import gradio as gr
from fpl_client import FPLClient
from nlp_utils import process_query

# Theme builder
# gr.themes.builder()

theme = gr.themes.Soft(
    primary_hue="sky",
    neutral_hue="slate",
)

# Initialize the FPL client
fpl_client = FPLClient()

# Function to handle user input and generate a response
def chatbot_response(query):
    response = process_query(query, fpl_client)
    # if response if a JSON boject iterate over the elements and conver is a list like "a": "b" "/n" "c": "d"
    if isinstance(response, dict):
        response = "\n".join([f"{key}: {value}" for key, value in response.items()])
    return response


# Set up the Gradio interface
iface = gr.Interface(
    fn=chatbot_response,
    inputs=gr.Textbox(label="Ask our FPL Expert"),
    outputs=gr.Textbox(label="Hope it helps!"),
    theme=theme,
    title="FPL Chatbot"
)
if __name__ == "__main__":
    iface.launch()