Update app.py

app.py

@@ -1,10 +1,9 @@
+import spaces
 import gradio as gr
 from transformers import pipeline, TextIteratorStreamer
 import torch
 import threading
-import spaces
 
-# --- Model and Tokenizer Setup ---
 # Load model and tokenizer
 model_name = "krish10/Qwen3_0.6B_16bit_TA_screen"
 pipe = pipeline("text-generation", model=model_name, device=0)
@@ -16,12 +15,11 @@ MAX_TOKENS = 3000
 TEMPERATURE = 0.1
 TOP_P = 0.9
 
-# --- Backend Function ---
 @spaces.GPU
 def respond_stream(population, intervention, comparison, outcome, study_design, summary, title, abstract):
     # Validate required fields
     if not title.strip() or not abstract.strip():
-        return "❌ **Error:** Title and Abstract are required fields."
+        return "❌ Error: Title and Abstract are required."
 
     criteria_parts = []
     if population.strip():
@@ -35,9 +33,8 @@ def respond_stream(population, intervention, comparison, outcome, study_design,
     if study_design.strip():
         criteria_parts.append(f"Study design of interest = {study_design.strip()}")
 
-    # Ensure at least one PICOS criteria is provided if no summary exists
-    if not criteria_parts and not summary.strip():
-        return "❌ **Error:** You must fill out at least one of the five PICOS criteria or provide a PICO Summary."
+    if not criteria_parts:
+        return "❌ Error: At least one of the five PICOS criteria must be filled."
 
     # Build instruction section
     instruction = "Instruction: " + "\n".join(criteria_parts)
@@ -74,62 +71,31 @@ def respond_stream(population, intervention, comparison, outcome, study_design,
         partial_text += token
         yield partial_text
 
-# --- Modernized Gradio UI ---
-with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky")) as demo:
-    gr.Markdown("# 🤖 Qwen Streaming Chat: Structured Medical Abstract Evaluation")
-    gr.Markdown("Provide a study's title and abstract, and optionally add PICOS criteria to guide the model's analysis.")
-
-    with gr.Row(equal_height=False):
-        # Left Column: Main inputs (Title and Abstract)
-        with gr.Column(scale=2):
-            title = gr.Textbox(
-                label="Study Title",
-                lines=2,
-                placeholder="Enter the title of the medical study here...",
-                info="This field is required."
-            )
-            abstract = gr.Textbox(
-                label="Study Abstract",
-                lines=10,
-                placeholder="Paste the full abstract here...",
-                info="This field is required."
-            )
-
-        # Right Column: Optional PICOS criteria
-        with gr.Column(scale=1):
-            with gr.Accordion("Define PICOS Criteria (Optional)", open=False):
-                population = gr.Textbox(label="Population", info="e.g., 'patients with type 2 diabetes'")
-                intervention = gr.Textbox(label="Intervention", info="e.g., 'metformin'")
-                comparison = gr.Textbox(label="Comparison", info="e.g., 'placebo'")
-                outcome = gr.Textbox(label="Outcome", info="e.g., 'HbA1c levels'")
-                study_design = gr.Textbox(label="Study Design", info="e.g., 'randomized controlled trial'")
-            
-            summary = gr.Textbox(
-                label="PICO Summary (Optional)",
-                lines=4,
-                placeholder="Alternatively, describe the PICOS criteria in a short paragraph.",
-            )
-
-    # Output and Action Buttons
-    output_box = gr.Markdown(label="Model Response") # CORRECTED LINE
-
-    with gr.Row():
-        clear_btn = gr.Button("Clear")
-        generate_btn = gr.Button("Generate", variant="primary")
-
-    # --- Button Click Handlers ---
-    all_inputs = [population, intervention, comparison, outcome, study_design, summary, title, abstract]
+# Build Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 🤖 Qwen Streaming Chat — Structured Medical Abstract Evaluation")
+
+    with gr.Column():
+        population = gr.Textbox(label="Population of interest", lines=1)
+        intervention = gr.Textbox(label="Intervention/exposure of interest", lines=1)
+        comparison = gr.Textbox(label="Comparison of interest", lines=1)
+        outcome = gr.Textbox(label="Outcome of interest", lines=1)
+        study_design = gr.Textbox(label="Study design of interest", lines=1)
+
+    with gr.Column():
+        summary = gr.Textbox(label="PICOS Summary (optional)", lines=4)
+        title = gr.Textbox(label="Title", lines=2, placeholder="Required")
+        abstract = gr.Textbox(label="Abstract", lines=10, placeholder="Required")
+
+    output_box = gr.Textbox(label="Model Response", lines=15, interactive=False)
+    generate_btn = gr.Button("Generate")
 
     generate_btn.click(
         fn=respond_stream,
-        inputs=all_inputs,
+        inputs=[population, intervention, comparison, outcome, study_design, summary, title, abstract],
         outputs=[output_box]
     )
-    
-    # The clear button resets all input fields and the output box
-    clear_btn.click(lambda: (None, None, None, None, None, None, None, None, None), outputs=all_inputs + [output_box])
-
 
-# --- Launch the App ---
+# Launch the app
 if __name__ == "__main__":
     demo.launch()