Update app.py

app.py

@@ -7,25 +7,34 @@ import umap
 
 model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
 
+default_problems = """
+I manually rename files every week
+I convert PDFs to Excel
+I copy data between spreadsheets
+I send weekly reports manually
+I merge CSV files daily
+I manually download invoices
+I extract tables from PDFs
+I clean messy Excel sheets
+I manually schedule social posts
+I track expenses in spreadsheets
+"""
+
 def analyze_problems(text):
 
     problems = [p.strip() for p in text.split("\n") if p.strip()]
 
     embeddings = model.encode(problems)
 
-    # clustering
     k = min(5, len(problems))
     kmeans = KMeans(n_clusters=k, random_state=0).fit(embeddings)
 
-    clusters = kmeans.labels_
-
-    # dimensionality reduction for visualization
     reducer = umap.UMAP()
     coords = reducer.fit_transform(embeddings)
 
     df = pd.DataFrame({
         "problem": problems,
-        "cluster": clusters,
+        "cluster": kmeans.labels_,
         "x": coords[:,0],
         "y": coords[:,1]
     })
@@ -41,28 +50,24 @@ def analyze_problems(text):
 
     cluster_summary = df.groupby("cluster")["problem"].apply(list).to_dict()
 
-    summary_text = ""
+    summary = ""
 
     for c, items in cluster_summary.items():
-        summary_text += f"\nCluster {c}\n"
+        summary += f"\nCluster {c}\n"
         for i in items:
-            summary_text += f"- {i}\n"
-
-    return summary_text, fig
+            summary += f"- {i}\n"
 
+    return summary, fig
 
-with open("sample_problems.txt") as f:
-    default_text = f.read()
 
 demo = gr.Interface(
     fn=analyze_problems,
-    inputs=gr.Textbox(value=default_text, lines=15, label="Problem Signals"),
+    inputs=gr.Textbox(value=default_problems, lines=15, label="Problem Signals"),
     outputs=[
         gr.Textbox(label="Problem Clusters"),
         gr.Plot(label="Problem Market Map")
     ],
     title="Problem Discovery Engine Demo",
-    description="Detect clusters of real-world problems and visualize a Problem Market Map."
 )
 
 demo.launch()