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nileshhanotia
commited on
Commit
•
9e11341
1
Parent(s):
b4d7a19
Update app.py
Browse files
app.py
CHANGED
@@ -1,120 +1,13 @@
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import
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from
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import requests
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import json
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import os
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# Construct a more structured prompt
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prompt = f"""Given this SQL table schema:
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{schema_info}
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# Make API request to the Hugging Face Space
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payload = {
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"inputs": prompt,
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"options": {
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"use_cache": False
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}
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}
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try:
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response = requests.post(space_url, json=payload)
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if response.status_code == 200:
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return response.json().get('generated_text', '').strip()
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else:
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raise Exception(f"API request failed: {response.text}")
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except Exception as e:
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print(f"API Error: {str(e)}")
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return None
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def main():
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try:
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# Define the Hugging Face Space URL
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space_url = "https://huggingface.co/spaces/nileshhanotia/sql"
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# Define your schema information
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schema_info = """
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CREATE TABLE sales (
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pizza_id DECIMAL(8,2) PRIMARY KEY,
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order_id DECIMAL(8,2),
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pizza_name_id VARCHAR(14),
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quantity DECIMAL(4,2),
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order_date DATE,
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order_time VARCHAR(8),
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unit_price DECIMAL(5,2),
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total_price DECIMAL(5,2),
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pizza_size VARCHAR(3),
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pizza_category VARCHAR(7),
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pizza_ingredients VARCHAR(97),
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pizza_name VARCHAR(42)
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);
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"""
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# Establish connection to the database
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connection = mysql.connector.connect(
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host="localhost",
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database="pizza",
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user="root",
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password="root",
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port=8889
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)
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if connection.is_connected():
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cursor = connection.cursor()
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print("Database connected successfully!")
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while True:
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try:
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# Get user input
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print("\nEnter your question (or 'exit' to quit):")
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natural_language_query = input("> ").strip()
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if natural_language_query.lower() == 'exit':
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break
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# Generate and execute query
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sql_query = generate_sql_query(natural_language_query, schema_info, space_url)
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if sql_query:
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print(f"\nExecuting SQL Query:\n{sql_query}")
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cursor.execute(sql_query)
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records = cursor.fetchall()
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# Print results
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if records:
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print("\nResults:")
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# Get column names
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columns = [desc[0] for desc in cursor.description]
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print(" | ".join(columns))
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print("-" * (len(" | ".join(columns)) + 10))
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for row in records:
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print(" | ".join(str(val) for val in row))
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else:
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print("\nNo results found.")
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except KeyboardInterrupt:
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print("\nOperation cancelled by user.")
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continue
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except Exception as e:
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print(f"\nError: {str(e)}")
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continue
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except Error as e:
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print(f"\nDatabase error: {str(e)}")
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except Exception as e:
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print(f"\nApplication error: {str(e)}")
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finally:
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if 'connection' in locals() and connection.is_connected():
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cursor.close()
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connection.close()
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print("\nMySQL connection closed.")
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if __name__ == "__main__":
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main()
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import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "defog/sqlcoder-7b-2"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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def generate_sql(natural_language_query):
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# Define your SQL generation logic here
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return sql_query
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iface = gr.Interface(fn=generate_sql, inputs="text", outputs="text")
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iface.launch()
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