Update app.py

app.py

@@ -1,22 +1,35 @@
 import os
+import requests
 import streamlit as st
-from groq import Groq
 from googletrans import Translator
 import asyncio
 
-# Initialize the Groq client
-client = Groq(api_key="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")
+# Ensure you have the correct API URL for Groq and the key is set
+GROQ_API_URL = "https://api.groq.com/v1/completions"  # Replace with the actual endpoint if different
+API_KEY = os.environ.get("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")
+
+if not API_KEY:
+    raise ValueError("API key is missing. Make sure to set the GROQ_API_KEY environment variable.")
 
 # Function to get recommendations from Groq API based on user input
 def get_opportunities(user_query):
-    # Create a chat completion request
-    chat_completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": user_query}],
-        model="llama-3.3-70b-versatile"
-    )
+    headers = {
+        "Authorization": f"Bearer {API_KEY}",
+        "Content-Type": "application/json"
+    }
+    
+    payload = {
+        "model": "llama-3.3-70b-versatile",  # Example model, replace with the actual model you want
+        "messages": [{"role": "user", "content": user_query}],
+    }
+    
+    # Send the request to the Groq API
+    response = requests.post(GROQ_API_URL, json=payload, headers=headers)
     
-    # Return the response content
-    return chat_completion.choices[0].message.content
+    if response.status_code == 200:
+        return response.json()  # Adjust as per Groq's response format
+    else:
+        raise ValueError(f"Error fetching data from Groq API: {response.status_code}, {response.text}")
 
 # Function to translate text into the selected language (async version)
 async def translate_text(text, target_language):
@@ -78,10 +91,13 @@ if st.button("Send"):
         with st.spinner("Fetching opportunities..."):
             try:
                 # Get the opportunity details based on user query
-                opportunities = get_opportunities(user_query)
+                opportunities_response = get_opportunities(user_query)
+                
+                # Extract the response content, modify based on actual response format
+                opportunities_text = opportunities_response.get("choices", [{}])[0].get("message", {}).get("content", "No data found.")
                 
                 # Run the async translate function and get the translated text
-                translated_opportunities = asyncio.run(translate_text(opportunities, languages[selected_language]))
+                translated_opportunities = asyncio.run(translate_text(opportunities_text, languages[selected_language]))
                 
                 # Append AI response to chat history
                 st.session_state.messages.append({"role": "ai", "content": translated_opportunities})