException(status_code=response.status, detail="Error fetching AI response")
 
-                response_content = ""
                 async for line in response.content:
                     line = line.decode('utf-8').strip()
-                    if line.startswith('data: {'):
+                    if line.startswith('data:'):
                         json_data = line[6:]
                         try:
                             parsed_data = json.loads(json_data)
                             content = parsed_data.get("choices", [{}])[0].get("delta", {}).get("content", '')
                             if content:
-                                content = content.replace("\n", " ")
-                                response_content += f"data: {content}\n\n"
                                 yield f"data: {content}\n\n"
                         except json.JSONDecodeError as e:
-                            print(f"Error decoding JSON: {e}")
                             yield f"data: Error decoding JSON\n\n"
 
-                # Cache the full response
-                cache[cache_key] = (response_content, current_time)
+                # Cache the full response if available
+                # response_content = "full response would be stored here if needed"
+                # cache[cache_key] = (response_content, current_time)
 
     return StreamingResponse(stream_response(), media_type='text/event-stream')