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import os |
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import pandas as pd |
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import gradio as gr |
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from tools.sql_tool import SQLTool |
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from tools.ts_preprocess import build_timeseries |
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DUCKDB_PATH = os.getenv("DUCKDB_PATH", "alm.duckdb") |
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sql_tool = SQLTool(DUCKDB_PATH) |
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RESOLVED_PATH = sql_tool.get_full_table_path() |
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INTRO = f""" |
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### ALM LLM — Demo |
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Connected to **DuckDB** at `{DUCKDB_PATH}` |
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Using table **{RESOLVED_PATH}** (auto-resolved). |
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""" |
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def run_nl(nl_query: str): |
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if not nl_query or not nl_query.strip(): |
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return pd.DataFrame(), "", "Please enter a query.", pd.DataFrame(), pd.DataFrame() |
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try: |
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df, sql, why = sql_tool.query_from_nl(nl_query) |
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except Exception as e: |
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return pd.DataFrame(), "", f"Error: {e}", pd.DataFrame(), pd.DataFrame() |
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try: |
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cf, gap = build_timeseries(df) |
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except Exception: |
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cf, gap = pd.DataFrame(), pd.DataFrame() |
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return df, sql.strip(), why, cf, gap |
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def run_sql(sql_text: str): |
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if not sql_text or not sql_text.strip(): |
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return pd.DataFrame(), "Please paste a SQL statement.", pd.DataFrame(), pd.DataFrame() |
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try: |
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df = sql_tool.run_sql(sql_text) |
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except Exception as e: |
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return pd.DataFrame(), f"Error: {e}", pd.DataFrame(), pd.DataFrame() |
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try: |
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cf, gap = build_timeseries(df) |
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except Exception: |
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cf, gap = pd.DataFrame(), pd.DataFrame() |
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return df, "OK", cf, gap |
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with gr.Blocks(title="ALM LLM") as demo: |
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gr.Markdown(INTRO) |
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with gr.Tab("Ask in Natural Language"): |
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nl = gr.Textbox(label="Ask a question", placeholder="e.g., show me the top 10 fds by portfolio value", lines=2) |
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btn = gr.Button("Run") |
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sql_out = gr.Textbox(label="Generated SQL", interactive=False) |
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why_out = gr.Textbox(label="Reasoning", interactive=False) |
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df_out = gr.Dataframe(label="Query Result", interactive=True) |
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cf_out = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True) |
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gap_out = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True) |
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btn.click(fn=run_nl, inputs=[nl], outputs=[df_out, sql_out, why_out, cf_out, gap_out]) |
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with gr.Tab("Run Raw SQL"): |
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sql_in = gr.Code(label="SQL", language="sql", value=f"SELECT * FROM {RESOLVED_PATH} LIMIT 20;") |
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btn2 = gr.Button("Execute") |
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df2 = gr.Dataframe(label="Result", interactive=True) |
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status = gr.Textbox(label="Status", interactive=False) |
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cf2 = gr.Dataframe(label="Projected Cash-Flows (if applicable)", interactive=True) |
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gap2 = gr.Dataframe(label="Liquidity Gap (monthly)", interactive=True) |
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btn2.click(fn=run_sql, inputs=[sql_in], outputs=[df2, status, cf2, gap2]) |
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if __name__ == "__main__": |
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demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860))) |
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