import gradio as gr
import openai
import os

# Set the OpenAI API key and endpoint
openai.api_key = os.getenv("GROQ_API_KEY")
openai.api_base = "https://api.groq.com/openai/v1"

# Check if the API key is set properly
if not openai.api_key:
    raise ValueError("API key is missing. Please set the GROQ_API_KEY environment variable.")

def get_groq_response(message):
    try:
        # Log the request to help with debugging
        print(f"Sending message: {message}")
        
        # Make the API call
        response = openai.ChatCompletion.create(
            model="llama-3.3-70b-versatile",
            messages=[
                {"role": "system", "content": "Precise answer"},
                {"role": "user", "content": message}
            ]
        )
        
        # Check if the response contains 'choices'
        if not response.get('choices'):
            raise ValueError("API response does not contain choices.")
        
        # Extract the bot's message from the response
        bot_message = response['choices'][0]['message']['content']
        
        # Log the bot's response
        print(f"Received response: {bot_message}")
        
        return bot_message

    except openai.error.AuthenticationError:
        return "Authentication error: Invalid API key."
    except openai.error.RateLimitError:
        return "Rate limit exceeded: Too many requests. Please try again later."
    except openai.error.APIError as e:
        return f"API error: {e.user_message} Please try again later."
    except openai.error.Timeout:
        return "Request timed out. Please try again later."
    except Exception as e:
        # Catch all other exceptions
        return f"An unexpected error occurred: {str(e)}"

def chatbot(user_input, history=None):
    # Initialize history as an empty list if None is passed
    if history is None:
        history = []
    
    # Avoid processing empty user input
    if not user_input.strip():
        return history, history
    
    # Get the bot's response
    bot_response = get_groq_response(user_input)
    
    # Append the interaction to the conversation history
    history.append((user_input, bot_response))
    
    return history, history

# Create the Gradio interface
chat_interface = gr.Interface(
    fn=chatbot,
    inputs=["text", "state"],
    outputs=["chatbot", "state"],
    live=False,
    title="My Chatbot",
    description="Mom: We have ChatGPT at Home, \nChatGPT at Home: "
)

# Launch the Gradio app
chat_interface.launch()