Update app.py

app.py

@@ -10,41 +10,49 @@ base_model = AutoModelForCausalLM.from_pretrained("BeastGokul/Bio-Mistral-7B-fin
 base_model.resize_token_embeddings(len(tokenizer))
 model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3")
 
-def get_model_response(user_query):
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Set up Hugging Face client
+client = InferenceClient(api_key="YOUR_HF_API_KEY")
+
+def get_response(user_query):
+    # Define the request message with a biomedical role
     messages = [
         {
             "role": "user",
             "content": user_query
         }
-        {
-            "role": "biomedical assistant",
-            "content": ""
-        }
     ]
     
-    
+    # Make a call to the model
     response = client.chat_completions.create(
-        model=model,
+        model="mistralai/Mistral-7B-Instruct-v0.3",
         messages=messages,
         max_tokens=500
     )
-    
-    # Extract and return the response content
-    return response.choices[0].message['content']
 
+    # Collect and return the output
+    reply = "".join(chunk.choices[0].delta.content for chunk in response)
+    return reply
+
+# Define the UI with examples
+example_queries = [
+    "What are the symptoms of anemia?",
+    "Explain the genetic basis of cystic fibrosis.",
+    "What are the latest treatments for Alzheimer's disease?",
+    "How does insulin affect blood sugar levels?",
+    "Can you summarize recent advances in cancer immunotherapy?"
+]
+
+# Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Biomedical Query Chatbot")
-    with gr.Row():
-        user_input = gr.Textbox(
-            placeholder="Enter your biomedical query...",
-            label="Your Query",
-            lines=1
-        )
-        submit_button = gr.Button("Submit")
-        
-    output = gr.Textbox(label="Response from Biomedical Assistant")
-
-    submit_button.click(get_model_response, inputs=user_input, outputs=output)
-
-# Launch the app
+    gr.Markdown("# Biomedical Assistant")
+    user_input = gr.Textbox(placeholder="Enter your biomedical query...", label="Your Query")
+    output_text = gr.Textbox(label="Response")
+    example = gr.Examples(examples=example_queries, inputs=user_input)
+    
+    submit_btn = gr.Button("Get Response")
+    submit_btn.click(fn=get_response, inputs=user_input, outputs=output_text)
+
 demo.launch()