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| title: Multi-Agentic SQL Generator | |
| sdk: gradio | |
| app_file: app.py | |
| license: apache-2.0 | |
| tags: | |
| - sql | |
| - openai | |
| - multi-agent | |
| - demo | |
| sdk_version: 5.19.0 | |
| # Multi-Agentic SQL Generator | |
| The Multi-Agentic SQL Generator is a modular, multi-step system that translates natural language queries into SQL queries, validates and optimizes them, and then executes them against a SQLite database. The system leverages OpenAI's language models (via a LangGraph workflow) for query understanding, validation, and optimization. It also provides evaluation capabilities using RAGAS metrics (such as context precision and context recall) to assess performance and quality. | |
| ## Capabilities | |
| - **Natural Language Query Understanding:** | |
| Converts natural language queries into structured SQL metadata according to a predefined database schema. | |
| - **Query Validation:** | |
| Checks the generated SQL for syntax errors and security risks (e.g., harmful operations like `DROP`, `DELETE`). | |
| - **Query Optimization:** | |
| Optimizes SQL queries for performance, ensuring only the necessary columns, joins, and filtering conditions are included. | |
| - **SQL Execution:** | |
| Executes the optimized SQL query against a SQLite database and returns the results. | |
| - **Evaluation with RAGAS Metrics:** | |
| Evaluates the generated output using metrics like: | |
| - **Faithfulness:** (0.7500) Faithfulness measures how well the generated SQL execution results match the expected (ground truth) results. | |
| - **Answer Relevancy:** (0.2280) Answer relevancy measures how well the generated SQL results match the intent of the user's query. | |
| - **Context Precision:** (0.3000) Context Precision measures how much of the generated SQL execution result is actually relevant to the query. | |
| - **Context Recall:** (0.3500) Context Recall measures how much of the expected result was actually retrieved. | |
| - **Extensibility and Deployment:** | |
| Easily integrable with front-end frameworks (e.g., Chainlit) and deployable on platforms like Hugging Face Spaces. | |
| ## Installation | |
| 1. **Clone the Repository:** | |
| ```bash | |
| git clone https://github.com/yourusername/multi-agent-sql-generator.git | |
| cd multi-agent-sql-generator |