Update app.py

app.py

@@ -1,90 +1,51 @@
 import streamlit as st
 import requests
+from transformers import pipeline
 
-# Set up the Streamlit page
-st.title("AI Opportunity Finder for Youth")
-st.write("Find Scholarships, Internships, Online Courses, and more!")
+# Initialize the language model (Hugging Face's pre-trained model for text generation)
+generator = pipeline('text-generation', model='gpt-2')  # You can choose any suitable language model
 
-# Function to get scholarships data from the Groq API
-def get_scholarships(location, interests):
-    # Define the headers with your Groq API key
-    headers = {
-        "Authorization": "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",  # Replace with your actual API key
-    }
-    
-    # Define the query parameters
-    params = {
-        "location": location,
-        "interests": interests,
-    }
-    
-    # Send GET request to the Groq API (Use your specific endpoint from Groq's API)
-    response = requests.get("https://api.groq.ai/scholarships", headers=headers, params=params)
-    
-    if response.status_code == 200:
-        return response.json()  # This assumes the response is a list of scholarships in JSON format
-    else:
-        st.error(f"Error fetching scholarships: {response.status_code}")
-        return []
+# Title and Description of the App
+st.title("AI-powered Opportunity Finder for Youth")
+st.write("Find scholarships, internships, competitions, and more based on your skills and interests using AI!")
 
-# Function to get internships data from the Groq API
-def get_internships(location, interests):
-    # Define the headers with your Groq API key
-    headers = {
-        "Authorization": "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",  # Replace with your actual API key
-    }
+# Collect user input
+interests = st.text_input("Enter your interests (e.g., AI, web development, etc.)")
+skills = st.text_input("Enter your skills (e.g., Python, Data Analysis, etc.)")
+location = st.text_input("Enter your location")
+
+# Button to trigger the AI recommendations
+if st.button("Find Opportunities"):
+    # Combine the input into a prompt for the language model
+    prompt = f"Find scholarships, internships, competitions, and online courses for a person interested in {interests}, skilled in {skills}, and located in {location}. Provide recommendations with details like title, link, and description."
     
-    # Define the query parameters
-    params = {
-        "location": location,
-        "interests": interests,
-    }
+    # Use the language model to generate recommendations
+    response = generator(prompt, max_length=150, num_return_sequences=1)
     
-    # Send GET request to the Groq API (Use your specific endpoint from Groq's API)
-    response = requests.get("https://api.groq.ai/internships", headers=headers, params=params)
+    # Parse and display the generated text
+    recommendations = response[0]['generated_text']
     
-    if response.status_code == 200:
-        return response.json()  # This assumes the response is a list of internships in JSON format
-    else:
-        st.error(f"Error fetching internships: {response.status_code}")
-        return []
-
-# User input for profile
-st.sidebar.header("User Profile")
-location = st.sidebar.text_input("Location", "Pakistan")  # Default to 'Pakistan'
-skills = st.sidebar.text_input("Skills (e.g., Python, Marketing)")
-interests = st.sidebar.text_input("Interests (e.g., Technology, Science)")
-
-# Fetch scholarships based on user input
-scholarships = get_scholarships(location, interests)
-
-# Display scholarships if available
-if scholarships:
-    st.write("Scholarships found:")
-    for scholarship in scholarships:
-        st.write(f"Title: {scholarship['title']}")
-        st.write(f"Description: {scholarship['description']}")
-        st.write(f"Eligibility: {scholarship['eligibility']}")
-        st.write("---")
-else:
-    st.write("No scholarships found based on your criteria.")
-
-# Fetch internships based on user input
-internships = get_internships(location, interests)
-
-# Display internships if available
-if internships:
-    st.write("Internships found:")
-    for internship in internships:
-        st.write(f"Title: {internship['jobtitle']}")
-        st.write(f"Company: {internship['company']}")
-        st.write(f"Location: {internship['location']}")
-        st.write(f"Snippet: {internship['snippet']}")
-        st.write("---")
-else:
-    st.write("No internships found.")
-
-# AI-based recommendations (can use Groq API or other AI methods)
-if st.sidebar.button("Get AI Recommendations"):
-    # Example AI recommendation logic (replace with actual Groq API or custom logic)
-    st.write("AI Recommendations coming soon...")
+    # Display the generated recommendations
+    st.write("Recommended Opportunities based on your input:")
+    st.write(recommendations)
+
+    # Example to further integrate Groq API (if you need more personalized results)
+    # You can replace the following code with an actual API request to Groq for more detailed results
+    # Make sure to replace the placeholder with your Groq API endpoint and parameters
+    try:
+        api_response = requests.post("https://api.groq.com/recommendations", json={
+            "interests": interests,
+            "skills": skills,
+            "location": location
+        })
+
+        if api_response.status_code == 200:
+            api_recommendations = api_response.json()
+            st.write("Groq API Recommendations:")
+            for rec in api_recommendations:
+                st.write(f"- {rec['title']}: {rec['link']}")
+        else:
+            st.write("Unable to fetch recommendations from Groq API.")
+
+    except Exception as e:
+        st.write(f"Error while fetching recommendations from Groq API: {e}")