Update app.py

app.py

@@ -6,45 +6,30 @@ import gradio as gr
 from tools.sql_tool import SQLTool
 from tools.ts_preprocess import build_timeseries
 
-# --- 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")
+DEFAULT_PATH = "my_db.main.masterdataset_v"
 
 sql_tool = SQLTool(DUCKDB_PATH)
 
 INTRO = f"""
 ### 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"*
+Connected to **DuckDB** at `{DUCKDB_PATH}`  
+Using table **{DEFAULT_PATH}**.
 """
 
-# --- Handlers ---
+# ---------------------- 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 building projections and liquidity gap
     try:
         cf, gap = build_timeseries(df)
     except Exception:
         cf, gap = pd.DataFrame(), pd.DataFrame()
-
     return df, sql.strip(), why, cf, gap
 
 
@@ -55,57 +40,38 @@ def run_sql(sql_text: str):
         df = sql_tool.run_sql(sql_text)
     except Exception as e:
         return pd.DataFrame(), f"Error: {e}", pd.DataFrame(), pd.DataFrame()
-
     try:
         cf, gap = build_timeseries(df)
     except Exception:
         cf, gap = pd.DataFrame(), pd.DataFrame()
-
     return df, "OK", cf, gap
 
-
-# --- UI ---
+# ---------------------- 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,
-        )
+        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],
-        )
+        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;",
+            value=f"SELECT * FROM {DEFAULT_PATH} LIMIT 20;",
         )
         btn2 = gr.Button("Execute")
         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)
+        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__":
     demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))