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import gradio as gr
from transformers import pipeline
def stockmarket_qa(question):
model_name = "AventIQ-AI/t5-stockmarket-qa-chatbot"
print("Loading model...")
generator = pipeline("text2text-generation", model=model_name, device=0) # Use GPU if available
# Correcting the input format based on the model's README
instruction = "question: " # If required by the model
input_text = f"{instruction}{question}"
print(f"Processing input: {input_text}")
response = generator(input_text, max_new_tokens=200)[0]['generated_text']
print(f"Response: {response}")
return response
iface = gr.Interface(
fn=stockmarket_qa,
inputs=gr.Textbox(label="πŸ“ˆ Ask a Stock Market Question", placeholder="Enter your query about the stock market...", lines=3),
outputs=gr.Textbox(label="πŸ’‘ Expert Answer", interactive=True),
title="πŸ“Š AI-Powered Stock Market Q&A Chatbot",
description="πŸ€– Enter a stock market-related question, and the AI chatbot will generate a detailed response based on financial knowledge.",
theme="compact",
allow_flagging="never",
examples=[
["What are the best stocks to invest in right now?"],
["How does inflation affect stock prices?"],
["What is technical analysis in stock trading?"],
["Explain the difference between a bull and bear market."],
["How do interest rates impact the stock market?"]
],
)
if __name__ == "__main__":
iface.launch()