id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
a1409c1b5e0f-126 | 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 meth... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-127 | 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 lang... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-128 | query_name (langchain.vectorstores.SupabaseVectorStore attribute)
query_params (langchain.document_loaders.GitHubIssuesLoader property)
(langchain.tools.APIOperation property)
query_suffix (langchain.utilities.SearxSearchWrapper attribute)
question_generator (langchain.chains.ChatVectorDBChain attribute)
(langchain.cha... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-129 | 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)
(langcha... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-130 | 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 att... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-131 | (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.GraphCypherQAChain attribute)
(langchain.chains.SQLDatabas... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-132 | return_stopped_response() (langchain.agents.Agent method)
(langchain.agents.BaseMultiActionAgent method)
(langchain.agents.BaseSingleActionAgent method)
return_urls (langchain.tools.SteamshipImageGenerationTool attribute)
return_values (langchain.agents.Agent property)
(langchain.agents.BaseMultiActionAgent property)
(... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-133 | (langchain.chains.GraphCypherQAChain method)
(langchain.chains.GraphQAChain method)
(langchain.chains.HypotheticalDocumentEmbedder method)
(langchain.chains.KuzuQAChain method)
(langchain.chains.LLMBashChain method)
(langchain.chains.LLMChain method)
(langchain.chains.LLMCheckerChain method)
(langchain.chains.LLMMathCh... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-134 | (langchain.chains.TransformChain method)
(langchain.chains.VectorDBQA method)
(langchain.chains.VectorDBQAWithSourcesChain method)
(langchain.tools.BaseTool method)
(langchain.utilities.ArxivAPIWrapper method)
(langchain.utilities.BashProcess method)
(langchain.utilities.BingSearchAPIWrapper method)
(langchain.utilitie... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-135 | S3FileLoader (class in langchain.document_loaders)
safesearch (langchain.utilities.DuckDuckGoSearchAPIWrapper attribute)
sample_rows_in_table_info (langchain.utilities.PowerBIDataset attribute)
sanitize_input (langchain.tools.PythonAstREPLTool attribute)
(langchain.tools.PythonREPLTool attribute)
save() (langchain.agen... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-136 | (langchain.chains.NatBotChain method)
(langchain.chains.NebulaGraphQAChain method)
(langchain.chains.OpenAIModerationChain method)
(langchain.chains.OpenAPIEndpointChain method)
(langchain.chains.PALChain method)
(langchain.chains.QAGenerationChain method)
(langchain.chains.QAWithSourcesChain method)
(langchain.chains.... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-137 | (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 metho... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-138 | (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.ConversationEnti... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-139 | (langchain.chains.VectorDBQA attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)
(langchain.retrievers.SelfQueryRetriever attribute)
(langchain.retrievers.TimeWeightedVectorStoreRetriever attribute)
(langchain.utilities.BraveSearchWrapper attribute)
search_type (langchain.chains.VectorDBQA attribute)
(la... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-140 | 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.utilities.SerpAPIW... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-141 | (langchain.vectorstores.AwaDB method)
(langchain.vectorstores.AzureSearch method)
(langchain.vectorstores.Cassandra method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.Clarifai method)
(langchain.vectorstores.Clickhouse method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.ElasticV... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-142 | (langchain.vectorstores.AwaDB method)
(langchain.vectorstores.Cassandra method)
(langchain.vectorstores.Chroma method)
(langchain.vectorstores.Clickhouse method)
(langchain.vectorstores.DeepLake method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Hologres method)
(langchain.vectorstores.Milvus method)... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-143 | (langchain.vectorstores.DeepLake method)
(langchain.vectorstores.ElasticVectorSearch method)
(langchain.vectorstores.FAISS method)
(langchain.vectorstores.Hologres method)
(langchain.vectorstores.Milvus method)
(langchain.vectorstores.MongoDBAtlasVectorSearch method)
(langchain.vectorstores.OpenSearchVectorSearch metho... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-144 | size (langchain.tools.SteamshipImageGenerationTool attribute)
skip_special_tokens (langchain.llms.TextGen attribute)
SKLearnVectorStore (class in langchain.vectorstores)
SlackDirectoryLoader (class in langchain.document_loaders)
SnowflakeLoader (class in langchain.document_loaders)
SOL (langchain.text_splitter.Language... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-145 | StarRocks (class in langchain.vectorstores)
start_with_retrieval (langchain.chains.FlareChain attribute)
state (langchain.document_loaders.GitHubIssuesLoader attribute)
status (langchain.experimental.GenerativeAgent attribute)
StdInInquireTool() (in module langchain.tools)
StdOutCallbackHandler (class in langchain.call... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-146 | StreamingStdOutCallbackHandler (class in langchain.callbacks)
StreamlitCallbackHandler() (in module langchain.callbacks)
strip_outputs (langchain.chains.SimpleSequentialChain attribute)
StripeLoader (class in langchain.document_loaders)
STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION (langchain.agents.AgentType attribute)
... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-147 | (langchain.chains.ConversationChain attribute)
(langchain.chains.FlareChain attribute)
(langchain.chains.GraphCypherQAChain attribute)
(langchain.chains.GraphQAChain attribute)
(langchain.chains.HypotheticalDocumentEmbedder attribute)
(langchain.chains.KuzuQAChain attribute)
(langchain.chains.LLMBashChain attribute)
(l... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-148 | (langchain.chains.StuffDocumentsChain attribute)
(langchain.chains.TransformChain attribute)
(langchain.chains.VectorDBQA attribute)
(langchain.chains.VectorDBQAWithSourcesChain attribute)
(langchain.llms.AI21 attribute)
(langchain.llms.AlephAlpha attribute)
(langchain.llms.AmazonAPIGateway attribute)
(langchain.llms.A... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-149 | (langchain.llms.NLPCloud attribute)
(langchain.llms.OctoAIEndpoint attribute)
(langchain.llms.OpenAI attribute)
(langchain.llms.OpenAIChat attribute)
(langchain.llms.OpenLLM attribute)
(langchain.llms.OpenLM attribute)
(langchain.llms.Petals attribute)
(langchain.llms.PipelineAI attribute)
(langchain.llms.PredictionGua... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-150 | (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 attrib... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-151 | TextSplitter (class in langchain.text_splitter)
tfidf_array (langchain.retrievers.TFIDFRetriever attribute)
threshold (langchain.prompts.example_selector.NGramOverlapExampleSelector attribute)
(langchain.prompts.NGramOverlapExampleSelector attribute)
Tigris (class in langchain.vectorstores)
tiktoken_model_name (langcha... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-152 | (langchain.chains.MultiPromptChain method)
(langchain.chains.MultiRetrievalQAChain method)
(langchain.chains.MultiRouteChain method)
(langchain.chains.NatBotChain method)
(langchain.chains.NebulaGraphQAChain method)
(langchain.chains.OpenAIModerationChain method)
(langchain.chains.OpenAPIEndpointChain method)
(langchai... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-153 | (langchain.chains.LLMChain method)
(langchain.chains.LLMCheckerChain method)
(langchain.chains.LLMMathChain method)
(langchain.chains.LLMRequestsChain method)
(langchain.chains.LLMRouterChain method)
(langchain.chains.LLMSummarizationCheckerChain method)
(langchain.chains.MapReduceChain method)
(langchain.chains.MapRed... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-154 | 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 (lang... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-155 | (langchain.llms.Petals attribute)
(langchain.llms.TextGen attribute)
(langchain.llms.VertexAI attribute)
(langchain.retrievers.ChatGPTPluginRetriever attribute)
(langchain.retrievers.DataberryRetriever attribute)
(langchain.retrievers.DocArrayRetriever attribute), [1]
(langchain.retrievers.PineconeHybridSearchRetriever... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-156 | tracing_enabled() (in module langchain.callbacks)
traits (langchain.experimental.GenerativeAgent attribute)
transform (langchain.chains.TransformChain attribute)
transform_documents() (langchain.document_transformers.EmbeddingsRedundantFilter method)
(langchain.schema.BaseDocumentTransformer method)
(langchain.text_spl... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-157 | UnstructuredAPIFileLoader (class in langchain.document_loaders)
UnstructuredCSVLoader (class in langchain.document_loaders)
UnstructuredEmailLoader (class in langchain.document_loaders)
UnstructuredEPubLoader (class in langchain.document_loaders)
UnstructuredExcelLoader (class in langchain.document_loaders)
Unstructure... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-158 | (langchain.llms.Banana class method)
(langchain.llms.Baseten class method)
(langchain.llms.Beam class method)
(langchain.llms.Bedrock class method)
(langchain.llms.CerebriumAI class method)
(langchain.llms.Clarifai class method)
(langchain.llms.Cohere class method)
(langchain.llms.CTransformers class method)
(langchain... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-159 | (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 m... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-160 | (langchain.tools.IFTTTWebhook attribute)
urls (langchain.document_loaders.PlaywrightURLLoader attribute)
(langchain.document_loaders.SeleniumURLLoader attribute)
use() (langchain.vectorstores.AwaDB method)
use_mlock (langchain.embeddings.LlamaCppEmbeddings attribute)
(langchain.llms.GPT4All attribute)
(langchain.llms.L... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-161 | 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.prompts.example_selector.SemanticSimilarityExamp... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-162 | (langchain.chains.MapReduceDocumentsChain attribute)
(langchain.chains.MapRerankDocumentsChain attribute)
(langchain.chains.MultiPromptChain attribute)
(langchain.chains.MultiRetrievalQAChain attribute)
(langchain.chains.MultiRouteChain attribute)
(langchain.chains.NatBotChain attribute)
(langchain.chains.NebulaGraphQA... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-163 | (langchain.llms.CerebriumAI attribute)
(langchain.llms.Clarifai 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.G... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-164 | (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_o... | https://api.python.langchain.com/en/stable/genindex.html |
a1409c1b5e0f-165 | writer_org_id (langchain.llms.Writer attribute)
Y
yield_blobs() (langchain.document_loaders.BlobLoader method)
(langchain.document_loaders.FileSystemBlobLoader method)
(langchain.document_loaders.YoutubeAudioLoader method)
YoutubeAudioLoader (class in langchain.document_loaders)
YoutubeLoader (class in langchain.docume... | https://api.python.langchain.com/en/stable/genindex.html |
17154dc0c4bf-0 | Agentsο
Reference guide for Agents and associated abstractions.
Agents
Tools
Agent Toolkits | https://api.python.langchain.com/en/stable/agents.html |
c73826eb6edd-0 | Memoryο
class langchain.memory.CassandraChatMessageHistory(contact_points, session_id, port=9042, username='cassandra', password='cassandra', keyspace_name='chat_history', table_name='message_store')[source]ο
Bases: langchain.schema.BaseChatMessageHistory
Chat message history that stores history in Cassandra.
Parameter... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-1 | None
class langchain.memory.CombinedMemory(*, memories)[source]ο
Bases: langchain.schema.BaseMemory
Class for combining multiple memoriesβ data together.
Parameters
memories (List[langchain.schema.BaseMemory]) β
Return type
None
attribute memories: List[langchain.schema.BaseMemory] [Required]ο
For tracking all the mem... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-2 | load_memory_variables(inputs)[source]ο
Return history buffer.
Parameters
inputs (Dict[str, Any]) β
Return type
Dict[str, Any]
property buffer: Anyο
String buffer of memory.
class langchain.memory.ConversationBufferWindowMemory(*, chat_memory=None, output_key=None, input_key=None, return_messages=False, human_prefix='H... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-3 | class langchain.memory.ConversationEntityMemory(*, chat_memory=None, output_key=None, input_key=None, return_messages=False, human_prefix='Human', ai_prefix='AI', llm, entity_extraction_prompt=PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template='You are an AI assistan... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-4 | "That sounds like a lot of work! What kind of things are you doing to make Langchain better?"\nLast line:\nPerson #1: i\'m trying to improve Langchain\'s interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I\'m working with Person #2.\nOutput: Langchain, Person #2\nEND OF ... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-5 | Bases: langchain.memory.chat_memory.BaseChatMemory
Entity extractor & summarizer memory.
Extracts named entities from the recent chat history and generates summaries.
With a swapable entity store, persisting entities across conversations.
Defaults to an in-memory entity store, and can be swapped out for a Redis,
SQLite... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-6 | attribute entity_extraction_prompt: langchain.prompts.base.BasePromptTemplate = PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template='You are an AI assistant reading the transcript of a conversation between an AI and a human. Extract all of the proper nouns from the la... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-7 | line:\nPerson #1: i\'m trying to improve Langchain\'s interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I\'m working with Person #2.\nOutput: Langchain, Person #2\nEND OF EXAMPLE\n\nConversation history (for reference only):\n{history}\nLast line of conversation (for ext... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-8 | attribute entity_store: langchain.memory.entity.BaseEntityStore [Optional]ο
attribute entity_summarization_prompt: langchain.prompts.base.BasePromptTemplate = PromptTemplate(input_variables=['entity', 'summary', 'history', 'input'], output_parser=None, partial_variables={}, template='You are an AI assistant helping a h... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-9 | Parameters
inputs (Dict[str, Any]) β
Return type
Dict[str, Any]
save_context(inputs, outputs)[source]ο
Save context from this conversation history to the entity store.
Generates a summary for each entity in the entity cache by prompting
the model, and saves these summaries to the entity store.
Parameters
inputs (Dict[... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-10 | class langchain.memory.ConversationKGMemory(*, chat_memory=None, output_key=None, input_key=None, return_messages=False, k=2, human_prefix='Human', ai_prefix='AI', kg=None, knowledge_extraction_prompt=PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template="You are a netw... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-11 | NONE\nEND OF EXAMPLE\n\nEXAMPLE\nConversation history:\nPerson #1: What do you know about Descartes?\nAI: Descartes was a French philosopher, mathematician, and scientist who lived in the 17th century.\nPerson #1: The Descartes I'm referring to is a standup comedian and interior designer from Montreal.\nAI: Oh yes, He ... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-12 | history:\nPerson #1: how\'s it going today?\nAI: "It\'s going great! How about you?"\nPerson #1: good! busy working on Langchain. lots to do.\nAI: "That sounds like a lot of work! What kind of things are you doing to make Langchain better?"\nLast line:\nPerson #1: i\'m trying to improve Langchain\'s interfaces, the UX,... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-13 | Bases: langchain.memory.chat_memory.BaseChatMemory
Knowledge graph memory for storing conversation memory.
Integrates with external knowledge graph to store and retrieve
information about knowledge triples in the conversation.
Parameters
chat_memory (langchain.schema.BaseChatMessageHistory) β
output_key (Optional[str]... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-14 | attribute entity_extraction_prompt: langchain.prompts.base.BasePromptTemplate = PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template='You are an AI assistant reading the transcript of a conversation between an AI and a human. Extract all of the proper nouns from the la... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-15 | line:\nPerson #1: i\'m trying to improve Langchain\'s interfaces, the UX, its integrations with various products the user might want ... a lot of stuff. I\'m working with Person #2.\nOutput: Langchain, Person #2\nEND OF EXAMPLE\n\nConversation history (for reference only):\n{history}\nLast line of conversation (for ext... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-16 | attribute human_prefix: str = 'Human'ο
attribute k: int = 2ο
attribute kg: langchain.graphs.networkx_graph.NetworkxEntityGraph [Optional]ο | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-17 | attribute knowledge_extraction_prompt: langchain.prompts.base.BasePromptTemplate = PromptTemplate(input_variables=['history', 'input'], output_parser=None, partial_variables={}, template="You are a networked intelligence helping a human track knowledge triples about all relevant people, things, concepts, etc. and integ... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-18 | Descartes was a French philosopher, mathematician, and scientist who lived in the 17th century.\nPerson #1: The Descartes I'm referring to is a standup comedian and interior designer from Montreal.\nAI: Oh yes, He is a comedian and an interior designer. He has been in the industry for 30 years. His favorite food is bak... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-19 | attribute llm: langchain.base_language.BaseLanguageModel [Required]ο
attribute summary_message_cls: Type[langchain.schema.BaseMessage] = <class 'langchain.schema.SystemMessage'>ο
Number of previous utterances to include in the context.
clear()[source]ο
Clear memory contents.
Return type
None
get_current_entities(input_... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-20 | attribute input_key: Optional[str] = Noneο
attribute output_key: Optional[str] = Noneο
clear()[source]ο
Clear memory contents.
Return type
None
load_memory_variables(inputs)[source]ο
Return history buffer.
Parameters
inputs (Dict[str, Any]) β
Return type
Dict[str, str]
save_context(inputs, outputs)[source]ο
Save conte... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-21 | Will always return list of memory variables.
:meta private:
class langchain.memory.ConversationSummaryBufferMemory(*, human_prefix='Human', ai_prefix='AI', llm, prompt=PromptTemplate(input_variables=['summary', 'new_lines'], output_parser=None, partial_variables={}, template='Progressively summarize the lines of conver... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-22 | output_key (Optional[str]) β
input_key (Optional[str]) β
return_messages (bool) β
max_token_limit (int) β
moving_summary_buffer (str) β
memory_key (str) β
Return type
None
attribute max_token_limit: int = 2000ο
attribute memory_key: str = 'history'ο
attribute moving_summary_buffer: str = ''ο
clear()[source]ο
Clea... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-23 | Return type
None
property buffer: List[langchain.schema.BaseMessage]ο
class langchain.memory.ConversationSummaryMemory(*, human_prefix='Human', ai_prefix='AI', llm, prompt=PromptTemplate(input_variables=['summary', 'new_lines'], output_parser=None, partial_variables={}, template='Progressively summarize the lines of co... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-24 | input_key (Optional[str]) β
return_messages (bool) β
buffer (str) β
memory_key (str) β
Return type
None
attribute buffer: str = ''ο
clear()[source]ο
Clear memory contents.
Return type
None
classmethod from_messages(llm, chat_memory, *, summarize_step=2, **kwargs)[source]ο
Parameters
llm (langchain.base_language.Bas... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-25 | max_token_limit (int) β
Return type
None
attribute ai_prefix: str = 'AI'ο
attribute human_prefix: str = 'Human'ο
attribute llm: langchain.base_language.BaseLanguageModel [Required]ο
attribute max_token_limit: int = 2000ο
attribute memory_key: str = 'history'ο
load_memory_variables(inputs)[source]ο
Return history buffe... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-26 | Retrieve the messages from Cosmos
Return type
None
add_message(message)[source]ο
Add a self-created message to the store
Parameters
message (langchain.schema.BaseMessage) β
Return type
None
upsert_messages()[source]ο
Update the cosmosdb item.
Return type
None
clear()[source]ο
Clear session memory from this memory and ... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-27 | Parameters
file_path (str) β path of the local file to store the messages.
property messages: List[langchain.schema.BaseMessage]ο
Retrieve the messages from the local file
add_message(message)[source]ο
Append the message to the record in the local file
Parameters
message (langchain.schema.BaseMessage) β
Return type
No... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-28 | See https://gomomento.com/
Parameters
session_id (str) β
cache_client (momento.CacheClient) β
cache_name (str) β
key_prefix (str) β
ttl (Optional[timedelta]) β
ensure_cache_exists (bool) β
classmethod from_client_params(session_id, cache_name, ttl, *, configuration=None, auth_token=None, **kwargs)[source]ο
Constr... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-29 | session_id (str) β arbitrary key that is used to store the messages
of a single chat session.
database_name (str) β name of the database to use
collection_name (str) β name of the collection to use
property messages: List[langchain.schema.BaseMessage]ο
Retrieve the messages from MongoDB
add_message(message)[source]ο
Ap... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-30 | Delete a session
Return type
None
async init()[source]ο
Return type
None
load_memory_variables(values)[source]ο
Return key-value pairs given the text input to the chain.
If None, return all memories
Parameters
values (Dict[str, Any]) β
Return type
Dict[str, Any]
save_context(inputs, outputs)[source]ο
Save context from... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-31 | Nothing to clear, got a memory like a vault.
Return type
None
load_memory_variables(inputs)[source]ο
Load memory variables from memory.
Parameters
inputs (Dict[str, Any]) β
Return type
Dict[str, str]
save_context(inputs, outputs)[source]ο
Nothing should be saved or changed
Parameters
inputs (Dict[str, Any]) β
outputs... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-32 | that TTL is extended by 3 days every time the entity is read back.
Parameters
session_id (str) β
url (str) β
key_prefix (str) β
ttl (Optional[int]) β
recall_ttl (Optional[int]) β
args (Any) β
redis_client (Any) β
Return type
None
attribute key_prefix: str = 'memory_store'ο
attribute recall_ttl: Optional[int] = 2... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-33 | property messages: List[langchain.schema.BaseMessage]ο
Retrieve all messages from db
add_message(message)[source]ο
Append the message to the record in db
Parameters
message (langchain.schema.BaseMessage) β
Return type
None
clear()[source]ο
Clear session memory from db
Return type
None
class langchain.memory.SQLiteEnti... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-34 | Simple memory for storing context or other bits of information that shouldnβt
ever change between prompts.
Parameters
memories (Dict[str, Any]) β
Return type
None
attribute memories: Dict[str, Any] = {}ο
clear()[source]ο
Nothing to clear, got a memory like a vault.
Return type
None
load_memory_variables(inputs)[source... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-35 | attribute return_docs: bool = Falseο
Whether or not to return the result of querying the database directly.
clear()[source]ο
Nothing to clear.
Return type
None
load_memory_variables(inputs)[source]ο
Return history buffer.
Parameters
inputs (Dict[str, Any]) β
Return type
Dict[str, Union[List[langchain.schema.Document],... | https://api.python.langchain.com/en/stable/modules/memory.html |
c73826eb6edd-36 | properties.
For more information on the zep-python package, see:
https://github.com/getzep/zep-python
Parameters
session_id (str) β
url (str) β
Return type
None
property messages: List[langchain.schema.BaseMessage]ο
Retrieve messages from Zep memory
property zep_messages: List[Message]ο
Retrieve summary from Zep memo... | https://api.python.langchain.com/en/stable/modules/memory.html |
2b28b54605b7-0 | Vector Storesο
Wrappers on top of vector stores.
class langchain.vectorstores.AlibabaCloudOpenSearch(embedding, config, **kwargs)[source]ο
Bases: langchain.vectorstores.base.VectorStore
Alibaba Cloud OpenSearch Vector Store
Parameters
embedding (langchain.embeddings.base.Embeddings) β
config (langchain.vectorstores.al... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-1 | score_threshold: Optional, a floating point value between 0 to 1 to
filter the resulting set of retrieved docs
search_filter (Optional[dict]) β
kwargs (Any) β
Returns
List of Tuples of (doc, similarity_score)
Return type
List[Tuple[langchain.schema.Document, float]]
similarity_search_by_vector(embedding, k=4, search_... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-2 | metadatas (Optional[List[dict]]) β
config (Optional[langchain.vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearchSettings]) β
kwargs (Any) β
Return type
langchain.vectorstores.alibabacloud_opensearch.AlibabaCloudOpenSearch
classmethod from_documents(documents, embedding, ids=None, config=None, **kwargs)[sour... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-3 | vector store and opensearch instance configuration table field names:
{
βidβ: βThe id field name map of index document.β,
βdocumentβ: βThe text field name map of index document.β,
βembeddingβ: βIn the embedding field of the opensearch instance,
the values must be in float16 multivalue type and separated by commas.β,
βm... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-4 | collection_name is the name of the collection to use. (default: langchain)
NOTE: This is not the name of the table, but the name of the collection.The tables will be created when initializing the store (if not exists)
So, make sure the user has the right permissions to create tables.
pre_delete_collection if True, will... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-5 | k (int) β Number of results to return. Defaults to 4.
filter (Optional[Dict[str, str]]) β Filter by metadata. Defaults to None.
kwargs (Any) β
Returns
List of Documents most similar to the query.
Return type
List[langchain.schema.Document]
similarity_search_with_score(query, k=4, filter=None)[source]ο
Return docs most... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-6 | Return VectorStore initialized from texts and embeddings.
Postgres Connection string is required
Either pass it as a parameter
or set the PG_CONNECTION_STRING environment variable.
Parameters
texts (List[str]) β
embedding (langchain.embeddings.base.Embeddings) β
metadatas (Optional[List[dict]]) β
embedding_dimension... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-7 | user (str) β
password (str) β
Return type
str
class langchain.vectorstores.Annoy(embedding_function, index, metric, docstore, index_to_docstore_id)[source]ο
Bases: langchain.vectorstores.base.VectorStore
Wrapper around Annoy vector database.
To use, you should have the annoy python package installed.
Example
from lan... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-8 | Parameters
query β Text to look up documents similar to.
k (int) β Number of Documents to return. Defaults to 4.
search_k (int) β inspect up to search_k nodes which defaults
to n_trees * n if not provided
embedding (List[float]) β
Returns
List of Documents most similar to the query and score for each
Return type
List[... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-9 | Parameters
embedding (List[float]) β Embedding to look up documents similar to.
k (int) β Number of Documents to return. Defaults to 4.
search_k (int) β inspect up to search_k nodes which defaults
to n_trees * n if not provided
kwargs (Any) β
Returns
List of Documents most similar to the embedding.
Return type
List[la... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-10 | Maximal marginal relevance optimizes for similarity to query AND diversity
among selected documents.
Parameters
embedding (List[float]) β Embedding to look up documents similar to.
fetch_k (int) β Number of Documents to fetch to pass to MMR algorithm.
k (int) β Number of Documents to return. Defaults to 4.
lambda_mult ... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-11 | Parameters
texts (List[str]) β List of documents to index.
embedding (langchain.embeddings.base.Embeddings) β Embedding function to use.
metadatas (Optional[List[dict]]) β List of metadata dictionaries to associate with documents.
metric (str) β Metric to use for indexing. Defaults to βangularβ.
trees (int) β Number of... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-12 | Return type
langchain.vectorstores.annoy.Annoy
This is a user friendly interface that:
Creates an in memory docstore with provided embeddings
Initializes the Annoy database
This is intended to be a quick way to get started.
Example
from langchain import Annoy
from langchain.embeddings import OpenAIEmbeddings
embeddings... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-13 | Example
from langchain.vectorstores import AtlasDB
from langchain.embeddings.openai import OpenAIEmbeddings
embeddings = OpenAIEmbeddings()
vectorstore = AtlasDB("my_project", embeddings.embed_query)
Parameters
name (str) β
embedding_function (Optional[Embeddings]) β
api_key (Optional[str]) β
description (str) β
is... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-14 | List of documents most similar to the query text.
Return type
List[Document]
classmethod from_texts(texts, embedding=None, metadatas=None, ids=None, name=None, api_key=None, description='A description for your project', is_public=True, reset_project_if_exists=False, index_kwargs=None, **kwargs)[source]ο
Create an Atlas... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-15 | api_key (str) β Your nomic API key,
documents (List[Document]) β List of documents to add to the vectorstore.
embedding (Optional[Embeddings]) β Embedding function. Defaults to None.
ids (Optional[List[str]]) β Optional list of document IDs. If None,
ids will be auto created
description (str) β A description for your p... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-16 | :param kwargs: vectorstore specific parameters.
Returns
List of ids from adding the texts into the vectorstore.
Parameters
texts (Iterable[str]) β
metadatas (Optional[List[dict]]) β
is_duplicate_texts (Optional[bool]) β
kwargs (Any) β
Return type
List[str]
load_local(table_name, **kwargs)[source]ο
Parameters
table_... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-17 | Parameters
embedding (Optional[List[float]]) β Embedding to look up documents similar to.
k (int) β Number of Documents to return. Defaults to 4.
scores (Optional[list]) β
kwargs (Any) β
Returns
List of Documents most similar to the query vector.
Return type
List[langchain.schema.Document]
create_table(table_name, **... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-18 | kwargs (Any) β
Returns
AwaDB vectorstore.
Return type
AwaDB
classmethod from_documents(documents, embedding=None, table_name='langchain_awadb', log_and_data_dir=None, client=None, **kwargs)[source]ο
Create an AwaDB vectorstore from a list of documents.
If a log_and_data_dir specified, the table will be persisted there... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-19 | similarity_search(query, k=4, **kwargs)[source]ο
Return docs most similar to query.
Parameters
query (str) β
k (int) β
kwargs (Any) β
Return type
List[langchain.schema.Document]
vector_search(query, k=4, **kwargs)[source]ο
Returns the most similar indexed documents to the query text.
Parameters
query (str) β The que... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-20 | Parameters
query (str) β Text to look up documents similar to.
k (int) β Number of Documents to return. Defaults to 4.
filters (Optional[str]) β
Returns
List of Documents most similar to the query and score for each
Return type
List[Tuple[langchain.schema.Document, float]]
semantic_hybrid_search(query, k=4, **kwargs)[... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
2b28b54605b7-21 | kwargs (Any) β
Return type
langchain.vectorstores.azuresearch.AzureSearch
class langchain.vectorstores.Cassandra(embedding, session, keyspace, table_name, ttl_seconds=None)[source]ο
Bases: langchain.vectorstores.base.VectorStore
Wrapper around Cassandra embeddings platform.
There is no notion of a default table name, ... | https://api.python.langchain.com/en/stable/modules/vectorstores.html |
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