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

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

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

if 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 API URL
    url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent?key={API_KEY}"
    
    headers = {'Content-Type': 'application/json'}
    
    # Combine user responses into a single input
    input_text = " ".join(user_answers)
    
    # Payload for the API request
    payload = {
        "contents": [
            {
                "parts": [
                    {"text": f"Analyze the mood based on these inputs: {input_text}. Provide recommendations."}
                ]
            }
        ]
    }

    try:
        # Send POST request
        response = requests.post(url, headers=headers, json=payload)
        
        if response.status_code == 200:
            result = response.json()
            
            # Extract recommendations from the response
            recommendations = result.get("contents", [{}])[0].get("parts", [{}])[0].get("text", "")
            return recommendations
        else:
            # Handle API error
            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
def main():
    st.title("Mood Analysis and Suggestions")
    st.write("Answer the following 3 questions to help us understand your mood:")

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

    # Query the API if all questions are answered
    if len(responses) == len(questions):
        st.write("Processing your answers...")

        # Query the Gemini API
        recommendations = query_gemini_api(responses)

        if recommendations:
            st.write("### Recommendations to Improve Your Mood:")
            st.write(recommendations)
        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()