langchain-aws: 0.2.9

agents

Classes

agents.base.BedrockAgentAction	AgentAction with session id information.
agents.base.BedrockAgentFinish	AgentFinish with session id information.
agents.base.BedrockAgentsRunnable	Invoke a Bedrock Agent
agents.base.GuardrailConfiguration

Functions

agents.base.get_boto_session([...])	Construct the boto3 session
agents.base.parse_agent_response(response)	Parses the raw response from Bedrock Agent

chat_models

Classes

chat_models.bedrock.ChatBedrock	A chat model that uses the Bedrock API.
chat_models.bedrock.ChatPromptAdapter()	Adapter class to prepare the inputs from Langchain to prompt format that Chat model expects.
chat_models.bedrock_converse.ChatBedrockConverse	Bedrock chat model integration built on the Bedrock converse API.

Functions

chat_models.bedrock.convert_messages_to_prompt_anthropic(...)	Format a list of messages into a full prompt for the Anthropic model
chat_models.bedrock.convert_messages_to_prompt_llama(...)	Convert a list of messages to a prompt for llama.
chat_models.bedrock.convert_messages_to_prompt_llama3(...)	Convert a list of messages to a prompt for llama.
chat_models.bedrock.convert_messages_to_prompt_mistral(...)	Convert a list of messages to a prompt for mistral.

embeddings

Classes

embeddings.bedrock.BedrockEmbeddings

Bedrock embedding models.

function_calling

Classes

function_calling.AnthropicTool
function_calling.FunctionDescription	Representation of a callable function to send to an LLM.
function_calling.ToolDescription	Representation of a callable function to the OpenAI API.
function_calling.ToolsOutputParser

Functions

function_calling.convert_to_anthropic_tool(tool)
function_calling.get_system_message(tools)

graphs

Classes

graphs.neptune_graph.BaseNeptuneGraph()
graphs.neptune_graph.NeptuneAnalyticsGraph(...)	Neptune Analytics wrapper for graph operations.
graphs.neptune_graph.NeptuneGraph(host[, ...])	Neptune wrapper for graph operations.
graphs.neptune_graph.NeptuneQueryException(...)	Exception for the Neptune queries.
graphs.neptune_rdf_graph.NeptuneRdfGraph(host)	Neptune wrapper for RDF graph operations.

llms

Classes

llms.bedrock.AnthropicTool
llms.bedrock.BedrockBase	Base class for Bedrock models.
llms.bedrock.BedrockLLM	Bedrock models.
llms.bedrock.LLMInputOutputAdapter()	Adapter class to prepare the inputs from Langchain to a format that LLM model expects.
llms.sagemaker_endpoint.ContentHandlerBase()	A handler class to transform input from LLM to a format that SageMaker endpoint expects.
llms.sagemaker_endpoint.LLMContentHandler()	Content handler for LLM class.
llms.sagemaker_endpoint.LineIterator(stream)	A helper class for parsing the byte stream input.
llms.sagemaker_endpoint.SagemakerEndpoint	Sagemaker Inference Endpoint models.

Functions

llms.bedrock.extract_tool_calls(content)
llms.sagemaker_endpoint.enforce_stop_tokens(...)	Cut off the text as soon as any stop words occur.

retrievers

Classes

retrievers.bedrock.AmazonKnowledgeBasesRetriever	Amazon Bedrock Knowledge Bases retrieval.
retrievers.bedrock.RetrievalConfig	Configuration for retrieval.
retrievers.bedrock.SearchFilter	Filter configuration for retrieval.
retrievers.bedrock.VectorSearchConfig	Configuration for vector search.
retrievers.kendra.AdditionalResultAttribute	Additional result attribute.
retrievers.kendra.AdditionalResultAttributeValue	Value of an additional result attribute.
retrievers.kendra.AmazonKendraRetriever	Amazon Kendra Index retriever.
retrievers.kendra.DocumentAttribute	Document attribute.
retrievers.kendra.DocumentAttributeValue	Value of a document attribute.
retrievers.kendra.Highlight	Information that highlights the keywords in the excerpt.
retrievers.kendra.QueryResult	Amazon Kendra Query API search result.
retrievers.kendra.QueryResultItem	Query API result item.
retrievers.kendra.ResultItem	Base class of a result item.
retrievers.kendra.RetrieveResult	Amazon Kendra Retrieve API search result.
retrievers.kendra.RetrieveResultItem	Retrieve API result item.
retrievers.kendra.TextWithHighLights	Text with highlights.

Functions

retrievers.kendra.clean_excerpt(excerpt)	Clean an excerpt from Kendra.
retrievers.kendra.combined_text(item)	Combine a ResultItem title and excerpt into a single string.

utilities

Classes

utilities.redis.TokenEscaper([escape_chars_re])	Escape punctuation within an input string.
utilities.utils.DistanceStrategy(value[, ...])	Enumerator of the Distance strategies for calculating distances between vectors.

Functions

utilities.math.cosine_similarity(X, Y)	Row-wise cosine similarity between two equal-width matrices.
utilities.math.cosine_similarity_top_k(X, Y)	Row-wise cosine similarity with optional top-k and score threshold filtering.
utilities.redis.get_client(redis_url, **kwargs)	Get a redis client from the connection url given.
utilities.utils.filter_complex_metadata(...)	Filter out metadata types that are not supported for a vector store.
utilities.utils.maximal_marginal_relevance(...)	Calculate maximal marginal relevance.

utils

Functions

utils.enforce_stop_tokens(text, stop)	Cut off the text as soon as any stop words occur.
utils.get_num_tokens_anthropic(text)	Get the number of tokens in a string of text.
utils.get_token_ids_anthropic(text)	Get the token ids for a string of text.

vectorstores

Classes

vectorstores.inmemorydb.base.InMemoryVectorStore(...)	InMemoryVectorStore vector database.
vectorstores.inmemorydb.base.InMemoryVectorStoreRetriever	Retriever for InMemoryVectorStore.
vectorstores.inmemorydb.cache.InMemorySemanticCache(...)	Cache that uses MemoryDB as a vector-store backend.
vectorstores.inmemorydb.filters.InMemoryDBFilter()	Collection of InMemoryDBFilterFields.
vectorstores.inmemorydb.filters.InMemoryDBFilterExpression([...])	Logical expression of InMemoryDBFilterFields.
vectorstores.inmemorydb.filters.InMemoryDBFilterField(field)	Base class for InMemoryDBFilterFields.
vectorstores.inmemorydb.filters.InMemoryDBFilterOperator(value)	InMemoryDBFilterOperator enumerator is used to create InMemoryDBFilterExpressions
vectorstores.inmemorydb.filters.InMemoryDBNum(field)	InMemoryDBFilterField representing a numeric field in a InMemoryDB index.
vectorstores.inmemorydb.filters.InMemoryDBTag(field)	InMemoryDBFilterField representing a tag in a InMemoryDB index.
vectorstores.inmemorydb.filters.InMemoryDBText(field)	InMemoryDBFilterField representing a text field in a InMemoryDB index.
vectorstores.inmemorydb.schema.FlatVectorField	Schema for flat vector fields in Redis.
vectorstores.inmemorydb.schema.HNSWVectorField	Schema for HNSW vector fields in Redis.
vectorstores.inmemorydb.schema.InMemoryDBDistanceMetric(value)	Distance metrics for Redis vector fields.
vectorstores.inmemorydb.schema.InMemoryDBField	Base class for Redis fields.
vectorstores.inmemorydb.schema.InMemoryDBModel	Schema for MemoryDB index.
vectorstores.inmemorydb.schema.InMemoryDBVectorField	Base class for Redis vector fields.
vectorstores.inmemorydb.schema.NumericFieldSchema	Schema for numeric fields in Redis.
vectorstores.inmemorydb.schema.TagFieldSchema	Schema for tag fields in Redis.
vectorstores.inmemorydb.schema.TextFieldSchema	Schema for text fields in Redis.

Functions

vectorstores.inmemorydb.base.check_index_exists(...)	Check if MemoryDB index exists.
vectorstores.inmemorydb.filters.check_operator_misuse(func)	Decorator to check for misuse of equality operators.
vectorstores.inmemorydb.schema.read_schema(...)	Read in the index schema from a dict or yaml file.