Update app.py

app.py

@@ -1,8 +1,6 @@
 from flask import Flask, request, jsonify
 import hmac, hashlib, secrets, time, os
 from openai import OpenAI
-from flask_limiter import Limiter
-from flask_limiter.util import get_remote_address
 
 app = Flask(__name__)
 
@@ -11,8 +9,6 @@ SECRET_KEY = os.getenv("SECRET_KEY")
 GITHUB_TOKEN = os.getenv("GITHUB_TOKEN")
 endpoint = "https://models.inference.ai.azure.com"
 client = OpenAI(base_url=endpoint,api_key=GITHUB_TOKEN)
-# Initialize Flask-Limiter (without global default limits)
-limiter = Limiter(get_remote_address, app=app)
 
 # Track API statistics
 request_count = 0
@@ -78,28 +74,22 @@ def generate_response(query:str) -> str:
         return response.choices[0].message.content
     except:
         return "API Server is under maintenance. Please Try After Some Time Thank You for using TrueSyncAI Chat API. Have a great day."
- 
-# Custom Rate Limit Error Handler
-@app.errorhandler(429)
-def ratelimit_exceeded(e):
-    return jsonify({
-        "error": "Rate limit exceeded",
-        "message": "You have reached the maximum limit of 5 requests per minute. Please try again later."
-    }), 429
-   
+    
 # Chat Endpoint
 @app.route("/v1/chat/completions", methods=["POST"])
-@limiter.limit("5 per minute")  # Apply limit only to this function
 def chat():
     global request_count
     data = request.json
-    api_key, message = data.get("api_key"), data.get("message", "").strip()
+    api_key = data.get("api_key")
+    message = data.get("message", "").strip()
     
     if not api_key or not validate_api_key(api_key):
         return jsonify({"error": "Invalid API Key"}), 401
+    
     if not message:
         return jsonify({"error": "Message cannot be empty"}), 400
     
+    # Basic AI response (Can integrate LLMs here)
     response = generate_response(message)
     request_count += 1
     return jsonify({"response": response})