a final answer based on the user question and the query result.Be careful while using this approach as it is susceptible to SQL Injection:The chain is executing queries that are created by an LLM, and weren't validatede.g. records may be created, modified or deleted unintentionally_This is why we see the SQLDatabaseChain is inside langchain_experimental.Go deeper‚ÄãLooking under the hoodWe can use the LangSmith trace to see what is happening under the hood:As discussed above, first we create the query:text: ' SELECT COUNT(*) FROM "Employee";'Then, it executes the query and passes the results to an LLM for synthesis.ImprovementsThe performance of the SQLDatabaseChain can be enhanced in several ways:Adding sample rowsSpecifying custom table informationUsing Query Checker self-correct invalid SQL using parameter use_query_checker=TrueCustomizing the LLM Prompt include specific instructions or relevant information, using parameter prompt=CUSTOM_PROMPTGet intermediate steps access the SQL statement as well as the final result using parameter return_intermediate_steps=TrueLimit the number of rows a query will return using parameter top_k=5You might find SQLDatabaseSequentialChain
Open In Colab
Open In Colab ->: a final answer based on the user question and the query result.Be careful while using this approach as it is susceptible to SQL Injection:The chain is executing queries that are created by an LLM, and weren't validatede.g. records may be created, modified or deleted unintentionally_This is why we see the SQLDatabaseChain is inside langchain_experimental.Go deeper‚ÄãLooking under the hoodWe can use the LangSmith trace to see what is happening under the hood:As discussed above, first we create the query:text: ' SELECT COUNT(*) FROM "Employee";'Then, it executes the query and passes the results to an LLM for synthesis.ImprovementsThe performance of the SQLDatabaseChain can be enhanced in several ways:Adding sample rowsSpecifying custom table informationUsing Query Checker self-correct invalid SQL using parameter use_query_checker=TrueCustomizing the LLM Prompt include specific instructions or relevant information, using parameter prompt=CUSTOM_PROMPTGet intermediate steps access the SQL statement as well as the final result using parameter return_intermediate_steps=TrueLimit the number of rows a query will return using parameter top_k=5You might find SQLDatabaseSequentialChain