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aesthetics
Browse files
app.py
CHANGED
@@ -5,7 +5,6 @@ from smolagents import tool, CodeAgent, HfApiModel
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import spaces
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import pandas as pd
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# Import the persistent database
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from database import engine, receipts
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import pandas as pd
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@@ -69,7 +68,7 @@ def query_sql(user_query: str) -> str:
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Returns:
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The query result from the database as a formatted string.
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"""
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-
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schema_info = (
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"The database has a table named 'receipts' with the following schema:\n"
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"- receipt_id (INTEGER, primary key)\n"
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@@ -80,14 +79,11 @@ def query_sql(user_query: str) -> str:
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"DO NOT explain your reasoning, and DO NOT return anything other than the SQL query itself."
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)
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# Generate SQL query using the provided schema
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generated_sql = agent.run(f"{schema_info} Convert this request into SQL: {user_query}")
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# Ensure generated_sql is always a string
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if not isinstance(generated_sql, str):
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return f"Unexpected result: {generated_sql}" # Handle unexpected numerical result
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# Log the generated SQL for debugging
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print(f"Generated SQL: {generated_sql}")
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if not generated_sql.strip().lower().startswith(("select", "show", "pragma")):
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@@ -95,7 +91,6 @@ def query_sql(user_query: str) -> str:
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result = sql_engine(generated_sql)
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#print(f"SQL Query Result: {result}")
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print(f"{result}")
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try:
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@@ -114,11 +109,10 @@ def handle_query(user_input: str) -> str:
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Returns:
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The SQL query result as a plain string to be displayed in the UI.
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"""
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return query_sql(user_input)
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# Initialize CodeAgent to generate SQL queries from natural language
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agent = CodeAgent(
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tools=[sql_engine],
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model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
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)
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@@ -126,18 +120,16 @@ with gr.Blocks() as demo:
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gr.Markdown("## Natural Language to SQL Executor with Live Data")
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with gr.Row():
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with gr.Column(scale=1):
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user_input = gr.Textbox(label="Enter your query in plain English")
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query_output = gr.Textbox(label="Query Result")
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with gr.Column(scale=2):
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gr.Markdown("### Receipts Table (Live View)")
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receipts_table = gr.Dataframe(value=get_receipts_table(), label="Receipts Table")
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# Query handling function
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user_input.change(fn=handle_query, inputs=user_input, outputs=query_output)
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# Auto-refresh table every 5 seconds
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demo.load(fn=get_receipts_table, outputs=receipts_table)
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if __name__ == "__main__":
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import spaces
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import pandas as pd
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from database import engine, receipts
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import pandas as pd
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Returns:
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The query result from the database as a formatted string.
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"""
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schema_info = (
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"The database has a table named 'receipts' with the following schema:\n"
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"- receipt_id (INTEGER, primary key)\n"
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"DO NOT explain your reasoning, and DO NOT return anything other than the SQL query itself."
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)
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generated_sql = agent.run(f"{schema_info} Convert this request into SQL: {user_query}")
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if not isinstance(generated_sql, str):
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return f"Unexpected result: {generated_sql}" # Handle unexpected numerical result
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print(f"Generated SQL: {generated_sql}")
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if not generated_sql.strip().lower().startswith(("select", "show", "pragma")):
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result = sql_engine(generated_sql)
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print(f"{result}")
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try:
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Returns:
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The SQL query result as a plain string to be displayed in the UI.
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"""
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return query_sql(user_input)
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agent = CodeAgent(
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tools=[sql_engine],
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model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
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)
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gr.Markdown("## Natural Language to SQL Executor with Live Data")
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with gr.Row():
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with gr.Column(scale=1):
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user_input = gr.Textbox(label="Enter your query in plain English")
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query_output = gr.Textbox(label="Query Result")
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with gr.Column(scale=2):
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gr.Markdown("### Receipts Table (Live View)")
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receipts_table = gr.Dataframe(value=get_receipts_table(), label="Receipts Table")
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user_input.change(fn=handle_query, inputs=user_input, outputs=query_output)
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demo.load(fn=get_receipts_table, outputs=receipts_table)
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if __name__ == "__main__":
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