langchain-aws
This package ref has not yet been fully migrated to v1.
This page contains reference documentation for AWS. See the docs for conceptual guides, tutorials, and examples on using AWS modules.
A handler class to transform input from LLM and BaseChatModel to a
Representation of a callable function to send to an LLM.
Representation of a callable function to the OpenAI API.
Amazon Q Runnable wrapper.
Bedrock embedding models.
AmazonS3VectorsRetriever is a retriever for Amazon S3 Vectors.
Information that highlights the keywords in the excerpt.
Text with highlights.
Value of an additional result attribute.
Additional result attribute.
Value of a document attribute.
Document attribute.
Base class of a result item.
Query API result item.
Retrieve API result item.
Amazon Kendra Query API search result.
Amazon Kendra Retrieve API search result.
Amazon Kendra Index retriever.
Filter configuration for retrieval.
Configuration for vector search.
Configuration for retrieval.
Amazon Bedrock Knowledge Bases retrieval.
A helper class for parsing the byte stream input.
Content handler for ChatSagemakerEndpoint class.
A chat model that uses a HuggingFace TGI compatible SageMaker Endpoint.
Bedrock chat model integration built on the Bedrock converse API.
Adapter class to prepare the inputs from Langchain to prompt format that Chat
A chat model that uses the Bedrock API.
Manages browser sessions for different threads.
Input for NavigateTool.
Input for ClickTool.
Input for GetElementsTool.
Input for ExtractTextTool.
Input for ExtractHyperlinksTool.
Input for NavigateBackTool.
Input for CurrentWebPageTool.
Input for TypeTextTool.
Input for ScreenshotTool.
Input for ScrollTool.
Input for WaitForElementTool.
Base class for thread-aware browser tools.
Tool for navigating a browser to a URL with thread support.
Tool for clicking on an element with the given CSS selector.
Tool for typing text into input fields on a webpage.
Tool for capturing screenshots of the current webpage.
Tool for scrolling the webpage.
Tool for waiting until an element appears or reaches a specific state.
Toolkit for navigating web with AWS browser with thread support.
Input schema for execute_code tool.
Input schema for execute_command tool.
Input schema for read_files tool.
Input schema for write_files tool.
Input schema for list_files tool.
Input schema for delete_files tool.
Input schema for upload_file tool.
Input schema for install_packages tool.
Toolkit for working with AWS code interpreter environment.
Base class for Nova system tools.
Helper for Nova's web grounding system tool.
Helper for Nova's code interpreter system tool.
Document compressor that uses AWS Bedrock Rerank API.
Exception for the Neptune queries.
Neptune Analytics wrapper for graph operations.
Neptune wrapper for graph operations.
Neptune wrapper for RDF graph operations.
AgentFinish with session id information.
AgentAction with session id information.
Configurations for an Inline Agent.
Invoke a Bedrock Agent
Invoke Bedrock Inline Agent as a Runnable.
S3Vectors is Amazon S3 Vectors database.
InMemoryDBFilterOperator enumerator is used to create
Collection of InMemoryDBFilterFields.
Base class for InMemoryDBFilterFields.
InMemoryDBFilterField representing a tag in a InMemoryDB index.
InMemoryDBFilterField representing a numeric field in a InMemoryDB index.
InMemoryDBFilterField representing a text field in a InMemoryDB index.
Logical expression of InMemoryDBFilterFields.
Cache that uses MemoryDB as a vector-store backend.
Distance metrics for Redis vector fields.
Base class for Redis fields.
Schema for text fields in Redis.
Schema for tag fields in Redis.
Schema for numeric fields in Redis.
Base class for Redis vector fields.
Schema for flat vector fields in Redis.
Schema for HNSW vector fields in Redis.
Schema for MemoryDB index.
InMemoryVectorStore vector database.
Retriever for InMemoryVectorStore.
A helper class for parsing the byte stream input.
Content handler for LLM class.
Sagemaker Inference Endpoint models.
Adapter class to prepare the inputs from Langchain to a format
Base class for Bedrock models.
Bedrock models.
Cut off the text as soon as any stop words occur.
Check if all requirements for Anthropic count_tokens() are met.
Get the number of tokens in a string of text.
Get the token IDs for a string of text.
Helper function to validate AWS credentials and create an AWS client.
Check if the thinking parameter is enabled in the request.
Trim trailing whitespace from final AIMessage content.
Clean an excerpt from Kendra.
Combine a ResultItem title and excerpt into a single string.
Convert a list of messages to a prompt for llama.
Convert a list of messages to a prompt for Llama 3.
Convert a list of messages to a prompt for Llama 4.
Format a list of messages into a full prompt for the Anthropic model
Convert a list of messages to a prompt for mistral.
Convert a list of messages to a prompt for DeepSeek-R1.
Convert a list of messages to a prompt for Writer.
Convert a list of messages to a Harmony format prompt for OpenAI API.
Asynchronously get the current page of the browser.
Get the current page of the browser.
Create thread-aware browser tools that use the session manager.
Create a BrowserToolkit with thread support
Create and setup a CodeInterpreterToolkit.
Construct the boto3 session
Parses the raw response from Bedrock Agent
Extract SPARQL code from a text.
Selects the final prompt.
Chain for question-answering against a Neptune graph
Trim the query to only include Cypher keywords.
Extract Cypher code from text using Regex.
Decides whether to use the simple prompt
Selects the final prompt
Chain for question-answering against a Neptune graph
Decorator to check for misuse of equality operators.
Read in the index schema from a dict or yaml file.
Check if MemoryDB index exists.
Cut off the text as soon as any stop words occur.
