tj;ddlmZmZmZmZddlmZddlmZddl m Z ddl m Z ddl mZmZGdded ZGd d ed Zed ddGdde ZdS))AnyDictListOptional) deprecated)CallbackManagerForRetrieverRun)Document) BaseRetriever) BaseModelmodel_validatorc"eZdZUdZdZeed<dS)VectorSearchConfigz Configuration for vector search.numberOfResultsN)__name__ __module__ __qualname____doc__rint__annotations__d/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/retrievers/bedrock.pyrr s(**OSrrallow)extraceZdZUdZeed<dS)RetrievalConfigzConfiguration for retrieval.vectorSearchConfigurationN)rrrrrrrrrrrs$&&111111rrz0.3.16z1.0z+langchain_aws.AmazonKnowledgeBasesRetriever)sinceremovalalternative_importceZdZUdZeed<dZeeed<dZeeed<dZ eeed<e ed<e ed<e d e d eee fd e fd Zdeded eefdZdS)AmazonKnowledgeBasesRetrievera Amazon Bedrock Knowledge Bases retriever. See https://aws.amazon.com/bedrock/knowledge-bases for more info. Setup: Install ``langchain-aws``: .. code-block:: bash pip install -U langchain-aws Key init args: knowledge_base_id: Knowledge Base ID. region_name: The aws region e.g., `us-west-2`. Fallback to AWS_DEFAULT_REGION env variable or region specified in ~/.aws/config. credentials_profile_name: The name of the profile in the ~/.aws/credentials or ~/.aws/config files, which has either access keys or role information specified. If not specified, the default credential profile or, if on an EC2 instance, credentials from IMDS will be used. client: boto3 client for bedrock agent runtime. retrieval_config: Configuration for retrieval. Instantiate: .. code-block:: python from langchain_community.retrievers import AmazonKnowledgeBasesRetriever retriever = AmazonKnowledgeBasesRetriever( knowledge_base_id="", retrieval_config={ "vectorSearchConfiguration": { "numberOfResults": 4 } }, ) Usage: .. code-block:: python query = "..." retriever.invoke(query) Use within a chain: .. code-block:: python from langchain_aws import ChatBedrockConverse from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate from langchain_core.runnables import RunnablePassthrough from langchain_openai import ChatOpenAI prompt = ChatPromptTemplate.from_template( """Answer the question based only on the context provided. Context: {context} Question: {question}""" ) llm = ChatBedrockConverse( model_id="anthropic.claude-3-5-sonnet-20240620-v1:0" ) def format_docs(docs): return "\n\n".join(doc.page_content for doc in docs) chain = ( {"context": retriever | format_docs, "question": RunnablePassthrough()} | prompt | llm | StrOutputParser() ) chain.invoke("...") knowledge_base_idN region_namecredentials_profile_name endpoint_urlclientretrieval_configbefore)modevaluesreturncJ|d|S ddl}ddlm}ddlm}|dr||d}n|}d|ddd di i}|d r |d |d <|d r |d |d <|jdi||d<|S#t$rtd|$r}td|d}~wt$r}td|d}~wwxYw)Nr(r)Config)UnknownServiceErrorr&) profile_nameconfigx max_attempts)connect_timeout read_timeoutretriesr%r'bedrock-agent-runtimezRCould not import boto3 python package. Please install it with `pip install boto3`.zjEnsure that you have installed the latest boto3 package that contains the API for `bedrock-runtime-agent`.zCould not load credentials to authenticate with AWS client. Please check that credentials in the specified profile name are valid.)r8) getboto3botocore.clientr/botocore.exceptionsr0Sessionr( ImportError Exception ValueError)clsr,r:r/r0session client_paramses r create_clientz+AmazonKnowledgeBasesRetriever.create_clientrs ::h   +M(  LLL . . . . . . ? ? ? ? ? ?zz455 *--V #   E    *   s$B9CD"0D D" DD"query run_managerc|jd|i|j|j}|d}g}|D]n}|dd}|dd|vrd|d<d|vr|d|d<|t|| o|S) Ntext)retrievalQueryknowledgeBaseIdretrievalConfigurationretrievalResultscontentscorermetadatasource_metadata) page_contentrP) r(retrievestripr$r)dictpopappendr )selfrFrGresponseresults documentsresultrNs r_get_relevant_documentsz5AmazonKnowledgeBasesRetriever._get_relevant_documentss;''"EKKMM2 2#'#8#=#=#?#?(   -.   FY'/G JJy ! ! !f$$"#wV##,2JJz,B,B()   !(#    r)rrrrstrrr%rr&r'rrr classmethodrrErrr r]rrrr#r#s MM^!%K#%%%.2hsm222"&L(3-&&& KKK%%%%_(###,4S>,c,,,[$#,\*H hrr#N)typingrrrrlangchain_core._api.deprecationrlangchain_core.callbacksrlangchain_core.documentsr langchain_core.retrieversr pydanticr r rrr#rrrrfsR,,,,,,,,,,,,666666CCCCCC------333333////////' 22222iw2222    D _____M__  ___r