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("""
""", 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("""
""", unsafe_allow_html=True)