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app.py

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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="📈 Ask a Stock Market Question", placeholder="Enter your query about the stock market...", lines=3),
+    outputs=gr.Textbox(label="💡 Expert Answer", interactive=True),
+    title="📊 AI-Powered Stock Market Q&A Chatbot",
+    description="🤖 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()

requirements.txt

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+torch
+transformers
+gradio
+sentencepiece