Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import sys
 from flask import Flask, request, jsonify
-from flask_cors import CORS # Import CORS (ensure this line is there!)
+from flask_cors import CORS # Ensure Flask-CORS is imported
 import numpy as np 
 import json 
 import google.api_core.exceptions
@@ -19,11 +19,9 @@ load_dotenv()
 app = Flask(__name__)
 
 # --- CRITICAL FIX: CORS Configuration ---
-# Ensure this exact URL matches your Vercel frontend URL, WITHOUT a trailing slash.
-# If you have multiple origins, you can provide a list: ["https://sales-doc.vercel.app", "http://localhost:3000"]
-# For production, avoid "*" (wildcard) as it's a security risk.
-cors_origins = "https://sales-doc.vercel.app" # Your exact Vercel frontend URL
-CORS(app, resources={r"/*": {"origins": cors_origins, "allow_headers": ["Content-Type", "Authorization"]}}) 
+# This MUST EXACTLY match your Vercel frontend URL, WITHOUT a trailing slash.
+# We explicitly allow Content-Type and Authorization headers for preflight requests.
+CORS(app, resources={r"/*": {"origins": "https://sales-doc.vercel.app", "allow_headers": ["Content-Type", "Authorization"]}}) 
 
 # --- Global Model Instances ---
 sales_agent = None
@@ -61,6 +59,7 @@ except ImportError as e:
 print("Debug Point: Attempting to instantiate sales.Agent (core RL model).")
 if sales is not None: 
     try:
+        # Relying on Dockerfile to make /.deepmost writable 
         sales_agent = sales.Agent(
             model_path="https://huggingface.co/DeepMostInnovations/sales-conversion-model-reinf-learning/resolve/main/sales_conversion_model.zip",
             auto_download=True,
@@ -95,7 +94,6 @@ if GEMINI_API_KEY:
         print(f"Error Type: {type(e).__name__}") 
         print(f"Error Message: {e}")
         print("Ensure your GEMINI_API_KEY is correct and has access to Gemini 1.5 Flash.")
-        print("This means LLM chat functionality and enriched metrics will not work.")
         import traceback
         traceback.print_exc()
         gemini_model = None