Update app.py

app.py

@@ -4,7 +4,10 @@ from openai import OpenAI
 
 # ----------------------- CONSTANTS ----------------------- #
 SYSTEM_PROMPT = """
-Given the research context, design an ablation study for the specified module or process.\nBegin the design with a clear statement of the research objective, followed by a detailed description of the experiment setup.\nDo not include the discussion of results or conclusions in the response, as the focus is solely on the experimental design.\nThe response should be within 300 words. Present the response in **Markdown** format (use headings, bold text, and bullet or numbered lists where appropriate).
+Given the research context, design an ablation study for the specified module or process.
+Begin the design with a clear statement of the research objective, followed by a detailed description of the experiment setup.
+Do not include the discussion of results or conclusions in the response, as the focus is solely on the experimental design.
+The response should be within 300 words. Present the response in **Markdown** format (use headings, bold text, and bullet or numbered lists where appropriate).
 """.strip()
 
 # ----------------------- HELPERS ------------------------- #
@@ -41,12 +44,12 @@ def generate_ablation_design(
     module_name,
     api_key,
 ):
-    """Combine inputs ➜ call OpenAI ➜ return the ablation-study design text (Markdown)."""
-    # 1 ) validate the API key
+    """Combine inputs ➜ call OpenAI ➜ return the ablation‑study design text (Markdown)."""
+    # 1) Validate the API key format.
     if not api_key or not api_key.startswith("sk-"):
         return "❌ **Please enter a valid OpenAI API key in the textbox above.**"
 
-    # 2 ) build the chat conversation
+    # 2) Build the chat conversation payload.
     messages = [
         {"role": "system", "content": SYSTEM_PROMPT},
         {
@@ -61,7 +64,7 @@ def generate_ablation_design(
         },
     ]
 
-    # 3 ) call the model
+    # 3) Call the model and return the assistant response.
     client = OpenAI(api_key=api_key)
     try:
         response = client.chat.completions.create(
@@ -76,41 +79,48 @@ def generate_ablation_design(
 
 # ----------------------- UI LAYOUT ----------------------- #
 with gr.Blocks(title="Ablation Study Designer") as demo:
-    gr.Markdown(
-        """
-        # 🧪 Ablation Study Designer  \n
-        Supply your study details below, then click **Generate** to receive a tailored ablation-study design rendered in Markdown.
-        """
-    )
+    # Main two‑column layout.
+    with gr.Row():
+        # ---------- LEFT COLUMN: INPUTS ----------
+        with gr.Column(scale=1):
+            gr.Markdown(
+                """
+                # 🧪 Ablation Study Designer  
+                Fill in the study details below, then click **Generate** to receive a tailored ablation‑study design rendered in Markdown.
+                """,
+                elem_id="header",
+            )
 
-    # API-key field (required)
-    api_key = gr.Textbox(
-        label="🔑 OpenAI API Key (required)",
-        type="password",
-        placeholder="sk-...",
-    )
+            # API‑key field (required)
+            api_key = gr.Textbox(
+                label="🔑 OpenAI API Key (required)",
+                type="password",
+                placeholder="sk-...",
+            )
 
-    research_background = gr.Textbox(
-        label="Research Background", lines=6, placeholder="Describe the broader research context…"
-    )
-    method = gr.Textbox(
-        label="Method Description", lines=6, placeholder="Summarize the method section…"
-    )
-    experiment_setup = gr.Textbox(
-        label="Main Experiment – Setup", lines=6, placeholder="Datasets, hyper-parameters, etc."
-    )
-    experiment_results = gr.Textbox(
-        label="Main Experiment – Results", lines=6, placeholder="Key quantitative or qualitative findings…"
-    )
-    module_name = gr.Textbox(
-        label="Module / Process for Ablation", placeholder="e.g., Attention mechanism"
-    )
+            research_background = gr.Textbox(
+                label="Research Background", lines=6, placeholder="Describe the broader research context…"
+            )
+            method = gr.Textbox(
+                label="Method Description", lines=6, placeholder="Summarize the method section…"
+            )
+            experiment_setup = gr.Textbox(
+                label="Main Experiment – Setup", lines=6, placeholder="Datasets, hyper‑parameters, etc."
+            )
+            experiment_results = gr.Textbox(
+                label="Main Experiment – Results", lines=6, placeholder="Key quantitative or qualitative findings…"
+            )
+            module_name = gr.Textbox(
+                label="Module / Process for Ablation", placeholder="e.g., Attention mechanism"
+            )
 
-    generate_btn = gr.Button("Generate Ablation Study Design")
+            generate_btn = gr.Button("Generate Ablation Study Design")
 
-    # Markdown output area — dynamic, renders Markdown
-    output_md = gr.Markdown(value="", label="Ablation Study Design")
+        # ---------- RIGHT COLUMN: OUTPUT ----------
+        with gr.Column(scale=1):
+            output_md = gr.Markdown(value="", label="Ablation Study Design")
 
+    # Button click: trigger generation with a loading indicator.
     generate_btn.click(
         fn=generate_ablation_design,
         inputs=[
@@ -122,8 +132,9 @@ with gr.Blocks(title="Ablation Study Designer") as demo:
             api_key,
         ],
         outputs=output_md,
+        show_progress="full",  # Display a full‑screen progress bar.
     )
 
 # ----------------------- LAUNCH -------------------------- #
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()