Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import streamlit as st
 import requests
 from groq import Groq
@@ -5,13 +6,15 @@ from groq import Groq
 # Function to scrape LinkedIn profile using Firecrawl API
 def scrape_linkedin_profile(linkedin_url):
     api_url = "https://api.firecrawl.dev/v1/scrape"  # Endpoint for scraping
-    headers = {"Authorization": "fc-123456789"}  # Replace with your actual API key
+    firecrawl_api_key = "YOUR_FIRECRAWL_API_KEY"  # Replace with your actual Firecrawl API key
+    headers = {"Authorization": firecrawl_api_key}  # Set the API key without 'Bearer'
+    
     response = requests.post(api_url, json={"url": linkedin_url}, headers=headers)
     
     if response.status_code == 200:
         return response.json()['data']  # Adjust based on actual response structure
     else:
-        return "Error scraping LinkedIn profile."
+        return f"Error scraping LinkedIn profile: {response.text}"  # Improved error message
 
 # Function to generate email using Llama 3.2 from Groq with ReAct methodology
 def generate_email(name, email, phone, role, tokens, linkedin_url):
@@ -28,7 +31,7 @@ def generate_email(name, email, phone, role, tokens, linkedin_url):
     reasoning_trace.append(f"Obtained profile data: {profile_data}.")
 
     # Initialize Groq client
-    client = Groq(api_key='YOUR_GROQ_API_KEY')  # Replace with your actual API key
+    client = Groq(api_key='YOUR_GROQ_API_KEY')  # Replace with your actual Groq API key
     
     # Prepare messages for Llama model
     messages = [