# -*- coding: utf-8 -*-
import gradio as gr
import os
import requests
import openai
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Initialize OpenAI client your openai key
openai.api_key = os.getenv('OPENAI_API_KEY')


def get_current_weather(location, unit='celsius'):
    weather_api_key = userdata.get('WEATHER_API_KEY')
    base_url = f"http://api.openweathermap.org/data/2.5/weather?q={location}&appid={weather_api_key}&units=metric"
    response = requests.get(base_url)
    data = response.json()

    weather_description = data['weather'][0]['description']
    return {
        "location": location,
        "temperature": data['main']['temp'],
        "weather": weather_description
    }

#print(get_current_weather("fremont"))

# format is referred from opeai Function Chat->Tools->Add->Function->get_weather()
functions = [
    {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "The city, e.g. San Francisco"
                },
                "unit": {
                    "type": "string",
                    "enum": ["celsius", "fahrenheit"]
                }
            },
            "required": ["location"]
        }
    }
]

functions

#Function Definition and Initial Message Handling
def weather_chat(user_message):
    messages=[]
    messages.append({"role": "user", "content": user_message})
    messages.append({"role": "assistant", "content": "You are a weather bot . Answer only in Celsius and answer only related to weather related questions. If user asks other than weather then politely decline it"})

        # Sending Initial Message to OpenAI
    response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            temperature = 0,
            max_tokens=256,
            top_p=0.2,
            frequency_penalty=0,
            presence_penalty=0,
            messages=messages,
            functions=functions
        )
    #print(f'response1 is : {response}')

    #Handling Function Calls and Fetching Weather Data
    try:
        function_call = response['choices'][0]['message']['function_call']
        #print(f'function_call : {function_call}')
        # Extract function name and arguments
        arguments = eval(function_call['arguments']) # we are passing locatioon in arguments. this line of code is taking the string representation of the arguments returned by the OpenAI API and converting it into a usable Python dictionary, which you then use to call your get_current_weather function.
        #print(f'arguments : {arguments}')
        # Fetch weather data using the extracted arguments
        weather_data = get_current_weather(arguments['location'])

        # Append the function call and weather data to the messages
        messages.append({"role": "assistant", "content": None, "function_call": {"name": "get_current_weather", "arguments": str(arguments)}})
        messages.append({"role": "function", "name": "get_current_weather", "content": str(weather_data)})

        #print(f'message : {messages}')
#magic of llm
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=messages
        )
        #print(f'response2 : {response}')
        return response['choices'][0]['message']['content']
    except Exception as e:
        return "I'm here to provide weather updates. Please ask me questions related to weather."

#import gradio as gr
# Define Gradio interface
# iface = gr.Interface(
    # fn=weather_chat,
    # inputs=gr.Textbox(label="Weather Queries"),
    # outputs=gr.Textbox(label="Weather Updates", lines=5),
    # title = "Weather Bot",
    # description = "Ask me anything about weather!"
# )

# Launch the Gradio interface
#iface.launch(share="True")

# To create a customized Gradio Interference, following is the prompt.
# import gradio as gr
# # Define Gradio interface
# iface = gr.Interface(
#     fn=weather_chat,
#     inputs=gr.Textbox(label="Weather Queries"),
#     outputs=gr.Textbox(label="Weather Updates", lines=5),
#     title = "Weather Bot",
#     description = "Ask me anything about weather!"
# )

# # Launch the Gradio interface
# iface.launch(share="True")

# make the above gradio app more professional, use blocks and add 2 columns format, give option for famous cities in a drop down or give a option of manually submitting the city, also add the logo
# https://github.com/Decoding-Data-Science/airesidency/blob/main/dds_logo.jpg

# List of famous cities for the dropdown
FAMOUS_CITIES = [
    "New York", "London", "Tokyo", "Paris", "Dubai",
    "Singapore", "Hong Kong", "Sydney", "Mumbai", "Toronto",
    "Los Angeles", "Chicago", "San Francisco", "Berlin", "Madrid",
    "Rome", "Barcelona", "Amsterdam", "Bangkok", "Seoul",
    "Shanghai", "Beijing", "Istanbul", "Moscow", "Mexico City"
]

def process_weather_query(city_dropdown, custom_city, query):
    """
    Process weather query based on city selection and custom input
    """
    # Determine which city to use
    city = custom_city.strip() if custom_city.strip() else city_dropdown

    # Combine city with query if query exists
    if query.strip():
        full_query = f"{query} in {city}"
    else:
        full_query = f"What's the weather in {city}?"

    # Call your weather_chat function
    response = weather_chat(full_query)
    return response

# Create the Gradio Blocks interface
with gr.Blocks(theme=gr.themes.Soft(), title="Weather Bot") as iface:

    # Header with logo
    with gr.Row():
        gr.Image(
            #"https://github.com/Decoding-Data-Science/airesidency/blob/main/dds_logo.jpg?raw=true",
            "weather_bot.jpg",
            label=None,
            show_label=False,
            height=100,
            width=200,
            show_download_button=False,
            container=False
        )

    # Title and description
    gr.Markdown(
        """
        # 🌤️ Weather Bot
        ### Get real-time weather information for any city around the world
        """
    )

    # Main content with two columns
    with gr.Row():
        # Left Column - Input Section
        with gr.Column(scale=1):
            gr.Markdown("### 📍 Select or Enter City")

            city_dropdown = gr.Dropdown(
                choices=FAMOUS_CITIES,
                value="New York",
                label="Choose from Popular Cities",
                info="Select a city from the dropdown"
            )

            gr.Markdown("**OR**")

            custom_city = gr.Textbox(
                label="Enter Custom City",
                placeholder="Type any city name...",
                info="Leave empty to use the dropdown selection"
            )

            query_input = gr.Textbox(
                label="Additional Query (Optional)",
                placeholder="e.g., temperature, forecast, humidity...",
                lines=2,
                info="Ask specific weather questions"
            )

            with gr.Row():
                submit_btn = gr.Button("Get Weather 🌍", variant="primary", size="lg")
                clear_btn = gr.Button("Clear 🔄", variant="secondary")

        # Right Column - Output Section
        with gr.Column(scale=1):
            gr.Markdown("### 🌡️ Weather Information")

            output = gr.Textbox(
                label="Weather Updates",
                lines=12,
                placeholder="Weather information will appear here...",
                show_copy_button=True
            )

    # Example queries
    gr.Markdown("### 💡 Example Queries")
    gr.Examples(
        examples=[
            ["London", "", "What's the current temperature?"],
            ["", "Seattle", "Will it rain today?"],
            ["Tokyo", "", "7-day forecast"],
            ["", "Mumbai", "humidity levels"],
            ["Paris", "", ""]
        ],
        inputs=[city_dropdown, custom_city, query_input],
        label="Try these examples"
    )

    # Event handlers
    submit_btn.click(
        fn=process_weather_query,
        inputs=[city_dropdown, custom_city, query_input],
        outputs=output
    )

    clear_btn.click(
        fn=lambda: ("New York", "", "", ""),
        inputs=None,
        outputs=[city_dropdown, custom_city, query_input, output]
    )

    # Footer
    gr.Markdown(
        """
        ---
        <p style='text-align: center; color: #666;'>
        Powered by AI | Built with Gradio
        </p>
        """
    )

# Launch the interface
if __name__ == "__main__":
    iface.launch(share=True)