Update app3.py

app3.py

@@ -147,6 +147,24 @@ Return only the revised labels, one per line.
 
     return "Labels refined!", csv_str, df.head(10).to_markdown(index=False)
 
+import gradio as gr
+import pandas as pd
+
+# === Placeholder Functions (replace with actual logic) ===
+def run_initial_analysis(file, context, n_clusters):
+    try:
+        df = pd.read_csv(file.name, encoding='latin1')
+        preview = df.head(10).to_csv(index=False)
+        # Dummy status and download file path (replace with real logic)
+        status = f"Successfully processed {len(df)} rows into {n_clusters} topics."
+        return status, file, preview
+    except Exception as e:
+        return f"Error during initial analysis: {e}", None, ""
+
+def refine_labels(feedback):
+    # Dummy response (replace with real logic)
+    return f"Refined using feedback: {feedback}", None, ""
+
 # === GRADIO UI ===
 with gr.Blocks(title="Falcon Topic Modeling") as demo:
     gr.Markdown("# 🎯 Falcon-Powered Topic Modeling")
@@ -154,9 +172,9 @@ with gr.Blocks(title="Falcon Topic Modeling") as demo:
 
     with gr.Row():
         with gr.Column():
-            upload = gr.File(label="Upload CSV ('text' column)")
+            upload = gr.File(label="Upload CSV ('text' column)", file_types=[".csv"])
             context = gr.Textbox(label="Context/Instruction", lines=5, value="Group these into common themes.")
-            cluster_slider = gr.Slider(2, 20, value=10, label="Number of Topics")
+            cluster_slider = gr.Slider(2, 20, value=10, step=1, label="Number of Topics")
             run_btn = gr.Button("Run Initial Analysis")
 
         with gr.Column():
@@ -171,4 +189,4 @@ with gr.Blocks(title="Falcon Topic Modeling") as demo:
     refine_btn.click(fn=refine_labels, inputs=[feedback], outputs=[status, download, preview])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()