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  1. app.py +31 -0
  2. requirements.txt +4 -0
app.py ADDED
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+ import gradio as gr
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+ from transformers import pipeline
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+
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+ def medical_chatbot(question):
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+ model_name = "AventIQ-AI/t5-medical-chatbot"
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+ generator = pipeline("text2text-generation", model=model_name)
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+
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+ instruction = "As a medical expert, provide a detailed and accurate diagnosis based on the patient's symptoms."
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+ input_text = f"{instruction} {question}"
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+
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+ response = generator(input_text, max_length=256)[0]['generated_text']
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+
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+ return response
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+
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+ iface = gr.Interface(
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+ fn=medical_chatbot,
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+ inputs=gr.Textbox(label="🩺 Ask a Medical Question", placeholder="Describe your symptoms or ask a medical query...", lines=3),
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+ outputs=gr.Textbox(label="💡 Expert Diagnosis", interactive=True),
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+ title="🔬 AI-Powered Medical Chatbot",
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+ description="🤖 Enter a medical question, and the chatbot will generate a detailed response based on expert knowledge.",
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+ theme="compact",
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+ allow_flagging="never",
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+ examples=[
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+ ["I have a fever and sore throat. What could it be?"],
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+ ["What are the symptoms of diabetes?"],
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+ ["How can I manage high blood pressure naturally?"]
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+ ],
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+ )
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+
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+ if __name__ == "__main__":
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+ iface.launch()
requirements.txt ADDED
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+ torch
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+ transformers
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+ gradio
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+ sentencepiece