Update app.py

app.py

@@ -6,7 +6,7 @@ import gradio as gr
 from tools.sql_tool import SQLTool
 from tools.ts_preprocess import build_timeseries
 
-# Ensure DB path & defaults (you can set these in Space Settings → Variables)
+# --- Environment & defaults ---
 DUCKDB_PATH = os.getenv("DUCKDB_PATH", "alm.duckdb")
 DEFAULT_SCHEMA = os.getenv("SQL_DEFAULT_SCHEMA", "main")
 DEFAULT_TABLE  = os.getenv("SQL_DEFAULT_TABLE",  "masterdataset_v")
@@ -14,36 +14,43 @@ DEFAULT_TABLE  = os.getenv("SQL_DEFAULT_TABLE",  "masterdataset_v")
 sql_tool = SQLTool(DUCKDB_PATH)
 
 INTRO = f"""
-### ALM LLM — Demo  
+### ALM LLM — Demo
+
 Connected to **DuckDB** at `{DUCKDB_PATH}` using table **{DEFAULT_SCHEMA}.{DEFAULT_TABLE}**.
 
-**Try:**  
-- *"show me the top 10 fds by portfolio value"*  
-- *"top 10 assets by portfolio value"*  
-- *"sum portfolio value by currency"*  
+**Try:**
+- *"show me the top 10 fds by portfolio value"*
+- *"top 10 assets by portfolio value"*
+- *"sum portfolio value by currency"*
 """
 
+# --- Handlers ---
 def run_nl(nl_query: str):
     if not nl_query or not nl_query.strip():
-        return pd.DataFrame(), "", "Please enter a query.", pd.DataFrame(), pd.DataFrame()
-
+        return (
+            pd.DataFrame(),
+            "",
+            "Please enter a query.",
+            pd.DataFrame(),
+            pd.DataFrame(),
+        )
     try:
         df, sql, why = sql_tool.query_from_nl(nl_query)
     except Exception as e:
         return pd.DataFrame(), "", f"Error: {e}", pd.DataFrame(), pd.DataFrame()
 
-    # Try to build timeseries cashflows + gap if columns match masterdataset_v
+    # Try building projections and liquidity gap
     try:
         cf, gap = build_timeseries(df)
-    except Exception as e:
+    except Exception:
         cf, gap = pd.DataFrame(), pd.DataFrame()
 
     return df, sql.strip(), why, cf, gap
 
+
 def run_sql(sql_text: str):
     if not sql_text or not sql_text.strip():
         return pd.DataFrame(), "Please paste a SQL statement.", pd.DataFrame(), pd.DataFrame()
-
     try:
         df = sql_tool.run_sql(sql_text)
     except Exception as e:
@@ -53,29 +60,52 @@ def run_sql(sql_text: str):
         cf, gap = build_timeseries(df)
     except Exception:
         cf, gap = pd.DataFrame(), pd.DataFrame()
+
     return df, "OK", cf, gap
 
-with gr.Tab("Ask in Natural Language"):
-    nl = gr.Textbox(label="Ask a question", placeholder="e.g., show me the top 10 fds by portfolio value")
-    btn = gr.Button("Run")
-    sql_out = gr.Textbox(label="Generated SQL", interactive=False)
-    why_out = gr.Textbox(label="Reasoning", interactive=False)
-    df_out  = gr.Dataframe(label="Query Result", interactive=True)
-    cf_out  = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True)
-    gap_out = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True)
 
-    btn.click(fn=run_nl, inputs=[nl], outputs=[df_out, sql_out, why_out, cf_out, gap_out])
+# --- UI ---
+with gr.Blocks(title="ALM LLM") as demo:
+    gr.Markdown(INTRO)
+
+    with gr.Tab("Ask in Natural Language"):
+        nl = gr.Textbox(
+            label="Ask a question",
+            placeholder="e.g., show me the top 10 fds by portfolio value",
+            lines=2,
+        )
+        btn = gr.Button("Run")
+        sql_out = gr.Textbox(label="Generated SQL", interactive=False)
+        why_out = gr.Textbox(label="Reasoning", interactive=False)
+        df_out  = gr.Dataframe(label="Query Result", interactive=True)
+        cf_out  = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True)
+        gap_out = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True)
+
+        # IMPORTANT: keep event binding INSIDE the Blocks context
+        btn.click(
+            fn=run_nl,
+            inputs=[nl],
+            outputs=[df_out, sql_out, why_out, cf_out, gap_out],
+        )
 
     with gr.Tab("Run Raw SQL"):
-        sql_in = gr.Code(label="SQL", language="sql", value=f"SELECT * FROM {DEFAULT_SCHEMA}.{DEFAULT_TABLE} LIMIT 20;")
+        sql_in = gr.Code(
+            label="SQL",
+            language="sql",
+            value=f"SELECT * FROM {DEFAULT_SCHEMA}.{DEFAULT_TABLE} LIMIT 20;",
+        )
         btn2 = gr.Button("Execute")
-        df2  = gr.Dataframe(label="Result", interactive=True)
+        df2   = gr.Dataframe(label="Result", interactive=True)
         status = gr.Textbox(label="Status", interactive=False)
-        cf2   = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True)
-        gap2  = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True)
+        cf2    = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True)
+        gap2   = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True)
 
-    btn2.click(fn=run_sql, inputs=[sql_in], outputs=[df2, status, cf2, gap2])
+        btn2.click(
+            fn=run_sql,
+            inputs=[sql_in],
+            outputs=[df2, status, cf2, gap2],
+        )
 
+# --- Launch ---
 if __name__ == "__main__":
-    # Spaces set PORT automatically; otherwise, Gradio defaults are fine.
     demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))