app.py

from typing import final
import gradio as gr
import os
import json
from bs4 import BeautifulSoup
import requests
from huggingface_hub import InferenceClient
from datetime import datetime, timedelta
import json


# Define global variables
BOT_AVATAR = 'https://automatedstockmining.org/wp-content/uploads/2024/08/south-west-value-mining-logo.webp'
client = InferenceClient(token=os.getenv("HF_TOKEN"))
custom_css = '''
.gradio-container {
    font-family: 'Roboto', sans-serif;
}

.main-header {
    text-align: center;
    color: #4a4a4a;
    margin-bottom: 2rem;
}

.tab-header {
    font-size: 1.2rem;
    font-weight: bold;
    margin-bottom: 1rem;
}

.custom-chatbot {
    border-radius: 10px;
    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
}

.custom-button {
    background-color: #3498db;
    color: white;
    border: none;
    padding: 10px 20px;
    border-radius: 5px;
    cursor: pointer;
    transition: background-color 0.3s ease;
}

.custom-button:hover {
    background-color: #2980b9;
}
'''


def extract_text_from_webpage(html):
    soup = BeautifulSoup(html, "html.parser")
    # Extract visible text, removing unnecessary elements (e.g., scripts, styles)
    for script in soup(["script", "style"]):
        script.decompose()
    visible_text = soup.get_text(separator=" ", strip=True)
    return visible_text

def search(query):
    term = query
    max_chars_per_page = 8000
    all_results = []

    with requests.Session() as session:
        try:
            # Send a search request to Google
            resp = session.get(
                url="https://www.google.com/search",
                headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"},
                params={"q": term, "num": 4},
                timeout=5
            )
            resp.raise_for_status()  # Ensure the request was successful

            soup = BeautifulSoup(resp.text, "html.parser")
            result_block = soup.find_all("div", attrs={"class": "g"})

            for result in result_block:
                link = result.find("a", href=True)
                if link:
                    link = link["href"]
                    try:
                        # Fetch the webpage at the found link
                        webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0"}, timeout=5)
                        webpage.raise_for_status()

                        # Extract visible text from the webpage
                        visible_text = extract_text_from_webpage(webpage.text)
                        if len(visible_text) > max_chars_per_page:
                            visible_text = visible_text[:max_chars_per_page]

                        all_results.append({"link": link, "text": visible_text})

                    except requests.exceptions.RequestException as e:
                        print(f"Failed to retrieve {link}: {e}")
                        all_results.append({"link": link, "text": None})
        except requests.exceptions.RequestException as e:
            print(f"Google search failed: {e}")

    return all_results
def process_query(user_input, history):
  if len(history) > 0 and history[-1]['role'] == 'user' and history[-1]['content'].lower() == user_input.lower():
        gr.Info('Searching the web for the latest data...', duration=4)
  else:
      # Append new user message to the history
      history.append({"role": "user", "content": user_input})

  search_results = search(user_input)
  search_results_str = json.dumps(search_results)
  response = client.chat_completion(
              model="Qwen/Qwen2.5-72B-Instruct",
              messages=[{"role": "user", "content": f"YOU ARE IM.X, AN INVESTMENT CHATBOT BUILT BY automatedstockmining.org. Answer the user's request '{user_input}' using the following information: {search_results_str} and the chat history{history}. Provide a concise, direct answer in no more than 2-3 sentences. use the appropriate emojis for some of your responses"}],
              max_tokens=400,
              stream=False
          )
  final_response = response.choices[0].message['content']
  history.append({"role": "assistant", "content": final_response})

  return history, ""  # Clear the input box after sending the response


def clear_history():
    return [], ""  # Return empty history and clear the input box

# Function to undo the last user-bot message pair
def undo_last(history):
    if len(history) >= 2:  # Ensure that there's at least one user-bot message pair
        history.pop()  # Remove the bot's response
        history.pop()  # Remove the user's input
    return history, ""  # Return updated history and clear the input box

# Gradio UI setup


theme = gr.themes.Citrus(
    primary_hue="blue",
    neutral_hue="slate",
)


with gr.Blocks(theme = theme,css = custom_css) as demo:
    gr.Markdown("<h1 style='text-align: center;'>IM.B - Intelligent Investing with automatedstockmining.org</h1>")

    with gr.Column():
        chatbot_display = gr.Chatbot(label="IM.B chat", avatar_images=[None, BOT_AVATAR], height=600, type="messages", layout="panel")

        # 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")

        example_inputs = [
            ["What's the current price of bitcoin"],
            ["What's the latest news on Cisco Systems stock"],
            ["Analyze technical indicators for Adobe, are they presenting buy or sell signals"],
            ["What's the current price of Apple stock"],
            ["What are the best stocks to buy this month"],
            ['what companies report earnings this week'],
            ["whats apple's current market cap"]
        ]

        # Add examples to the UI
        gr.Examples(examples=example_inputs, inputs=user_input)

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

    # History is now handled as part of the chatbot_display
    send_button.click(process_query, inputs=[user_input, chatbot_display], outputs=[chatbot_display, user_input])

    # Allow pressing Enter to submit the input
    user_input.submit(process_query, 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()