Add application file

app.py

@@ -0,0 +1,44 @@
+# -*- coding: utf-8 -*-
+"""NLP - GRADIO.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1mrV6DhKMqFwtVE1E89DygsKexajnb60N
+"""
+
+import gradio as gr
+import torch
+from transformers import pipeline
+
+def generate_chat_response(query):
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    pipe = pipeline("text-generation", model="TinyLlama/TinyLlama-1.1B-Chat-v1.0", torch_dtype=torch.bfloat16, device=device)
+
+    # Define system message to indicate context
+    system_message = "You are a medical chatbot who is answering questions about cancer. Please be considerate."
+
+    # Convert query to Gradio input format
+    gradio_input = [{"role": "system", "content": system_message}, {"role": "user", "content": query}]
+
+    # Apply chat template
+    prompt = pipe.tokenizer.apply_chat_template(gradio_input, add_special_tokens=False, tokenize=False, add_prefix_space=True, add_generation_prompt=True)
+
+    # Generate response
+    outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+
+    # Extract generated text
+    generated_responses = [output["generated_text"] for output in outputs]
+    return generated_responses
+
+# Define Gradio interface
+demo = gr.Interface(
+    fn=generate_chat_response,
+    inputs="text",
+    outputs="text",
+    title="Medical Chatbot",
+    description="Enter your question about cancer to interact with the medical chatbot."
+)
+
+# Launch Gradio interface
+demo.launch()