app.py

from flask import Flask, request, jsonify
import hmac, hashlib, secrets, time

app = Flask(__name__)

# 🔑 Secret key for API authentication (Load from environment in production)
SECRET_KEY = "MySuperSecretKey_TrueSyncAI"

# Store API keys temporarily (use a database for real applications)
API_KEYS = {}

# Generate API Key
@app.route("/generate_api_key", methods=["POST"])
def generate_api_key():
    random_part = secrets.token_hex(16)
    signature = hmac.new(SECRET_KEY.encode(), random_part.encode(), hashlib.sha256).hexdigest()[:16]
    api_key = f"TrueSyncAI-{random_part}-{signature}"
    
    # Store the key with a timestamp
    API_KEYS[api_key] = time.time()
    return jsonify({"api_key": api_key})

# Validate API Key
def validate_api_key(api_key):
    parts = api_key.split("-")
    if len(parts) != 3 or parts[0] != "TrueSyncAI":
        return False
    
    random_part, received_signature = parts[1], parts[2]
    expected_signature = hmac.new(SECRET_KEY.encode(), random_part.encode(), hashlib.sha256).hexdigest()[:16]
    return expected_signature == received_signature and api_key in API_KEYS

# Chat Endpoint
@app.route("/chat", methods=["POST"])
def chat():
    data = request.json
    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 = f"TrueSyncAI: You said '{message}', but I'm still learning!"
    return jsonify({"response": response})

if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860)  # Hugging Face Spaces default port