Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import sys
 from flask import Flask, request, jsonify
-from flask_cors import CORS
+from flask_cors import CORS # Import CORS (ensure this line is there!)
 import numpy as np 
 import json 
 import google.api_core.exceptions
@@ -18,9 +18,12 @@ load_dotenv()
 
 app = Flask(__name__)
 
-# IMPORTANT: Configure CORS to allow requests from your Vercel frontend
-# Replace 'https://sales-doc.vercel.app' with your actual Vercel URL.
-CORS(app, resources={r"/*": {"origins": "https://sales-doc.vercel.app"}}) 
+# --- 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"]}}) 
 
 # --- Global Model Instances ---
 sales_agent = None
@@ -58,9 +61,6 @@ 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 ---
-        # NO local_model_path argument here. deepmost expects to write to /.deepmost by default
-        # and doesn't take local_model_path in this constructor.
         sales_agent = sales.Agent(
             model_path="https://huggingface.co/DeepMostInnovations/sales-conversion-model-reinf-learning/resolve/main/sales_conversion_model.zip",
             auto_download=True,
@@ -87,7 +87,6 @@ print("\nDebug Point: Attempting to initialize Gemini 1.5 Flash model.")
 if GEMINI_API_KEY:
     try:
         gemini_model = genai.GenerativeModel('gemini-1.5-flash-latest') 
-        # Small test call to ensure connectivity
         test_response = gemini_model.generate_content("Hello.", generation_config=GenerationConfig(max_output_tokens=10))
         print(f"Debug Point: Gemini 1.5 Flash test response: {test_response.text[:50]}...")
         print("Debug Point: Gemini LLM (1.5 Flash) initialized successfully.")
@@ -215,7 +214,7 @@ def get_llm_advice():
                 print(f"ERROR: JSON parsing error for overall advice: {json_e}. Raw string: {raw_json_string}")
                 return jsonify({"points": ["Error parsing LLM JSON advice. This happens with incomplete LLM responses (e.g., due to API rate limits or max tokens). Please try a shorter conversation or wait a moment. Raw response starts with: " + raw_json_string[:100] + "..."]})
             except Exception as parse_e:
-                print(f"ERROR: General error during JSON parsing attempt for chat_llm (Gemini): {parse_e}. Raw string: {json_response}")
+                print(f"ERROR: General error during JSON parsing attempt for chat_llm (Gemini): {parse_e}. Raw string: {raw_json_string}")
                 return jsonify({"points": ["General error with LLM JSON parsing. Raw response starts with: " + raw_json_string[:100] + "..."]})
                 
         except google.api_core.exceptions.ResourceExhausted as quota_e: