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Update app.py
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app.py
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import streamlit as st
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import requests
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import pandas as pd
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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# Set up the Streamlit page
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st.title("AI Opportunity Finder for Youth")
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st.write("Find Scholarships, Internships, Online Courses, and more!")
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#
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def get_scholarships(country, interests):
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url = f"https://jsonplaceholder.typicode.com/posts" # Mock API
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response = requests.get(url)
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return [{"title": f"Scholarship {i+1}", "description":
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else:
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return []
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# Function to get internships data from a mock API
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def get_internships(country):
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# Example: Replace with a real API URL (mocked for demonstration)
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url = f"https://jsonplaceholder.typicode.com/posts" # Mock API for testing
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else:
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return []
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# Function to recommend opportunities based on user input
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def recommend_opportunities(user_interests, user_skills, opportunities):
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user_profile = [f"{user_interests} {user_skills}"]
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opportunities_text = [f"{opportunity.get('description', 'No description available')} {opportunity.get('eligibility', 'No eligibility available')}" for opportunity in opportunities]
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# Form to gather user profile and country selection
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with st.form(key='user_form'):
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st.sidebar.header("User Profile")
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location = st.selectbox("Select your Country", ["
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skills = st.text_input("Skills (e.g., Python, Marketing)")
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interests = st.text_input("Interests (e.g., Technology, Science)")
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submit_button = st.form_submit_button("Find Opportunities")
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if scholarships:
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st.write("Scholarships found:")
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for scholarship in scholarships:
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st.write("---")
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else:
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st.write("No scholarships found for the selected country.")
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if internships:
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st.write("Internships found:")
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for internship in internships:
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st.write("---")
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else:
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st.write("No internships found for the selected country.")
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st.write("AI-based Recommended Opportunities based on your profile:")
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for opportunity in recommended_opportunities:
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st.write("---")
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import streamlit as st
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import requests
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from sklearn.feature_extraction.text import TfidfVectorizer
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from sklearn.metrics.pairwise import cosine_similarity
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from transformers import MarianMTModel, MarianTokenizer
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# Set up the Streamlit page
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st.title("AI Opportunity Finder for Youth")
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st.write("Find Scholarships, Internships, Online Courses, and more!")
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# Language Translation Function
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def translate_text(text, target_lang='de'):
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# Use Hugging Face's MarianMT for translation
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model_name = f'Helsinki-NLP/opus-mt-en-{target_lang}'
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model = MarianMTModel.from_pretrained(model_name)
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tokenizer = MarianTokenizer.from_pretrained(model_name)
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translated = model.generate(**tokenizer(text, return_tensors="pt", padding=True, truncation=True))
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translated_text = tokenizer.decode(translated[0], skip_special_tokens=True)
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return translated_text
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# Mock function to get data from APIs (replace with actual API calls)
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def get_scholarships(country, interests):
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url = f"https://jsonplaceholder.typicode.com/posts" # Mock API (replace with real one)
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# Simulate API response based on country
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if country == "USA":
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return [{"title": f"USA Scholarship {i+1}", "description": f"Description for scholarship {i+1} in USA.", "eligibility": "Any student from USA."} for i in range(5)]
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elif country == "Germany":
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return [{"title": f"Germany Scholarship {i+1}", "description": f"Description for scholarship {i+1} in Germany.", "eligibility": "Any student from Germany."} for i in range(5)]
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else:
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return [{"title": f"Scholarship {i+1}", "description": f"Description for scholarship {i+1} in {country}.", "eligibility": "Any student from any background."} for i in range(5)]
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def get_internships(country):
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url = f"https://jsonplaceholder.typicode.com/posts" # Mock API for testing
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# Simulate internships data
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if country == "USA":
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return [{"jobtitle": f"Internship {i+1}", "company": "USA Company", "location": "USA", "snippet": "Description of internship in USA."} for i in range(5)]
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elif country == "Germany":
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return [{"jobtitle": f"Internship {i+1}", "company": "Germany Company", "location": "Germany", "snippet": "Description of internship in Germany."} for i in range(5)]
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else:
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return [{"jobtitle": f"Internship {i+1}", "company": "Sample Company", "location": "Remote", "snippet": "Description of internship."} for i in range(5)]
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def recommend_opportunities(user_interests, user_skills, opportunities):
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user_profile = [f"{user_interests} {user_skills}"]
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opportunities_text = [f"{opportunity.get('description', 'No description available')} {opportunity.get('eligibility', 'No eligibility available')}" for opportunity in opportunities]
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# Form to gather user profile and country selection
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with st.form(key='user_form'):
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st.sidebar.header("User Profile")
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location = st.selectbox("Select your Country", ["USA", "Germany", "UK", "India", "Australia", "Pakistan"]) # You can add more countries here
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skills = st.text_input("Skills (e.g., Python, Marketing)")
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interests = st.text_input("Interests (e.g., Technology, Science)")
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target_language = st.selectbox("Select target language", ['de', 'fr', 'es', 'it', 'pt']) # Available language codes for translation
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submit_button = st.form_submit_button("Find Opportunities")
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if scholarships:
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st.write("Scholarships found:")
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for scholarship in scholarships:
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title = translate_text(scholarship.get('title', 'No title available'), target_language)
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description = translate_text(scholarship.get('description', 'No description available'), target_language)
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eligibility = translate_text(scholarship.get('eligibility', 'No eligibility available'), target_language)
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st.write(f"Title: {title}")
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st.write(f"Description: {description}")
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st.write(f"Eligibility: {eligibility}")
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st.write("---")
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else:
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st.write("No scholarships found for the selected country.")
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if internships:
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st.write("Internships found:")
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for internship in internships:
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title = translate_text(internship.get('jobtitle', 'No title available'), target_language)
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company = translate_text(internship.get('company', 'No company available'), target_language)
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location = translate_text(internship.get('location', 'No location available'), target_language)
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snippet = translate_text(internship.get('snippet', 'No snippet available'), target_language)
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st.write(f"Title: {title}")
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st.write(f"Company: {company}")
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st.write(f"Location: {location}")
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st.write(f"Snippet: {snippet}")
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st.write("---")
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else:
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st.write("No internships found for the selected country.")
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st.write("AI-based Recommended Opportunities based on your profile:")
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for opportunity in recommended_opportunities:
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title = translate_text(opportunity.get('title', 'No title available'), target_language)
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description = translate_text(opportunity.get('description', 'No description available'), target_language)
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eligibility = translate_text(opportunity.get('eligibility', 'Not available'), target_language)
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st.write(f"Title: {title}")
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st.write(f"Description: {description}")
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st.write(f"Eligibility: {eligibility}")
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st.write("---")
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