from huggingface_hub import InferenceClient
import requests
from bs4 import BeautifulSoup
import lxml
import gradio as gr
import os
# Initialize the InferenceClient
client = InferenceClient(token=os.getenv("HF_TOKEN"))
secretkey = os.getenv("FMP_KEY")

# BOT avatar for chat interface
BOT_AVATAR = 'https://automatedstockmining.org/wp-content/uploads/2024/09/logo.webp'

# API Documentation (placed outside the function)
data = '''
# Stock List API
stock_list_api = f"https://financialmodelingprep.com/api/v3/stock/list?apikey={secretkey}"

# Exchange Traded Fund Search API
etf_search_api = f"https://financialmodelingprep.com/api/v3/etf/list?apikey={secretkey}"

# Statement Symbols List API
statement_symbols_list_api = f"https://financialmodelingprep.com/api/v3/financial-statement-symbol-lists?apikey={secretkey}"

# Tradable Search API
tradable_search_api = f"https://financialmodelingprep.com/api/v3/available-traded/list?apikey={secretkey}"

# Commitment of Traders Report API
commitment_of_traders_report_api = f"https://financialmodelingprep.com/api/v4/commitment_of_traders_report/list?apikey={secretkey}"

# CIK List API
cik_list_api = f"https://financialmodelingprep.com/api/v3/cik_list?apikey={secretkey}"

# Euronext Symbols API
euronext_symbols_api = f"https://financialmodelingprep.com/api/v3/symbol/available-euronext?apikey={secretkey}"

# Symbol Changes API
symbol_changes_api = f"https://financialmodelingprep.com/api/v4/symbol_change?apikey={secretkey}"

# Exchange Symbols API
exchange_symbols_api = f"https://financialmodelingprep.com/api/v3/symbol/{exchange}?apikey={secretkey}"

# Available Indexes API
available_indexes_api = f"https://financialmodelingprep.com/api/v3/symbol/available-indexes?apikey={secretkey}"

# Company Profile API
company_profile_api = f"https://financialmodelingprep.com/api/v3/profile/{symbol}?apikey={secretkey}"

# Executive Compensation API
executive_compensation_api = f"https://financialmodelingprep.com/api/v4/governance/executive_compensation?symbol={symbol}&apikey={secretkey}"

# Compensation Benchmark API
compensation_benchmark_api = f"https://financialmodelingprep.com/api/v4/executive-compensation-benchmark?year={year}&apikey={secretkey}"

# Company Notes API
company_notes_api = f"https://financialmodelingprep.com/api/v4/company-notes?symbol={symbol}&apikey={secretkey}"

# Historical Employee API
historical_employee_api = f"https://financialmodelingprep.com/api/v4/historical/employee_count?symbol={symbol}&apikey={secretkey}"

# Employee Count API
employee_count_api = f"https://financialmodelingprep.com/api/v4/employee_count?symbol={symbol}&apikey={secretkey}"

# Screener (Stock) API
stock_screener_api = f"https://financialmodelingprep.com/api/v3/stock-screener?apikey={secretkey}"

# Stock Grade API
stock_grade_api = f"https://financialmodelingprep.com/api/v3/grade/{symbol}?apikey={secretkey}"

# Executives API
executives_api = f"https://financialmodelingprep.com/api/v3/key-executives/{symbol}?apikey={secretkey}"

# Company Core Information Summary API
company_core_info_summary_api = f"https://financialmodelingprep.com/api/v4/company-core-information?symbol={symbol}&apikey={secretkey}"

# Market Cap API
market_cap_api = f"https://financialmodelingprep.com/api/v3/market-capitalization/{symbol}?apikey={secretkey}"

# Historical Market Cap API
historical_market_cap_api = f"https://financialmodelingprep.com/api/v3/historical-market-capitalization/{symbol}?limit={limit}&from={start_date}&to={end_date}&apikey={secretkey}"

# All Countries API
all_countries_api = f"https://financialmodelingprep.com/api/v3/get-all-countries?apikey={secretkey}"

# Analyst Estimates API
analyst_estimates_api = f"https://financialmodelingprep.com/api/v3/analyst-estimates/{symbol}?apikey={secretkey}"

# Analyst Recommendation API
analyst_recommendation_api = f"https://financialmodelingprep.com/api/v3/analyst-stock-recommendations/{symbol}?apikey={secretkey}"

# Company Logo API
company_logo_api = f"https://financialmodelingprep.com/image-stock/{symbol}.png?apikey={secretkey}"

# Company Outlook API
company_outlook_api = f"https://financialmodelingprep.com/api/v4/company-outlook?symbol={symbol}&apikey={secretkey}"

# Stock Peers API
stock_peers_api = f"https://financialmodelingprep.com/api/v4/stock_peers?symbol={symbol}&apikey={secretkey}"

# Holidays and Trading Hours API
market_open_api = f"https://financialmodelingprep.com/api/v3/is-the-market-open?exchange={exchange}&apikey={secretkey}"

# All Exchanges Trading Hours API
all_exchanges_trading_hours_api = f"https://financialmodelingprep.com/api/v3/is-the-market-open-all?apikey={secretkey}"

# Delisted Companies API
delisted_companies_api = f"https://financialmodelingprep.com/api/v3/delisted-companies?apikey={secretkey}"

# Company Share Float API
company_share_float_api = f"https://financialmodelingprep.com/api/v4/shares_float?symbol={symbol}&apikey={secretkey}"

# Historical Share Float API
historical_share_float_api = f"https://financialmodelingprep.com/api/v4/historical/shares_float?symbol={symbol}&apikey={secretkey}"

# All Shares Float API
all_shares_float_api = f"https://financialmodelingprep.com/api/v4/shares_float/all?apikey={secretkey}"

# All Available Sectors API
available_sectors_api = f"https://financialmodelingprep.com/api/v3/sectors-list?apikey={secretkey}"

# All Available Industries API
available_industries_api = f"https://financialmodelingprep.com/api/v3/industries-list?apikey={secretkey}"

# All Available Exchanges API
available_exchanges_api = f"https://financialmodelingprep.com/api/v3/exchanges-list?apikey={secretkey}"

# Full Quote API
full_quote_api = f"https://financialmodelingprep.com/api/v3/quote/{symbol}?apikey={secretkey}"

# Quote Order API
quote_order_api = f"https://financialmodelingprep.com/api/v3/quote-order/{symbol}?apikey={secretkey}"

# Simple Quote API
simple_quote_api = f"https://financialmodelingprep.com/api/v3/quote-short/{symbol}?apikey={secretkey}"

# OTC Quote API
otc_quote_api = f"https://financialmodelingprep.com/api/v3/otc/real-time-price/{symbol}?apikey={secretkey}"

# Exchange Prices API
exchange_prices_api = f"https://financialmodelingprep.com/api/v3/quotes/{exchange}?apikey={secretkey}"

# Stock Price Change API
stock_price_change_api = f"https://financialmodelingprep.com/api/v3/stock-price-change/{symbol}?apikey={secretkey}"

# Aftermarket Trade API
aftermarket_trade_api = f"https://financialmodelingprep.com/api/v4/pre-post-market-trade/{symbol}?apikey={secretkey}"

# Aftermarket Quote API
aftermarket_quote_api = f"https://financialmodelingprep.com/api/v4/pre-post-market/{symbol}?apikey={secretkey}"

# Batch Quote API
batch_quote_api = f"https://financialmodelingprep.com/api/v4/batch-pre-post-market/{symbol}?apikey={secretkey}"

# Batch Trade API
batch_trade_api = f"https://financialmodelingprep.com/api/v4/batch-pre-post-market-trade/{symbol}?apikey={secretkey}"

# Last Forex API
last_forex_api = f"https://financialmodelingprep.com/api/v4/forex/last/{symbol}?apikey={secretkey}"




# Live Full Price w/ Orders API
live_full_price_api = f"https://financialmodelingprep.com/api/v3/stock/full/real-time-price/{symbol}?apikey={secretkey}"

# All Live Full Price w/ Orders API
all_live_full_price_api = f"https://financialmodelingprep.com/api/v3/stock/full/real-time-price?apikey={secretkey}"

# Forex Prices API
forex_prices_api = f"https://financialmodelingprep.com/api/v3/fx/{symbol}?apikey={secretkey}"

# Ratios API
ratios_api = f"https://financialmodelingprep.com/api/v3/ratios/{symbol}?period={period}&apikey={secretkey}"

# Ratios TTM API
ratios_ttm_api = f"https://financialmodelingprep.com/api/v3/ratios-ttm/{symbol}?apikey={secretkey}"

# Cashflow Growth API
cashflow_growth_api = f"https://financialmodelingprep.com/api/v3/cash-flow-statement-growth/{symbol}?period={period}&apikey={secretkey}"

# Income Growth API
income_growth_api = f"https://financialmodelingprep.com/api/v3/income-statement-growth/{symbol}?period={period}&apikey={secretkey}"

# Balance Sheet Growth API
balance_sheet_growth_api = f"https://financialmodelingprep.com/api/v3/balance-sheet-statement-growth/{symbol}?period={period}&apikey={secretkey}"

# Financial Growth API
financial_growth_api = f"https://financialmodelingprep.com/api/v3/financial-growth/{symbol}?period={period}&apikey={secretkey}"

# Financial Score API
financial_score_api = f"https://financialmodelingprep.com/api/v4/score?symbol={symbol}&apikey={secretkey}"

# Owner Earnings API
owner_earnings_api = f"https://financialmodelingprep.com/api/v4/owner_earnings?symbol={symbol}&apikey={secretkey}"

# Enterprise Values API
enterprise_values_api = f"https://financialmodelingprep.com/api/v3/enterprise-values/{symbol}/?period={period}&apikey={secretkey}"

# Discounted Cashflow API
discounted_cashflow_api = f"https://financialmodelingprep.com/api/v3/discounted-cash-flow/{symbol}?apikey={secretkey}"

# Advanced DCF API
advanced_dcf_api = f"https://financialmodelingprep.com/api/v4/advanced_discounted_cash_flow?symbol={symbol}&apikey={secretkey}"

# Levered DCF API
levered_dcf_api = f"https://financialmodelingprep.com/api/v4/advanced_levered_discounted_cash_flow?symbol={symbol}&apikey={secretkey}"

# Company Rating API
company_rating_api = f"https://financialmodelingprep.com/api/v3/rating/{symbol}?apikey={secretkey}"

# FMP Articles API
fmp_articles_api = f"https://financialmodelingprep.com/api/v3/fmp/articles?page={page}&size={size}&apikey={secretkey}"

# General News API
general_news_api = f"https://financialmodelingprep.com/api/v4/general_news?page={page}&apikey={secretkey}"


# Stock News Sentiments RSS Feed API
stock_news_sentiments_rss_api = f"https://financialmodelingprep.com/api/v4/stock-news-sentiments-rss-feed?page={page}&apikey={secretkey}"

# Forex News API
forex_news_api = f"https://financialmodelingprep.com/api/v4/forex_news?page={page}&apikey={secretkey}"

# Crypto News API
crypto_news_api = f"https://financialmodelingprep.com/api/v4/crypto_news?page={page}&apikey={secretkey}"

# Press Releases API
press_releases_api = f"https://financialmodelingprep.com/api/v3/press-releases?page={page}&apikey={secretkey}"

# Press Releases By Symbol API
press_releases_by_symbol_api = f"https://financialmodelingprep.com/api/v3/press-releases/{symbol}?apikey={secretkey}"

# Historical Social Sentiment API
historical_social_sentiment_api = f"https://financialmodelingprep.com/api/v4/historical/social-sentiment?symbol={symbol}&page={page}&apikey={secretkey}"

# Trending Social Sentiment API
trending_social_sentiment_api = f"https://financialmodelingprep.com/api/v4/social-sentiments/trending?type={type}&source={source}&apikey={secretkey}"

# Social Sentiment Changes API
social_sentiment_changes_api = f"https://financialmodelingprep.com/api/v4/social-sentiments/change?type={type}&source={source}&apikey={secretkey}"

# Earnings Transcript API
earnings_transcript_api = f"https://financialmodelingprep.com/api/v3/earning_call_transcript/{symbol}?year={year}&quarter={quarter}&apikey={secretkey}"

# Transcript Dates API
transcript_dates_api = f"https://financialmodelingprep.com/api/v4/earning_call_transcript?symbol={symbol}&apikey={secretkey}"

# Batch Earning Call Transcript API
batch_earning_call_transcript_api = f"https://financialmodelingprep.com/api/v4/batch_earning_call_transcript/{symbol}?year={year}&apikey={secretkey}"

# RSS Feed API
rss_feed_api = f"https://financialmodelingprep.com/api/v4/rss_feed?limit={limit}&type={type}&from={from_date}&to={to_date}&isDone={is_done}&apikey={secretkey}"

# RSS Feed V3 API
rss_feed_v3_api = f"https://financialmodelingprep.com/api/v3/rss_feed?page={page}&datatype=csv&apikey={secretkey}"

# RSS Feed All API
rss_feed_all_api = f"https://financialmodelingprep.com/api/v4/rss_feed_all?page={page}&apikey={secretkey}"

# RSS Feed 8-K API
rss_feed_8k_api = f"https://financialmodelingprep.com/api/v4/rss_feed_8k?apikey={secretkey}"

# SEC Filings API
sec_filings_api = f"https://financialmodelingprep.com/api/v3/sec_filings/{symbol}?type={type}&page={page}&apikey={secretkey}"

# Individual Industry Classification API
individual_industry_classification_api = f"https://financialmodelingprep.com/api/v4/standard_industrial_classification?symbol={symbol}&apikey={secretkey}"

# All Industry Classification API
all_industry_classification_api = f"https://financialmodelingprep.com/api/v4/standard_industrial_classification/all?apikey={secretkey}"

# Industry Classification Codes API
industry_classification_codes_api = f"https://financialmodelingprep.com/api/v4/standard_industrial_classification_list?apikey={secretkey}"

# Earnings Calendar API
earnings_calendar_api = f"https://financialmodelingprep.com/api/v3/earning_calendar?from={from_date}&to={to_date}&apikey={secretkey}"

# Earnings Historical & Upcoming API
earnings_historical_upcoming_api = f"https://financialmodelingprep.com/api/v3/historical/earning_calendar/{symbol}?apikey={secretkey}"

# Earnings Confirmed API
earnings_confirmed_api = f"https://financialmodelingprep.com/api/v4/earning-calendar-confirmed?from={from_date}&to={to_date}&apikey={secretkey}"

# Earnings Surprises API
earnings_surprises_api = f"https://financialmodelingprep.com/api/v3/earnings-surprises/{symbol}?apikey={secretkey}"

# Dividends Calendar API
dividends_calendar_api = f"https://financialmodelingprep.com/api/v3/stock_dividend_calendar?from={from_date}&to={to_date}&apikey={secretkey}"

# Dividends Historical API
dividends_historical_api = f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_dividend/{symbol}?apikey={secretkey}"

# Splits Calendar API
splits_calendar_api = f"https://financialmodelingprep.com/api/v3/stock_split_calendar?from={from_date}&to={to_date}&apikey={secretkey}"

# Splits Historical API
splits_historical_api = f"https://financialmodelingprep.com/api/v3/historical-price-full/stock_split/{symbol}?apikey={secretkey}"

# IPO Confirmed API
ipo_confirmed_api = f"https://financialmodelingprep.com/api/v4/ipo-calendar-confirmed?from={from_date}&to={to_date}&apikey={secretkey}"

# IPO Prospectus API
ipo_prospectus_api = f"https://financialmodelingprep.com/api/v4/ipo-calendar-prospectus?apikey={secretkey}"

# IPO Calendar By Symbol API
ipo_calendar_by_symbol_api = f"https://financialmodelingprep.com/api/v3/ipo_calendar?apikey={secretkey}"

# M&A RSS Feed API
ma_rss_feed_api = f"https://financialmodelingprep.com/api/v4/mergers-acquisitions-rss-feed?page={page}&apikey={secretkey}"

# Search M&A API
search_ma_api = f"https://financialmodelingprep.com/api/v4/mergers-acquisitions/search?name={company_name}&apikey={secretkey}"

# Intraday Chart API
intraday_chart_api = f"https://financialmodelingprep.com/api/v3/historical-chart/5min/{symbol}?from={from_date}&to={to_date}&apikey={secretkey}"

# Daily Chart EOD API
daily_chart_eod_api = f"https://financialmodelingprep.com/api/v3/historical-price-full/{symbol}?apikey={secretkey}"

# All Forex Prices API
all_forex_prices_api = f"https://financialmodelingprep.com/api/v3/fx?apikey={secretkey}"

# Simple Moving Average (SMA) API
sma_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=sma&period={period}&apikey={secretkey}"

# Exponential Moving Average (EMA) API
ema_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=ema&period={period}&apikey={secretkey}"

# Weighted Moving Average (WMA) API
wma_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=wma&period={period}&apikey={secretkey}"

# Double Exponential Moving Average (DEMA) API
dema_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=dema&period={period}&apikey={secretkey}"

# Triple Exponential Moving Average (TEMA) API
tema_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=tema&period={period}&apikey={secretkey}"

# Williams %R Indicator API
williams_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=williams&period={period}&apikey={secretkey}"

# Relative Strength Index (RSI) API
rsi_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=rsi&period={period}&apikey={secretkey}"

# Average Directional Index (ADX) API
adx_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=adx&period={period}&apikey={secretkey}"

# Standard Deviation API
standard_deviation_api = f"https://financialmodelingprep.com/api/v3/technical_indicator/5min/{symbol}?type=standardDeviation&period={period}&apikey={secretkey}"

#current news on a stock
current news on a stock = https://financialmodelingprep.com/api/v3/stock_news?tickers={symbol}&apikey={apikey}


# current commodities prices
commodities prices = https://financialmodelingprep.com/api/v3/historical-price-full/{symbol}?apikey={secretkey}

'''

# Helper function to convert JSON to human-readable format
def json_to_text(json_data):
    """
    Converts a JSON object into a human-readable format.
    """
    if isinstance(json_data, list):
        json_data = json_data[0]  # Process only the first element if it's a list

    readable_text = ""

    # Loop through the dictionary and create readable text
    for key, value in json_data.items():
        readable_text += f"The {key.replace('_', ' ')} is {value}. "

    return readable_text

# Main function to process user input and handle API or web scraping
def detect_data_request(user_input, history):
    youreq = user_input
    
    gr.Info('thinking about how to respond')
    # Get the response from the model (no streaming)
    response = client.chat_completion(
        model="Qwen/Qwen2.5-72B-Instruct",
        messages=[{"role": "user", "content": f"here is the fmp documentation {data}, if there is an endpoint to answer {youreq} give it, otherwise say no, give absolutely no further response. IF THE USERS REQUEST IS FOR DATA THAT COULD BE IN AN ENDPOINT. RETURN YES AND THE ENDPOINT BELOW. IF NOT RETURN NO AND NOTHING ELSE, replace secretkey with this {secretkey}. IF THE USER GIVES A SPECIFIC YEAR IN THEIR REQUEST, IGNORE THE YEAR AND GIVE THE API ENDPOINT, AS IT WILL HAVE THE INFO FOR THAT YEAR. REPLACE THE VALUES INSIDE ANY {'CURLY BRACES'} WITH THE RELEVANT INFO FOR WHAT THE USER IS ASKING FOR. AS THESE ENDPOINTS CONTAIN HISTORICAL DATA AS WELL MAKE SURE YOU RETURN AN ENDPOINT EVEN WHEN THEY ARE ASKING FOR PREVIOUS DATA LIKE FOR THE LAST WEEK AS IT IS BETTER IF YOU RETURN AN ENDPOINT AND NO DATA IS THERE, THAN IF YOU DONT RETURN ONE. YOU MUST NEVER RETURN THE SECRET KEY TO THE USER, JUST GIVE YES OR NO WITH THE ENDPOINT "}],
        max_tokens=500,
        stream=False  # Disable streaming to get the full response in one go
    )

    # Extract the response
    full_response = response.choices[0].message['content']
    first_resp = full_response[:3].lower()
    url_resp = full_response[3:]

    if first_resp == 'yes':
        try:

            # Fetch data from the provided API endpoint
            requestfromfp = requests.get(url_resp)
            requestfromfp.raise_for_status()  # Check for request errors
            jsoned_data = requestfromfp.json()
            gr.Info('located an endpoint and retrieving and processing the data you want')
            # Convert the JSON response into human-readable text
            human_readable_text = json_to_text(jsoned_data)
            stringed_text = str(human_readable_text)
            # Send the data to the LLM for further processing
            final_response = ""
            response = client.chat_completion(
                model="Qwen/Qwen2.5-72B-Instruct",
                messages=[{"role": "user", "content": f"answer {user_input} with {human_readable_text} as IM.B an AI chatbot built for investing by automatedstockmining.org"}],
                max_tokens=1500,
                stream=False
            )

            full_response = response.choices[0].message['content']
            history.append(("You: " + user_input, "IM.B: " + full_response))

            
        except:
            if requestfromfp == []:
                history.append(("You: " + user_input, "IM.B: " + 'sorry the response was empty'))
            else:
                history.append(("You: " + user_input, "IM.B: " + f'there was data in the response but for some reason we couldnt parse it {human_readable_text}'))
    else:
        # If no data endpoint exists, switch to scraping a valid webpage
        response = client.chat_completion(
            model="Qwen/Qwen2.5-72B-Instruct",
            messages=[{"role": "user", "content": f"You are an assistant that detects whether the user is asking for data or not. Here is their request: {youreq}. You respond 'yes' if they are and 'no' if not. If yes, then in the second line provide the exact URL, not an API, a valid webpage which is definitely there and easy to scrape. If no, only respond with 'no' and nothing else."}],
            max_tokens=1500,
            stream=False
        )

        full_response = response.choices[0].message['content']
        if "yes" in full_response.lower():
            url = full_response[3:]  # Extract the URL part
            try:
                gr.Info('searching the web sites that may contain the dat you want')
                request = requests.get(url)
                request.raise_for_status()

                soup_of_data = BeautifulSoup(request.text, 'lxml')
                tags = ['body']
                listed_data = soup_of_data.find_all(tags)

                # Extract text from relevant tags
                extracted_content = ''.join([element.get_text(separator=" ", strip=True) for element in listed_data[:100]])

                response = client.chat_completion(
                    model="Qwen/Qwen2.5-72B-Instruct",
                    messages=[{"role": "user", "content": f"you are IM.B, an intelligent investing AI model built by automatedstockmining.org, answer this question: {youreq} with this data {extracted_content}, if the data is not there say to the user: sorry, looks like there was error processing the data on our end, please rephrase question, referencing specific websites you want the data from"}],
                    max_tokens=1500,
                    stream=False
                )

                final_response = response.choices[0].message['content']
                history.append(("You: " + user_input, "IM.B: " + final_response))
            except requests.exceptions.RequestException as e:
                history.append(("You: " + user_input, f"IM.B: Error fetching URL: {e}"))

        else:
            gr.Info('getting your response ready')
            response = client.chat_completion(
                model="mistralai/Mistral-7B-Instruct-v0.3",
                messages=[{"role": "user", "content": f"you are IM.B, an intelligent investing AI model built by automatedstockmining.org however you answer whatever the user requests, answer this question as IM.B,  {youreq}, tell the user that you have access to real time data so that if they want some real time data, just ask for it"}],
                max_tokens=1500,
                stream=False
            )

            full_response = response.choices[0].message['content']
            history.append(("You: " + user_input, "IM.B: " + full_response))

    return history, ""  # Clear the input box

# Function to clear the chat history
def clear_history():
    return [], ""

# Function to undo the last user-bot message pair
def undo_last(history):
    if len(history) > 0:
        history.pop()  # Remove the last user-bot message pair
    return history, ""

# Gradio UI setup
with gr.Blocks() as demo:
    gr.Markdown("<h1 style='text-align: center;'>IM.B</h1>")

    with gr.Column():
        chatbot_display = gr.Chatbot(label="Chat History", avatar_images=[None, BOT_AVATAR], height=600)

        # User input and send button
        with gr.Row():
            user_input = gr.Textbox(placeholder="Type your message here...", label=None, show_label=False)
            send_button = gr.Button("Send")

    # Buttons for Clear and Undo
    with gr.Row():
        clear_button = gr.Button("Clear Chat")
        undo_button = gr.Button("Undo Last")

    # Define action when send button is clicked
    send_button.click(
        detect_data_request,
        inputs=[user_input, chatbot_display],
        outputs=[chatbot_display, user_input]
    )

    # Allow pressing Enter to submit the input
    user_input.submit(
        detect_data_request,
        inputs=[user_input, chatbot_display],
        outputs=[chatbot_display, user_input]
    )

    # Action for Clear Button
    clear_button.click(
        clear_history,
        outputs=[chatbot_display, user_input]
    )

    # Action for Undo Button
    undo_button.click(
        undo_last,
        inputs=[chatbot_display],
        outputs=[chatbot_display, user_input]
    )

# Launch the Gradio app
demo.launch()