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import streamlit as st
import google.generativeai as genai
from dotenv import load_dotenv
import os
import json
# Load environment variables
load_dotenv()
# Configure Gemini
genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
model = genai.GenerativeModel('gemini-pro')
# Load questionnaire from JSON
def load_questionnaire():
with open('assets/questionnaire.json', 'r') as f:
return json.load(f)
# Render questions based on type
def render_question(question):
question_type = question.get("type")
if question_type == "slider":
return st.slider(
question["question"],
min_value=question.get("min", 1),
max_value=question.get("max", 10),
value=question.get("default", 5)
)
elif question_type == "select_slider":
return st.select_slider(
question["question"],
options=question["options"],
value=question.get("default")
)
elif question_type == "radio":
return st.radio(
question["question"],
options=question["options"]
)
elif question_type == "select":
return st.selectbox(
question["question"],
options=question["options"]
)
elif question_type == "multiselect":
return st.multiselect(
question["question"],
options=question["options"]
)
elif question_type == "number":
return st.number_input(
question["question"],
min_value=question.get("min", 0),
max_value=question.get("max", 24),
value=question.get("default", 4)
)
else:
st.warning(f"Unsupported question type: {question_type}")
return None
# Main function
def main():
st.title("JEE SOCA Analysis System 🚀")
st.subheader("AI-Powered Skill Assessment for JEE Aspirants")
# Load questionnaire
questionnaire = load_questionnaire()
# Collect responses
responses = {}
with st.form("student_form"):
st.header("Student Questionnaire")
# Render questions from JSON
for section in questionnaire["questionnaire"]:
st.subheader(f"📚 {section['section']}")
for question in section["questions"]:
response = render_question(question)
if response is not None:
responses[question["question"]] = response
# Submit button
submitted = st.form_submit_button("Generate SOCA Analysis")
if submitted:
with st.spinner("Analyzing responses..."):
# Prepare prompt for Gemini
prompt = "Analyze this JEE student's profile and create a SOCA analysis:\n\n"
for question, response in responses.items():
prompt += f"- {question}: {response}\n"
prompt += """
Provide the analysis in this format:
**Strengths:** [Identify 3 key strengths]
**Opportunities:** [Suggest 3 improvement areas]
**Challenges:** [List 3 main challenges]
**Action Plan:** [Create 4 actionable steps]
"""
# Get Gemini response
try:
response = model.generate_content(prompt)
st.subheader("SOCA Analysis Report")
st.markdown(response.text)
except Exception as e:
st.error(f"An error occurred while generating the analysis: {e}")
# Run the app
if __name__ == "__main__":
main() |