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The `FewShotSQLTool` gets some SQL query examples from a `BaseExampleSelector` for a given question. This is useful to provide [few-shot examples](https://python.langchain.com/docs/how_to/sql_prompting/#few-shot-examples) capability to an SQL agent. Example usage: ```python from langchain.agents.agent_toolkits.sql.prompt import SQL_PREFIX embeddings = OpenAIEmbeddings() example_selector = SemanticSimilarityExampleSelector.from_examples( examples, embeddings, AstraDB, k=5, input_keys=["input"], collection_name="lc_few_shots", token=ASTRA_DB_APPLICATION_TOKEN, api_endpoint=ASTRA_DB_API_ENDPOINT, ) few_shot_sql_tool = FewShotSQLTool( example_selector=example_selector, description="Input to this tool is the input question, output is a few SQL query examples related to the input question. Always use this tool before checking the query with sql_db_query_checker!" ) agent = create_sql_agent( llm=llm, db=db, prefix=SQL_PREFIX + "\nYou MUST get some example queries before creating the query.", extra_tools=[few_shot_sql_tool] ) result = agent.invoke({"input": "How many artists are there?"}) ``` --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>
🦜️🧑🤝🧑 LangChain Community
Quick Install
pip install langchain-community
What is it?
LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.
For full documentation see the API reference.
📕 Releases & Versioning
langchain-community is currently on version 0.0.x
All changes will be accompanied by a patch version increase.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.