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SQL | 🦜️🔗 LangChain

One of the most common types of databases that we can build Q&A systems for are SQL databases. LangChain comes with a number of built-in chains and agents that are compatible with any SQL dialect supported by SQLAlchemy (e.g., MySQL, PostgreSQL, Oracle SQL, Databricks, SQLite). They enable use cases such as:

• Generating queries that will be run based on natural language questions,
• Creating chatbots that can answer questions based on database data,
• Building custom dashboards based on insights a user wants to analyze,

and much more.

Building Q&A systems of SQL databases requires executing model-generated SQL queries. There are inherent risks in doing this. Make sure that your database connection permissions are always scoped as narrowly as possible for your chain/agent's needs. This will mitigate though not eliminate the risks of building a model-driven system. For more on general security best practices, see here.

Head to the Quickstart page to get started.

Once you've familiarized yourself with the basics, you can head to the advanced guides:

• Agents: Building agents that can interact with SQL DBs.
• Prompting strategies: Strategies for improving SQL query generation.
• Query validation: How to validate SQL queries.
• Large databases: How to interact with DBs with many tables and high-cardinality columns.

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