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| import os | |
| import streamlit as st | |
| from groq import Groq | |
| # Set the Groq API key | |
| os.environ["GROQ_API_KEY"] = "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" | |
| # Initialize Groq client | |
| client = Groq(api_key=os.environ.get("GROQ_API_KEY")) | |
| # Define the LLaMA model to be used | |
| MODEL_NAME = "llama3-8b-8192" | |
| # Function to call Groq API | |
| def call_groq_api(prompt): | |
| try: | |
| chat_completion = client.chat.completions.create( | |
| messages=[{"role": "user", "content": prompt}], | |
| model=MODEL_NAME | |
| ) | |
| return chat_completion.choices[0].message.content | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| # Define functions for each tool | |
| def personalized_learning_assistant(topic): | |
| examples = [ | |
| "Explain quantum mechanics with a real-world example.", | |
| "Describe general relativity and its significance.", | |
| "Provide a simple explanation of machine learning and its applications." | |
| ] | |
| prompt = f"Here are some example explanations:\n\n{examples}\n\nNow, explain the topic: {topic}. Provide a detailed, yet simple explanation with a practical example." | |
| return call_groq_api(prompt) | |
| def ai_coding_mentor(code_snippet): | |
| examples = [ | |
| "Review this code snippet for optimization opportunities:\n\nCode: 'for i in range(10): print(i)'\nSuggestion: Use list comprehension for more efficient code.", | |
| "Analyze this code snippet for best practices:\n\nCode: 'def add(a, b): return a + b'\nSuggestion: Include type hints to improve readability and maintainability." | |
| ] | |
| prompt = f"Here are some code review examples:\n\n{examples}\n\nReview the following code snippet and provide suggestions for improvement:\n{code_snippet}. Include any potential issues or improvements." | |
| return call_groq_api(prompt) | |
| def smart_document_summarizer(document_text): | |
| examples = [ | |
| "Summarize this text:\n\nText: 'Quantum computing represents a revolutionary approach to computing that leverages quantum mechanics.'\nSummary: 'Quantum computing uses quantum mechanics to advance computing technology.'", | |
| "Create a summary for this passage:\n\nText: 'The rise of electric vehicles is a major step towards reducing global carbon emissions and combating climate change.'\nSummary: 'Electric vehicles help reduce carbon emissions and fight climate change.'" | |
| ] | |
| prompt = f"Here are some document summarization examples:\n\n{examples}\n\nSummarize the following document text concisely:\n{document_text}. Focus on capturing the main points clearly." | |
| return call_groq_api(prompt) | |
| def interactive_study_planner(exam_schedule): | |
| examples = [ | |
| "Generate a study plan for a schedule with multiple exams in a week:\n\nSchedule: '3 exams in one week'\nPlan: 'Allocate 2 hours per subject each day, with review sessions on weekends.'", | |
| "Create a study plan for preparing for exams over a period of 2 weeks:\n\nSchedule: 'Exams in 2 weeks'\nPlan: 'Prioritize subjects based on difficulty and importance, with daily reviews and mock tests.'" | |
| ] | |
| prompt = f"Here are some study planning examples:\n\n{examples}\n\nCreate a tailored study plan based on the following schedule:\n{exam_schedule}. Include daily study goals and break times." | |
| return call_groq_api(prompt) | |
| def real_time_qa_support(question): | |
| examples = [ | |
| "Provide an answer to this question:\n\nQuestion: 'What is Newton's third law of motion?'\nAnswer: 'Newton's third law states that for every action, there is an equal and opposite reaction.'", | |
| "Explain this concept:\n\nQuestion: 'What is the principle of conservation of energy?'\nAnswer: 'The principle of conservation of energy states that energy cannot be created or destroyed, only transformed from one form to another.'" | |
| ] | |
| prompt = f"Here are some examples of answers to academic questions:\n\n{examples}\n\nAnswer the following question:\n{question}. Provide a clear and comprehensive explanation." | |
| return call_groq_api(prompt) | |
| def mental_health_check_in(feelings): | |
| examples = [ | |
| "Offer advice for managing exam stress:\n\nFeeling: 'Stressed about upcoming exams'\nAdvice: 'Develop a study schedule, take regular breaks, and practice relaxation techniques.'", | |
| "Provide support for feeling overwhelmed:\n\nFeeling: 'Feeling overwhelmed with coursework'\nAdvice: 'Break tasks into smaller, manageable parts and seek support from peers or a counselor.'" | |
| ] | |
| prompt = f"Here are some examples of mental health advice:\n\n{examples}\n\nProvide advice based on the following feeling:\n{feelings}. Offer practical suggestions for improving well-being." | |
| return call_groq_api(prompt) | |
| # Initialize session state if not already set | |
| if 'responses' not in st.session_state: | |
| st.session_state['responses'] = { | |
| "personalized_learning_assistant": "", | |
| "ai_coding_mentor": "", | |
| "smart_document_summarizer": "", | |
| "interactive_study_planner": "", | |
| "real_time_qa_support": "", | |
| "mental_health_check_in": "" | |
| } | |
| # Define Streamlit app | |
| st.set_page_config(page_title="EduNexus", page_icon=":book:", layout="wide") | |
| # Add custom styling using Streamlit | |
| st.markdown(""" | |
| <style> | |
| .css-1o7k8tt { | |
| background-color: #f5f5f5; | |
| color: #333333; | |
| } | |
| .css-1o7k8tt h1 { | |
| color: #333333; | |
| } | |
| .stButton { | |
| background-color: #007bff; | |
| color: #ffffff; | |
| border-radius: 5px; | |
| padding: 8px 16px; | |
| font-size: 14px; | |
| } | |
| .stButton:hover { | |
| background-color: #0056b3; | |
| } | |
| .stTextInput, .stTextArea { | |
| border: 1px solid #ced4da; | |
| border-radius: 4px; | |
| background-color: #ffffff; | |
| color: #333333; | |
| } | |
| .stTextInput::placeholder, .stTextArea::placeholder { | |
| color: #6c757d; | |
| } | |
| .stSidebar { | |
| background-color: #ffffff; | |
| } | |
| .stSidebar .stMarkdown { | |
| color: #333333; | |
| } | |
| .footer { | |
| background-color: #f5f5f5; | |
| padding: 10px; | |
| text-align: center; | |
| color: #333333; | |
| border-top: 1px solid #dee2e6; | |
| } | |
| .footer a { | |
| color: #007bff; | |
| margin: 0 10px; | |
| text-decoration: none; | |
| font-size: 16px; | |
| } | |
| .footer a:hover { | |
| color: #0056b3; | |
| } | |
| .footer i { | |
| font-size: 18px; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # Define function to clear all inputs | |
| def clear_chat(): | |
| st.session_state['responses'] = { | |
| "personalized_learning_assistant": "", | |
| "ai_coding_mentor": "", | |
| "smart_document_summarizer": "", | |
| "interactive_study_planner": "", | |
| "real_time_qa_support": "", | |
| "mental_health_check_in": "" | |
| } | |
| # Add Clear Chat button | |
| if st.sidebar.button("Clear All", key="clear_button"): | |
| clear_chat() | |
| # Navigation sidebar | |
| st.sidebar.title("EduNexus Tools") | |
| selected_tool = st.sidebar.radio( | |
| "Select a tool", | |
| ("Personalized Learning Assistant", "AI Coding Mentor", "Smart Document Summarizer", | |
| "Interactive Study Planner", "Real-Time Q&A Support", "Mental Health Check-In") | |
| ) | |
| # Display tool based on selection | |
| st.title("EduNexus :book:") | |
| # Common function to display response and download button | |
| def display_response(response_key, response): | |
| st.write(response) | |
| st.download_button( | |
| "Download Response", | |
| response, | |
| file_name=f"{response_key}.txt" | |
| ) | |
| if selected_tool == "Personalized Learning Assistant": | |
| st.header("Personalized Learning Assistant") | |
| with st.form(key="learning_form"): | |
| topic_input = st.text_input("Enter a topic you want to learn about", placeholder="e.g., Quantum Mechanics") | |
| submit_button = st.form_submit_button("Get Explanation") | |
| if submit_button: | |
| explanation = personalized_learning_assistant(topic_input) | |
| st.session_state['responses']['personalized_learning_assistant'] = explanation | |
| if st.session_state['responses']['personalized_learning_assistant']: | |
| display_response("personalized_learning_assistant", st.session_state['responses']['personalized_learning_assistant']) | |
| elif selected_tool == "AI Coding Mentor": | |
| st.header("AI Coding Mentor") | |
| with st.form(key="coding_form"): | |
| code_input = st.text_area("Enter your code snippet", placeholder="e.g., def add(a, b): return a + b") | |
| submit_button = st.form_submit_button("Review Code") | |
| if submit_button: | |
| review = ai_coding_mentor(code_input) | |
| st.session_state['responses']['ai_coding_mentor'] = review | |
| if st.session_state['responses']['ai_coding_mentor']: | |
| display_response("ai_coding_mentor", st.session_state['responses']['ai_coding_mentor']) | |
| elif selected_tool == "Smart Document Summarizer": | |
| st.header("Smart Document Summarizer") | |
| with st.form(key="document_form"): | |
| document_input = st.text_area("Paste your document text", placeholder="e.g., In this paper, we explore the...") | |
| submit_button = st.form_submit_button("Summarize Document") | |
| if submit_button: | |
| summary = smart_document_summarizer(document_input) | |
| st.session_state['responses']['smart_document_summarizer'] = summary | |
| if st.session_state['responses']['smart_document_summarizer']: | |
| display_response("smart_document_summarizer", st.session_state['responses']['smart_document_summarizer']) | |
| elif selected_tool == "Interactive Study Planner": | |
| st.header("Interactive Study Planner") | |
| with st.form(key="planner_form"): | |
| schedule_input = st.text_input("Describe your exam schedule", placeholder="e.g., 3 exams next week") | |
| submit_button = st.form_submit_button("Create Study Plan") | |
| if submit_button: | |
| plan = interactive_study_planner(schedule_input) | |
| st.session_state['responses']['interactive_study_planner'] = plan | |
| if st.session_state['responses']['interactive_study_planner']: | |
| display_response("interactive_study_planner", st.session_state['responses']['interactive_study_planner']) | |
| elif selected_tool == "Real-Time Q&A Support": | |
| st.header("Real-Time Q&A Support") | |
| with st.form(key="qa_form"): | |
| question_input = st.text_input("Ask your question", placeholder="e.g., What is Newton's third law?") | |
| submit_button = st.form_submit_button("Get Answer") | |
| if submit_button: | |
| answer = real_time_qa_support(question_input) | |
| st.session_state['responses']['real_time_qa_support'] = answer | |
| if st.session_state['responses']['real_time_qa_support']: | |
| display_response("real_time_qa_support", st.session_state['responses']['real_time_qa_support']) | |
| elif selected_tool == "Mental Health Check-In": | |
| st.header("Mental Health Check-In") | |
| with st.form(key="mental_health_form"): | |
| feelings_input = st.text_area("Describe how you're feeling", placeholder="e.g., I'm feeling stressed about exams") | |
| submit_button = st.form_submit_button("Get Support") | |
| if submit_button: | |
| advice = mental_health_check_in(feelings_input) | |
| st.session_state['responses']['mental_health_check_in'] = advice | |
| if st.session_state['responses']['mental_health_check_in']: | |
| display_response("mental_health_check_in", st.session_state['responses']['mental_health_check_in']) | |
| # Footer with social links | |
| st.markdown(""" | |
| <div class="footer"> | |
| <a href="https://github.com/" target="_blank"><i class="fab fa-github"></i> GitHub</a> | |
| <a href="https://linkedin.com/" target="_blank"><i class="fab fa-linkedin"></i> LinkedIn</a> | |
| <a href="https://twitter.com/" target="_blank"><i class="fab fa-twitter"></i> Twitter</a> | |
| </div> | |
| """, unsafe_allow_html=True) | |