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chains.openai_functions.extraction.create_extraction_chain(...) Deprecated since version 0.1.14: LangChain has introduced a method called with_structured_output thatis available on ChatModels capable of tool calling.You can read more about the method here: <https://python.langchain.com/docs/modules/model_io/chat/struct...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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chains.openai_functions.qa_with_structure.create_qa_with_sources_chain(llm) Deprecated since version 0.2.13: This function is deprecated. Refer to this guide on retrieval and question answering with sources: https://python.langchain.com/v0.2/docs/how_to/qa_sources/#structure-sources-in-model-response chains.openai_func...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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chains.openai_functions.tagging.create_tagging_chain_pydantic(...) Deprecated since version 0.2.13: LangChain has introduced a method called with_structured_output that is available on ChatModels capable of tool calling. See API reference for this function for replacement: <https://api.python.langchain.com/en/latest/ch...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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Deprecated since version 0.2.13: Use load_query_constructor_runnable instead. chains.question_answering.chain.load_qa_chain(llm) Deprecated since version 0.2.13: This class is deprecated. See the following migration guides for replacements based on chain_type: chains.structured_output.base.create_openai_fn_runnable(......
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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an interface where “chat messages” are the inputs and outputs. Class hierarchy: BaseLanguageModel --> BaseChatModel --> <name> # Examples: ChatOpenAI, ChatGooglePalm Main helpers: AIMessage, BaseMessage, HumanMessage Functions¶ chat_models.base.init_chat_model() langchain.embeddings¶ Embedding models are wrappers aro...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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Grading the accuracy of a response against ground truth answers: QAEvalChain Comparing the output of two models: PairwiseStringEvalChain or LabeledPairwiseStringEvalChain when there is additionally a reference label. Judging the efficacy of an agent’s tool usage: TrajectoryEvalChain Checking whether an output complies ...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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evaluation.criteria.eval_chain.Criteria(value) A Criteria to evaluate. evaluation.criteria.eval_chain.CriteriaEvalChain LLM Chain for evaluating runs against criteria. evaluation.criteria.eval_chain.CriteriaResultOutputParser A parser for the output of the CriteriaEvalChain. evaluation.criteria.eval_chain.LabeledCriter...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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The types of the evaluators. evaluation.schema.LLMEvalChain A base class for evaluators that use an LLM. evaluation.schema.PairwiseStringEvaluator() Compare the output of two models (or two outputs of the same model). evaluation.schema.StringEvaluator() Grade, tag, or otherwise evaluate predictions relative to their in...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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globals.get_llm_cache() Get the value of the llm_cache global setting. globals.get_verbose() Get the value of the verbose global setting. globals.set_debug(value) Set a new value for the debug global setting. globals.set_llm_cache(value) Set a new LLM cache, overwriting the previous value, if any. globals.set_verbose(v...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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Class hierarchy for ChatMessageHistory: BaseChatMessageHistory --> <name>ChatMessageHistory # Example: ZepChatMessageHistory Main helpers: AIMessage, BaseMessage, HumanMessage Classes¶ memory.buffer.ConversationBufferMemory Buffer for storing conversation memory. memory.buffer.ConversationStringBufferMemory Buffer for...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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Get the prompt input key. Deprecated classes¶ memory.summary.SummarizerMixin Deprecated since version 0.2.12: Refer here for how to incorporate summaries of conversation history: https://langchain-ai.github.io/langgraph/how-tos/memory/add-summary-conversation-history/ langchain.model_laboratory¶ Experiment with differe...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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Wrap a parser and try to fix parsing errors. output_parsers.retry.RetryWithErrorOutputParserRetryChainInput output_parsers.structured.ResponseSchema Schema for a response from a structured output parser. output_parsers.structured.StructuredOutputParser Parse the output of an LLM call to a structured output. output_pars...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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retrievers.document_compressors.cross_encoder.BaseCrossEncoder() Interface for cross encoder models. retrievers.document_compressors.cross_encoder_rerank.CrossEncoderReranker Document compressor that uses CrossEncoder for reranking. retrievers.document_compressors.embeddings_filter.EmbeddingsFilter Document compressor ...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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retrievers.document_compressors.chain_extract.default_get_input(...) Return the compression chain input. retrievers.document_compressors.chain_filter.default_get_input(...) Return the compression chain input. retrievers.ensemble.unique_by_key(iterable, key) Yield unique elements of an iterable based on a key function. ...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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An example of this is shown below, assuming you’ve created a LangSmith dataset called <my_dataset_name>: from langsmith import Client from langchain_community.chat_models import ChatOpenAI from langchain.chains import LLMChain from langchain.smith import RunEvalConfig, run_on_dataset # Chains may have memory. Passing i...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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def evaluation_name(self) -> str: return "exact_match" def _evaluate_strings(self, prediction, reference=None, input=None, **kwargs) -> dict: return {"score": prediction == reference} evaluation_config = RunEvalConfig( custom_evaluators = [MyStringEvaluator()], ) run_on_dataset( client, ...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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smith.evaluation.string_run_evaluator.StringExampleMapper Map an example, or row in the dataset, to the inputs of an evaluation. smith.evaluation.string_run_evaluator.StringRunEvaluatorChain Evaluate Run and optional examples. smith.evaluation.string_run_evaluator.StringRunMapper Extract items to evaluate from the run ...
https://api.python.langchain.com/en/latest/langchain_api_reference.html
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langchain_together 0.1.6¶ langchain_together.chat_models¶ Wrapper around Together AI’s Chat Completions API. Classes¶ chat_models.ChatTogether ChatTogether chat model. langchain_together.embeddings¶ Wrapper around Together AI’s Embeddings API. Classes¶ embeddings.TogetherEmbeddings Together embedding model integration....
https://api.python.langchain.com/en/latest/together_api_reference.html
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langchain_google_genai 1.0.10¶ langchain_google_genai.chat_models¶ Classes¶ chat_models.ChatGoogleGenerativeAI Google AI chat models integration. chat_models.ChatGoogleGenerativeAIError Custom exception class for errors associated with the Google GenAI API. langchain_google_genai.embeddings¶ Classes¶ embeddings.GoogleG...
https://api.python.langchain.com/en/latest/google_genai_api_reference.html
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langchain_exa 0.1.0¶ langchain_exa.retrievers¶ Classes¶ retrievers.ExaSearchRetriever Exa Search retriever. langchain_exa.tools¶ Tool for the Exa Search API. Classes¶ tools.ExaFindSimilarResults Tool that queries the Metaphor Search API and gets back json. tools.ExaSearchResults Exa Search tool.
https://api.python.langchain.com/en/latest/exa_api_reference.html
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langchain_mongodb 0.1.9¶ langchain_mongodb.cache¶ LangChain MongoDB Caches. Classes¶ cache.MongoDBAtlasSemanticCache(...[, ...]) MongoDB Atlas Semantic cache. cache.MongoDBCache(connection_string[, ...]) MongoDB Atlas cache langchain_mongodb.chat_message_histories¶ Classes¶ chat_message_histories.MongoDBChatMessageHist...
https://api.python.langchain.com/en/latest/mongodb_api_reference.html
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to create MongoDB’s core Vector Search Retriever. Classes¶ retrievers.full_text_search.MongoDBAtlasFullTextSearchRetriever Hybrid Search Retriever performs full-text searches using Lucene's standard (BM25) analyzer. retrievers.hybrid_search.MongoDBAtlasHybridSearchRetriever Hybrid Search Retriever combines vector and f...
https://api.python.langchain.com/en/latest/mongodb_api_reference.html
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langchain_ai21 0.1.8¶ langchain_ai21.ai21_base¶ Classes¶ ai21_base.AI21Base Base class for AI21 models. langchain_ai21.chat¶ Classes¶ chat.chat_adapter.ChatAdapter() Common interface for the different Chat models available in AI21. chat.chat_adapter.J2ChatAdapter() Adapter for J2Chat models. chat.chat_adapter.JambaChat...
https://api.python.langchain.com/en/latest/ai21_api_reference.html
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langchain_pinecone 0.1.3¶ langchain_pinecone.embeddings¶ Classes¶ embeddings.PineconeEmbeddings PineconeEmbeddings embedding model. langchain_pinecone.vectorstores¶ Classes¶ vectorstores.PineconeVectorStore([index, ...]) Pinecone vector store integration. Deprecated classes¶ vectorstores.Pinecone([index, embedding, ......
https://api.python.langchain.com/en/latest/pinecone_api_reference.html
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langchain_voyageai 0.1.1¶ langchain_voyageai.embeddings¶ Classes¶ embeddings.VoyageAIEmbeddings VoyageAIEmbeddings embedding model. langchain_voyageai.rerank¶ Classes¶ rerank.VoyageAIRerank Document compressor that uses VoyageAI Rerank API.
https://api.python.langchain.com/en/latest/voyageai_api_reference.html
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langchain_qdrant 0.1.3¶ langchain_qdrant.fastembed_sparse¶ Classes¶ fastembed_sparse.FastEmbedSparse([...]) An interface for sparse embedding models to use with Qdrant. langchain_qdrant.qdrant¶ Classes¶ qdrant.QdrantVectorStore(client, collection_name) Qdrant vector store integration. qdrant.QdrantVectorStoreError Qdra...
https://api.python.langchain.com/en/latest/qdrant_api_reference.html
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langchain_azure_dynamic_sessions 0.1.0¶ langchain_azure_dynamic_sessions.tools¶ This package provides tools for managing dynamic sessions in Azure. Classes¶ tools.sessions.RemoteFileMetadata(filename, ...) Metadata for a file in the session. tools.sessions.SessionsPythonREPLTool Azure Dynamic Sessions tool.
https://api.python.langchain.com/en/latest/azure_dynamic_sessions_api_reference.html
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langchain_ollama 0.1.3¶ langchain_ollama.chat_models¶ Ollama chat models. Classes¶ chat_models.ChatOllama Ollama chat model integration. langchain_ollama.embeddings¶ Classes¶ embeddings.OllamaEmbeddings Ollama embedding model integration. langchain_ollama.llms¶ Ollama large language models. Classes¶ llms.OllamaLLM Olla...
https://api.python.langchain.com/en/latest/ollama_api_reference.html
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langchain_ibm 0.1.9¶
https://api.python.langchain.com/en/latest/ibm_api_reference.html
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langchain_astradb 0.3.5¶ langchain_astradb.cache¶ Astra DB - based caches. Classes¶ cache.AstraDBCache(*[, collection_name, ...]) Cache that uses Astra DB as a backend. cache.AstraDBSemanticCache(*[, ...]) Astra DB semantic cache. langchain_astradb.chat_message_histories¶ Astra DB - based chat message history, based on...
https://api.python.langchain.com/en/latest/astradb_api_reference.html
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langchain_astradb.vectorstores¶ Astra DB vector store integration. Classes¶ vectorstores.AstraDBVectorStore(*, ...[, ...]) AstraDB vector store integration.
https://api.python.langchain.com/en/latest/astradb_api_reference.html
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langchain_postgres 0.0.10¶ langchain_postgres.chat_message_histories¶ Client for persisting chat message history in a Postgres database. This client provides support for both sync and async via psycopg 3. Classes¶ chat_message_histories.PostgresChatMessageHistory(...) Client for persisting chat message history in a Pos...
https://api.python.langchain.com/en/latest/postgres_api_reference.html
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langchain_huggingface 0.0.3¶ langchain_huggingface.chat_models¶ Classes¶ chat_models.huggingface.ChatHuggingFace Hugging Face LLM's as ChatModels. chat_models.huggingface.TGI_MESSAGE(role, ...) Message to send to the TextGenInference API. chat_models.huggingface.TGI_RESPONSE(...) Response from the TextGenInference API....
https://api.python.langchain.com/en/latest/huggingface_api_reference.html
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langchain_nomic 0.1.2¶
https://api.python.langchain.com/en/latest/nomic_api_reference.html
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langchain_aws 0.1.17¶ langchain_aws.agents¶ Classes¶ agents.base.BedrockAgentAction AgentAction with session id information. agents.base.BedrockAgentFinish AgentFinish with session id information. agents.base.BedrockAgentsRunnable Invoke a Bedrock Agent agents.base.GuardrailConfiguration Functions¶ agents.base.get_boto...
https://api.python.langchain.com/en/latest/aws_api_reference.html
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for supported model providers Classes¶ function_calling.AnthropicTool function_calling.FunctionDescription Representation of a callable function to send to an LLM. function_calling.ToolDescription Representation of a callable function to the OpenAI API. function_calling.ToolsOutputParser Fields Functions¶ function_call...
https://api.python.langchain.com/en/latest/aws_api_reference.html
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llms.sagemaker_endpoint.enforce_stop_tokens(...) Cut off the text as soon as any stop words occur. Deprecated classes¶ llms.bedrock.Bedrock Deprecated since version 0.1.0: Use BedrockLLM instead. langchain_aws.retrievers¶ Classes¶ retrievers.bedrock.AmazonKnowledgeBasesRetriever Amazon Bedrock Knowledge Bases retrieval...
https://api.python.langchain.com/en/latest/aws_api_reference.html
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Classes¶ utilities.redis.TokenEscaper([escape_chars_re]) Escape punctuation within an input string. utilities.utils.DistanceStrategy(value) Enumerator of the Distance strategies for calculating distances between vectors. Functions¶ utilities.math.cosine_similarity(X, Y) Row-wise cosine similarity between two equal-widt...
https://api.python.langchain.com/en/latest/aws_api_reference.html
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vectorstores.inmemorydb.filters.InMemoryDBNum(field) InMemoryDBFilterField representing a numeric field in a InMemoryDB index. vectorstores.inmemorydb.filters.InMemoryDBTag(field) InMemoryDBFilterField representing a tag in a InMemoryDB index. vectorstores.inmemorydb.filters.InMemoryDBText(field) InMemoryDBFilterField ...
https://api.python.langchain.com/en/latest/aws_api_reference.html
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langchain_google_vertexai 1.0.10¶ langchain_google_vertexai.callbacks¶ Classes¶ callbacks.VertexAICallbackHandler() Callback Handler that tracks VertexAI info. langchain_google_vertexai.chains¶ Functions¶ chains.create_structured_runnable(function, ...) Create a runnable sequence that uses OpenAI functions. chains.get_...
https://api.python.langchain.com/en/latest/google_vertexai_api_reference.html
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gemma.GemmaVertexAIModelGarden Create a new model by parsing and validating input data from keyword arguments. Functions¶ gemma.gemma_messages_to_prompt(history) Converts a list of messages to a chat prompt for Gemma. langchain_google_vertexai.llms¶ Classes¶ llms.VertexAI Google Vertex AI large language models. langcha...
https://api.python.langchain.com/en/latest/google_vertexai_api_reference.html
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vectorstores.vectorstores.VectorSearchVectorStoreGCS(...) Alias of VectorSearchVectorStore for consistency with the rest of vector stores with different document storage backends. langchain_google_vertexai.vision_models¶ Classes¶ vision_models.VertexAIImageCaptioning Implementation of the Image Captioning model as an L...
https://api.python.langchain.com/en/latest/google_vertexai_api_reference.html
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langchain_robocorp 0.0.10¶ langchain_robocorp.toolkits¶ Robocorp Action Server toolkit. Classes¶ toolkits.ActionServerRequestTool Requests POST tool with LLM-instructed extraction of truncated responses. toolkits.ActionServerToolkit Toolkit exposing Robocorp Action Server provided actions as individual tools. toolkits....
https://api.python.langchain.com/en/latest/robocorp_api_reference.html
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langchain_core.beta.runnables.context.config_with_context¶ langchain_core.beta.runnables.context.config_with_context(config: RunnableConfig, steps: List[Runnable]) → RunnableConfig[source]¶ Patch a runnable config with context getters and setters. Parameters config (RunnableConfig) – The runnable config. steps (List[Ru...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.config_with_context.html
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langchain_core.beta.runnables.context.aconfig_with_context¶ langchain_core.beta.runnables.context.aconfig_with_context(config: RunnableConfig, steps: List[Runnable]) → RunnableConfig[source]¶ Asynchronously patch a runnable config with context getters and setters. Parameters config (RunnableConfig) – The runnable confi...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.aconfig_with_context.html
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langchain_core.beta.runnables.context.Context¶ class langchain_core.beta.runnables.context.Context[source]¶ Context for a runnable. The Context class provides methods for creating context scopes, getters, and setters within a runnable. It allows for managing and accessing contextual information throughout the execution...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.Context.html
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Returns The context scope. Return type PrefixContext static getter(key: Union[str, List[str]], /) → ContextGet[source]¶ Parameters key (Union[str, List[str]]) – Return type ContextGet static setter(_key: Optional[str] = None, _value: Optional[Union[Runnable[Input, Output], Callable[[Input], Output], Callable[[Input], ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.Context.html
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langchain_core.beta.runnables.context.PrefixContext¶ class langchain_core.beta.runnables.context.PrefixContext(prefix: str = '')[source]¶ Context for a runnable with a prefix. Attributes prefix Methods __init__([prefix]) getter(key, /) setter([_key, _value]) Parameters prefix (str) – __init__(prefix: str = '')[source]...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.PrefixContext.html
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langchain_core.beta.runnables.context.ContextGet¶ Note ContextGet implements the standard Runnable Interface. 🏃 The Runnable Interface has additional methods that are available on runnables, such as with_types, with_retry, assign, bind, get_graph, and more. class langchain_core.beta.runnables.context.ContextGet[source...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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Returns A list of outputs from the Runnable. Return type List[Output] async abatch_as_completed(inputs: Sequence[Input], config: Optional[Union[RunnableConfig, Sequence[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → AsyncIterator[Tuple[int, Union[Output, Exception]]]¶ Run ainvo...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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kwargs (Any) – Return type Any as_tool(args_schema: Optional[Type[BaseModel]] = None, *, name: Optional[str] = None, description: Optional[str] = None, arg_types: Optional[Dict[str, Type]] = None) → BaseTool¶ Beta This API is in beta and may change in the future. Create a BaseTool from a Runnable. as_tool will instant...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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dict input, specifying schema via args_schema: from typing import Any, Dict, List from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.runnables import RunnableLambda def f(x: Dict[str, Any]) -> str: return str(x["a"] * max(x["b"])) class FSchema(BaseModel): """Apply a function to an inte...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. Parameters input (Input) – The input to the Runnable. config (Optional[RunnableConfig]) – The config to use for the Runnable. Defaults to None. kwargs (Optional[Any]) – Additional keyword arg...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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The order of the parent IDs is from the root to the immediate parent. Only available for v2 version of the API. The v1 version of the API will return an empty list. tags: Optional[List[str]] - The tags of the Runnable that generatedthe event. metadata: Optional[Dict[str, Any]] - The metadata of the Runnablethat generat...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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on_retriever_end [retriever name] {“query”: “hello”} [Document(…), ..] on_prompt_start [template_name] {“question”: “hello”} on_prompt_end [template_name] {“question”: “hello”} ChatPromptValue(messages: [SystemMessage, …]) In addition to the standard events, users can also dispatch custom events (see example below). Cu...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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] # will produce the following events (run_id, and parent_ids # has been omitted for brevity): [ { "data": {"input": "hello"}, "event": "on_chain_start", "metadata": {}, "name": "reverse", "tags": [], }, { "data": {"chunk": "olleh"}, "event": "on_chain...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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return "Done" slow_thing = RunnableLambda(slow_thing) async for event in slow_thing.astream_events("some_input", version="v2"): print(event) Parameters input (Any) – The input to the Runnable. config (Optional[RunnableConfig]) – The config to use for the Runnable. version (Literal['v1', 'v2']) – The version of the ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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Return type AsyncIterator[Union[StandardStreamEvent, CustomStreamEvent]] batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶ Default implementation runs invoke in parallel using a thread pool execut...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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Configure alternatives for Runnables that can be set at runtime. Parameters which (ConfigurableField) – The ConfigurableField instance that will be used to select the alternative. default_key (str) – The default key to use if no alternative is selected. Defaults to “default”. prefix_keys (bool) – Whether to prefix the ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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Returns A new Runnable with the fields configured. Return type RunnableSerializable[Input, Output] from langchain_core.runnables import ConfigurableField from langchain_openai import ChatOpenAI model = ChatOpenAI(max_tokens=20).configurable_fields( max_tokens=ConfigurableField( id="output_token_number", ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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kwargs (Optional[Any]) – Additional keyword arguments to pass to the Runnable. Yields The output of the Runnable. Return type Iterator[Output] to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ Serialize the Runnable to JSON. Returns A JSON-serializable representation of the Runnable. Return type Union...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextGet.html
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langchain_core.beta.runnables.context.ContextSet¶ Note ContextSet implements the standard Runnable Interface. 🏃 The Runnable Interface has additional methods that are available on runnables, such as with_types, with_retry, assign, bind, get_graph, and more. class langchain_core.beta.runnables.context.ContextSet[source...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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Returns A list of outputs from the Runnable. Return type List[Output] async abatch_as_completed(inputs: Sequence[Input], config: Optional[Union[RunnableConfig, Sequence[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → AsyncIterator[Tuple[int, Union[Output, Exception]]]¶ Run ainvo...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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kwargs (Any) – Return type Any as_tool(args_schema: Optional[Type[BaseModel]] = None, *, name: Optional[str] = None, description: Optional[str] = None, arg_types: Optional[Dict[str, Type]] = None) → BaseTool¶ Beta This API is in beta and may change in the future. Create a BaseTool from a Runnable. as_tool will instant...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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dict input, specifying schema via args_schema: from typing import Any, Dict, List from langchain_core.pydantic_v1 import BaseModel, Field from langchain_core.runnables import RunnableLambda def f(x: Dict[str, Any]) -> str: return str(x["a"] * max(x["b"])) class FSchema(BaseModel): """Apply a function to an inte...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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Default implementation of astream, which calls ainvoke. Subclasses should override this method if they support streaming output. Parameters input (Input) – The input to the Runnable. config (Optional[RunnableConfig]) – The config to use for the Runnable. Defaults to None. kwargs (Optional[Any]) – Additional keyword arg...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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The order of the parent IDs is from the root to the immediate parent. Only available for v2 version of the API. The v1 version of the API will return an empty list. tags: Optional[List[str]] - The tags of the Runnable that generatedthe event. metadata: Optional[Dict[str, Any]] - The metadata of the Runnablethat generat...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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on_retriever_end [retriever name] {“query”: “hello”} [Document(…), ..] on_prompt_start [template_name] {“question”: “hello”} on_prompt_end [template_name] {“question”: “hello”} ChatPromptValue(messages: [SystemMessage, …]) In addition to the standard events, users can also dispatch custom events (see example below). Cu...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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] # will produce the following events (run_id, and parent_ids # has been omitted for brevity): [ { "data": {"input": "hello"}, "event": "on_chain_start", "metadata": {}, "name": "reverse", "tags": [], }, { "data": {"chunk": "olleh"}, "event": "on_chain...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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return "Done" slow_thing = RunnableLambda(slow_thing) async for event in slow_thing.astream_events("some_input", version="v2"): print(event) Parameters input (Any) – The input to the Runnable. config (Optional[RunnableConfig]) – The config to use for the Runnable. version (Literal['v1', 'v2']) – The version of the ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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Return type AsyncIterator[Union[StandardStreamEvent, CustomStreamEvent]] batch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, return_exceptions: bool = False, **kwargs: Optional[Any]) → List[Output]¶ Default implementation runs invoke in parallel using a thread pool execut...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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Configure alternatives for Runnables that can be set at runtime. Parameters which (ConfigurableField) – The ConfigurableField instance that will be used to select the alternative. default_key (str) – The default key to use if no alternative is selected. Defaults to “default”. prefix_keys (bool) – Whether to prefix the ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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Returns A new Runnable with the fields configured. Return type RunnableSerializable[Input, Output] from langchain_core.runnables import ConfigurableField from langchain_openai import ChatOpenAI model = ChatOpenAI(max_tokens=20).configurable_fields( max_tokens=ConfigurableField( id="output_token_number", ...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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kwargs (Optional[Any]) – Additional keyword arguments to pass to the Runnable. Yields The output of the Runnable. Return type Iterator[Output] to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶ Serialize the Runnable to JSON. Returns A JSON-serializable representation of the Runnable. Return type Union...
https://api.python.langchain.com/en/latest/beta/langchain_core.beta.runnables.context.ContextSet.html
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langchain_community.chat_loaders.imessage.nanoseconds_from_2001_to_datetime¶ langchain_community.chat_loaders.imessage.nanoseconds_from_2001_to_datetime(nanoseconds: int) → datetime[source]¶ Convert nanoseconds since 2001 to a datetime object. Parameters nanoseconds (int) – Nanoseconds since January 1, 2001. Returns Da...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.imessage.nanoseconds_from_2001_to_datetime.html
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langchain_community.chat_loaders.gmail.GMailLoader¶ class langchain_community.chat_loaders.gmail.GMailLoader(creds: Any, n: int = 100, raise_error: bool = False)[source]¶ Deprecated since version 0.0.32: Use langchain_google_community.GMailLoader instead. Load data from GMail. There are many ways you could want to load...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.gmail.GMailLoader.html
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Returns An iterator of chat sessions. Return type Iterator[ChatSession] load() → List[ChatSession]¶ Eagerly load the chat sessions into memory. Returns A list of chat sessions. Return type List[ChatSession] Examples using GMailLoader¶ GMail
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.gmail.GMailLoader.html
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langchain_community.chat_loaders.imessage.IMessageChatLoader¶ class langchain_community.chat_loaders.imessage.IMessageChatLoader(path: Optional[Union[str, Path]] = None)[source]¶ Load chat sessions from the iMessage chat.db SQLite file. It only works on macOS when you have iMessage enabled and have the chat.db file. Th...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.imessage.IMessageChatLoader.html
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Eagerly load the chat sessions into memory. Returns A list of chat sessions. Return type List[ChatSession] Examples using IMessageChatLoader¶ iMessage
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.imessage.IMessageChatLoader.html
6b4df8dc4ccf-0
langchain_community.chat_loaders.facebook_messenger.SingleFileFacebookMessengerChatLoader¶ class langchain_community.chat_loaders.facebook_messenger.SingleFileFacebookMessengerChatLoader(path: Union[Path, str])[source]¶ Load Facebook Messenger chat data from a single file. Parameters path (Union[Path, str]) – The path ...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.facebook_messenger.SingleFileFacebookMessengerChatLoader.html
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langchain_community.chat_loaders.facebook_messenger.FolderFacebookMessengerChatLoader¶ class langchain_community.chat_loaders.facebook_messenger.FolderFacebookMessengerChatLoader(path: Union[str, Path])[source]¶ Load Facebook Messenger chat data from a folder. Parameters path (Union[str, Path]) – The path to the direct...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.facebook_messenger.FolderFacebookMessengerChatLoader.html
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langchain_community.chat_loaders.utils.map_ai_messages_in_session¶ langchain_community.chat_loaders.utils.map_ai_messages_in_session(chat_sessions: ChatSession, sender: str) → ChatSession[source]¶ Convert messages from the specified ‘sender’ to AI messages. This is useful for fine-tuning the AI to adapt to your voice. ...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.utils.map_ai_messages_in_session.html
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langchain_community.chat_loaders.slack.SlackChatLoader¶ class langchain_community.chat_loaders.slack.SlackChatLoader(path: Union[str, Path])[source]¶ Load Slack conversations from a dump zip file. Initialize the chat loader with the path to the exported Slack dump zip file. Parameters path (Union[str, Path]) – Path to ...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.slack.SlackChatLoader.html
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langchain_community.chat_loaders.telegram.TelegramChatLoader¶ class langchain_community.chat_loaders.telegram.TelegramChatLoader(path: Union[str, Path])[source]¶ Load telegram conversations to LangChain chat messages. To export, use the Telegram Desktop app from https://desktop.telegram.org/, select a conversation, cli...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.telegram.TelegramChatLoader.html
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langchain_community.chat_loaders.utils.merge_chat_runs¶ langchain_community.chat_loaders.utils.merge_chat_runs(chat_sessions: Iterable[ChatSession]) → Iterator[ChatSession][source]¶ Merge chat runs together. A chat run is a sequence of messages from the same sender. Parameters chat_sessions (Iterable[ChatSession]) – A ...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.utils.merge_chat_runs.html
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langchain_core.chat_loaders.BaseChatLoader¶ class langchain_core.chat_loaders.BaseChatLoader[source]¶ Base class for chat loaders. Methods __init__() lazy_load() Lazy load the chat sessions. load() Eagerly load the chat sessions into memory. __init__()¶ abstract lazy_load() → Iterator[ChatSession][source]¶ Lazy load th...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_core.chat_loaders.BaseChatLoader.html
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langchain_community.chat_loaders.whatsapp.WhatsAppChatLoader¶ class langchain_community.chat_loaders.whatsapp.WhatsAppChatLoader(path: str)[source]¶ Load WhatsApp conversations from a dump zip file or directory. Initialize the WhatsAppChatLoader. Parameters path (str) – Path to the exported WhatsApp chat zip directory,...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.whatsapp.WhatsAppChatLoader.html
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langchain_community.chat_loaders.langsmith.LangSmithDatasetChatLoader¶ class langchain_community.chat_loaders.langsmith.LangSmithDatasetChatLoader(*, dataset_name: str, client: Optional['Client'] = None)[source]¶ Load chat sessions from a LangSmith dataset with the “chat” data type. dataset_name¶ The name of the LangSm...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.langsmith.LangSmithDatasetChatLoader.html
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Eagerly load the chat sessions into memory. Returns A list of chat sessions. Return type List[ChatSession] Examples using LangSmithDatasetChatLoader¶ LangSmith Chat Datasets
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.langsmith.LangSmithDatasetChatLoader.html
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langchain_community.chat_loaders.utils.map_ai_messages¶ langchain_community.chat_loaders.utils.map_ai_messages(chat_sessions: Iterable[ChatSession], sender: str) → Iterator[ChatSession][source]¶ Convert messages from the specified ‘sender’ to AI messages. This is useful for fine-tuning the AI to adapt to your voice. Pa...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.utils.map_ai_messages.html
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langchain_community.chat_loaders.utils.merge_chat_runs_in_session¶ langchain_community.chat_loaders.utils.merge_chat_runs_in_session(chat_session: ChatSession, delimiter: str = '\n\n') → ChatSession[source]¶ Merge chat runs together in a chat session. A chat run is a sequence of messages from the same sender. Parameter...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.utils.merge_chat_runs_in_session.html
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langchain_community.chat_loaders.langsmith.LangSmithRunChatLoader¶ class langchain_community.chat_loaders.langsmith.LangSmithRunChatLoader(runs: Iterable[Union[str, Run]], client: Optional['Client'] = None)[source]¶ Load chat sessions from a list of LangSmith “llm” runs. runs¶ The list of LLM run IDs or run objects. Ty...
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.langsmith.LangSmithRunChatLoader.html
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Return type Iterator[ChatSession] load() → List[ChatSession]¶ Eagerly load the chat sessions into memory. Returns A list of chat sessions. Return type List[ChatSession] Examples using LangSmithRunChatLoader¶ LangSmith LLM Runs
https://api.python.langchain.com/en/latest/chat_loaders/langchain_community.chat_loaders.langsmith.LangSmithRunChatLoader.html
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langchain.globals.set_verbose¶ langchain.globals.set_verbose(value: bool) → None[source]¶ Set a new value for the verbose global setting. Parameters value (bool) – Return type None Examples using set_verbose¶ How to debug your LLM apps OpaquePrompts
https://api.python.langchain.com/en/latest/globals/langchain.globals.set_verbose.html
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langchain_core.globals.set_debug¶ langchain_core.globals.set_debug(value: bool) → None[source]¶ Set a new value for the debug global setting. Parameters value (bool) – The new value for the debug global setting. Return type None Examples using set_debug¶ Bittensor Document Comparison How to debug your LLM apps OpaquePr...
https://api.python.langchain.com/en/latest/globals/langchain_core.globals.set_debug.html
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langchain_core.globals.get_verbose¶ langchain_core.globals.get_verbose() → bool[source]¶ Get the value of the verbose global setting. Returns The value of the verbose global setting. Return type bool
https://api.python.langchain.com/en/latest/globals/langchain_core.globals.get_verbose.html
da6f9eef2df5-0
langchain_core.globals.set_llm_cache¶ langchain_core.globals.set_llm_cache(value: Optional[BaseCache]) → None[source]¶ Set a new LLM cache, overwriting the previous value, if any. Parameters value (Optional[BaseCache]) – The new LLM cache to use. If None, the LLM cache is disabled. Return type None Examples using set_l...
https://api.python.langchain.com/en/latest/globals/langchain_core.globals.set_llm_cache.html
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langchain_core.globals.get_llm_cache¶ langchain_core.globals.get_llm_cache() → BaseCache[source]¶ Get the value of the llm_cache global setting. Returns The value of the llm_cache global setting. Return type BaseCache
https://api.python.langchain.com/en/latest/globals/langchain_core.globals.get_llm_cache.html
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langchain_core.globals.get_debug¶ langchain_core.globals.get_debug() → bool[source]¶ Get the value of the debug global setting. Returns The value of the debug global setting. Return type bool
https://api.python.langchain.com/en/latest/globals/langchain_core.globals.get_debug.html
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langchain.globals.get_llm_cache¶ langchain.globals.get_llm_cache() → BaseCache[source]¶ Get the value of the llm_cache global setting. Return type BaseCache
https://api.python.langchain.com/en/latest/globals/langchain.globals.get_llm_cache.html