Update interface - three columns (and force recent

app.py

@@ -242,26 +242,82 @@ model_choices = [
     "mistralai/Mistral-Small-3.1-24B-Instruct-2503"
 ]
 
-with gr.Blocks() as demo:
-    gr.Markdown("## Clinical Chatbot (Streaming)")
+# Example patient database
+patient_db = {
+    "001 - John Doe": {
+        "name": "John Doe",
+        "age": "45",
+        "id": "001",
+        "notes": "History of chest pain and hypertension. No prior surgeries."
+    },
+    "002 - Maria Sanchez": {
+        "name": "Maria Sanchez",
+        "age": "62",
+        "id": "002",
+        "notes": "Suspected pulmonary embolism. Shortness of breath, tachycardia."
+    },
+    "003 - Ahmed Al-Farsi": {
+        "name": "Ahmed Al-Farsi",
+        "age": "29",
+        "id": "003",
+        "notes": "Persistent migraines. MRI scheduled for brain imaging."
+    },
+    "004 - Lin Wei": {
+        "name": "Lin Wei",
+        "age": "51",
+        "id": "004",
+        "notes": "Annual screening. Family history of breast cancer."
+    }
+}
+
+def autofill_patient(patient_key):
+    if patient_key in patient_db:
+        info = patient_db[patient_key]
+        return info["name"], info["age"], info["id"], info["notes"]
+    return "", "", "", ""
+
+with gr.Blocks(css=".gradio-container {height: 100vh; overflow: hidden;}") as demo:
+    gr.Markdown("## Radiologist's Companion")
 
     default_model = gr.State(model_choices[0])
 
-    with gr.Row():
-        mode = gr.Radio(["Choose from list", "Enter custom model"], value="Choose from list", label="Model Input Mode")
-        model_selector = gr.Dropdown(choices=model_choices, label="Select Predefined Model")
-        model_textbox = gr.Textbox(label="Or Enter HF Model Name")
-
-    model_status = gr.Textbox(label="Model Status", interactive=False)
-    chatbot = gr.Chatbot(label="Chat", type="messages")
-    msg = gr.Textbox(label="Your message", placeholder="Enter clinical input...", show_label=False)
-    with gr.Row():
-        submit_btn = gr.Button("Submit", variant="primary")
-        clear_btn = gr.Button("Clear", variant="secondary")
-        
+    with gr.Row(equal_height=True):  # <-- make columns same height
+        with gr.Column(scale=1):
+            gr.Markdown("### Patient Information")
+            patient_selector = gr.Dropdown(
+                choices=list(patient_db.keys()), label="Select Patient", allow_custom_value=False
+            )
+            patient_name = gr.Textbox(label="Name", placeholder="e.g., John Doe")
+            patient_age = gr.Textbox(label="Age", placeholder="e.g., 45")
+            patient_id = gr.Textbox(label="Patient ID", placeholder="e.g., 123456")
+            patient_notes = gr.Textbox(label="Clinical Notes", lines=10, placeholder="e.g., History of chest pain...")
+
+        with gr.Column(scale=2):
+            gr.Markdown("### Chat")
+            chatbot = gr.Chatbot(label="Chat", type="messages", height=500)  # <-- fixed height
+            msg = gr.Textbox(label="Your message", placeholder="Enter your chat message...", show_label=False)
+            with gr.Row():
+                submit_btn = gr.Button("Submit", variant="primary")
+                clear_btn = gr.Button("Clear", variant="secondary")
+
+        with gr.Column(scale=1):
+            gr.Markdown("### Model Settings")
+            mode = gr.Radio(["Choose from list", "Enter custom model"], value="Choose from list", label="Model Input Mode")
+            model_selector = gr.Dropdown(choices=model_choices, label="Select Predefined Model")
+            model_textbox = gr.Textbox(label="Or Enter HF Model Name")
+            model_status = gr.Textbox(label="Model Status", interactive=False)
+
+    # Functions for resolving model choice
     def resolve_model_choice(mode, dropdown_value, textbox_value):
         return textbox_value.strip() if mode == "Enter custom model" else dropdown_value
 
+    # Link patient selector
+    patient_selector.change(
+        autofill_patient,
+        inputs=[patient_selector],
+        outputs=[patient_name, patient_age, patient_id, patient_notes]
+    )
+
     # Load on launch
     demo.load(fn=load_model_on_selection, inputs=default_model, outputs=model_status)
 
@@ -286,6 +342,4 @@ with gr.Blocks() as demo:
 
     clear_btn.click(lambda: [], None, chatbot, queue=False)
 
-
-
 demo.launch()

requirements.txt

@@ -1,4 +1,4 @@
-transformers
+transformers>=4.40.0
 accelerate
 torch
 gradio