app.py

import os
import requests
import streamlit as st
from dotenv import load_dotenv

# Load environment variables from the .env file
load_dotenv()

# Get the Gemini API key from the .env file
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")

if GEMINI_API_KEY is None:
    st.error("API key not found! Please set the GEMINI_API_KEY in your .env file.")
    st.stop()

# Define the 3 questions for mood analysis
questions = [
    "How are you feeling today in one word?",
    "What's currently on your mind?",
    "Do you feel calm or overwhelmed right now?",
]

# Function to query the Gemini API
def query_gemini_api(user_answers):
    # Correct Gemini API endpoint
    url = f"https://generativelanguage.googleapis.com/v1beta/models/text-bison-001:generateText?key={GEMINI_API_KEY}"
    
    headers = {'Content-Type': 'application/json'}
    
    # Combine the user answers into a single input text
    input_text = " ".join(user_answers)
    
    # Payload for the API
    payload = {
        "prompt": {
            "text": f"Analyze the following mood based on these inputs: {input_text}. Provide suggestions to improve the mood."
        },
        "temperature": 0.7,
        "maxOutputTokens": 256,
        "topP": 0.8,
        "topK": 40
    }

    try:
        # Send the POST request
        response = requests.post(url, headers=headers, json=payload)

        # Check if the response is successful
        if response.status_code == 200:
            result = response.json()
            
            # Extract the generated text from the response
            generated_text = result.get("candidates", [{}])[0].get("output", "")
            return generated_text
        else:
            st.error(f"API Error {response.status_code}: {response.text}")
            return None
    except requests.exceptions.RequestException as e:
        st.error(f"An error occurred: {e}")
        return None

# Streamlit app for collecting answers
def main():
    st.title("Mood Analysis and Suggestions")

    st.write("Answer the following 3 questions to help us understand your mood:")

    # Collect responses from the user
    responses = []
    for i, question in enumerate(questions):
        response = st.text_input(f"{i+1}. {question}")
        if response:
            responses.append(response)

    # If all 3 responses are collected, send them to Gemini for analysis
    if len(responses) == len(questions):
        st.write("Processing your answers...")

        # Query the Gemini API
        generated_text = query_gemini_api(responses)

        if generated_text:
            # Display the generated mood analysis and recommendations
            st.write("### Mood Analysis and Suggestions:")
            st.write(generated_text)
        else:
            st.warning("Could not generate mood analysis. Please try again later.")
    else:
        st.info("Please answer all 3 questions to receive suggestions.")

if __name__ == "__main__":
    main()