import requests
import streamlit as st
import json

# Access API keys from Streamlit secrets
openweather_api_key = st.secrets["weather_api_key"]
groq_api_key = st.secrets["groq_api_key"]

# Function to get user's IP-based location
def get_location_by_ip():
    try:
        response = requests.get("https://ipinfo.io")
        location_data = response.json()
        return location_data['city']
    except Exception as e:
        st.warning("Could not auto-detect location.")
        return None

# Function to get weather data from OpenWeatherMap
def get_weather_data(city):
    weather_url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={openweather_api_key}&units=metric"
    response = requests.get(weather_url)
    if response.status_code == 200:
        return response.json()
    else:
        st.error("Could not retrieve weather data. Please check your API key and city name.")
        return None

# Function to get outfit suggestion from Groq text generation model
def get_outfit_suggestion(weather_condition, temperature, city, gender):
    url = "https://api.groq.com/v1/completions"  # Groq's text generation endpoint
    headers = {
        "Authorization": f"Bearer {groq_api_key}",
        "Content-Type": "application/json"
    }
    
    # Construct a prompt based on the weather and user details
    prompt = (
        f"Suggest an outfit for a {gender} in {city} where the weather is {weather_condition} "
        f"with a temperature of {temperature}°C. Make it practical and stylish."
    )
    
    payload = {
        "model": "llama3-8b-8192",  # Use an appropriate Groq model
        "messages": [{"role": "user", "content": prompt}]
    }
    
    response = requests.post(url, headers=headers, data=json.dumps(payload))
    if response.status_code == 200:
        return response.json().get("choices")[0]["message"]["content"]
    else:
        st.error("Could not retrieve outfit suggestions. Please check your Groq API.")
        return None

# Enhanced UI with background color and icons
st.markdown(
    """
    <style>
    body {
        background-color: #f0f2f6;
        color: #333;
        font-family: Arial, sans-serif;
    }
    .main-header {
        font-size: 2.5em;
        color: #6C63FF;
        text-align: center;
    }
    .weather-box {
        background-color: #ffffff;
        padding: 20px;
        border-radius: 10px;
        box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
    }
    </style>
    """, unsafe_allow_html=True
)

# Main app UI
st.markdown("<h1 class='main-header'>Weather-Based Outfit Suggestion App</h1>", unsafe_allow_html=True)

# Try auto-detecting location if city is empty
city = st.text_input("Enter your location:", value=get_location_by_ip() or "")
gender = st.radio("Select Gender", options=["Male", "Female"], index=0)

if city:
    weather_data = get_weather_data(city)
    if weather_data:
        # Extract weather information
        weather_condition = weather_data["weather"][0]["main"]
        temperature = weather_data["main"]["temp"]
        feels_like = weather_data["main"]["feels_like"]
        humidity = weather_data["main"]["humidity"]
        wind_speed = weather_data["wind"]["speed"]

        # Display weather information with icons and enhancements
        st.markdown("<div class='weather-box'>", unsafe_allow_html=True)
        st.subheader(f"🌍 Weather in {city}")
        st.write(f"🌤️ Condition: {weather_condition}")
        st.write(f"🌡️ Temperature: {temperature}°C (Feels like: {feels_like}°C)")
        st.write(f"💧 Humidity: {humidity}%")
        st.write(f"💨 Wind Speed: {wind_speed} m/s")
        st.markdown("</div>", unsafe_allow_html=True)

        # Get outfit suggestion based on weather and gender
        outfit_suggestion = get_outfit_suggestion(weather_condition, temperature, city, gender)
        if outfit_suggestion:
            st.subheader("👗 Outfit Suggestion")
            st.write(outfit_suggestion)
        else:
            st.warning("No outfit suggestion available for this weather condition.")
else:
    st.info("Please enter your location to get weather and outfit suggestions.")








# import requests
# import streamlit as st
# import groq

# # Access API keys from Streamlit secrets
# openweather_api_key = st.secrets["weather_api_key"]
# groq_api_key = st.secrets["groq_api_key"]

# # Function to get weather data from OpenWeatherMap
# def get_weather_data(city):
#     api_key = openweather_api_key  # Use the secret API key
#     url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric"
#     try:
#         response = requests.get(url)
#         response.raise_for_status()  # Raise an HTTPError if the HTTP request returned an unsuccessful status code
#         return response.json()
#     except requests.exceptions.HTTPError as err:
#         st.error(f"HTTP error occurred: {err}")
#     except Exception as err:
#         st.error(f"An error occurred: {err}")
#     return None

# # Function to parse weather data
# def parse_weather_data(weather_data):
#     temperature = weather_data["main"]["temp"]
#     weather_description = weather_data["weather"][0]["description"]
#     return temperature, weather_description

# # Function to get outfit suggestion using Groq's LLaMA model
# def get_outfit_suggestion(temperature, description, style, fabric):
#     # Initialize Groq's API
#     try:
#         client = groq.Groq(api_key=groq_api_key)  # Use the secret API key
        
#         prompt = f"The current weather is {description} with a temperature of {temperature}°C. Suggest an outfit. The user prefers a {style} style and {fabric} fabric."

#         # Use Groq's chat completion to get the text response
#         response = client.chat.completions.create(
#             messages=[{"role": "user", "content": prompt}],
#             model="llama3-8b-8192",  # Change to a valid Groq model if necessary
#         )
#         return response.choices[0].message.content.strip()
#     except Exception as e:
#         st.error(f"Error using Groq API: {e}")
#         return None

# # Streamlit UI for user input
# st.title("Weather-Based Outfit Suggestion App")

# city = st.text_input("Enter your location:")

# # Add style and fabric input options
# style = st.selectbox("Select your preferred style", ["Casual", "Formal", "Sporty", "Business", "Chic"])
# fabric = st.selectbox("Select your preferred fabric", ["Cotton", "Linen", "Wool", "Polyester", "Silk", "Leather"])

# if city:
#     weather_data = get_weather_data(city)
    
#     if weather_data and weather_data["cod"] == 200:
#         temperature, description = parse_weather_data(weather_data)
        
#         # Display current weather info
#         st.write(f"Current temperature in {city}: {temperature}°C")
#         st.write(f"Weather: {description}")
        
#         # Get outfit suggestion based on user preferences
#         outfit_suggestion = get_outfit_suggestion(temperature, description, style, fabric)
        
#         if outfit_suggestion:
#             # Display outfit suggestion
#             st.write("Outfit Suggestion:")
#             st.write(outfit_suggestion)
        
#         # Display weather icon
#         icon_code = weather_data["weather"][0]["icon"]
#         icon_url = f"http://openweathermap.org/img/wn/{icon_code}.png"
#         st.image(icon_url)
#     else:
#         st.write("Could not retrieve weather data. Please check the location.")
        
# # Optional: Add CSS for styling
# st.markdown(
#     """
#     <style>
#     .reportview-container {
#         background: #f5f5f5;
#     }
#     .stButton>button {
#         background-color: #ff5733;
#         color: white;
#     }
#     </style>
#     """,
#     unsafe_allow_html=True
# )



# --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------



# import requests
# import streamlit as st
# import groq
# import os

# # Function to get weather data from OpenWeatherMap

# import os

# # Replace with environment variables
# openweather_api_key = os.getenv("weather_api_key")
# groq_api_key = os.getenv("groq_api_key")


# def get_weather_data(city):
#     api_key = openweather_api_key  # Replace with your OpenWeatherMap API key
#     url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}&units=metric"
#     try:
#         response = requests.get(url)
#         response.raise_for_status()  # Raise an HTTPError if the HTTP request returned an unsuccessful status code
#         return response.json()
#     except requests.exceptions.HTTPError as err:
#         st.error(f"HTTP error occurred: {err}")
#     except Exception as err:
#         st.error(f"An error occurred: {err}")
#     return None

# # Function to parse weather data
# def parse_weather_data(weather_data):
#     temperature = weather_data["main"]["temp"]
#     weather_description = weather_data["weather"][0]["description"]
#     return temperature, weather_description

# # Function to get outfit suggestion using Groq's LLaMA model
# def get_outfit_suggestion(temperature, description, style, fabric):
#     # Initialize Groq's API
#     try:
#         client = groq.Groq(api_key=groq_api_key)  # Replace with your Groq API key
        
#         prompt = f"The current weather is {description} with a temperature of {temperature}°C. Suggest an outfit. The user prefers a {style} style and {fabric} fabric."

#         # Use Groq's chat completion to get the text response
#         response = client.chat.completions.create(
#             messages=[{"role": "user", "content": prompt}],
#             model="llama3-8b-8192",  # Change to a valid Groq model if necessary
#         )
#         return response.choices[0].message.content.strip()
#     except Exception as e:
#         st.error(f"Error using Groq API: {e}")
#         return None

# # Streamlit UI for user input
# st.title("Weather-Based Outfit Suggestion App")

# city = st.text_input("Enter your location:")

# # Add style and fabric input options
# style = st.selectbox("Select your preferred style", ["Casual", "Formal", "Sporty", "Business", "Chic"])
# fabric = st.selectbox("Select your preferred fabric", ["Cotton", "Linen", "Wool", "Polyester", "Silk", "Leather"])

# if city:
#     weather_data = get_weather_data(city)
    
#     if weather_data and weather_data["cod"] == 200:
#         temperature, description = parse_weather_data(weather_data)
        
#         # Display current weather info
#         st.write(f"Current temperature in {city}: {temperature}°C")
#         st.write(f"Weather: {description}")
        
#         # Get outfit suggestion based on user preferences
#         outfit_suggestion = get_outfit_suggestion(temperature, description, style, fabric)
        
#         if outfit_suggestion:
#             # Display outfit suggestion
#             st.write("Outfit Suggestion:")
#             st.write(outfit_suggestion)
        
#         # Display weather icon
#         icon_code = weather_data["weather"][0]["icon"]
#         icon_url = f"http://openweathermap.org/img/wn/{icon_code}.png"
#         st.image(icon_url)
#     else:
#         st.write("Could not retrieve weather data. Please check the location.")
        
# # Optional: Add CSS for styling
# st.markdown(
#     """
#     <style>
#     .reportview-container {
#         background: #f5f5f5;
#     }
#     .stButton>button {
#         background-color: #ff5733;
#         color: white;
#     }
#     </style>
#     """,
#     unsafe_allow_html=True
# )