Update app.py

app.py

@@ -1,6 +1,7 @@
 from flask import Flask, request, jsonify
 import hmac, hashlib, secrets, time, os
 from openai import OpenAI
+from datetime import datetime, timedelta
 import logging
 
 logging.basicConfig(level=logging.INFO)
@@ -12,6 +13,13 @@ GITHUB_TOKEN = os.getenv("GITHUB_TOKEN")
 endpoint = "https://models.inference.ai.azure.com"
 client = OpenAI(base_url=endpoint,api_key=GITHUB_TOKEN)
 
+# Track API statistics
+api_usage = {}  # Stores {api_key: {"count": X, "reset_time": timestamp}}
+
+# ✅ Request Limit Configuration
+REQUEST_LIMIT = 2 # Max requests per day
+SPECIAL_API_KEY = "TrueSyncAI-888d3e23fa5801834aa385118e05bd72-394215579bc4e6ac"  # The restricted API key
+
 # Track API statistics
 request_count = 0
 start_time = time.time()
@@ -91,6 +99,23 @@ def chat():
     
     if not message:
         return jsonify({"error": "Message cannot be empty"}), 400
+        
+        # ✅ Apply Limit to the Specific API Key
+    if api_key == SPECIAL_API_KEY:
+        now = datetime.utcnow()
+        user_data = api_usage.get(api_key, {"count": 0, "reset_time": now + timedelta(days=1)})
+        
+        # Reset count if the reset time has passed
+        if now >= user_data["reset_time"]:
+            user_data = {"count": 0, "reset_time": now + timedelta(days=1)}
+        
+        # Block requests if limit exceeded
+        if user_data["count"] >= REQUEST_LIMIT:
+            return jsonify({"error": "Request limit reached. Try again tomorrow."}), 429
+        
+        # Increase request count
+        user_data["count"] += 1
+        api_usage[api_key] = user_data  # Update storage
     
     # Basic AI response (Can integrate LLMs here)
     response = generate_response(message)