import gradio as gr
import google.generativeai as genai
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

# Retrieve API key from environment variable
GEMINI_API_KEY = "AIzaSyA0SnGcdEuesDusLiM93N68-vaFF14RCYg"  # public api 

# Configure Google Gemini API
genai.configure(api_key=GEMINI_API_KEY)

# Create the model configuration
generation_config = {
    "temperature": 0.7,
    "top_p": 0.95,
    "top_k": 64,
    "max_output_tokens": 512,  # Adjust as needed
    "response_mime_type": "text/plain",
}

# Simplified safety settings (or try removing them to test)
safety_settings = [
    {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"},
    {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"}
]

# Function to generate a response based on user input and chat history
def generate_response(user_input, chat_history):
    """Generates a response based on user input and chat history."""

    # Update system content with the full character description
    updated_system_content = "You are Shadow the Hedgehog and you must act like Shadow the Hedgehog's personality."

    # Create the generative model
    model = genai.GenerativeModel(
        model_name="gemini-1.5-pro", 
        generation_config=generation_config,
        safety_settings=safety_settings,
        system_instruction=updated_system_content,
    )

    # Add user input to history
    chat_history.append(("user", user_input))

    # Limit history length to the last 10 messages
    chat_history = chat_history[-10:]

    retry_attempts = 3
    for attempt in range(retry_attempts):
        try:
            # Start a new chat session
            chat_session = model.start_chat()

            # Send the entire chat history as the first message
            response = chat_session.send_message("\n".join([f"{role}: {msg}" for role, msg in chat_history]))
            chat_history.append(("assistant", response.text))
            return chat_history

        except Exception as e:
            if attempt < retry_attempts - 1:
                continue
            else:
                chat_history.append(("assistant", f"Error after {retry_attempts} attempts: {str(e)}"))
                return chat_history

# Build the Gradio interface using ChatInterface
with gr.Blocks() as iface:
    chatbot = gr.Chatbot()  # Create a Chatbot component
    user_input = gr.Textbox(label="Talk to AI", placeholder="Enter your message here...")
    chat_history_state = gr.State([])  # State input for chat history

    # Define the layout and components
    user_input.submit(
        fn=generate_response,
        inputs=[user_input, chat_history_state],
        outputs=chatbot
    )

iface.launch()