Update app.py

app.py

@@ -3,10 +3,10 @@ import requests
 import os
 from openai import OpenAI
 
-# Initialize the NVIDIA LLM client
+# Initialize the Groq Cloud LLM client
 client = OpenAI(
-    base_url="https://integrate.api.nvidia.com/v1",
-    api_key=os.getenv("NVIDIA_API_KEY")  # Use your NVIDIA API key
+    base_url="https://api.groq.com/openai/v1",
+    api_key=os.getenv("GROQ_API_KEY")  # Use your Groq Cloud API key
 )
 
 class AutonomousEmailAgent:
@@ -52,9 +52,9 @@ class AutonomousEmailAgent:
         After generating the email, reflect on whether the content aligns with the role and company and whether any improvements are needed. Respond clearly with one of the above options.
         """
         
-        # Send the reasoning prompt to the LLM
+        # Send the reasoning prompt to the Groq Cloud LLM
         completion = client.chat.completions.create(
-            model="nvidia/llama-3.1-nemotron-70b-instruct",
+            model="llama3-8b-8192",  # Adjust model if necessary
             messages=[{"role": "user", "content": reasoning_prompt}],
             temperature=0.5,
             top_p=1,
@@ -113,7 +113,6 @@ class AutonomousEmailAgent:
                 self.company_url = None
         else:
             print(f"Error fetching company URL: {response.status_code}. Retrying with fallback or alternative...")
-            # Additional logic to retry with alternative API or handle error
 
     # Fetch LinkedIn data via Proxycurl
     def fetch_linkedin_data(self):
@@ -160,9 +159,9 @@ class AutonomousEmailAgent:
             print(f"Error: Unable to fetch company info via Firecrawl. Retrying or using fallback...")
             self.company_info = "A leading company in its field."
 
-    # Final Action: Generate the email using NVIDIA LLM with "Start with Why" framework
+    # Final Action: Generate the email using Groq Cloud LLM with "Start with Why" framework
     def generate_email(self):
-        print("Action: Generating the email using NVIDIA LLM with the gathered information.")
+        print("Action: Generating the email using Groq Cloud LLM with the gathered information.")
 
         prompt = f"""
         Write a professional job application email applying for the {self.role} position at {self.company_name}.
@@ -191,7 +190,7 @@ class AutonomousEmailAgent:
         """
 
         completion = client.chat.completions.create(
-            model="nvidia/llama-3.1-nemotron-70b-instruct",
+            model="llama3-8b-8192",
             messages=[{"role": "user", "content": prompt}],
             temperature=0.5,
             top_p=1,