(langchain.document_loaders.AZLyricsLoader method)
(langchain.document_loaders.AzureBlobStorageContainerLoader method)
(langchain.document_loaders.AzureBlobStorageFileLoader method)
(langchain.document_loaders.BibtexLoader method)
(langchain.document_loaders.BigQueryLoader method)
(langchain.document_loaders.BiliBiliLoader method)
(langchain.document_loaders.BlackboardLoader method)
(langchain.document_loaders.BlockchainDocumentLoader method)
(langchain.document_loaders.BSHTMLLoader method)
(langchain.document_loaders.ChatGPTLoader method)
(langchain.document_loaders.CollegeConfidentialLoader method)
(langchain.document_loaders.ConfluenceLoader method)
(langchain.document_loaders.CoNLLULoader method)
(langchain.document_loaders.CSVLoader method)
(langchain.document_loaders.DataFrameLoader method)
(langchain.document_loaders.DiffbotLoader method)
(langchain.document_loaders.DirectoryLoader method)
(langchain.document_loaders.DiscordChatLoader method)
(langchain.document_loaders.DocugamiLoader method)
(langchain.document_loaders.Docx2txtLoader method)
(langchain.document_loaders.DuckDBLoader method)
(langchain.document_loaders.EverNoteLoader method)
(langchain.document_loaders.FacebookChatLoader method)
(langchain.document_loaders.FigmaFileLoader method)
(langchain.document_loaders.GCSDirectoryLoader method)
(langchain.document_loaders.GCSFileLoader method)
(langchain.document_loaders.GitbookLoader method)
(langchain.document_loaders.GitHubIssuesLoader method)
(langchain.document_loaders.GitLoader method)
(langchain.document_loaders.GoogleApiYoutubeLoader method)
(langchain.document_loaders.GoogleDriveLoader method)
(langchain.document_loaders.GutenbergLoader method)
(langchain.document_loaders.HNLoader method)


(langchain.document_loaders.HNLoader method)
(langchain.document_loaders.HuggingFaceDatasetLoader method)
(langchain.document_loaders.IFixitLoader method)
(langchain.document_loaders.ImageCaptionLoader method)
(langchain.document_loaders.IMSDbLoader method)
(langchain.document_loaders.IuguLoader method)
(langchain.document_loaders.JoplinLoader method)
(langchain.document_loaders.JSONLoader method)
(langchain.document_loaders.MastodonTootsLoader method)
(langchain.document_loaders.MathpixPDFLoader method)
(langchain.document_loaders.MaxComputeLoader method)
(langchain.document_loaders.ModernTreasuryLoader method)
(langchain.document_loaders.MWDumpLoader method)
(langchain.document_loaders.NotebookLoader method)
(langchain.document_loaders.NotionDBLoader method)
(langchain.document_loaders.NotionDirectoryLoader method)
(langchain.document_loaders.ObsidianLoader method)
(langchain.document_loaders.OneDriveFileLoader method)
(langchain.document_loaders.OneDriveLoader method)
(langchain.document_loaders.OnlinePDFLoader method)
(langchain.document_loaders.OutlookMessageLoader method)
(langchain.document_loaders.PDFMinerLoader method)
(langchain.document_loaders.PDFMinerPDFasHTMLLoader method)
(langchain.document_loaders.PDFPlumberLoader method)
(langchain.document_loaders.PlaywrightURLLoader method)
(langchain.document_loaders.PsychicLoader method)
(langchain.document_loaders.PyMuPDFLoader method)
(langchain.document_loaders.PyPDFDirectoryLoader method)
(langchain.document_loaders.PyPDFium2Loader method)
(langchain.document_loaders.PyPDFLoader method)
(langchain.document_loaders.PySparkDataFrameLoader method)
(langchain.document_loaders.ReadTheDocsLoader method)


(langchain.document_loaders.ReadTheDocsLoader method)
(langchain.document_loaders.RedditPostsLoader method)
(langchain.document_loaders.RoamLoader method)
(langchain.document_loaders.S3DirectoryLoader method)
(langchain.document_loaders.S3FileLoader method)
(langchain.document_loaders.SeleniumURLLoader method)
(langchain.document_loaders.SitemapLoader method)
(langchain.document_loaders.SlackDirectoryLoader method)
(langchain.document_loaders.SpreedlyLoader method)
(langchain.document_loaders.SRTLoader method)
(langchain.document_loaders.StripeLoader method)
(langchain.document_loaders.TelegramChatApiLoader method)
(langchain.document_loaders.TelegramChatFileLoader method)
(langchain.document_loaders.TextLoader method)
(langchain.document_loaders.ToMarkdownLoader method)
(langchain.document_loaders.TomlLoader method)
(langchain.document_loaders.TrelloLoader method)
(langchain.document_loaders.TwitterTweetLoader method)
(langchain.document_loaders.UnstructuredURLLoader method)
(langchain.document_loaders.WeatherDataLoader method)
(langchain.document_loaders.WebBaseLoader method)
(langchain.document_loaders.WhatsAppChatLoader method)
(langchain.document_loaders.WikipediaLoader method)
(langchain.document_loaders.YoutubeLoader method)
(langchain.utilities.ArxivAPIWrapper method)
(langchain.utilities.PubMedAPIWrapper method)
(langchain.utilities.WikipediaAPIWrapper method)
load_agent() (in module langchain.agents)
load_all_available_meta (langchain.utilities.ArxivAPIWrapper attribute)
(langchain.utilities.PubMedAPIWrapper attribute)
(langchain.utilities.WikipediaAPIWrapper attribute)
load_all_recursively (langchain.document_loaders.BlackboardLoader attribute)
load_chain() (in module langchain.chains)


load_chain() (in module langchain.chains)
load_comments() (langchain.document_loaders.HNLoader method)
load_device() (langchain.document_loaders.IFixitLoader method)
load_docs() (langchain.utilities.PubMedAPIWrapper method)
load_file() (langchain.document_loaders.DirectoryLoader method)
load_fn_kwargs (langchain.embeddings.SelfHostedHuggingFaceEmbeddings attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.SelfHostedPipeline attribute)
load_guide() (langchain.document_loaders.IFixitLoader method)
load_huggingface_tool() (in module langchain.agents)
load_local() (langchain.vectorstores.Annoy class method)
(langchain.vectorstores.FAISS class method)
load_max_docs (langchain.utilities.ArxivAPIWrapper attribute)
(langchain.utilities.PubMedAPIWrapper attribute)
load_memory_variables() (langchain.experimental.GenerativeAgentMemory method)
(langchain.memory.CombinedMemory method)
(langchain.memory.ConversationBufferMemory method)
(langchain.memory.ConversationBufferWindowMemory method)
(langchain.memory.ConversationEntityMemory method)
(langchain.memory.ConversationKGMemory method)
(langchain.memory.ConversationStringBufferMemory method)
(langchain.memory.ConversationSummaryBufferMemory method)
(langchain.memory.ConversationSummaryMemory method)
(langchain.memory.ConversationTokenBufferMemory method)
(langchain.memory.ReadOnlySharedMemory method)
(langchain.memory.SimpleMemory method)
(langchain.memory.VectorStoreRetrieverMemory method)
load_messages() (langchain.memory.CosmosDBChatMessageHistory method)
load_page() (langchain.document_loaders.NotionDBLoader method)
load_prompt() (in module langchain.prompts)


load_prompt() (in module langchain.prompts)
load_questions_and_answers() (langchain.document_loaders.IFixitLoader method)
load_results() (langchain.document_loaders.HNLoader method)
load_suggestions() (langchain.document_loaders.IFixitLoader static method)
load_tools() (in module langchain.agents)
load_trashed_files (langchain.document_loaders.GoogleDriveLoader attribute)
locals (langchain.python.PythonREPL attribute)
(langchain.utilities.PythonREPL attribute)
location (langchain.llms.VertexAI attribute)
log_probs (langchain.llms.AlephAlpha attribute)
logit_bias (langchain.llms.AlephAlpha attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
logitBias (langchain.llms.AI21 attribute)
logits_all (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
logprobs (langchain.llms.LlamaCpp attribute)
(langchain.llms.Writer attribute)
lookup_tool() (langchain.agents.AgentExecutor method)
lora_base (langchain.llms.LlamaCpp attribute)
lora_path (langchain.llms.LlamaCpp attribute)
M
MARKDOWN (langchain.text_splitter.Language attribute)
MarkdownTextSplitter (class in langchain.text_splitter)
MastodonTootsLoader (class in langchain.document_loaders)
MathpixPDFLoader (class in langchain.document_loaders)
max_checks (langchain.chains.LLMSummarizationCheckerChain attribute)
max_execution_time (langchain.agents.AgentExecutor attribute)


max_execution_time (langchain.agents.AgentExecutor attribute)
max_iter (langchain.chains.FlareChain attribute)
max_iterations (langchain.agents.agent_toolkits.PowerBIToolkit attribute)
(langchain.agents.AgentExecutor attribute)
(langchain.tools.QueryPowerBITool attribute)
max_length (langchain.llms.NLPCloud attribute)
(langchain.llms.Petals attribute)
(langchain.prompts.example_selector.LengthBasedExampleSelector attribute)
max_marginal_relevance_search() (langchain.vectorstores.Annoy method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.Qdrant method)
(langchain.vectorstores.SKLearnVectorStore method)
(langchain.vectorstores.SupabaseVectorStore method)
(langchain.vectorstores.VectorStore method)
(langchain.vectorstores.Weaviate method)
max_marginal_relevance_search_by_vector() (langchain.vectorstores.Annoy method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.SKLearnVectorStore method)
(langchain.vectorstores.SupabaseVectorStore method)
(langchain.vectorstores.VectorStore method)
(langchain.vectorstores.Weaviate method)
max_new_tokens (langchain.llms.Petals attribute)
max_output_tokens (langchain.llms.GooglePalm attribute)
(langchain.llms.VertexAI attribute)
max_results (langchain.utilities.DuckDuckGoSearchAPIWrapper attribute)
max_retries (langchain.chat_models.ChatOpenAI attribute)
(langchain.embeddings.OpenAIEmbeddings attribute)
(langchain.llms.AzureOpenAI attribute)


(langchain.llms.AzureOpenAI attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.PromptLayerOpenAIChat attribute)
max_token_limit (langchain.memory.ConversationSummaryBufferMemory attribute)
(langchain.memory.ConversationTokenBufferMemory attribute)
max_tokens (langchain.chat_models.ChatOpenAI attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.Cohere attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.PredictionGuard attribute)
(langchain.llms.Writer attribute)
max_tokens_for_prompt() (langchain.llms.AzureOpenAI method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenLM method)
(langchain.llms.PromptLayerOpenAI method)
max_tokens_limit (langchain.chains.ConversationalRetrievalChain attribute)
(langchain.chains.RetrievalQAWithSourcesChain attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)
max_tokens_per_generation (langchain.llms.RWKV attribute)
max_tokens_to_sample (langchain.llms.Anthropic attribute)
MaxComputeLoader (class in langchain.document_loaders)
maximum_tokens (langchain.llms.AlephAlpha attribute)
maxTokens (langchain.llms.AI21 attribute)
memories (langchain.memory.CombinedMemory attribute)
(langchain.memory.SimpleMemory attribute)
memory (langchain.chains.ConversationChain attribute)
(langchain.experimental.GenerativeAgent attribute)
(langchain.memory.ReadOnlySharedMemory attribute)
memory_key (langchain.memory.ConversationSummaryBufferMemory attribute)


memory_key (langchain.memory.ConversationSummaryBufferMemory attribute)
(langchain.memory.ConversationTokenBufferMemory attribute)
(langchain.memory.VectorStoreRetrieverMemory attribute)
memory_retriever (langchain.experimental.GenerativeAgentMemory attribute)
memory_stream (langchain.retrievers.TimeWeightedVectorStoreRetriever attribute)
memory_variables (langchain.experimental.GenerativeAgentMemory property)
(langchain.memory.CombinedMemory property)
(langchain.memory.ConversationStringBufferMemory property)
(langchain.memory.ReadOnlySharedMemory property)
(langchain.memory.SimpleMemory property)
(langchain.memory.VectorStoreRetrieverMemory property)
mentioned (langchain.document_loaders.GitHubIssuesLoader attribute)
merge_from() (langchain.vectorstores.FAISS method)
messages (langchain.memory.CassandraChatMessageHistory property)
(langchain.memory.ChatMessageHistory attribute)
(langchain.memory.DynamoDBChatMessageHistory property)
(langchain.memory.FileChatMessageHistory property)
(langchain.memory.MomentoChatMessageHistory property)
(langchain.memory.MongoDBChatMessageHistory property)
(langchain.memory.PostgresChatMessageHistory property)
(langchain.memory.RedisChatMessageHistory property)
metadata_column (langchain.vectorstores.MyScale property)
metadata_key (langchain.retrievers.RemoteLangChainRetriever attribute)
METADATA_KEY (langchain.vectorstores.Qdrant attribute)
MetalRetriever (class in langchain.retrievers)
metaphor_api_key (langchain.utilities.MetaphorSearchAPIWrapper attribute)
method (langchain.tools.APIOperation attribute)
metric (langchain.vectorstores.MyScaleSettings attribute)
milestone (langchain.document_loaders.GitHubIssuesLoader attribute)
Milvus (class in langchain.vectorstores)
min_chunk_size (langchain.document_loaders.DocugamiLoader attribute)


min_chunk_size (langchain.document_loaders.DocugamiLoader attribute)
min_length (langchain.llms.NLPCloud attribute)
min_prob (langchain.chains.FlareChain attribute)
min_token_gap (langchain.chains.FlareChain attribute)
min_tokens (langchain.llms.GooseAI attribute)
(langchain.llms.Writer attribute)
minimax_api_key (langchain.embeddings.MiniMaxEmbeddings attribute)
minimax_group_id (langchain.embeddings.MiniMaxEmbeddings attribute)
minimum_tokens (langchain.llms.AlephAlpha attribute)
minTokens (langchain.llms.AI21 attribute)
model (langchain.embeddings.AlephAlphaAsymmetricSemanticEmbedding attribute)
(langchain.embeddings.CohereEmbeddings attribute)
(langchain.embeddings.MiniMaxEmbeddings attribute)
(langchain.llms.AI21 attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.Cohere attribute)
(langchain.llms.CTransformers attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.PredictionGuard attribute)
(langchain.llms.RWKV attribute)
(langchain.retrievers.document_compressors.CohereRerank attribute)
model_file (langchain.llms.CTransformers attribute)
model_id (langchain.embeddings.BedrockEmbeddings attribute)
(langchain.embeddings.ModelScopeEmbeddings attribute)
(langchain.embeddings.SelfHostedHuggingFaceEmbeddings attribute)
(langchain.embeddings.SelfHostedHuggingFaceInstructEmbeddings attribute)
(langchain.llms.Bedrock attribute)
(langchain.llms.HuggingFacePipeline attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.Writer attribute)


(langchain.llms.Writer attribute)
model_key (langchain.llms.Banana attribute)
model_kwargs (langchain.chat_models.ChatOpenAI attribute)
(langchain.embeddings.BedrockEmbeddings attribute)
(langchain.embeddings.HuggingFaceEmbeddings attribute)
(langchain.embeddings.HuggingFaceHubEmbeddings attribute)
(langchain.embeddings.HuggingFaceInstructEmbeddings attribute)
(langchain.embeddings.SagemakerEndpointEmbeddings attribute)
(langchain.llms.Anyscale attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.Banana attribute)
(langchain.llms.Beam attribute)
(langchain.llms.Bedrock attribute)
(langchain.llms.CerebriumAI attribute)
(langchain.llms.Databricks attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.HuggingFaceEndpoint attribute)
(langchain.llms.HuggingFaceHub attribute)
(langchain.llms.HuggingFacePipeline attribute)
(langchain.llms.Modal attribute)
(langchain.llms.MosaicML attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.PromptLayerOpenAIChat attribute)
(langchain.llms.SagemakerEndpoint attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.StochasticAI attribute)
model_load_fn (langchain.embeddings.SelfHostedHuggingFaceEmbeddings attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.SelfHostedPipeline attribute)
model_name (langchain.chains.OpenAIModerationChain attribute)
(langchain.chat_models.ChatGooglePalm attribute)


(langchain.chat_models.ChatGooglePalm attribute)
(langchain.chat_models.ChatOpenAI attribute)
(langchain.chat_models.ChatVertexAI attribute)
(langchain.embeddings.HuggingFaceEmbeddings attribute)
(langchain.embeddings.HuggingFaceInstructEmbeddings attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.PromptLayerOpenAIChat attribute)
(langchain.tools.SteamshipImageGenerationTool attribute)
model_path (langchain.llms.LlamaCpp attribute)
model_reqs (langchain.embeddings.SelfHostedHuggingFaceEmbeddings attribute)
(langchain.embeddings.SelfHostedHuggingFaceInstructEmbeddings attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.SelfHostedPipeline attribute)
model_type (langchain.llms.CTransformers attribute)
model_url (langchain.embeddings.TensorflowHubEmbeddings attribute)
modelname_to_contextsize() (langchain.llms.AzureOpenAI method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenLM method)
(langchain.llms.PromptLayerOpenAI method)
ModernTreasuryLoader (class in langchain.document_loaders)
    module

langchain.agents
langchain.agents.agent_toolkits
langchain.chains
langchain.chat_models
langchain.docstore
langchain.document_loaders
langchain.document_transformers
langchain.embeddings
langchain.llms
langchain.memory
langchain.output_parsers
langchain.prompts


langchain.llms
langchain.memory
langchain.output_parsers
langchain.prompts
langchain.prompts.example_selector
langchain.python
langchain.retrievers
langchain.retrievers.document_compressors
langchain.serpapi
langchain.text_splitter
langchain.tools
langchain.utilities
langchain.utilities.searx_search
langchain.vectorstores
MomentoChatMessageHistory (class in langchain.memory)
MongoDBAtlasVectorSearch (class in langchain.vectorstores)
MongoDBChatMessageHistory (class in langchain.memory)
moving_summary_buffer (langchain.memory.ConversationSummaryBufferMemory attribute)
MWDumpLoader (class in langchain.document_loaders)
MyScale (class in langchain.vectorstores)
N
n (langchain.chat_models.ChatGooglePalm attribute)
(langchain.chat_models.ChatOpenAI attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Writer attribute)
n_batch (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
n_ctx (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
n_gpu_layers (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.LlamaCpp attribute)
n_parts (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
n_predict (langchain.llms.GPT4All attribute)


n_predict (langchain.llms.GPT4All attribute)
n_threads (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
name (langchain.agents.agent_toolkits.VectorStoreInfo attribute)
(langchain.experimental.GenerativeAgent attribute)
(langchain.output_parsers.ResponseSchema attribute)
(langchain.tools.BaseTool attribute)
(langchain.tools.ClickTool attribute)
(langchain.tools.CopyFileTool attribute)
(langchain.tools.CurrentWebPageTool attribute)
(langchain.tools.DeleteFileTool attribute)
(langchain.tools.ExtractHyperlinksTool attribute)
(langchain.tools.ExtractTextTool attribute)
(langchain.tools.FileSearchTool attribute)
(langchain.tools.GetElementsTool attribute)
(langchain.tools.GmailCreateDraft attribute)
(langchain.tools.GmailGetMessage attribute)
(langchain.tools.GmailGetThread attribute)
(langchain.tools.GmailSearch attribute)
(langchain.tools.GmailSendMessage attribute)
(langchain.tools.ListDirectoryTool attribute)
(langchain.tools.MoveFileTool attribute)
(langchain.tools.NavigateBackTool attribute)
(langchain.tools.NavigateTool attribute)
(langchain.tools.ReadFileTool attribute)
(langchain.tools.ShellTool attribute)
(langchain.tools.Tool attribute)
(langchain.tools.WriteFileTool attribute)
nla_tools (langchain.agents.agent_toolkits.NLAToolkit attribute)
NLTKTextSplitter (class in langchain.text_splitter)
no_update_value (langchain.output_parsers.RegexDictParser attribute)
normalize (langchain.embeddings.AlephAlphaAsymmetricSemanticEmbedding attribute)
NotebookLoader (class in langchain.document_loaders)
NotionDBLoader (class in langchain.document_loaders)
NotionDirectoryLoader (class in langchain.document_loaders)


NotionDirectoryLoader (class in langchain.document_loaders)
num_beams (langchain.llms.NLPCloud attribute)
num_pad_tokens (langchain.chains.FlareChain attribute)
num_results (langchain.tools.BingSearchResults attribute)
(langchain.tools.DuckDuckGoSearchResults attribute)
(langchain.tools.GoogleSearchResults attribute)
num_return_sequences (langchain.llms.NLPCloud attribute)
numResults (langchain.llms.AI21 attribute)
O
object_ids (langchain.document_loaders.OneDriveLoader attribute)
observation_prefix (langchain.agents.Agent property)
(langchain.agents.ConversationalAgent property)
(langchain.agents.ConversationalChatAgent property)
(langchain.agents.StructuredChatAgent property)
(langchain.agents.ZeroShotAgent property)
ObsidianLoader (class in langchain.document_loaders)
OnlinePDFLoader (class in langchain.document_loaders)
openai_api_base (langchain.chat_models.AzureChatOpenAI attribute)
(langchain.chat_models.ChatOpenAI attribute)
openai_api_key (langchain.chains.OpenAIModerationChain attribute)
(langchain.chat_models.AzureChatOpenAI attribute)
(langchain.chat_models.ChatOpenAI attribute)
openai_api_type (langchain.chat_models.AzureChatOpenAI attribute)
openai_api_version (langchain.chat_models.AzureChatOpenAI attribute)
openai_organization (langchain.chains.OpenAIModerationChain attribute)
(langchain.chat_models.AzureChatOpenAI attribute)
(langchain.chat_models.ChatOpenAI attribute)
openai_proxy (langchain.chat_models.AzureChatOpenAI attribute)
(langchain.chat_models.ChatOpenAI attribute)
OpenSearchVectorSearch (class in langchain.vectorstores)
openweathermap_api_key (langchain.utilities.OpenWeatherMapAPIWrapper attribute)
operation_id (langchain.tools.APIOperation attribute)


operation_id (langchain.tools.APIOperation attribute)
other_score_keys (langchain.retrievers.TimeWeightedVectorStoreRetriever attribute)
OutlookMessageLoader (class in langchain.document_loaders)
output (langchain.llms.PredictionGuard attribute)
output_key (langchain.chains.QAGenerationChain attribute)
(langchain.memory.ConversationStringBufferMemory attribute)
output_key_to_format (langchain.output_parsers.RegexDictParser attribute)
output_keys (langchain.chains.ConstitutionalChain property)
(langchain.chains.FlareChain property)
(langchain.chains.HypotheticalDocumentEmbedder property)
(langchain.chains.QAGenerationChain property)
(langchain.experimental.BabyAGI property)
(langchain.output_parsers.RegexParser attribute)
output_parser (langchain.agents.Agent attribute)
(langchain.agents.ConversationalAgent attribute)
(langchain.agents.ConversationalChatAgent attribute)
(langchain.agents.LLMSingleActionAgent attribute)
(langchain.agents.StructuredChatAgent attribute)
(langchain.agents.ZeroShotAgent attribute)
(langchain.chains.FlareChain attribute)
(langchain.prompts.BasePromptTemplate attribute)
output_variables (langchain.chains.TransformChain attribute)
owm (langchain.utilities.OpenWeatherMapAPIWrapper attribute)
P
p (langchain.llms.Cohere attribute)
page_content_key (langchain.retrievers.RemoteLangChainRetriever attribute)
PagedPDFSplitter (in module langchain.document_loaders)
paginate_request() (langchain.document_loaders.ConfluenceLoader method)
param_mapping (langchain.chains.OpenAPIEndpointChain attribute)
params (langchain.serpapi.SerpAPIWrapper attribute)
(langchain.tools.ZapierNLARunAction attribute)


(langchain.tools.ZapierNLARunAction attribute)
(langchain.utilities.searx_search.SearxSearchWrapper attribute)
(langchain.utilities.SearxSearchWrapper attribute)
(langchain.utilities.SerpAPIWrapper attribute)
params_schema (langchain.tools.ZapierNLARunAction attribute)
parse() (langchain.agents.AgentOutputParser method)
(langchain.output_parsers.CommaSeparatedListOutputParser method)
(langchain.output_parsers.DatetimeOutputParser method)
(langchain.output_parsers.GuardrailsOutputParser method)
(langchain.output_parsers.ListOutputParser method)
(langchain.output_parsers.OutputFixingParser method)
(langchain.output_parsers.PydanticOutputParser method)
(langchain.output_parsers.RegexDictParser method)
(langchain.output_parsers.RegexParser method)
(langchain.output_parsers.RetryOutputParser method)
(langchain.output_parsers.RetryWithErrorOutputParser method)
(langchain.output_parsers.StructuredOutputParser method)
parse_filename() (langchain.document_loaders.BlackboardLoader method)
parse_issue() (langchain.document_loaders.GitHubIssuesLoader method)
parse_obj() (langchain.tools.OpenAPISpec class method)
parse_sitemap() (langchain.document_loaders.SitemapLoader method)
parse_with_prompt() (langchain.output_parsers.RetryOutputParser method)
(langchain.output_parsers.RetryWithErrorOutputParser method)
parser (langchain.output_parsers.OutputFixingParser attribute)
(langchain.output_parsers.RetryOutputParser attribute)
(langchain.output_parsers.RetryWithErrorOutputParser attribute)
partial() (langchain.prompts.BasePromptTemplate method)
(langchain.prompts.ChatPromptTemplate method)
password (langchain.vectorstores.MyScaleSettings attribute)
patch() (langchain.utilities.TextRequestsWrapper method)


patch() (langchain.utilities.TextRequestsWrapper method)
path (langchain.tools.APIOperation attribute)
path_params (langchain.tools.APIOperation property)
pause_to_reflect() (langchain.experimental.GenerativeAgentMemory method)
PDFMinerLoader (class in langchain.document_loaders)
PDFMinerPDFasHTMLLoader (class in langchain.document_loaders)
PDFPlumberLoader (class in langchain.document_loaders)
penalty_alpha_frequency (langchain.llms.RWKV attribute)
penalty_alpha_presence (langchain.llms.RWKV attribute)
penalty_bias (langchain.llms.AlephAlpha attribute)
penalty_exceptions (langchain.llms.AlephAlpha attribute)
penalty_exceptions_include_stop_sequences (langchain.llms.AlephAlpha attribute)
persist() (langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.SKLearnVectorStore method)
PHP (langchain.text_splitter.Language attribute)
Pinecone (class in langchain.vectorstores)
pipeline_key (langchain.llms.PipelineAI attribute)
pipeline_kwargs (langchain.llms.HuggingFacePipeline attribute)
(langchain.llms.PipelineAI attribute)
pl_tags (langchain.chat_models.PromptLayerChatOpenAI attribute)
plan() (langchain.agents.Agent method)
(langchain.agents.BaseMultiActionAgent method)
(langchain.agents.BaseSingleActionAgent method)
(langchain.agents.LLMSingleActionAgent method)
playwright_strict (langchain.tools.ClickTool attribute)
playwright_timeout (langchain.tools.ClickTool attribute)
PlaywrightURLLoader (class in langchain.document_loaders)
plugin (langchain.tools.AIPluginTool attribute)
port (langchain.vectorstores.MyScaleSettings attribute)
post() (langchain.utilities.TextRequestsWrapper method)


post() (langchain.utilities.TextRequestsWrapper method)
PostgresChatMessageHistory (class in langchain.memory)
powerbi (langchain.agents.agent_toolkits.PowerBIToolkit attribute)
(langchain.tools.InfoPowerBITool attribute)
(langchain.tools.ListPowerBITool attribute)
(langchain.tools.QueryPowerBITool attribute)
predict() (langchain.chains.LLMChain method)
(langchain.llms.AI21 method)
(langchain.llms.AlephAlpha method)
(langchain.llms.Anthropic method)
(langchain.llms.Anyscale method)
(langchain.llms.AzureOpenAI method)
(langchain.llms.Banana method)
(langchain.llms.Beam method)
(langchain.llms.Bedrock method)
(langchain.llms.CerebriumAI method)
(langchain.llms.Cohere method)
(langchain.llms.CTransformers method)
(langchain.llms.Databricks method)
(langchain.llms.DeepInfra method)
(langchain.llms.FakeListLLM method)
(langchain.llms.ForefrontAI method)
(langchain.llms.GooglePalm method)
(langchain.llms.GooseAI method)
(langchain.llms.GPT4All method)
(langchain.llms.HuggingFaceEndpoint method)
(langchain.llms.HuggingFaceHub method)
(langchain.llms.HuggingFacePipeline method)
(langchain.llms.HuggingFaceTextGenInference method)
(langchain.llms.HumanInputLLM method)
(langchain.llms.LlamaCpp method)
(langchain.llms.Modal method)
(langchain.llms.MosaicML method)
(langchain.llms.NLPCloud method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenAIChat method)
(langchain.llms.OpenLM method)


(langchain.llms.OpenAIChat method)
(langchain.llms.OpenLM method)
(langchain.llms.Petals method)
(langchain.llms.PipelineAI method)
(langchain.llms.PredictionGuard method)
(langchain.llms.PromptLayerOpenAI method)
(langchain.llms.PromptLayerOpenAIChat method)
(langchain.llms.Replicate method)
(langchain.llms.RWKV method)
(langchain.llms.SagemakerEndpoint method)
(langchain.llms.SelfHostedHuggingFaceLLM method)
(langchain.llms.SelfHostedPipeline method)
(langchain.llms.StochasticAI method)
(langchain.llms.VertexAI method)
(langchain.llms.Writer method)
predict_and_parse() (langchain.chains.LLMChain method)
predict_messages() (langchain.llms.AI21 method)
(langchain.llms.AlephAlpha method)
(langchain.llms.Anthropic method)
(langchain.llms.Anyscale method)
(langchain.llms.AzureOpenAI method)
(langchain.llms.Banana method)
(langchain.llms.Beam method)
(langchain.llms.Bedrock method)
(langchain.llms.CerebriumAI method)
(langchain.llms.Cohere method)
(langchain.llms.CTransformers method)
(langchain.llms.Databricks method)
(langchain.llms.DeepInfra method)
(langchain.llms.FakeListLLM method)
(langchain.llms.ForefrontAI method)
(langchain.llms.GooglePalm method)
(langchain.llms.GooseAI method)
(langchain.llms.GPT4All method)
(langchain.llms.HuggingFaceEndpoint method)
(langchain.llms.HuggingFaceHub method)
(langchain.llms.HuggingFacePipeline method)


(langchain.llms.HuggingFacePipeline method)
(langchain.llms.HuggingFaceTextGenInference method)
(langchain.llms.HumanInputLLM method)
(langchain.llms.LlamaCpp method)
(langchain.llms.Modal method)
(langchain.llms.MosaicML method)
(langchain.llms.NLPCloud method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenAIChat method)
(langchain.llms.OpenLM method)
(langchain.llms.Petals method)
(langchain.llms.PipelineAI method)
(langchain.llms.PredictionGuard method)
(langchain.llms.PromptLayerOpenAI method)
(langchain.llms.PromptLayerOpenAIChat method)
(langchain.llms.Replicate method)
(langchain.llms.RWKV method)
(langchain.llms.SagemakerEndpoint method)
(langchain.llms.SelfHostedHuggingFaceLLM method)
(langchain.llms.SelfHostedPipeline method)
(langchain.llms.StochasticAI method)
(langchain.llms.VertexAI method)
(langchain.llms.Writer method)
prefix (langchain.prompts.FewShotPromptTemplate attribute)
(langchain.prompts.FewShotPromptWithTemplates attribute)
prefix_messages (langchain.llms.OpenAIChat attribute)
(langchain.llms.PromptLayerOpenAIChat attribute)
prep_prompts() (langchain.chains.LLMChain method)
prep_streaming_params() (langchain.llms.AzureOpenAI method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenLM method)
(langchain.llms.PromptLayerOpenAI method)
prepare_cosmos() (langchain.memory.CosmosDBChatMessageHistory method)
presence_penalty (langchain.llms.AlephAlpha attribute)


presence_penalty (langchain.llms.AlephAlpha attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.Cohere attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Writer attribute)
presencePenalty (langchain.llms.AI21 attribute)
prioritize_tasks() (langchain.experimental.BabyAGI method)
process (langchain.tools.ShellTool attribute)
process_attachment() (langchain.document_loaders.ConfluenceLoader method)
process_doc() (langchain.document_loaders.ConfluenceLoader method)
process_image() (langchain.document_loaders.ConfluenceLoader method)
process_index_results() (langchain.vectorstores.Annoy method)
process_output() (langchain.utilities.BashProcess method)
process_page() (langchain.document_loaders.ConfluenceLoader method)
process_pages() (langchain.document_loaders.ConfluenceLoader method)
process_pdf() (langchain.document_loaders.ConfluenceLoader method)
process_svg() (langchain.document_loaders.ConfluenceLoader method)
process_xls() (langchain.document_loaders.ConfluenceLoader method)
project (langchain.llms.VertexAI attribute)
Prompt (in module langchain.prompts)
prompt (langchain.chains.ConversationChain attribute)
(langchain.chains.LLMBashChain attribute)
(langchain.chains.LLMChain attribute)
(langchain.chains.LLMMathChain attribute)
(langchain.chains.PALChain attribute)
(langchain.chains.SQLDatabaseChain attribute)
prompt_func (langchain.tools.HumanInputRun attribute)
properties (langchain.tools.APIOperation attribute)
PROTO (langchain.text_splitter.Language attribute)
prune() (langchain.memory.ConversationSummaryBufferMemory method)


prune() (langchain.memory.ConversationSummaryBufferMemory method)
PsychicLoader (class in langchain.document_loaders)
put() (langchain.utilities.TextRequestsWrapper method)
pydantic_object (langchain.output_parsers.PydanticOutputParser attribute)
PyMuPDFLoader (class in langchain.document_loaders)
PyPDFDirectoryLoader (class in langchain.document_loaders)
PyPDFium2Loader (class in langchain.document_loaders)
PyPDFLoader (class in langchain.document_loaders)
PySparkDataFrameLoader (class in langchain.document_loaders)
PYTHON (langchain.text_splitter.Language attribute)
python_globals (langchain.chains.PALChain attribute)
python_locals (langchain.chains.PALChain attribute)
PythonCodeTextSplitter (class in langchain.text_splitter)
PythonLoader (class in langchain.document_loaders)
Q
qa_chain (langchain.chains.GraphCypherQAChain attribute)
(langchain.chains.GraphQAChain attribute)
Qdrant (class in langchain.vectorstores)
query_checker_prompt (langchain.chains.SQLDatabaseChain attribute)
query_instruction (langchain.embeddings.HuggingFaceInstructEmbeddings attribute)
(langchain.embeddings.MosaicMLInstructorEmbeddings attribute)
(langchain.embeddings.SelfHostedHuggingFaceInstructEmbeddings attribute)
query_name (langchain.vectorstores.SupabaseVectorStore attribute)
query_params (langchain.document_loaders.GitHubIssuesLoader property)
(langchain.tools.APIOperation property)
query_suffix (langchain.utilities.searx_search.SearxSearchWrapper attribute)
(langchain.utilities.SearxSearchWrapper attribute)
question_generator_chain (langchain.chains.FlareChain attribute)
question_to_checked_assertions_chain (langchain.chains.LLMCheckerChain attribute)
R


question_to_checked_assertions_chain (langchain.chains.LLMCheckerChain attribute)
R
raw_completion (langchain.llms.AlephAlpha attribute)
REACT_DOCSTORE (langchain.agents.AgentType attribute)
ReadTheDocsLoader (class in langchain.document_loaders)
recall_ttl (langchain.memory.RedisEntityStore attribute)
recursive (langchain.document_loaders.GoogleDriveLoader attribute)
RecursiveCharacterTextSplitter (class in langchain.text_splitter)
RedditPostsLoader (class in langchain.document_loaders)
Redis (class in langchain.vectorstores)
redis_client (langchain.memory.RedisEntityStore attribute)
RedisChatMessageHistory (class in langchain.memory)
reduce_k_below_max_tokens (langchain.chains.RetrievalQAWithSourcesChain attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)
reflection_threshold (langchain.experimental.GenerativeAgentMemory attribute)
regex (langchain.output_parsers.RegexParser attribute)
regex_pattern (langchain.output_parsers.RegexDictParser attribute)
region (langchain.utilities.DuckDuckGoSearchAPIWrapper attribute)
region_name (langchain.embeddings.BedrockEmbeddings attribute)
(langchain.embeddings.SagemakerEndpointEmbeddings attribute)
(langchain.llms.Bedrock attribute)
(langchain.llms.SagemakerEndpoint attribute)
relevancy_threshold (langchain.retrievers.KNNRetriever attribute)
(langchain.retrievers.SVMRetriever attribute)
remove_end_sequence (langchain.llms.NLPCloud attribute)
remove_input (langchain.llms.NLPCloud attribute)
repeat_last_n (langchain.llms.GPT4All attribute)
repeat_penalty (langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)


(langchain.llms.LlamaCpp attribute)
repetition_penalties_include_completion (langchain.llms.AlephAlpha attribute)
repetition_penalties_include_prompt (langchain.llms.AlephAlpha attribute)
repetition_penalty (langchain.llms.ForefrontAI attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.Writer attribute)
repo_id (langchain.embeddings.HuggingFaceHubEmbeddings attribute)
(langchain.llms.HuggingFaceHub attribute)
request_body (langchain.tools.APIOperation attribute)
request_timeout (langchain.chat_models.ChatOpenAI attribute)
(langchain.embeddings.OpenAIEmbeddings attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
request_url (langchain.utilities.PowerBIDataset property)
requests (langchain.chains.OpenAPIEndpointChain attribute)
(langchain.utilities.TextRequestsWrapper property)
requests_kwargs (langchain.document_loaders.WebBaseLoader attribute)
requests_per_second (langchain.document_loaders.WebBaseLoader attribute)
requests_wrapper (langchain.agents.agent_toolkits.OpenAPIToolkit attribute)
(langchain.chains.APIChain attribute)
(langchain.chains.LLMRequestsChain attribute)
response_chain (langchain.chains.FlareChain attribute)
response_key (langchain.retrievers.RemoteLangChainRetriever attribute)
response_schemas (langchain.output_parsers.StructuredOutputParser attribute)
results() (langchain.serpapi.SerpAPIWrapper method)
(langchain.utilities.BingSearchAPIWrapper method)
(langchain.utilities.DuckDuckGoSearchAPIWrapper method)
(langchain.utilities.GoogleSearchAPIWrapper method)
(langchain.utilities.GoogleSerperAPIWrapper method)
(langchain.utilities.MetaphorSearchAPIWrapper method)


(langchain.utilities.MetaphorSearchAPIWrapper method)
(langchain.utilities.searx_search.SearxSearchWrapper method)
(langchain.utilities.SearxSearchWrapper method)
(langchain.utilities.SerpAPIWrapper method)
results_async() (langchain.utilities.MetaphorSearchAPIWrapper method)
retrieve_article() (langchain.utilities.PubMedAPIWrapper method)
retriever (langchain.chains.ConversationalRetrievalChain attribute)
(langchain.chains.FlareChain attribute)
(langchain.chains.RetrievalQA attribute)
(langchain.chains.RetrievalQAWithSourcesChain attribute)
(langchain.memory.VectorStoreRetrieverMemory attribute)
retry_chain (langchain.output_parsers.OutputFixingParser attribute)
(langchain.output_parsers.RetryOutputParser attribute)
(langchain.output_parsers.RetryWithErrorOutputParser attribute)
retry_sleep (langchain.embeddings.MosaicMLInstructorEmbeddings attribute)
(langchain.llms.MosaicML attribute)
return_all (langchain.chains.SequentialChain attribute)
return_direct (langchain.chains.SQLDatabaseChain attribute)
(langchain.tools.BaseTool attribute)
(langchain.tools.Tool attribute)
return_docs (langchain.memory.VectorStoreRetrieverMemory attribute)
return_intermediate_steps (langchain.agents.AgentExecutor attribute)
(langchain.chains.ConstitutionalChain attribute)
(langchain.chains.OpenAPIEndpointChain attribute)
(langchain.chains.PALChain attribute)
(langchain.chains.SQLDatabaseChain attribute)
(langchain.chains.SQLDatabaseSequentialChain attribute)
return_pl_id (langchain.chat_models.PromptLayerChatOpenAI attribute)
return_stopped_response() (langchain.agents.Agent method)
(langchain.agents.BaseMultiActionAgent method)
(langchain.agents.BaseSingleActionAgent method)


(langchain.agents.BaseSingleActionAgent method)
return_urls (langchain.tools.SteamshipImageGenerationTool attribute)
return_values (langchain.agents.Agent property)
(langchain.agents.BaseMultiActionAgent property)
(langchain.agents.BaseSingleActionAgent property)
revised_answer_prompt (langchain.chains.LLMCheckerChain attribute)
revised_summary_prompt (langchain.chains.LLMSummarizationCheckerChain attribute)
revision_chain (langchain.chains.ConstitutionalChain attribute)
RoamLoader (class in langchain.document_loaders)
root_dir (langchain.agents.agent_toolkits.FileManagementToolkit attribute)
RST (langchain.text_splitter.Language attribute)
RUBY (langchain.text_splitter.Language attribute)
run() (langchain.python.PythonREPL method)
(langchain.serpapi.SerpAPIWrapper method)
(langchain.tools.BaseTool method)
(langchain.utilities.ArxivAPIWrapper method)
(langchain.utilities.BashProcess method)
(langchain.utilities.BingSearchAPIWrapper method)
(langchain.utilities.DuckDuckGoSearchAPIWrapper method)
(langchain.utilities.GooglePlacesAPIWrapper method)
(langchain.utilities.GoogleSearchAPIWrapper method)
(langchain.utilities.GoogleSerperAPIWrapper method)
(langchain.utilities.GraphQLAPIWrapper method)
(langchain.utilities.LambdaWrapper method)
(langchain.utilities.OpenWeatherMapAPIWrapper method)
(langchain.utilities.PowerBIDataset method)
(langchain.utilities.PubMedAPIWrapper method)
(langchain.utilities.PythonREPL method)
(langchain.utilities.searx_search.SearxSearchWrapper method)
(langchain.utilities.SearxSearchWrapper method)
(langchain.utilities.SerpAPIWrapper method)
(langchain.utilities.SparkSQL method)
(langchain.utilities.TwilioAPIWrapper method)
(langchain.utilities.WikipediaAPIWrapper method)


(langchain.utilities.WikipediaAPIWrapper method)
(langchain.utilities.WolframAlphaAPIWrapper method)
run_creation() (langchain.llms.Beam method)
run_no_throw() (langchain.utilities.SparkSQL method)
RUST (langchain.text_splitter.Language attribute)
rwkv_verbose (langchain.llms.RWKV attribute)
S
S3DirectoryLoader (class in langchain.document_loaders)
S3FileLoader (class in langchain.document_loaders)
safesearch (langchain.utilities.DuckDuckGoSearchAPIWrapper attribute)
sample_rows_in_table_info (langchain.utilities.PowerBIDataset attribute)
save() (langchain.agents.AgentExecutor method)
(langchain.agents.BaseMultiActionAgent method)
(langchain.agents.BaseSingleActionAgent method)
(langchain.llms.AI21 method)
(langchain.llms.AlephAlpha method)
(langchain.llms.Anthropic method)
(langchain.llms.Anyscale method)
(langchain.llms.AzureOpenAI method)
(langchain.llms.Banana method)
(langchain.llms.Beam method)
(langchain.llms.Bedrock method)
(langchain.llms.CerebriumAI method)
(langchain.llms.Cohere method)
(langchain.llms.CTransformers method)
(langchain.llms.Databricks method)
(langchain.llms.DeepInfra method)
(langchain.llms.FakeListLLM method)
(langchain.llms.ForefrontAI method)
(langchain.llms.GooglePalm method)
(langchain.llms.GooseAI method)
(langchain.llms.GPT4All method)
(langchain.llms.HuggingFaceEndpoint method)
(langchain.llms.HuggingFaceHub method)
(langchain.llms.HuggingFacePipeline method)


(langchain.llms.HuggingFacePipeline method)
(langchain.llms.HuggingFaceTextGenInference method)
(langchain.llms.HumanInputLLM method)
(langchain.llms.LlamaCpp method)
(langchain.llms.Modal method)
(langchain.llms.MosaicML method)
(langchain.llms.NLPCloud method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenAIChat method)
(langchain.llms.OpenLM method)
(langchain.llms.Petals method)
(langchain.llms.PipelineAI method)
(langchain.llms.PredictionGuard method)
(langchain.llms.PromptLayerOpenAI method)
(langchain.llms.PromptLayerOpenAIChat method)
(langchain.llms.Replicate method)
(langchain.llms.RWKV method)
(langchain.llms.SagemakerEndpoint method)
(langchain.llms.SelfHostedHuggingFaceLLM method)
(langchain.llms.SelfHostedPipeline method)
(langchain.llms.StochasticAI method)
(langchain.llms.VertexAI method)
(langchain.llms.Writer method)
(langchain.prompts.BasePromptTemplate method)
(langchain.prompts.ChatPromptTemplate method)
save_agent() (langchain.agents.AgentExecutor method)
save_context() (langchain.experimental.GenerativeAgentMemory method)
(langchain.memory.CombinedMemory method)
(langchain.memory.ConversationEntityMemory method)
(langchain.memory.ConversationKGMemory method)
(langchain.memory.ConversationStringBufferMemory method)
(langchain.memory.ConversationSummaryBufferMemory method)
(langchain.memory.ConversationSummaryMemory method)
(langchain.memory.ConversationTokenBufferMemory method)
(langchain.memory.ReadOnlySharedMemory method)
(langchain.memory.SimpleMemory method)
(langchain.memory.VectorStoreRetrieverMemory method)


(langchain.memory.SimpleMemory method)
(langchain.memory.VectorStoreRetrieverMemory method)
save_local() (langchain.vectorstores.Annoy method)
(langchain.vectorstores.FAISS method)
SCALA (langchain.text_splitter.Language attribute)
schemas (langchain.utilities.PowerBIDataset attribute)
scrape() (langchain.document_loaders.WebBaseLoader method)
scrape_all() (langchain.document_loaders.WebBaseLoader method)
scrape_page() (langchain.tools.ExtractHyperlinksTool static method)
search() (langchain.docstore.InMemoryDocstore method)
(langchain.docstore.Wikipedia method)
(langchain.vectorstores.VectorStore method)
search_kwargs (langchain.chains.ChatVectorDBChain attribute)
(langchain.chains.VectorDBQA attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)
(langchain.retrievers.SelfQueryRetriever attribute)
(langchain.retrievers.TimeWeightedVectorStoreRetriever attribute)
search_type (langchain.chains.VectorDBQA attribute)
(langchain.retrievers.SelfQueryRetriever attribute)
search_wrapper (langchain.tools.BraveSearch attribute)
searx_host (langchain.utilities.searx_search.SearxSearchWrapper attribute)
(langchain.utilities.SearxSearchWrapper attribute)
SearxResults (class in langchain.utilities.searx_search)
seed (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
select_examples() (langchain.prompts.example_selector.LengthBasedExampleSelector method)
(langchain.prompts.example_selector.MaxMarginalRelevanceExampleSelector method)
(langchain.prompts.example_selector.SemanticSimilarityExampleSelector method)


(langchain.prompts.example_selector.SemanticSimilarityExampleSelector method)
selected_tools (langchain.agents.agent_toolkits.FileManagementToolkit attribute)
SeleniumURLLoader (class in langchain.document_loaders)
SELF_ASK_WITH_SEARCH (langchain.agents.AgentType attribute)
send_pdf() (langchain.document_loaders.MathpixPDFLoader method)
SentenceTransformerEmbeddings (in module langchain.embeddings)
SentenceTransformersTokenTextSplitter (class in langchain.text_splitter)
sequential_chain (langchain.chains.LLMSummarizationCheckerChain attribute)
serpapi_api_key (langchain.serpapi.SerpAPIWrapper attribute)
(langchain.utilities.SerpAPIWrapper attribute)
serper_api_key (langchain.utilities.GoogleSerperAPIWrapper attribute)
service_account_key (langchain.document_loaders.GoogleDriveLoader attribute)
service_account_path (langchain.document_loaders.GoogleApiClient attribute)
service_name (langchain.retrievers.AzureCognitiveSearchRetriever attribute)
session_cache (langchain.tools.QueryPowerBITool attribute)
session_id (langchain.memory.RedisEntityStore attribute)
(langchain.memory.SQLiteEntityStore attribute)
set() (langchain.memory.InMemoryEntityStore method)
(langchain.memory.RedisEntityStore method)
(langchain.memory.SQLiteEntityStore method)
settings (langchain.document_loaders.OneDriveLoader attribute)
similarity_fn (langchain.document_transformers.EmbeddingsRedundantFilter attribute)
(langchain.retrievers.document_compressors.EmbeddingsFilter attribute)
similarity_search() (langchain.vectorstores.AnalyticDB method)
(langchain.vectorstores.Annoy method)
(langchain.vectorstores.AtlasDB method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.ElasticVectorSearch method)


(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.ElasticVectorSearch method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.LanceDB method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.MongoDBAtlasVectorSearch method)
(langchain.vectorstores.MyScale method)
(langchain.vectorstores.OpenSearchVectorSearch method)
(langchain.vectorstores.Pinecone method)
(langchain.vectorstores.Qdrant method)
(langchain.vectorstores.Redis method)
(langchain.vectorstores.SKLearnVectorStore method)
(langchain.vectorstores.SupabaseVectorStore method)
(langchain.vectorstores.Tair method)
(langchain.vectorstores.Typesense method)
(langchain.vectorstores.Vectara method)
(langchain.vectorstores.VectorStore method)
(langchain.vectorstores.Weaviate method)
similarity_search_by_index() (langchain.vectorstores.Annoy method)
similarity_search_by_text() (langchain.vectorstores.Weaviate method)
similarity_search_by_vector() (langchain.vectorstores.AnalyticDB method)
(langchain.vectorstores.Annoy method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.MyScale method)
(langchain.vectorstores.SupabaseVectorStore method)
(langchain.vectorstores.VectorStore method)
(langchain.vectorstores.Weaviate method)
similarity_search_by_vector_returning_embeddings() (langchain.vectorstores.SupabaseVectorStore method)
similarity_search_by_vector_with_relevance_scores() (langchain.vectorstores.SupabaseVectorStore method)
similarity_search_limit_score() (langchain.vectorstores.Redis method)
similarity_search_with_relevance_scores() (langchain.vectorstores.MyScale method)


similarity_search_with_relevance_scores() (langchain.vectorstores.MyScale method)
(langchain.vectorstores.SupabaseVectorStore method)
(langchain.vectorstores.VectorStore method)
similarity_search_with_score() (langchain.vectorstores.AnalyticDB method)
(langchain.vectorstores.Annoy method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.ElasticVectorSearch method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.MongoDBAtlasVectorSearch method)
(langchain.vectorstores.OpenSearchVectorSearch method)
(langchain.vectorstores.Pinecone method)
(langchain.vectorstores.Qdrant method)
(langchain.vectorstores.Redis method)
(langchain.vectorstores.SKLearnVectorStore method)
(langchain.vectorstores.Typesense method)
(langchain.vectorstores.Vectara method)
(langchain.vectorstores.Weaviate method)
similarity_search_with_score_by_index() (langchain.vectorstores.Annoy method)
similarity_search_with_score_by_vector() (langchain.vectorstores.AnalyticDB method)
(langchain.vectorstores.Annoy method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Milvus method)
similarity_threshold (langchain.document_transformers.EmbeddingsRedundantFilter attribute)
(langchain.retrievers.document_compressors.EmbeddingsFilter attribute)
since (langchain.document_loaders.GitHubIssuesLoader attribute)
SitemapLoader (class in langchain.document_loaders)
siterestrict (langchain.utilities.GoogleSearchAPIWrapper attribute)
size (langchain.tools.SteamshipImageGenerationTool attribute)
SKLearnVectorStore (class in langchain.vectorstores)
SlackDirectoryLoader (class in langchain.document_loaders)


SlackDirectoryLoader (class in langchain.document_loaders)
sort (langchain.document_loaders.GitHubIssuesLoader attribute)
SpacyTextSplitter (class in langchain.text_splitter)
SparkSQL (class in langchain.utilities)
sparse_encoder (langchain.retrievers.PineconeHybridSearchRetriever attribute)
spec (langchain.agents.agent_toolkits.JsonToolkit attribute)
split_documents() (langchain.text_splitter.TextSplitter method)
split_text() (langchain.text_splitter.CharacterTextSplitter method)
(langchain.text_splitter.NLTKTextSplitter method)
(langchain.text_splitter.RecursiveCharacterTextSplitter method)
(langchain.text_splitter.SentenceTransformersTokenTextSplitter method)
(langchain.text_splitter.SpacyTextSplitter method)
(langchain.text_splitter.TextSplitter method)
(langchain.text_splitter.TokenTextSplitter method)
split_text_on_tokens() (in module langchain.text_splitter)
SpreedlyLoader (class in langchain.document_loaders)
sql_chain (langchain.chains.SQLDatabaseSequentialChain attribute)
SRTLoader (class in langchain.document_loaders)
start_with_retrieval (langchain.chains.FlareChain attribute)
state (langchain.document_loaders.GitHubIssuesLoader attribute)
status (langchain.experimental.GenerativeAgent attribute)
steamship (langchain.tools.SteamshipImageGenerationTool attribute)
stop (langchain.agents.LLMSingleActionAgent attribute)
(langchain.chains.PALChain attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.Writer attribute)
stop_sequences (langchain.llms.AlephAlpha attribute)
store (langchain.memory.InMemoryEntityStore attribute)


store (langchain.memory.InMemoryEntityStore attribute)
strategy (langchain.llms.RWKV attribute)
stream() (langchain.llms.Anthropic method)
(langchain.llms.AzureOpenAI method)
(langchain.llms.LlamaCpp method)
(langchain.llms.OpenAI method)
(langchain.llms.OpenLM method)
(langchain.llms.PromptLayerOpenAI method)
streaming (langchain.chat_models.ChatOpenAI attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.PromptLayerOpenAIChat attribute)
strip_outputs (langchain.chains.SimpleSequentialChain attribute)
StripeLoader (class in langchain.document_loaders)
STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION (langchain.agents.AgentType attribute)
structured_query_translator (langchain.retrievers.SelfQueryRetriever attribute)
suffix (langchain.llms.LlamaCpp attribute)
(langchain.prompts.FewShotPromptTemplate attribute)
(langchain.prompts.FewShotPromptWithTemplates attribute)
summarize_related_memories() (langchain.experimental.GenerativeAgent method)
summary (langchain.experimental.GenerativeAgent attribute)
summary_message_cls (langchain.memory.ConversationKGMemory attribute)
summary_refresh_seconds (langchain.experimental.GenerativeAgent attribute)
SupabaseVectorStore (class in langchain.vectorstores)
SWIFT (langchain.text_splitter.Language attribute)
sync_browser (langchain.agents.agent_toolkits.PlayWrightBrowserToolkit attribute)
T
table (langchain.vectorstores.MyScaleSettings attribute)


T
table (langchain.vectorstores.MyScaleSettings attribute)
table_info (langchain.utilities.PowerBIDataset property)
table_name (langchain.memory.SQLiteEntityStore attribute)
(langchain.vectorstores.SupabaseVectorStore attribute)
table_names (langchain.utilities.PowerBIDataset attribute)
Tair (class in langchain.vectorstores)
task (langchain.embeddings.HuggingFaceHubEmbeddings attribute)
(langchain.llms.HuggingFaceEndpoint attribute)
(langchain.llms.HuggingFaceHub attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
tbs (langchain.utilities.GoogleSerperAPIWrapper attribute)
TelegramChatApiLoader (class in langchain.document_loaders)
TelegramChatFileLoader (class in langchain.document_loaders)
TelegramChatLoader (in module langchain.document_loaders)
temp (langchain.llms.GPT4All attribute)
temperature (langchain.chat_models.ChatGooglePalm attribute)
(langchain.chat_models.ChatOpenAI attribute)
(langchain.llms.AI21 attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.Cohere attribute)
(langchain.llms.ForefrontAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.PredictionGuard attribute)
(langchain.llms.RWKV attribute)
(langchain.llms.VertexAI attribute)
(langchain.llms.Writer attribute)
template (langchain.prompts.PromptTemplate attribute)


(langchain.llms.Writer attribute)
template (langchain.prompts.PromptTemplate attribute)
(langchain.tools.QueryPowerBITool attribute)
template_format (langchain.prompts.FewShotPromptTemplate attribute)
(langchain.prompts.FewShotPromptWithTemplates attribute)
(langchain.prompts.PromptTemplate attribute)
template_tool_response (langchain.agents.ConversationalChatAgent attribute)
text_length (langchain.chains.LLMRequestsChain attribute)
text_splitter (langchain.chains.AnalyzeDocumentChain attribute)
(langchain.chains.MapReduceChain attribute)
(langchain.chains.QAGenerationChain attribute)
TextLoader (class in langchain.document_loaders)
texts (langchain.retrievers.KNNRetriever attribute)
(langchain.retrievers.SVMRetriever attribute)
TextSplitter (class in langchain.text_splitter)
tfidf_array (langchain.retrievers.TFIDFRetriever attribute)
time (langchain.utilities.DuckDuckGoSearchAPIWrapper attribute)
to_typescript() (langchain.tools.APIOperation method)
token (langchain.llms.PredictionGuard attribute)
(langchain.utilities.PowerBIDataset attribute)
token_path (langchain.document_loaders.GoogleApiClient attribute)
(langchain.document_loaders.GoogleDriveLoader attribute)
Tokenizer (class in langchain.text_splitter)
tokenizer (langchain.llms.Petals attribute)
tokens (langchain.llms.AlephAlpha attribute)
tokens_path (langchain.llms.RWKV attribute)
tokens_per_chunk (langchain.text_splitter.Tokenizer attribute)
TokenTextSplitter (class in langchain.text_splitter)
ToMarkdownLoader (class in langchain.document_loaders)
TomlLoader (class in langchain.document_loaders)
tool() (in module langchain.agents)


tool() (in module langchain.agents)
(in module langchain.tools)
tool_run_logging_kwargs() (langchain.agents.Agent method)
(langchain.agents.BaseMultiActionAgent method)
(langchain.agents.BaseSingleActionAgent method)
(langchain.agents.LLMSingleActionAgent method)
tools (langchain.agents.agent_toolkits.JiraToolkit attribute)
(langchain.agents.agent_toolkits.ZapierToolkit attribute)
(langchain.agents.AgentExecutor attribute)
top_k (langchain.chains.SQLDatabaseChain attribute)
(langchain.chat_models.ChatGooglePalm attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.ForefrontAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.Petals attribute)
(langchain.llms.VertexAI attribute)
(langchain.retrievers.ChatGPTPluginRetriever attribute)
(langchain.retrievers.DataberryRetriever attribute)
(langchain.retrievers.PineconeHybridSearchRetriever attribute)
top_k_docs_for_context (langchain.chains.ChatVectorDBChain attribute)
top_k_results (langchain.utilities.ArxivAPIWrapper attribute)
(langchain.utilities.GooglePlacesAPIWrapper attribute)
(langchain.utilities.PubMedAPIWrapper attribute)
(langchain.utilities.WikipediaAPIWrapper attribute)
top_n (langchain.retrievers.document_compressors.CohereRerank attribute)
top_p (langchain.chat_models.ChatGooglePalm attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.AzureOpenAI attribute)


(langchain.llms.Anthropic attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.ForefrontAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.RWKV attribute)
(langchain.llms.VertexAI attribute)
(langchain.llms.Writer attribute)
topP (langchain.llms.AI21 attribute)
traits (langchain.experimental.GenerativeAgent attribute)
transform (langchain.chains.TransformChain attribute)
transform_documents() (langchain.document_transformers.EmbeddingsRedundantFilter method)
(langchain.text_splitter.TextSplitter method)
transform_input_fn (langchain.llms.Databricks attribute)
transform_output_fn (langchain.llms.Databricks attribute)
transformers (langchain.retrievers.document_compressors.DocumentCompressorPipeline attribute)
TrelloLoader (class in langchain.document_loaders)
truncate (langchain.embeddings.CohereEmbeddings attribute)
(langchain.llms.Cohere attribute)
ts_type_from_python() (langchain.tools.APIOperation static method)
ttl (langchain.memory.RedisEntityStore attribute)
tuned_model_name (langchain.llms.VertexAI attribute)
TwitterTweetLoader (class in langchain.document_loaders)
type (langchain.utilities.GoogleSerperAPIWrapper attribute)
Typesense (class in langchain.vectorstores)
U
unsecure (langchain.utilities.searx_search.SearxSearchWrapper attribute)
(langchain.utilities.SearxSearchWrapper attribute)


(langchain.utilities.SearxSearchWrapper attribute)
UnstructuredAPIFileIOLoader (class in langchain.document_loaders)
UnstructuredAPIFileLoader (class in langchain.document_loaders)
UnstructuredEmailLoader (class in langchain.document_loaders)
UnstructuredEPubLoader (class in langchain.document_loaders)
UnstructuredExcelLoader (class in langchain.document_loaders)
UnstructuredFileIOLoader (class in langchain.document_loaders)
UnstructuredFileLoader (class in langchain.document_loaders)
UnstructuredHTMLLoader (class in langchain.document_loaders)
UnstructuredImageLoader (class in langchain.document_loaders)
UnstructuredMarkdownLoader (class in langchain.document_loaders)
UnstructuredODTLoader (class in langchain.document_loaders)
UnstructuredPDFLoader (class in langchain.document_loaders)
UnstructuredPowerPointLoader (class in langchain.document_loaders)
UnstructuredRTFLoader (class in langchain.document_loaders)
UnstructuredURLLoader (class in langchain.document_loaders)
UnstructuredWordDocumentLoader (class in langchain.document_loaders)
update_document() (langchain.vectorstores.Chroma method)
update_forward_refs() (langchain.llms.AI21 class method)
(langchain.llms.AlephAlpha class method)
(langchain.llms.Anthropic class method)
(langchain.llms.Anyscale class method)
(langchain.llms.AzureOpenAI class method)
(langchain.llms.Banana class method)
(langchain.llms.Beam class method)
(langchain.llms.Bedrock class method)
(langchain.llms.CerebriumAI class method)
(langchain.llms.Cohere class method)
(langchain.llms.CTransformers class method)
(langchain.llms.Databricks class method)


(langchain.llms.Databricks class method)
(langchain.llms.DeepInfra class method)
(langchain.llms.FakeListLLM class method)
(langchain.llms.ForefrontAI class method)
(langchain.llms.GooglePalm class method)
(langchain.llms.GooseAI class method)
(langchain.llms.GPT4All class method)
(langchain.llms.HuggingFaceEndpoint class method)
(langchain.llms.HuggingFaceHub class method)
(langchain.llms.HuggingFacePipeline class method)
(langchain.llms.HuggingFaceTextGenInference class method)
(langchain.llms.HumanInputLLM class method)
(langchain.llms.LlamaCpp class method)
(langchain.llms.Modal class method)
(langchain.llms.MosaicML class method)
(langchain.llms.NLPCloud class method)
(langchain.llms.OpenAI class method)
(langchain.llms.OpenAIChat class method)
(langchain.llms.OpenLM class method)
(langchain.llms.Petals class method)
(langchain.llms.PipelineAI class method)
(langchain.llms.PredictionGuard class method)
(langchain.llms.PromptLayerOpenAI class method)
(langchain.llms.PromptLayerOpenAIChat class method)
(langchain.llms.Replicate class method)
(langchain.llms.RWKV class method)
(langchain.llms.SagemakerEndpoint class method)
(langchain.llms.SelfHostedHuggingFaceLLM class method)
(langchain.llms.SelfHostedPipeline class method)
(langchain.llms.StochasticAI class method)
(langchain.llms.VertexAI class method)
(langchain.llms.Writer class method)
upsert_messages() (langchain.memory.CosmosDBChatMessageHistory method)


upsert_messages() (langchain.memory.CosmosDBChatMessageHistory method)
url (langchain.document_loaders.GitHubIssuesLoader property)
(langchain.document_loaders.MathpixPDFLoader property)
(langchain.llms.Beam attribute)
(langchain.retrievers.ChatGPTPluginRetriever attribute)
(langchain.retrievers.RemoteLangChainRetriever attribute)
(langchain.tools.IFTTTWebhook attribute)
urls (langchain.document_loaders.PlaywrightURLLoader attribute)
(langchain.document_loaders.SeleniumURLLoader attribute)
use_mlock (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
use_mmap (langchain.llms.LlamaCpp attribute)
use_multiplicative_presence_penalty (langchain.llms.AlephAlpha attribute)
use_query_checker (langchain.chains.SQLDatabaseChain attribute)
username (langchain.vectorstores.MyScaleSettings attribute)
V
validate_channel_or_videoIds_is_set() (langchain.document_loaders.GoogleApiClient class method)
(langchain.document_loaders.GoogleApiYoutubeLoader class method)
validate_init_args() (langchain.document_loaders.ConfluenceLoader static method)
validate_template (langchain.prompts.FewShotPromptTemplate attribute)
(langchain.prompts.FewShotPromptWithTemplates attribute)
(langchain.prompts.PromptTemplate attribute)
Vectara (class in langchain.vectorstores)
vectorizer (langchain.retrievers.TFIDFRetriever attribute)
VectorStore (class in langchain.vectorstores)
vectorstore (langchain.agents.agent_toolkits.VectorStoreInfo attribute)
(langchain.chains.ChatVectorDBChain attribute)
(langchain.chains.VectorDBQA attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)


(langchain.chains.VectorDBQAWithSourcesChain attribute)
(langchain.prompts.example_selector.SemanticSimilarityExampleSelector attribute)
(langchain.retrievers.SelfQueryRetriever attribute)
(langchain.retrievers.TimeWeightedVectorStoreRetriever attribute)
vectorstore_info (langchain.agents.agent_toolkits.VectorStoreToolkit attribute)
vectorstores (langchain.agents.agent_toolkits.VectorStoreRouterToolkit attribute)
verbose (langchain.llms.AI21 attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.Anthropic attribute)
(langchain.llms.Anyscale attribute)
(langchain.llms.AzureOpenAI attribute)
(langchain.llms.Banana attribute)
(langchain.llms.Beam attribute)
(langchain.llms.Bedrock attribute)
(langchain.llms.CerebriumAI attribute)
(langchain.llms.Cohere attribute)
(langchain.llms.CTransformers attribute)
(langchain.llms.Databricks attribute)
(langchain.llms.DeepInfra attribute)
(langchain.llms.FakeListLLM attribute)
(langchain.llms.ForefrontAI attribute)
(langchain.llms.GooglePalm attribute)
(langchain.llms.GooseAI attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.HuggingFaceEndpoint attribute)
(langchain.llms.HuggingFaceHub attribute)
(langchain.llms.HuggingFacePipeline attribute)
(langchain.llms.HuggingFaceTextGenInference attribute)
(langchain.llms.HumanInputLLM attribute)
(langchain.llms.LlamaCpp attribute)
(langchain.llms.Modal attribute)
(langchain.llms.MosaicML attribute)
(langchain.llms.NLPCloud attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)


(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.PipelineAI attribute)
(langchain.llms.PredictionGuard attribute)
(langchain.llms.Replicate attribute)
(langchain.llms.RWKV attribute)
(langchain.llms.SagemakerEndpoint attribute)
(langchain.llms.SelfHostedHuggingFaceLLM attribute)
(langchain.llms.SelfHostedPipeline attribute)
(langchain.llms.StochasticAI attribute)
(langchain.llms.VertexAI attribute)
(langchain.llms.Writer attribute)
(langchain.retrievers.SelfQueryRetriever attribute)
(langchain.tools.BaseTool attribute)
(langchain.tools.Tool attribute)
VespaRetriever (class in langchain.retrievers)
video_ids (langchain.document_loaders.GoogleApiYoutubeLoader attribute)
visible_only (langchain.tools.ClickTool attribute)
vocab_only (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.LlamaCpp attribute)
W
wait_for_processing() (langchain.document_loaders.MathpixPDFLoader method)
WeatherDataLoader (class in langchain.document_loaders)
Weaviate (class in langchain.vectorstores)
WeaviateHybridSearchRetriever (class in langchain.retrievers)
WeaviateHybridSearchRetriever.Config (class in langchain.retrievers)
web_path (langchain.document_loaders.WebBaseLoader property)
web_paths (langchain.document_loaders.WebBaseLoader attribute)
WebBaseLoader (class in langchain.document_loaders)
WhatsAppChatLoader (class in langchain.document_loaders)
Wikipedia (class in langchain.docstore)


Wikipedia (class in langchain.docstore)
WikipediaLoader (class in langchain.document_loaders)
wolfram_alpha_appid (langchain.utilities.WolframAlphaAPIWrapper attribute)
writer_api_key (langchain.llms.Writer attribute)
writer_org_id (langchain.llms.Writer attribute)
Y
YoutubeLoader (class in langchain.document_loaders)
Z
zapier_description (langchain.tools.ZapierNLARunAction attribute)
ZepRetriever (class in langchain.retrievers)
ZERO_SHOT_REACT_DESCRIPTION (langchain.agents.AgentType attribute)
Zilliz (class in langchain.vectorstores)
By Harrison Chase

      © Copyright 2023, Harrison Chase.

  Last updated on Jun 05, 2023.


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By Harrison Chase

      © Copyright 2023, Harrison Chase.

  Last updated on Jun 05, 2023.


.md
.pdf
Deployments
 Contents
Streamlit
Gradio (on Hugging Face)
Chainlit
Beam
Vercel
FastAPI + Vercel
Kinsta
Fly.io
Digitalocean App Platform
Google Cloud Run
SteamShip
Langchain-serve
BentoML
Databutton
Deployments#
So, you’ve created a really cool chain - now what? How do you deploy it and make it easily shareable with the world?
This section covers several options for that. Note that these options are meant for quick deployment of prototypes and demos, not for production systems. If you need help with the deployment of a production system, please contact us directly.
What follows is a list of template GitHub repositories designed to be easily forked and modified to use your chain. This list is far from exhaustive, and we are EXTREMELY open to contributions here.
Streamlit#
This repo serves as a template for how to deploy a LangChain with Streamlit.
It implements a chatbot interface.
It also contains instructions for how to deploy this app on the Streamlit platform.
Gradio (on Hugging Face)#
This repo serves as a template for how deploy a LangChain with Gradio.
It implements a chatbot interface, with a “Bring-Your-Own-Token” approach (nice for not wracking up big bills).
It also contains instructions for how to deploy this app on the Hugging Face platform.
This is heavily influenced by James Weaver’s excellent examples.
Chainlit#
This repo is a cookbook explaining how to visualize and deploy LangChain agents with Chainlit.
You create ChatGPT-like UIs with Chainlit. Some of the key features include intermediary steps visualisation, element management & display (images, text, carousel, etc.) as well as cloud deployment.
Chainlit doc on the integration with LangChain
Beam#


Chainlit doc on the integration with LangChain
Beam#
This repo serves as a template for how deploy a LangChain with Beam.
It implements a Question Answering app and contains instructions for deploying the app as a serverless REST API.
Vercel#
A minimal example on how to run LangChain on Vercel using Flask.
FastAPI + Vercel#
A minimal example on how to run LangChain on Vercel using FastAPI and LangCorn/Uvicorn.
Kinsta#
A minimal example on how to deploy LangChain to Kinsta using Flask.
Fly.io#
A minimal example of how to deploy LangChain to Fly.io using Flask.
Digitalocean App Platform#
A minimal example on how to deploy LangChain to DigitalOcean App Platform.
Google Cloud Run#
A minimal example on how to deploy LangChain to Google Cloud Run.
SteamShip#
This repository contains LangChain adapters for Steamship, enabling LangChain developers to rapidly deploy their apps on Steamship. This includes: production-ready endpoints, horizontal scaling across dependencies, persistent storage of app state, multi-tenancy support, etc.
Langchain-serve#
This repository allows users to serve local chains and agents as RESTful, gRPC, or WebSocket APIs, thanks to Jina. Deploy your chains & agents with ease and enjoy independent scaling, serverless and autoscaling APIs, as well as a Streamlit playground on Jina AI Cloud.
BentoML#
This repository provides an example of how to deploy a LangChain application with BentoML. BentoML is a framework that enables the containerization of machine learning applications as standard OCI images. BentoML also allows for the automatic generation of OpenAPI and gRPC endpoints. With BentoML, you can integrate models from all popular ML frameworks and deploy them as microservices running on the most optimal hardware and scaling independently.


Databutton#
These templates serve as examples of how to build, deploy, and share LangChain applications using Databutton. You can create user interfaces with Streamlit, automate tasks by scheduling Python code, and store files and data in the built-in store. Examples include a Chatbot interface with conversational memory, a Personal search engine, and a starter template for LangChain apps. Deploying and sharing is just one click away.
previous
Dependents
next
Tracing
 Contents

Streamlit
Gradio (on Hugging Face)
Chainlit
Beam
Vercel
FastAPI + Vercel
Kinsta
Fly.io
Digitalocean App Platform
Google Cloud Run
SteamShip
Langchain-serve
BentoML
Databutton
By Harrison Chase

      © Copyright 2023, Harrison Chase.

  Last updated on Jun 05, 2023.


.md
.pdf
Locally Hosted Setup
 Contents
Installation
Environment Setup
Locally Hosted Setup#
This page contains instructions for installing and then setting up the environment to use the locally hosted version of tracing.
Installation#
Ensure you have Docker installed (see Get Docker) and that it’s running.
Install the latest version of langchain: pip install langchain or pip install langchain -U to upgrade your
existing version.
Run langchain-server. This command was installed automatically when you ran the above command (pip install langchain).
This will spin up the server in the terminal, hosted on port 4137 by default.
Once you see the terminal
output langchain-langchain-frontend-1 | ➜ Local: [http://localhost:4173/](http://localhost:4173/), navigate
to http://localhost:4173/
You should see a page with your tracing sessions. See the overview page for a walkthrough of the UI.
Currently, trace data is not guaranteed to be persisted between runs of langchain-server. If you want to
persist your data, you can mount a volume to the Docker container. See the Docker docs for more info.
To stop the server, press Ctrl+C in the terminal where you ran langchain-server.
Environment Setup#
After installation, you must now set up your environment to use tracing.
This can be done by setting an environment variable in your terminal by running export LANGCHAIN_HANDLER=langchain.
You can also do this by adding the below snippet to the top of every script. IMPORTANT: this must go at the VERY TOP of your script, before you import anything from langchain.
import os
os.environ["LANGCHAIN_HANDLER"] = "langchain"
 Contents

Installation
Environment Setup
By Harrison Chase

      © Copyright 2023, Harrison Chase.


By Harrison Chase

      © Copyright 2023, Harrison Chase.

  Last updated on Jun 05, 2023.


.md
.pdf
Cloud Hosted Setup
 Contents
Installation
Environment Setup
Cloud Hosted Setup#
We offer a hosted version of tracing at langchainplus.vercel.app. You can use this to view traces from your run without having to run the server locally.
Note: we are currently only offering this to a limited number of users. The hosted platform is VERY alpha, in active development, and data might be dropped at any time. Don’t depend on data being persisted in the system long term and don’t log traces that may contain sensitive information. If you’re interested in using the hosted platform, please fill out the form here.
Installation#
Login to the system and click “API Key” in the top right corner. Generate a new key and keep it safe. You will need it to authenticate with the system.
Environment Setup#
After installation, you must now set up your environment to use tracing.
This can be done by setting an environment variable in your terminal by running export LANGCHAIN_HANDLER=langchain.
You can also do this by adding the below snippet to the top of every script. IMPORTANT: this must go at the VERY TOP of your script, before you import anything from langchain.
import os
os.environ["LANGCHAIN_HANDLER"] = "langchain"
You will also need to set an environment variable to specify the endpoint and your API key. This can be done with the following environment variables:
LANGCHAIN_ENDPOINT = “https://langchain-api-gateway-57eoxz8z.uc.gateway.dev”
LANGCHAIN_API_KEY - set this to the API key you generated during installation.
An example of adding all relevant environment variables is below:
import os
os.environ["LANGCHAIN_HANDLER"] = "langchain"
os.environ["LANGCHAIN_ENDPOINT"] = "https://langchain-api-gateway-57eoxz8z.uc.gateway.dev"


os.environ["LANGCHAIN_API_KEY"] = "my_api_key"  # Don't commit this to your repo! Better to set it in your terminal.
 Contents

Installation
Environment Setup
By Harrison Chase

      © Copyright 2023, Harrison Chase.

  Last updated on Jun 05, 2023.


.ipynb
.pdf
Tracing Walkthrough
 Contents
[Beta] Tracing V2
Tracing Walkthrough#
There are two recommended ways to trace your LangChains:
Setting the LANGCHAIN_TRACING environment variable to “true”.
Using a context manager with tracing_enabled() to trace a particular block of code.
Note if the environment variable is set, all code will be traced, regardless of whether or not it’s within the context manager.
import os
os.environ["LANGCHAIN_TRACING"] = "true"
## Uncomment below if using hosted setup.
# os.environ["LANGCHAIN_ENDPOINT"] = "https://langchain-api-gateway-57eoxz8z.uc.gateway.dev"
## Uncomment below if you want traces to be recorded to "my_session" instead of "default".
# os.environ["LANGCHAIN_SESSION"] = "my_session"
## Better to set this environment variable in the terminal
## Uncomment below if using hosted version. Replace "my_api_key" with your actual API Key.
# os.environ["LANGCHAIN_API_KEY"] = "my_api_key"
import langchain
from langchain.agents import Tool, initialize_agent, load_tools
from langchain.agents import AgentType
from langchain.callbacks import tracing_enabled
from langchain.chat_models import ChatOpenAI
from langchain.llms import OpenAI
# Agent run with tracing. Ensure that OPENAI_API_KEY is set appropriately to run this example.
llm = OpenAI(temperature=0)
tools = load_tools(["llm-math"], llm=llm)
agent = initialize_agent(
    tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
agent.run("What is 2 raised to .123243 power?")
> Entering new AgentExecutor chain...


> Entering new AgentExecutor chain...
 I need to use a calculator to solve this.
Action: Calculator
Action Input: 2^.123243
Observation: Answer: 1.0891804557407723
Thought: I now know the final answer.
Final Answer: 1.0891804557407723
> Finished chain.
'1.0891804557407723'
# Agent run with tracing using a chat model
agent = initialize_agent(
    tools, ChatOpenAI(temperature=0), agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
agent.run("What is 2 raised to .123243 power?")
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator
Action Input: 2 ^ .123243
Observation: Answer: 1.0891804557407723
Thought:I now know the answer to the question.
Final Answer: 1.0891804557407723
> Finished chain.
'1.0891804557407723'
# Both of the agent runs will be traced because the environment variable is set
agent.run("What is 2 raised to .123243 power?")
with tracing_enabled() as session:
    agent.run("What is 5 raised to .123243 power?")
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator
Action Input: 2 ^ .123243
Observation: Answer: 1.0891804557407723
Thought:I now know the answer to the question.
Final Answer: 1.0891804557407723
> Finished chain.
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator


I need to use a calculator to solve this.
Action: Calculator
Action Input: 5 ^ .123243
Observation: Answer: 1.2193914912400514
Thought:I now know the answer to the question.
Final Answer: 1.2193914912400514
> Finished chain.
# Now, we unset the environment variable and use a context manager.
if "LANGCHAIN_TRACING" in os.environ:
    del os.environ["LANGCHAIN_TRACING"]
# here, we are writing traces to "my_test_session"
with tracing_enabled("my_session") as session:
    assert session
    agent.run("What is 5 raised to .123243 power?")  # this should be traced
agent.run("What is 2 raised to .123243 power?")  # this should not be traced
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator
Action Input: 5 ^ .123243
Observation: Answer: 1.2193914912400514
Thought:I now know the answer to the question.
Final Answer: 1.2193914912400514
> Finished chain.
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator
Action Input: 2 ^ .123243
Observation: Answer: 1.0891804557407723
Thought:I now know the answer to the question.
Final Answer: 1.0891804557407723
> Finished chain.
'1.0891804557407723'
# The context manager is concurrency safe:
import asyncio
if "LANGCHAIN_TRACING" in os.environ:
    del os.environ["LANGCHAIN_TRACING"]


del os.environ["LANGCHAIN_TRACING"]

questions = [f"What is {i} raised to .123 power?" for i in range(1,4)]
# start a background task
task = asyncio.create_task(agent.arun(questions[0]))  # this should not be traced
with tracing_enabled() as session:
    assert session
    tasks = [agent.arun(q) for q in questions[1:3]]  # these should be traced
    await asyncio.gather(*tasks)
await task
> Entering new AgentExecutor chain...
> Entering new AgentExecutor chain...
> Entering new AgentExecutor chain...
I need to use a calculator to solve this.
Action: Calculator
Action Input: 3^0.123I need to use a calculator to solve this.
Action: Calculator
Action Input: 2^0.123Any number raised to the power of 0 is 1, but I'm not sure about a decimal power.
Action: Calculator
Action Input: 1^.123
Observation: Answer: 1.1446847956963533
Thought:
Observation: Answer: 1.0889970153361064
Thought:
Observation: Answer: 1.0
Thought:
> Finished chain.
> Finished chain.
> Finished chain.
'1.0'
[Beta] Tracing V2#
We are rolling out a newer version of our tracing service with more features coming soon. Here are the instructions on how to use it to trace your runs.
To use, you can use the tracing_v2_enabled context manager or set LANGCHAIN_TRACING_V2 = 'true'
Option 1 (Local):
Run the local LangChainPlus Server
pip install --upgrade langchain
langchain plus start
Option 2 (Hosted):


pip install --upgrade langchain
langchain plus start
Option 2 (Hosted):
After making an account an grabbing a LangChainPlus API Key, set the LANGCHAIN_ENDPOINT and LANGCHAIN_API_KEY environment variables
import os
os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_ENDPOINT"] = "https://api.langchain.plus"  # Uncomment this line if you want to use the hosted version
# os.environ["LANGCHAIN_API_KEY"] = "<YOUR-LANGCHAINPLUS-API-KEY>"  # Uncomment this line if you want to use the hosted version.
import langchain
from langchain.agents import Tool, initialize_agent, load_tools
from langchain.agents import AgentType
from langchain.callbacks import tracing_enabled
from langchain.chat_models import ChatOpenAI
from langchain.llms import OpenAI
# Agent run with tracing. Ensure that OPENAI_API_KEY is set appropriately to run this example.
llm = OpenAI(temperature=0)
tools = load_tools(["llm-math"], llm=llm)
agent = initialize_agent(
    tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
agent.run("What is 2 raised to .123243 power?")
> Entering new AgentExecutor chain...
 I need to use a calculator to solve this.
Action: Calculator
Action Input: 2^.123243
Observation: Answer: 1.0891804557407723
Thought: I now know the final answer.
Final Answer: 1.0891804557407723
> Finished chain.
'1.0891804557407723'
 Contents

[Beta] Tracing V2
By Harrison Chase

      © Copyright 2023, Harrison Chase.


Source code for langchain.text_splitter
"""Functionality for splitting text."""
from __future__ import annotations
import copy
import logging
import re
from abc import ABC, abstractmethod
from dataclasses import dataclass
from enum import Enum
from typing import (
    AbstractSet,
    Any,
    Callable,
    Collection,
    Iterable,
    List,
    Literal,
    Optional,
    Sequence,
    Type,
    TypeVar,
    Union,
)
from langchain.docstore.document import Document
from langchain.schema import BaseDocumentTransformer
logger = logging.getLogger(__name__)
TS = TypeVar("TS", bound="TextSplitter")
def _split_text(text: str, separator: str, keep_separator: bool) -> List[str]:
    # Now that we have the separator, split the text
    if separator:
        if keep_separator:
            # The parentheses in the pattern keep the delimiters in the result.
            _splits = re.split(f"({separator})", text)
            splits = [_splits[i] + _splits[i + 1] for i in range(1, len(_splits), 2)]
            if len(_splits) % 2 == 0:
                splits += _splits[-1:]
            splits = [_splits[0]] + splits
        else:
            splits = text.split(separator)
    else:
        splits = list(text)
    return [s for s in splits if s != ""]
[docs]class TextSplitter(BaseDocumentTransformer, ABC):
    """Interface for splitting text into chunks."""
    def __init__(
        self,
        chunk_size: int = 4000,
        chunk_overlap: int = 200,


chunk_overlap: int = 200,
        length_function: Callable[[str], int] = len,
        keep_separator: bool = False,
    ):
        """Create a new TextSplitter.
        Args:
            chunk_size: Maximum size of chunks to return
            chunk_overlap: Overlap in characters between chunks
            length_function: Function that measures the length of given chunks
            keep_separator: Whether or not to keep the separator in the chunks
        """
        if chunk_overlap > chunk_size:
            raise ValueError(
                f"Got a larger chunk overlap ({chunk_overlap}) than chunk size "
                f"({chunk_size}), should be smaller."
            )
        self._chunk_size = chunk_size
        self._chunk_overlap = chunk_overlap
        self._length_function = length_function
        self._keep_separator = keep_separator
[docs]    @abstractmethod
    def split_text(self, text: str) -> List[str]:
        """Split text into multiple components."""
[docs]    def create_documents(
        self, texts: List[str], metadatas: Optional[List[dict]] = None
    ) -> List[Document]:
        """Create documents from a list of texts."""
        _metadatas = metadatas or [{}] * len(texts)
        documents = []
        for i, text in enumerate(texts):
            for chunk in self.split_text(text):
                new_doc = Document(
                    page_content=chunk, metadata=copy.deepcopy(_metadatas[i])
                )
                documents.append(new_doc)
        return documents
[docs]    def split_documents(self, documents: Iterable[Document]) -> List[Document]:
        """Split documents."""
        texts, metadatas = [], []
        for doc in documents:
            texts.append(doc.page_content)


for doc in documents:
            texts.append(doc.page_content)
            metadatas.append(doc.metadata)
        return self.create_documents(texts, metadatas=metadatas)
    def _join_docs(self, docs: List[str], separator: str) -> Optional[str]:
        text = separator.join(docs)
        text = text.strip()
        if text == "":
            return None
        else:
            return text
    def _merge_splits(self, splits: Iterable[str], separator: str) -> List[str]:
        # We now want to combine these smaller pieces into medium size
        # chunks to send to the LLM.
        separator_len = self._length_function(separator)
        docs = []
        current_doc: List[str] = []
        total = 0
        for d in splits:
            _len = self._length_function(d)
            if (
                total + _len + (separator_len if len(current_doc) > 0 else 0)
                > self._chunk_size
            ):
                if total > self._chunk_size:
                    logger.warning(
                        f"Created a chunk of size {total}, "
                        f"which is longer than the specified {self._chunk_size}"
                    )
                if len(current_doc) > 0:
                    doc = self._join_docs(current_doc, separator)
                    if doc is not None:
                        docs.append(doc)
                    # Keep on popping if:
                    # - we have a larger chunk than in the chunk overlap
                    # - or if we still have any chunks and the length is long
                    while total > self._chunk_overlap or (
                        total + _len + (separator_len if len(current_doc) > 0 else 0)
                        > self._chunk_size
                        and total > 0


> self._chunk_size
                        and total > 0
                    ):
                        total -= self._length_function(current_doc[0]) + (
                            separator_len if len(current_doc) > 1 else 0
                        )
                        current_doc = current_doc[1:]
            current_doc.append(d)
            total += _len + (separator_len if len(current_doc) > 1 else 0)
        doc = self._join_docs(current_doc, separator)
        if doc is not None:
            docs.append(doc)
        return docs
[docs]    @classmethod
    def from_huggingface_tokenizer(cls, tokenizer: Any, **kwargs: Any) -> TextSplitter:
        """Text splitter that uses HuggingFace tokenizer to count length."""
        try:
            from transformers import PreTrainedTokenizerBase
            if not isinstance(tokenizer, PreTrainedTokenizerBase):
                raise ValueError(
                    "Tokenizer received was not an instance of PreTrainedTokenizerBase"
                )
            def _huggingface_tokenizer_length(text: str) -> int:
                return len(tokenizer.encode(text))
        except ImportError:
            raise ValueError(
                "Could not import transformers python package. "
                "Please install it with `pip install transformers`."
            )
        return cls(length_function=_huggingface_tokenizer_length, **kwargs)
[docs]    @classmethod
    def from_tiktoken_encoder(
        cls: Type[TS],
        encoding_name: str = "gpt2",
        model_name: Optional[str] = None,
        allowed_special: Union[Literal["all"], AbstractSet[str]] = set(),
        disallowed_special: Union[Literal["all"], Collection[str]] = "all",
        **kwargs: Any,
    ) -> TS:


**kwargs: Any,
    ) -> TS:
        """Text splitter that uses tiktoken encoder to count length."""
        try:
            import tiktoken
        except ImportError:
            raise ImportError(
                "Could not import tiktoken python package. "
                "This is needed in order to calculate max_tokens_for_prompt. "
                "Please install it with `pip install tiktoken`."
            )
        if model_name is not None:
            enc = tiktoken.encoding_for_model(model_name)
        else:
            enc = tiktoken.get_encoding(encoding_name)
        def _tiktoken_encoder(text: str) -> int:
            return len(
                enc.encode(
                    text,
                    allowed_special=allowed_special,
                    disallowed_special=disallowed_special,
                )
            )
        if issubclass(cls, TokenTextSplitter):
            extra_kwargs = {
                "encoding_name": encoding_name,
                "model_name": model_name,
                "allowed_special": allowed_special,
                "disallowed_special": disallowed_special,
            }
            kwargs = {**kwargs, **extra_kwargs}
        return cls(length_function=_tiktoken_encoder, **kwargs)
[docs]    def transform_documents(
        self, documents: Sequence[Document], **kwargs: Any
    ) -> Sequence[Document]:
        """Transform sequence of documents by splitting them."""
        return self.split_documents(list(documents))
[docs]    async def atransform_documents(
        self, documents: Sequence[Document], **kwargs: Any
    ) -> Sequence[Document]:
        """Asynchronously transform a sequence of documents by splitting them."""
        raise NotImplementedError
[docs]class CharacterTextSplitter(TextSplitter):
    """Implementation of splitting text that looks at characters."""


"""Implementation of splitting text that looks at characters."""
    def __init__(self, separator: str = "\n\n", **kwargs: Any):
        """Create a new TextSplitter."""
        super().__init__(**kwargs)
        self._separator = separator
[docs]    def split_text(self, text: str) -> List[str]:
        """Split incoming text and return chunks."""
        # First we naively split the large input into a bunch of smaller ones.
        splits = _split_text(text, self._separator, self._keep_separator)
        _separator = "" if self._keep_separator else self._separator
        return self._merge_splits(splits, _separator)
# should be in newer Python versions (3.10+)
# @dataclass(frozen=True, kw_only=True, slots=True)
[docs]@dataclass(frozen=True)
class Tokenizer:
    chunk_overlap: int
    tokens_per_chunk: int
    decode: Callable[[list[int]], str]
    encode: Callable[[str], List[int]]
[docs]def split_text_on_tokens(*, text: str, tokenizer: Tokenizer) -> List[str]:
    """Split incoming text and return chunks."""
    splits = []
    input_ids = tokenizer.encode(text)
    start_idx = 0
    cur_idx = min(start_idx + tokenizer.tokens_per_chunk, len(input_ids))
    chunk_ids = input_ids[start_idx:cur_idx]
    while start_idx < len(input_ids):
        splits.append(tokenizer.decode(chunk_ids))
        start_idx += tokenizer.tokens_per_chunk - tokenizer.chunk_overlap
        cur_idx = min(start_idx + tokenizer.tokens_per_chunk, len(input_ids))
        chunk_ids = input_ids[start_idx:cur_idx]
    return splits
[docs]class TokenTextSplitter(TextSplitter):


return splits
[docs]class TokenTextSplitter(TextSplitter):
    """Implementation of splitting text that looks at tokens."""
    def __init__(
        self,
        encoding_name: str = "gpt2",
        model_name: Optional[str] = None,
        allowed_special: Union[Literal["all"], AbstractSet[str]] = set(),
        disallowed_special: Union[Literal["all"], Collection[str]] = "all",
        **kwargs: Any,
    ):
        """Create a new TextSplitter."""
        super().__init__(**kwargs)
        try:
            import tiktoken
        except ImportError:
            raise ImportError(
                "Could not import tiktoken python package. "
                "This is needed in order to for TokenTextSplitter. "
                "Please install it with `pip install tiktoken`."
            )
        if model_name is not None:
            enc = tiktoken.encoding_for_model(model_name)
        else:
            enc = tiktoken.get_encoding(encoding_name)
        self._tokenizer = enc
        self._allowed_special = allowed_special
        self._disallowed_special = disallowed_special
[docs]    def split_text(self, text: str) -> List[str]:
        def _encode(_text: str) -> List[int]:
            return self._tokenizer.encode(
                _text,
                allowed_special=self._allowed_special,
                disallowed_special=self._disallowed_special,
            )
        tokenizer = Tokenizer(
            chunk_overlap=self._chunk_overlap,
            tokens_per_chunk=self._chunk_size,
            decode=self._tokenizer.decode,
            encode=_encode,
        )
        return split_text_on_tokens(text=text, tokenizer=tokenizer)
[docs]class SentenceTransformersTokenTextSplitter(TextSplitter):


[docs]class SentenceTransformersTokenTextSplitter(TextSplitter):
    """Implementation of splitting text that looks at tokens."""
    def __init__(
        self,
        chunk_overlap: int = 50,
        model_name: str = "sentence-transformers/all-mpnet-base-v2",
        tokens_per_chunk: Optional[int] = None,
        **kwargs: Any,
    ):
        """Create a new TextSplitter."""
        super().__init__(**kwargs, chunk_overlap=chunk_overlap)
        from transformers import AutoTokenizer
        self.model_name = model_name
        self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
        self._initialize_chunk_configuration(tokens_per_chunk=tokens_per_chunk)
    def _initialize_chunk_configuration(
        self, *, tokens_per_chunk: Optional[int]
    ) -> None:
        self.maximum_tokens_per_chunk = self.tokenizer.max_len_single_sentence
        if tokens_per_chunk is None:
            self.tokens_per_chunk = self.maximum_tokens_per_chunk
        else:
            self.tokens_per_chunk = tokens_per_chunk
        if self.tokens_per_chunk > self.maximum_tokens_per_chunk:
            raise ValueError(
                f"The token limit of the models '{self.model_name}'"
                f" is: {self.maximum_tokens_per_chunk}."
                f" Argument tokens_per_chunk={self.tokens_per_chunk}"
                f" > maximum token limit."
            )
[docs]    def split_text(self, text: str) -> List[str]:
        def encode_strip_start_and_stop_token_ids(text: str) -> List[int]:
            return self._encode(text)[1:-1]
        tokenizer = Tokenizer(
            chunk_overlap=self._chunk_overlap,
            tokens_per_chunk=self.tokens_per_chunk,
            decode=self.tokenizer.decode,