import gradio as gr
from typing import List
from langchain_google_genai import GoogleGenerativeAIEmbeddings
import google.generativeai as genai
from langchain_community.vectorstores import FAISS
from langchain_google_genai import ChatGoogleGenerativeAI
import re

genai.configure(api_key="AIzaSyD2o8vjePJb6z8vT_PVe82lVWMD3_cBL0g")

def format_gemini_response(text):
    bold_pattern = r"\*\*(.*?)\*\*"
    italic_pattern = r"\*(.*?)\*"
    code_pattern = r"```(.*?)```"
    text = text.replace('\n', '<br>')
    formatted_text = re.sub(code_pattern, "<pre><code>\\1</code></pre>", text)
    formatted_text = re.sub(bold_pattern, "<b>\\1</b>", formatted_text)
    formatted_text = re.sub(italic_pattern, "<i>\\1</i>", formatted_text)
    return formatted_text

def predict(message: str, chat_his: List[List[str]], d: dict) -> str:
    if not message.strip():
        return "Error: Message cannot be empty.", chat_his, d

    model = genai.GenerativeModel("gemini-pro")
    his = []
    for i, j in chat_his:
        his.extend([
            {"role": "user", "parts": i},
            {"role": "model", "parts": j},
        ])

    chat = model.start_chat(history=his)
    response = chat.send_message(message)
    
    # Update chat history
    chat_his.append((message, response.text))
    
    return format_gemini_response(response.text), chat_his, d

iface = gr.Interface(
    fn=predict,
    inputs=["text", "list", "json"],
    outputs="html"  # Change to HTML for proper rendering
)
iface.launch(share=True)