add plain english support

app.py

@@ -5,24 +5,32 @@ from sqlalchemy import text
 from smolagents import tool, CodeAgent, HfApiModel
 import spaces
 
+# Import database
 from database import engine, receipts
 
+# Load Hugging Face API token
 load_dotenv(override=True)
 hf_token = os.getenv("HF_TOKEN")
 
+if not hf_token:
+    raise ValueError("HF_TOKEN environment variable is not set.")
+
 @tool
 def sql_engine(query: str) -> str:
     """
-    Allows you to perform SQL queries on the table. Returns a string representation of the result.
-    The table is named 'receipts'. Its description is as follows:
-        Columns:
+    Executes an SQL query on the 'receipts' table and returns results.
+    
+    Table Schema:
         - receipt_id: INTEGER
         - customer_name: VARCHAR(16)
         - price: FLOAT
         - tip: FLOAT
 
     Args:
-        query: The query to perform. This should be correct SQL.
+        query: The SQL query to execute.
+    
+    Returns:
+        Query result as a string.
     """
     output = ""
     try:
@@ -34,21 +42,36 @@ def sql_engine(query: str) -> str:
         output = f"Error: {str(e)}"
     return output.strip()
 
+# Initialize CodeAgent to generate SQL queries from natural language
 agent = CodeAgent(
-    tools=[sql_engine],
+    tools=[sql_engine],  # Ensure sql_engine is properly registered
     model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct", token=hf_token),
 )
 
-def query_sql(user_query):
-    return sql_engine(user_query)
+def query_sql(user_query: str) -> str:
+    """
+    Converts natural language input to an SQL query using CodeAgent
+    and returns the execution results.
+    
+    Args:
+        user_query: The user's request in natural language.
+    
+    Returns:
+        The query result from the database.
+    """
+    # Generate SQL from natural language
+    generated_sql = agent.run(f"Convert this request into SQL: {user_query}")
+
+    # Execute the SQL query and return the result
+    return sql_engine(generated_sql)
 
 # Define Gradio interface
 demo = gr.Interface(
     fn=query_sql,
-    inputs=gr.Textbox(label="Enter your SQL Query"),
+    inputs=gr.Textbox(label="Enter your query in plain English"),
     outputs=gr.Textbox(label="Query Result"),
-    title="SQL Query Executor",
-    description="Enter SQL queries to interact with an in-memory SQLite database.",
+    title="Natural Language to SQL Executor",
+    description="Enter a plain English request, and the AI will generate an SQL query and return the results.",
     flagging_mode="never",
 )