app and requirements files added

app.py

@@ -1,7 +1,60 @@
 import gradio as gr
+from transformers import AutoModelWithLMHead, AutoTokenizer
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel, DataCollatorForLanguageModeling
 
-def greet(name):
-    return "Hello " + name + "!!"
+#def greet(name):
+#    return "Hello " + name + "!!"
+username = "chsubhasis"
+my_repo = "Medical-QnA-gpt2"
+my_checkpoint = username + '/' + my_repo
+loaded_model = AutoModelWithLMHead.from_pretrained(my_checkpoint)
+loaded_tokenizer = AutoTokenizer.from_pretrained(my_checkpoint)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+
+def generate_response(model, tokenizer, prompt, max_length=200):
+
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Check the device of the model
+    device = next(model.parameters()).device
+
+    # Move input_ids to the same device as the model
+    input_ids = input_ids.to(device)
+
+    # Create the attention mask and pad token id
+    attention_mask = torch.ones_like(input_ids)
+    pad_token_id = tokenizer.eos_token_id
+
+    output = model.generate(
+        input_ids,
+        max_length=max_length,
+        num_return_sequences=1,
+        attention_mask=attention_mask,
+        pad_token_id=pad_token_id
+    )
+
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+def generate_query_response(prompt, max_length=200):
+
+    model = loaded_model
+    tokenizer = loaded_tokenizer
+
+    return generate_response(model, tokenizer, prompt, max_length)
+
+#demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+#demo.launch()
+
+iface = gr.Interface(
+    fn=generate_query_response,
+    inputs=[
+        gr.Textbox(lines=2, placeholder="Enter your medical query here..."),
+        gr.Slider(minimum=50, maximum=500, value=200, label="Maximum Length")
+    ],
+    outputs="text",
+    title="Medical Question Answering Bot",
+    description="Ask your medical questions to get relevant answers."
+)
+
+iface.launch(share=True)

requirements.txt

@@ -1,3 +1,5 @@
 # Dependencies for application are to be added to this file
 
-numpy
+numpy
+gradio
+tensorflow