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    Pythonlangchain-classicchainselasticsearch_databasebaseElasticsearchDatabaseChain
    Class●Since v1.0

    ElasticsearchDatabaseChain

    Copy
    ElasticsearchDatabaseChain()

    Bases

    Chain

    Used in Docs

    • Elasticsearch integrations

    Attributes

    Methods

    Inherited fromChain

    Attributes

    Amemory: BaseMemory | None
    —

    Optional memory object.

    Acallbacks: CallbacksAverbose: boolAtags
    View source on GitHub
    : list[str] | None
    Ametadata: dict[str, Any] | None
    Acallback_manager: BaseCallbackManager | None
    —

    [DEPRECATED] Use callbacks instead.

    Methods

    Mget_input_schemaMget_output_schemaMinvokeMainvokeMraise_callback_manager_deprecation
    —

    Raise deprecation warning if callback_manager is used.

    Mset_verbose
    —

    Set the chain verbosity.

    Macall
    —

    Asynchronously execute the chain.

    Mprep_outputs
    —

    Validate and prepare chain outputs, and save info about this run to memory.

    Maprep_outputs
    —

    Validate and prepare chain outputs, and save info about this run to memory.

    Mprep_inputs
    —

    Prepare chain inputs, including adding inputs from memory.

    Maprep_inputs
    —

    Prepare chain inputs, including adding inputs from memory.

    Mrun
    —

    Convenience method for executing chain.

    Marun
    —

    Convenience method for executing chain.

    Mdict
    —

    Return dictionary representation of agent.

    Msave
    —

    Save the agent.

    Mapply
    —

    Utilize the LLM generate method for speed gains.

    Inherited fromRunnableSerializable(langchain_core)

    Attributes

    Aname

    Methods

    Mto_jsonMconfigurable_fieldsMconfigurable_alternatives

    Inherited fromSerializable(langchain_core)

    Attributes

    Alc_secretsAlc_attributes

    Methods

    Mis_lc_serializableMget_lc_namespaceMlc_idMto_jsonMto_json_not_implemented

    Inherited fromRunnable(langchain_core)

    Attributes

    AnameAInputTypeAOutputTypeAinput_schemaAoutput_schemaAconfig_specs

    Methods

    Mget_nameMget_input_schemaMget_input_jsonschemaMget_output_schemaMget_output_jsonschemaM
    attribute
    query_chain: Runnable

    Chain for creating the ES query.

    attribute
    answer_chain: Runnable

    Chain for answering the user question.

    attribute
    database: Any

    Elasticsearch database to connect to of type elasticsearch.Elasticsearch.

    attribute
    top_k: int

    Number of results to return from the query

    attribute
    ignore_indices: list[str] | None
    attribute
    include_indices: list[str] | None
    attribute
    input_key: str
    attribute
    output_key: str
    attribute
    sample_documents_in_index_info: int
    attribute
    return_intermediate_steps: bool

    Whether or not to return the intermediate steps along with the final answer.

    attribute
    model_config
    attribute
    input_keys: list[str]

    Return the singular input key.

    attribute
    output_keys: list[str]

    Return the singular output key.

    method
    from_llm

    Convenience method to construct ElasticsearchDatabaseChain from an LLM.

    Chain for interacting with Elasticsearch Database.

    Example:

    from langchain_classic.chains import ElasticsearchDatabaseChain
    from langchain_openai import OpenAI
    from elasticsearch import Elasticsearch
    
    database = Elasticsearch("http://localhost:9200")
    db_chain = ElasticsearchDatabaseChain.from_llm(OpenAI(), database)
    config_schema
    Mget_config_jsonschema
    Mget_graph
    Mget_prompts
    Mpipe
    Mpick
    Massign
    Minvoke
    Mainvoke
    Mbatch
    Mbatch_as_completed
    Mabatch
    Mabatch_as_completed
    Mstream
    Mastream
    Mastream_log
    Mastream_events
    Mtransform
    Matransform
    Mbind
    Mwith_config
    Mwith_listeners
    Mwith_alisteners
    Mwith_types
    Mwith_retry
    Mmap
    Mwith_fallbacks
    Mas_tool