From b7c0eb9ecbec4d66149fd433ee34c4f5beb69e3d Mon Sep 17 00:00:00 2001
From: William FH <13333726+hinthornw@users.noreply.github.com>
Date: Sat, 29 Jul 2023 08:44:32 -0700
Subject: [PATCH] Wfh/ref links (#8454)
---
docs/api_reference/guide_imports.json | 2 +-
.../generate_api_reference_links.py | 106 +++++---
.../llms/jsonformer_experimental.ipynb | 2 +-
.../llms/rellm_experimental.ipynb | 2 +-
.../integrations/providers/dataforseo.mdx | 2 +-
.../integrations/providers/rebuff.ipynb | 5 +-
.../extras/integrations/providers/rockset.mdx | 2 +-
docs/extras/integrations/providers/spacy.mdx | 2 +-
.../integrations/text_embedding/localai.ipynb | 2 +-
.../integrations/tools/dataforseo.ipynb | 2 +-
.../integrations/vectorstores/rockset.ipynb | 13 +-
.../modules/chains/how_to/custom_chain.ipynb | 13 +-
.../few_shot_examples_chat.ipynb | 81 +++---
.../agent_simulations/characters.ipynb | 2 +-
.../use_cases/autonomous_agents/autogpt.ipynb | 48 ++--
.../autonomous_agents/baby_agi.ipynb | 2 +-
.../baby_agi_with_agent.ipynb | 2 +-
.../autonomous_agents/marathon_times.ipynb | 2 +-
docs/extras/use_cases/code_writing/cpal.ipynb | 240 +-----------------
.../agents/agent_types/plan_and_execute.mdx | 2 +-
.../agents/agent_toolkits/__init__.py | 2 +
libs/langchain/langchain/prompts/chat.py | 14 +-
.../integration_tests/chains/test_cpal.py | 20 +-
23 files changed, 189 insertions(+), 379 deletions(-)
diff --git a/docs/api_reference/guide_imports.json b/docs/api_reference/guide_imports.json
index 741c7c8cc97..9efc571c7e9 100644
--- a/docs/api_reference/guide_imports.json
+++ b/docs/api_reference/guide_imports.json
@@ -1 +1 @@
-{"XinferenceEmbeddings": {"Xorbits inference (Xinference)": "https://python.langchain.com/docs/integrations/text_embedding/xinference"}, "DeepInfraEmbeddings": {"DeepInfra": "https://python.langchain.com/docs/integrations/text_embedding/deepinfra"}, "HuggingFaceEmbeddings": {"Hugging Face Hub": "https://python.langchain.com/docs/integrations/text_embedding/huggingfacehub", "Sentence Transformers Embeddings": "https://python.langchain.com/docs/integrations/text_embedding/sentence_transformers", "LOTR (Merger Retriever)": "https://python.langchain.com/docs/integrations/retrievers/merger_retriever", "Hugging Face": "https://python.langchain.com/docs/integrations/providers/huggingface", "Annoy": "https://python.langchain.com/docs/integrations/vectorstores/annoy", "Pairwise Embedding Distance ": "https://python.langchain.com/docs/guides/evaluation/comparison/pairwise_embedding_distance", "Embedding Distance": "https://python.langchain.com/docs/guides/evaluation/string/embedding_distance", "Lost in the middle: The problem with long contexts": "https://python.langchain.com/docs/modules/data_connection/document_transformers/post_retrieval/long_context_reorder"}, "GPT4AllEmbeddings": {"GPT4All": "https://python.langchain.com/docs/integrations/text_embedding/gpt4all", "Running LLMs locally": "https://python.langchain.com/docs/use_cases/question_answering/local_retrieval_qa", "Use local LLMs": "https://python.langchain.com/docs/use_cases/question_answering/how_to/local_retrieval_qa", "WebResearchRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/web_research"}, "MosaicMLInstructorEmbeddings": {"MosaicML embeddings": "https://python.langchain.com/docs/integrations/text_embedding/mosaicml"}, "OpenAIEmbeddings": {"OpenAI": "https://python.langchain.com/docs/integrations/providers/openai", "AzureOpenAI": "https://python.langchain.com/docs/integrations/text_embedding/azureopenai", "Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "kNN": "https://python.langchain.com/docs/integrations/retrievers/knn", "DocArray Retriever": "https://python.langchain.com/docs/integrations/retrievers/docarray_retriever", "SVM": "https://python.langchain.com/docs/integrations/retrievers/svm", "Pinecone Hybrid Search": "https://python.langchain.com/docs/integrations/retrievers/pinecone_hybrid_search", "LOTR (Merger Retriever)": "https://python.langchain.com/docs/integrations/retrievers/merger_retriever", "Azure OpenAI": "https://python.langchain.com/docs/integrations/providers/azure_openai", "Document Comparison": "https://python.langchain.com/docs/integrations/toolkits/document_comparison_toolkit", "Vectorstore Agent": "https://python.langchain.com/docs/integrations/toolkits/vectorstore", "LanceDB": "https://python.langchain.com/docs/integrations/vectorstores/lancedb", "Weaviate": "https://python.langchain.com/docs/integrations/vectorstores/weaviate", "Activeloop's Deep Lake": "https://python.langchain.com/docs/integrations/vectorstores/deeplake", "Redis": "https://python.langchain.com/docs/integrations/vectorstores/redis", "PGVector": "https://python.langchain.com/docs/integrations/vectorstores/pgvector", "Rockset": "https://python.langchain.com/docs/integrations/vectorstores/rockset", "Zilliz": "https://python.langchain.com/docs/integrations/vectorstores/zilliz", "SingleStoreDB": "https://python.langchain.com/docs/integrations/vectorstores/singlestoredb", "Typesense": "https://python.langchain.com/docs/integrations/vectorstores/typesense", "Atlas": "https://python.langchain.com/docs/integrations/vectorstores/atlas", "Chroma": "https://python.langchain.com/docs/integrations/vectorstores/chroma", "Alibaba Cloud OpenSearch": "https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch", "StarRocks": "https://python.langchain.com/docs/integrations/vectorstores/starrocks", "scikit-learn": "https://python.langchain.com/docs/integrations/vectorstores/sklearn", "DocArrayHnswSearch": "https://python.langchain.com/docs/integrations/vectorstores/docarray_hnsw", "MyScale": "https://python.langchain.com/docs/integrations/vectorstores/myscale", "ClickHouse Vector Search": "https://python.langchain.com/docs/integrations/vectorstores/clickhouse", "Qdrant": "https://python.langchain.com/docs/integrations/vectorstores/qdrant", "Tigris": "https://python.langchain.com/docs/integrations/vectorstores/tigris", "Supabase (Postgres)": "https://python.langchain.com/docs/integrations/vectorstores/supabase", "OpenSearch": "https://python.langchain.com/docs/integrations/vectorstores/opensearch", "Pinecone": "https://python.langchain.com/docs/integrations/vectorstores/pinecone", "Azure Cognitive Search": "https://python.langchain.com/docs/integrations/vectorstores/azuresearch", "Cassandra": "https://python.langchain.com/docs/integrations/vectorstores/cassandra", "Milvus": "https://python.langchain.com/docs/integrations/vectorstores/milvus", "ElasticSearch": "https://python.langchain.com/docs/integrations/vectorstores/elasticsearch", "DocArrayInMemorySearch": "https://python.langchain.com/docs/integrations/vectorstores/docarray_in_memory", "pg_embedding": "https://python.langchain.com/docs/integrations/vectorstores/pgembedding", "FAISS": "https://python.langchain.com/docs/integrations/vectorstores/faiss", "AnalyticDB": "https://python.langchain.com/docs/integrations/vectorstores/analyticdb", "Hologres": "https://python.langchain.com/docs/integrations/vectorstores/hologres", "MongoDB Atlas": "https://python.langchain.com/docs/integrations/vectorstores/mongodb_atlas", "Meilisearch": "https://python.langchain.com/docs/integrations/vectorstores/meilisearch", "Loading documents from a YouTube url": "https://python.langchain.com/docs/integrations/document_loaders/youtube_audio", "Psychic": "https://python.langchain.com/docs/integrations/document_loaders/psychic", "Docugami": "https://python.langchain.com/docs/integrations/document_loaders/docugami", "Caching integrations": "https://python.langchain.com/docs/integrations/llms/llm_caching", "Data Augmented Question Answering": "https://python.langchain.com/docs/guides/evaluation/examples/data_augmented_question_answering", "AutoGPT": "https://python.langchain.com/docs/use_cases/autonomous_agents/autogpt", "BabyAGI User Guide": "https://python.langchain.com/docs/use_cases/agents/baby_agi", "BabyAGI with Tools": "https://python.langchain.com/docs/use_cases/agents/baby_agi_with_agent", "!pip install bs4": "https://python.langchain.com/docs/use_cases/autonomous_agents/marathon_times", "Context aware text splitting and QA / Chat": "https://python.langchain.com/docs/use_cases/question_answering/document-context-aware-QA", "QA over Documents": "https://python.langchain.com/docs/use_cases/question_answering/index", "Question answering over a group chat messages using Activeloop's DeepLake": "https://python.langchain.com/docs/use_cases/question_answering/semantic-search-over-chat", "Perform context-aware text splitting": "https://python.langchain.com/docs/use_cases/question_answering/how_to/document-context-aware-QA", "Retrieve from vector stores directly": "https://python.langchain.com/docs/use_cases/question_answering/how_to/vector_db_text_generation", "Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "Improve document indexing with HyDE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/hyde", "Structure answers with OpenAI functions": "https://python.langchain.com/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa", "QA using Activeloop's DeepLake": "https://python.langchain.com/docs/use_cases/question_answering/integrations/semantic-search-over-chat", "Analysis of Twitter the-algorithm source code with LangChain, GPT4 and Activeloop's Deep Lake": "https://python.langchain.com/docs/use_cases/code/twitter-the-algorithm-analysis-deeplake", "Use LangChain, GPT and Activeloop's Deep Lake to work with code base": "https://python.langchain.com/docs/use_cases/code/code-analysis-deeplake", "Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval", "Generative Agents in LangChain": "https://python.langchain.com/docs/use_cases/agent_simulations/characters", "MultiQueryRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/MultiQueryRetriever", "WebResearchRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/web_research", "Weaviate self-querying ": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/weaviate_self_query", "Chroma self-querying ": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/chroma_self_query", "DeepLake self-querying ": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/deeplake_self_query", "Self-querying with Pinecone": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/pinecone", "Self-querying with MyScale": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/myscale_self_query", "Qdrant self-querying ": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/qdrant_self_query", "How to add memory to a Multi-Input Chain": "https://python.langchain.com/docs/modules/memory/adding_memory_chain_multiple_inputs", "Combine agents and vector stores": "https://python.langchain.com/docs/modules/agents/how_to/agent_vectorstore", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval", "Select by maximal marginal relevance (MMR)": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/mmr", "Few shot examples for chat models": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/few_shot_examples_chat", "Loading from LangChainHub": "https://python.langchain.com/docs/modules/chains/how_to/from_hub", "Retrieval QA using OpenAI functions": "https://python.langchain.com/docs/modules/chains/additional/openai_functions_retrieval_qa", "Vector store-augmented text generation": "https://python.langchain.com/docs/modules/chains/additional/vector_db_text_generation", "FLARE": "https://python.langchain.com/docs/modules/chains/additional/flare", "Hypothetical Document Embeddings": "https://python.langchain.com/docs/modules/chains/additional/hyde"}, "VertexAIEmbeddings": {"Google Cloud Platform Vertex AI PaLM ": "https://python.langchain.com/docs/integrations/text_embedding/google_vertex_ai_palm"}, "BedrockEmbeddings": {"Bedrock Embeddings": "https://python.langchain.com/docs/integrations/text_embedding/bedrock", "Bedrock": "https://python.langchain.com/docs/integrations/providers/bedrock"}, "LlamaCppEmbeddings": {"Llama-cpp": "https://python.langchain.com/docs/integrations/text_embedding/llamacpp", "Llama.cpp": "https://python.langchain.com/docs/integrations/providers/llamacpp"}, "NLPCloudEmbeddings": {"NLP Cloud": "https://python.langchain.com/docs/integrations/text_embedding/nlp_cloud"}, "SpacyEmbeddings": {"Spacy Embedding": "https://python.langchain.com/docs/integrations/text_embedding/spacy_embedding"}, "HuggingFaceInstructEmbeddings": {"InstructEmbeddings": "https://python.langchain.com/docs/integrations/text_embedding/instruct_embeddings"}, "CohereEmbeddings": {"Cohere": "https://python.langchain.com/docs/integrations/providers/cohere", "How to add memory to a Multi-Input Chain": "https://python.langchain.com/docs/modules/memory/adding_memory_chain_multiple_inputs", "Router": "https://python.langchain.com/docs/modules/chains/foundational/router"}, "ClarifaiEmbeddings": {"Clarifai": "https://python.langchain.com/docs/integrations/providers/clarifai"}, "AwaEmbeddings": {"AwaEmbedding": "https://python.langchain.com/docs/integrations/text_embedding/Awa"}, "MiniMaxEmbeddings": {"MiniMax": "https://python.langchain.com/docs/integrations/text_embedding/minimax", "Minimax": "https://python.langchain.com/docs/integrations/providers/minimax"}, "FakeEmbeddings": {"Fake Embeddings": "https://python.langchain.com/docs/integrations/text_embedding/fake", "DocArray Retriever": "https://python.langchain.com/docs/integrations/retrievers/docarray_retriever", "Vectara": "https://python.langchain.com/docs/integrations/vectorstores/vectara", "Tair": "https://python.langchain.com/docs/integrations/vectorstores/tair"}, "ElasticsearchEmbeddings": {"Elasticsearch": "https://python.langchain.com/docs/integrations/text_embedding/elasticsearch", "ElasticSearch": "https://python.langchain.com/docs/integrations/vectorstores/elasticsearch"}, "EmbaasEmbeddings": {"Embaas": "https://python.langchain.com/docs/integrations/text_embedding/embaas"}, "JinaEmbeddings": {"Jina": "https://python.langchain.com/docs/integrations/providers/jina"}, "AlephAlphaAsymmetricSemanticEmbedding": {"Aleph Alpha": "https://python.langchain.com/docs/integrations/text_embedding/aleph_alpha"}, "AlephAlphaSymmetricSemanticEmbedding": {"Aleph Alpha": "https://python.langchain.com/docs/integrations/providers/aleph_alpha"}, "DashScopeEmbeddings": {"DashScope": "https://python.langchain.com/docs/integrations/text_embedding/dashscope"}, "TensorflowHubEmbeddings": {"TensorflowHub": "https://python.langchain.com/docs/integrations/text_embedding/tensorflowhub"}, "ModelScopeEmbeddings": {"ModelScope": "https://python.langchain.com/docs/integrations/providers/modelscope"}, "SagemakerEndpointEmbeddings": {"SageMaker Endpoint Embeddings": "https://python.langchain.com/docs/integrations/text_embedding/sagemaker-endpoint", "SageMaker Endpoint": "https://python.langchain.com/docs/integrations/providers/sagemaker_endpoint"}, "EmbeddingsContentHandler": {"SageMaker Endpoint Embeddings": "https://python.langchain.com/docs/integrations/text_embedding/sagemaker-endpoint"}, "LocalAIEmbeddings": {"LocalAI": "https://python.langchain.com/docs/integrations/text_embedding/localai"}, "ElasticSearchBM25Retriever": {"ElasticSearch BM25": "https://python.langchain.com/docs/integrations/retrievers/elastic_search_bm25", "Elasticsearch": "https://python.langchain.com/docs/integrations/providers/elasticsearch"}, "ZepChatMessageHistory": {"Zep": "https://python.langchain.com/docs/integrations/retrievers/zep_memorystore"}, "HumanMessage": {"Zep": "https://python.langchain.com/docs/integrations/retrievers/zep_memorystore", "Zep Memory": "https://python.langchain.com/docs/integrations/memory/zep_memory", "Google Cloud Platform Vertex AI PaLM ": "https://python.langchain.com/docs/integrations/chat/google_vertex_ai_palm", "Azure": "https://python.langchain.com/docs/integrations/chat/azure_chat_openai", "PromptLayer ChatOpenAI": "https://python.langchain.com/docs/integrations/chat/promptlayer_chatopenai", "MLflow AI Gateway": "https://python.langchain.com/docs/integrations/providers/mlflow_ai_gateway", "Flyte": "https://python.langchain.com/docs/integrations/providers/flyte", "Arthur": "https://python.langchain.com/docs/integrations/providers/arthur_tracking", "Custom callback handlers": "https://python.langchain.com/docs/modules/callbacks/custom_callbacks", "Tools as OpenAI Functions": "https://python.langchain.com/docs/modules/agents/tools/tools_as_openai_functions", "Prompt Pipelining": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/prompts_pipelining", "Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/popular/openai_functions"}, "ZepRetriever": {"Zep": "https://python.langchain.com/docs/integrations/providers/zep", "Zep Memory": "https://python.langchain.com/docs/integrations/memory/zep_memory"}, "VespaRetriever": {"Vespa": "https://python.langchain.com/docs/integrations/providers/vespa"}, "AmazonKendraRetriever": {"Amazon Kendra": "https://python.langchain.com/docs/integrations/retrievers/amazon_kendra_retriever"}, "RecursiveCharacterTextSplitter": {"Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "Loading documents from a YouTube url": "https://python.langchain.com/docs/integrations/document_loaders/youtube_audio", "!pip install bs4": "https://python.langchain.com/docs/use_cases/autonomous_agents/marathon_times", "Context aware text splitting and QA / Chat": "https://python.langchain.com/docs/use_cases/question_answering/document-context-aware-QA", "QA over Documents": "https://python.langchain.com/docs/use_cases/question_answering/index", "Running LLMs locally": "https://python.langchain.com/docs/use_cases/question_answering/local_retrieval_qa", "Perform context-aware text splitting": "https://python.langchain.com/docs/use_cases/question_answering/how_to/document-context-aware-QA", "Use local LLMs": "https://python.langchain.com/docs/use_cases/question_answering/how_to/local_retrieval_qa", "MultiQueryRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/MultiQueryRetriever", "MarkdownHeaderTextSplitter": "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/markdown_header_metadata"}, "TextLoader": {"Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "Chat Over Documents with Vectara": "https://python.langchain.com/docs/integrations/providers/vectara/vectara_chat", "Vectorstore Agent": "https://python.langchain.com/docs/integrations/toolkits/vectorstore", "LanceDB": "https://python.langchain.com/docs/integrations/vectorstores/lancedb", "Weaviate": "https://python.langchain.com/docs/integrations/vectorstores/weaviate", "Activeloop's Deep Lake": "https://python.langchain.com/docs/integrations/vectorstores/deeplake", "Vectara": "https://python.langchain.com/docs/integrations/vectorstores/vectara", "Redis": "https://python.langchain.com/docs/integrations/vectorstores/redis", "PGVector": "https://python.langchain.com/docs/integrations/vectorstores/pgvector", "Rockset": "https://python.langchain.com/docs/integrations/vectorstores/rockset", "Zilliz": "https://python.langchain.com/docs/integrations/vectorstores/zilliz", "SingleStoreDB": "https://python.langchain.com/docs/integrations/vectorstores/singlestoredb", "Annoy": "https://python.langchain.com/docs/integrations/vectorstores/annoy", "Typesense": "https://python.langchain.com/docs/integrations/vectorstores/typesense", "Atlas": "https://python.langchain.com/docs/integrations/vectorstores/atlas", "Tair": "https://python.langchain.com/docs/integrations/vectorstores/tair", "Chroma": "https://python.langchain.com/docs/integrations/vectorstores/chroma", "Alibaba Cloud OpenSearch": "https://python.langchain.com/docs/integrations/vectorstores/alibabacloud_opensearch", "StarRocks": "https://python.langchain.com/docs/integrations/vectorstores/starrocks", "Clarifai": "https://python.langchain.com/docs/integrations/vectorstores/clarifai", "scikit-learn": "https://python.langchain.com/docs/integrations/vectorstores/sklearn", "DocArrayHnswSearch": "https://python.langchain.com/docs/integrations/vectorstores/docarray_hnsw", "MyScale": "https://python.langchain.com/docs/integrations/vectorstores/myscale", "ClickHouse Vector Search": "https://python.langchain.com/docs/integrations/vectorstores/clickhouse", "Qdrant": "https://python.langchain.com/docs/integrations/vectorstores/qdrant", "Tigris": "https://python.langchain.com/docs/integrations/vectorstores/tigris", "AwaDB": "https://python.langchain.com/docs/integrations/vectorstores/awadb", "Supabase (Postgres)": "https://python.langchain.com/docs/integrations/vectorstores/supabase", "OpenSearch": "https://python.langchain.com/docs/integrations/vectorstores/opensearch", "Pinecone": "https://python.langchain.com/docs/integrations/vectorstores/pinecone", "Azure Cognitive Search": "https://python.langchain.com/docs/integrations/vectorstores/azuresearch", "Cassandra": "https://python.langchain.com/docs/integrations/vectorstores/cassandra", "Milvus": "https://python.langchain.com/docs/integrations/vectorstores/milvus", "ElasticSearch": "https://python.langchain.com/docs/integrations/vectorstores/elasticsearch", "Marqo": "https://python.langchain.com/docs/integrations/vectorstores/marqo", "DocArrayInMemorySearch": "https://python.langchain.com/docs/integrations/vectorstores/docarray_in_memory", "pg_embedding": "https://python.langchain.com/docs/integrations/vectorstores/pgembedding", "FAISS": "https://python.langchain.com/docs/integrations/vectorstores/faiss", "AnalyticDB": "https://python.langchain.com/docs/integrations/vectorstores/analyticdb", "Hologres": "https://python.langchain.com/docs/integrations/vectorstores/hologres", "MongoDB Atlas": "https://python.langchain.com/docs/integrations/vectorstores/mongodb_atlas", "Meilisearch": "https://python.langchain.com/docs/integrations/vectorstores/meilisearch", "Question Answering Benchmarking: State of the Union Address": "https://python.langchain.com/docs/guides/evaluation/examples/qa_benchmarking_sota", "QA Generation": "https://python.langchain.com/docs/guides/evaluation/examples/qa_generation", "Question Answering Benchmarking: Paul Graham Essay": 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"https://python.langchain.com/docs/guides/evaluation/comparison/custom"}, "Criteria": {"Criteria Evaluation": "https://python.langchain.com/docs/guides/evaluation/string/criteria_eval_chain"}, "SQL_PROMPT": {"QA Correctness": "https://python.langchain.com/docs/guides/evaluation/string/qa"}, "StringEvaluator": {"Custom String Evaluator": "https://python.langchain.com/docs/guides/evaluation/string/custom"}, "StringDistance": {"String Distance": "https://python.langchain.com/docs/guides/evaluation/string/string_distance"}, "create_tagging_chain_pydantic": {"Tagging": "https://python.langchain.com/docs/modules/chains/additional/tagging"}, "get_openapi_chain": {"OpenAPI calls with OpenAI functions": "https://python.langchain.com/docs/modules/chains/additional/openapi_openai"}, "LLMRequestsChain": {"HTTP request chain": "https://python.langchain.com/docs/modules/chains/additional/llm_requests"}, "FileChatMessageHistory": {"AutoGPT": "https://python.langchain.com/docs/use_cases/autonomous_agents/autogpt"}, "BaseLLM": {"BabyAGI User Guide": "https://python.langchain.com/docs/use_cases/agents/baby_agi", "BabyAGI with Tools": "https://python.langchain.com/docs/use_cases/agents/baby_agi_with_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context"}, "VectorStore": {"BabyAGI User Guide": "https://python.langchain.com/docs/use_cases/agents/baby_agi", "BabyAGI with Tools": "https://python.langchain.com/docs/use_cases/agents/baby_agi_with_agent"}, "Chain": {"BabyAGI User Guide": "https://python.langchain.com/docs/use_cases/agents/baby_agi", "BabyAGI with Tools": "https://python.langchain.com/docs/use_cases/agents/baby_agi_with_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain"}, "BaseTool": {"!pip install bs4": "https://python.langchain.com/docs/use_cases/autonomous_agents/marathon_times", "Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools", "Combine agents and vector stores": "https://python.langchain.com/docs/modules/agents/how_to/agent_vectorstore", "Custom functions with OpenAI Functions Agent": "https://python.langchain.com/docs/modules/agents/how_to/custom-functions-with-openai-functions-agent"}, "BaseCombineDocumentsChain": {"!pip install bs4": "https://python.langchain.com/docs/use_cases/autonomous_agents/marathon_times"}, "MarkdownHeaderTextSplitter": {"Context aware text splitting and QA / Chat": "https://python.langchain.com/docs/use_cases/question_answering/document-context-aware-QA", "Perform context-aware text splitting": "https://python.langchain.com/docs/use_cases/question_answering/how_to/document-context-aware-QA", "MarkdownHeaderTextSplitter": "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/markdown_header_metadata"}, "MultiQueryRetriever": {"QA over Documents": "https://python.langchain.com/docs/use_cases/question_answering/index", "MultiQueryRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/MultiQueryRetriever"}, "create_citation_fuzzy_match_chain": {"Cite sources": "https://python.langchain.com/docs/use_cases/question_answering/how_to/qa_citations", "Question-Answering Citations": "https://python.langchain.com/docs/modules/chains/additional/qa_citations"}, "BaseRetriever": {"Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "FLARE": "https://python.langchain.com/docs/modules/chains/additional/flare"}, "AsyncCallbackManagerForRetrieverRun": {"Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "FLARE": "https://python.langchain.com/docs/modules/chains/additional/flare"}, "CallbackManagerForRetrieverRun": {"Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "FLARE": "https://python.langchain.com/docs/modules/chains/additional/flare"}, "FlareChain": {"Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "FLARE": "https://python.langchain.com/docs/modules/chains/additional/flare"}, "HypotheticalDocumentEmbedder": {"Improve document indexing with HyDE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/hyde", "Hypothetical Document Embeddings": "https://python.langchain.com/docs/modules/chains/additional/hyde"}, "StuffDocumentsChain": {"Structure answers with OpenAI functions": "https://python.langchain.com/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa", "Lost in the middle: The problem with long contexts": "https://python.langchain.com/docs/modules/data_connection/document_transformers/post_retrieval/long_context_reorder", "Retrieval QA using OpenAI functions": "https://python.langchain.com/docs/modules/chains/additional/openai_functions_retrieval_qa"}, "create_qa_with_sources_chain": {"Structure answers with OpenAI functions": "https://python.langchain.com/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa", "Retrieval QA using OpenAI functions": "https://python.langchain.com/docs/modules/chains/additional/openai_functions_retrieval_qa"}, "create_qa_with_structure_chain": {"Structure answers with OpenAI functions": "https://python.langchain.com/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa", "Retrieval QA using OpenAI functions": "https://python.langchain.com/docs/modules/chains/additional/openai_functions_retrieval_qa"}, "ElasticsearchDatabaseChain": {"Elasticsearch database": "https://python.langchain.com/docs/modules/chains/additional/elasticsearch_database"}, "create_sql_query_chain": {"SQL Query": "https://python.langchain.com/docs/use_cases/tabular/sql_query"}, "NeptuneGraph": {"Neptune Open Cypher QA Chain": "https://python.langchain.com/docs/modules/chains/additional/neptune_cypher_qa"}, "NeptuneOpenCypherQAChain": {"Neptune Open Cypher QA Chain": "https://python.langchain.com/docs/modules/chains/additional/neptune_cypher_qa"}, "NebulaGraphQAChain": {"NebulaGraphQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa"}, "NebulaGraph": {"NebulaGraphQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_nebula_qa"}, "KuzuGraph": {"KuzuQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_kuzu_qa"}, "KuzuQAChain": {"KuzuQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_kuzu_qa"}, "HugeGraphQAChain": {"HugeGraph QA Chain": "https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa"}, "HugeGraph": {"HugeGraph QA Chain": "https://python.langchain.com/docs/modules/chains/additional/graph_hugegraph_qa"}, "GraphSparqlQAChain": {"GraphSparqlQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_sparql_qa"}, "RdfGraph": {"GraphSparqlQAChain": "https://python.langchain.com/docs/modules/chains/additional/graph_sparql_qa"}, "ArangoGraph": {"ArangoDB QA chain": "https://python.langchain.com/docs/modules/chains/additional/graph_arangodb_qa"}, "ArangoGraphQAChain": {"ArangoDB QA chain": "https://python.langchain.com/docs/modules/chains/additional/graph_arangodb_qa"}, "GraphIndexCreator": {"Graph QA": "https://python.langchain.com/docs/modules/chains/additional/graph_qa"}, "GraphQAChain": {"Graph QA": "https://python.langchain.com/docs/modules/chains/additional/graph_qa"}, "NetworkxEntityGraph": {"Graph QA": "https://python.langchain.com/docs/modules/chains/additional/graph_qa"}, "GraphCypherQAChain": {"Graph DB QA chain": "https://python.langchain.com/docs/modules/chains/additional/graph_cypher_qa"}, "Neo4jGraph": {"Graph DB QA chain": "https://python.langchain.com/docs/modules/chains/additional/graph_cypher_qa"}, "LLMSingleActionAgent": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval"}, "AgentOutputParser": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval"}, "StringPromptTemplate": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval", "Custom prompt template": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/custom_prompt_template", "Connecting to a Feature Store": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/connecting_to_a_feature_store"}, "AgentFinish": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval", "Custom multi-action agent": "https://python.langchain.com/docs/modules/agents/how_to/custom_multi_action_agent", "Running Agent as an Iterator": "https://python.langchain.com/docs/modules/agents/how_to/agent_iter", "Custom agent": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval"}, "AIPlugin": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/agents/custom_agent_with_plugin_retrieval"}, "SteamshipImageGenerationTool": {"Multi-modal outputs: Image & Text": "https://python.langchain.com/docs/use_cases/multi_modal/image_agent"}, "BaseMessage": {"CAMEL Role-Playing Autonomous Cooperative Agents": "https://python.langchain.com/docs/use_cases/agent_simulations/camel_role_playing", "Multi-agent decentralized speaker selection": "https://python.langchain.com/docs/use_cases/agent_simulations/multiagent_bidding", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/agent_simulations/multiagent_authoritarian", "Multi-Player Dungeons & Dragons": "https://python.langchain.com/docs/use_cases/agent_simulations/multi_player_dnd", "Simulated Environment: Gymnasium": "https://python.langchain.com/docs/use_cases/agent_simulations/gymnasium", "Agent Debates with Tools": "https://python.langchain.com/docs/use_cases/agent_simulations/two_agent_debate_tools"}, "LLMBashChain": {"Bash chain": "https://python.langchain.com/docs/modules/chains/additional/llm_bash"}, "BashOutputParser": {"Bash chain": "https://python.langchain.com/docs/modules/chains/additional/llm_bash"}, "BashProcess": {"Bash chain": "https://python.langchain.com/docs/modules/chains/additional/llm_bash"}, "LLMSymbolicMathChain": {"LLM Symbolic Math ": "https://python.langchain.com/docs/modules/chains/additional/llm_symbolic_math"}, "create_extraction_chain": {"Extraction with OpenAI Functions": "https://python.langchain.com/docs/use_cases/extraction/openai_extraction", "Extraction": "https://python.langchain.com/docs/modules/chains/additional/extraction"}, "create_extraction_chain_pydantic": {"Extraction with OpenAI Functions": "https://python.langchain.com/docs/use_cases/extraction/openai_extraction", "Extraction": "https://python.langchain.com/docs/modules/chains/additional/extraction"}, "LLMSummarizationCheckerChain": {"Summarization checker chain": "https://python.langchain.com/docs/modules/chains/additional/llm_summarization_checker"}, "LLMCheckerChain": {"Self-checking chain": "https://python.langchain.com/docs/modules/chains/additional/llm_checker"}, "RegexParser": {"Multi-Agent Simulated Environment: Petting Zoo": "https://python.langchain.com/docs/use_cases/agent_simulations/petting_zoo", "Multi-agent decentralized speaker selection": "https://python.langchain.com/docs/use_cases/agent_simulations/multiagent_bidding", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/agent_simulations/multiagent_authoritarian", "Simulated Environment: Gymnasium": "https://python.langchain.com/docs/use_cases/agent_simulations/gymnasium"}, "TimeWeightedVectorStoreRetriever": {"Generative Agents in LangChain": "https://python.langchain.com/docs/use_cases/agent_simulations/characters"}, "EnsembleRetriever": {"Ensemble Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/ensemble"}, "PydanticOutputParser": {"MultiQueryRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/MultiQueryRetriever", "WebResearchRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/web_research", "Retry parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/retry", "Pydantic (JSON) parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/pydantic"}, "WebResearchRetriever": {"WebResearchRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/web_research"}, "SentenceTransformersTokenTextSplitter": {"Split by tokens ": "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/split_by_token"}, "NLTKTextSplitter": {"Split by tokens ": "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/split_by_token"}, "ChatMessageHistory": {"Adding Message Memory backed by a database to an Agent": "https://python.langchain.com/docs/modules/memory/agent_with_memory_in_db"}, "BaseMemory": {"How to create a custom Memory class": "https://python.langchain.com/docs/modules/memory/custom_memory"}, "ConversationKGMemory": {"Conversation Knowledge Graph Memory": "https://python.langchain.com/docs/modules/memory/types/kg"}, "ConversationTokenBufferMemory": {"ConversationTokenBufferMemory": "https://python.langchain.com/docs/modules/memory/types/token_buffer"}, "MessagesPlaceholder": {"How to add Memory to an LLMChain": "https://python.langchain.com/docs/modules/memory/adding_memory", "Add Memory to OpenAI Functions Agent": "https://python.langchain.com/docs/modules/agents/how_to/add_memory_openai_functions", "Types of `MessagePromptTemplate`": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/msg_prompt_templates"}, "CombinedMemory": {"How to use multiple memory classes in the same chain": "https://python.langchain.com/docs/modules/memory/multiple_memory"}, "ConversationSummaryMemory": {"How to use multiple memory classes in the same chain": "https://python.langchain.com/docs/modules/memory/multiple_memory"}, "ConversationSummaryBufferMemory": {"ConversationSummaryBufferMemory": "https://python.langchain.com/docs/modules/memory/types/summary_buffer"}, "BaseCallbackHandler": {"Custom callback handlers": "https://python.langchain.com/docs/modules/callbacks/custom_callbacks", "Multiple callback handlers": "https://python.langchain.com/docs/modules/callbacks/multiple_callbacks", "Async callbacks": "https://python.langchain.com/docs/modules/callbacks/async_callbacks", "Streaming final agent output": "https://python.langchain.com/docs/modules/agents/how_to/streaming_stdout_final_only"}, "tracing_enabled": {"Multiple callback handlers": "https://python.langchain.com/docs/modules/callbacks/multiple_callbacks"}, "get_openai_callback": {"Token counting": "https://python.langchain.com/docs/modules/callbacks/token_counting", "Tracking token usage": "https://python.langchain.com/docs/modules/model_io/models/llms/token_usage_tracking"}, "FileCallbackHandler": {"Logging to file": "https://python.langchain.com/docs/modules/callbacks/filecallbackhandler"}, "LLMResult": {"Async callbacks": "https://python.langchain.com/docs/modules/callbacks/async_callbacks"}, "AsyncCallbackHandler": {"Async callbacks": "https://python.langchain.com/docs/modules/callbacks/async_callbacks"}, "StructuredTool": {"Multi-Input Tools": "https://python.langchain.com/docs/modules/agents/tools/multi_input_tool", "Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools"}, "AsyncCallbackManagerForToolRun": {"Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools"}, "CallbackManagerForToolRun": {"Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools"}, "ToolException": {"Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools"}, "format_tool_to_openai_function": {"Tools as OpenAI Functions": "https://python.langchain.com/docs/modules/agents/tools/tools_as_openai_functions"}, "RequestsGetTool": {"Tool Input Schema": "https://python.langchain.com/docs/modules/agents/tools/tool_input_validation"}, "HumanApprovalCallbackHandler": {"Human-in-the-loop Tool Validation": "https://python.langchain.com/docs/modules/agents/tools/human_approval"}, "DocstoreExplorer": {"ReAct document store": "https://python.langchain.com/docs/modules/agents/agent_types/react_docstore"}, "ReadOnlySharedMemory": {"Shared memory across agents and tools": "https://python.langchain.com/docs/modules/agents/how_to/sharedmemory_for_tools"}, "BaseMultiActionAgent": {"Custom multi-action agent": "https://python.langchain.com/docs/modules/agents/how_to/custom_multi_action_agent"}, "FinalStreamingStdOutCallbackHandler": {"Streaming final agent output": "https://python.langchain.com/docs/modules/agents/how_to/streaming_stdout_final_only"}, "LangChainTracer": {"Async API": "https://python.langchain.com/docs/modules/agents/how_to/async_agent"}, "BaseSingleActionAgent": {"Custom agent": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent"}, "HumanInputChatModel": {"Human input Chat Model": "https://python.langchain.com/docs/modules/model_io/models/chat/human_input_chat_model"}, "FakeListLLM": {"Fake LLM": "https://python.langchain.com/docs/modules/model_io/models/llms/fake_llm"}, "CallbackManagerForLLMRun": {"Custom LLM": "https://python.langchain.com/docs/modules/model_io/models/llms/custom_llm"}, "LLM": {"Custom LLM": "https://python.langchain.com/docs/modules/model_io/models/llms/custom_llm"}, "HumanInputLLM": {"Human input LLM": "https://python.langchain.com/docs/modules/model_io/models/llms/human_input_llm"}, "OutputFixingParser": {"Retry parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/retry"}, "RetryOutputParser": {"Retry parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/retry"}, "RetryWithErrorOutputParser": {"Retry parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/retry"}, "EnumOutputParser": {"Enum parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/enum"}, "DatetimeOutputParser": {"Datetime parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/datetime"}, "MaxMarginalRelevanceExampleSelector": {"Select by maximal marginal relevance (MMR)": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/mmr"}, "SemanticSimilarityExampleSelector": {"Select by maximal marginal relevance (MMR)": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/mmr", "Few shot examples for chat models": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/few_shot_examples_chat"}, "FewShotPromptTemplate": {"Select by maximal marginal relevance (MMR)": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/mmr", "Select by n-gram overlap": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/ngram_overlap"}, "BaseExampleSelector": {"Custom example selector": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/custom_example_selector"}, "NGramOverlapExampleSelector": {"Select by n-gram overlap": "https://python.langchain.com/docs/modules/model_io/prompts/example_selectors/ngram_overlap"}, "FewShotChatMessagePromptTemplate": {"Few shot examples for chat models": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/few_shot_examples_chat"}, "load_prompt": {"Serialization": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/prompt_serialization"}, "ChatMessagePromptTemplate": {"Types of `MessagePromptTemplate`": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/msg_prompt_templates"}, "MultiPromptChain": {"Router": "https://python.langchain.com/docs/modules/chains/foundational/router"}, "LLMRouterChain": {"Router": "https://python.langchain.com/docs/modules/chains/foundational/router"}, "RouterOutputParser": {"Router": "https://python.langchain.com/docs/modules/chains/foundational/router"}, "EmbeddingRouterChain": {"Router": "https://python.langchain.com/docs/modules/chains/foundational/router"}, "BaseLanguageModel": {"Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain"}, "AsyncCallbackManagerForChainRun": {"Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain"}, "CallbackManagerForChainRun": {"Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain"}, "BasePromptTemplate": {"Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain"}, "load_chain": {"Serialization": "https://python.langchain.com/docs/modules/chains/how_to/serialization", "Loading from LangChainHub": "https://python.langchain.com/docs/modules/chains/how_to/from_hub"}, "create_openai_fn_chain": {"Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/popular/openai_functions"}, "create_structured_output_chain": {"Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/popular/openai_functions"}}
\ No newline at end of file
diff --git a/docs/docs_skeleton/generate_api_reference_links.py b/docs/docs_skeleton/generate_api_reference_links.py
index 3fb97163b22..4dc52bd88d2 100644
--- a/docs/docs_skeleton/generate_api_reference_links.py
+++ b/docs/docs_skeleton/generate_api_reference_links.py
@@ -5,16 +5,22 @@ import logging
import os
import re
from pathlib import Path
+import argparse
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
# Base URL for all class documentation
-_BASE_URL = "https://api.python.langchain.com/en/latest/"
+_BASE_URL = "https://api.python.langchain.com/en/latest"
# Regular expression to match Python code blocks
code_block_re = re.compile(r"^(```python\n)(.*?)(```\n)", re.DOTALL | re.MULTILINE)
# Regular expression to match langchain import lines
-_IMPORT_RE = re.compile(r"(from\s+(langchain\.\w+(\.\w+)*?)\s+import\s+)(\w+)")
+_IMPORT_RE = re.compile(
+ r"from\s+(langchain\.\w+(\.\w+)*?)\s+import\s+"
+ r"((?:\w+(?:,\s*)?)*" # Match zero or more words separated by a comma+optional ws
+ r"(?:\s*\(.*?\))?)", # Match optional parentheses block
+ re.DOTALL, # Match newlines as well
+)
_CURRENT_PATH = Path(__file__).parent.absolute()
# Directory where generated markdown files are stored
@@ -24,6 +30,10 @@ _JSON_PATH = _CURRENT_PATH.parent / "api_reference" / "guide_imports.json"
def find_files(path):
"""Find all MDX files in the given path"""
+ # Check if is file first
+ if os.path.isfile(path):
+ yield path
+ return
for root, _, files in os.walk(path):
for file in files:
if file.endswith(".mdx") or file.endswith(".md"):
@@ -37,20 +47,33 @@ def get_full_module_name(module_path, class_name):
return inspect.getmodule(class_).__name__
+def get_args():
+ parser = argparse.ArgumentParser()
+ parser.add_argument(
+ "--docs_dir",
+ type=str,
+ default=_DOCS_DIR,
+ help="Directory where generated markdown files are stored",
+ )
+ return parser.parse_args()
+
+
def main():
"""Main function"""
+ args = get_args()
global_imports = {}
- for file in find_files(_DOCS_DIR):
+ for file in find_files(args.docs_dir):
print(f"Adding links for imports in {file}")
-
- # replace_imports now returns the import information rather than writing it to a file
file_imports = replace_imports(file)
if file_imports:
# Use relative file path as key
- relative_path = os.path.relpath(file, _DOCS_DIR)
- doc_url = f"https://python.langchain.com/docs/{relative_path.replace('.mdx', '').replace('.md', '')}"
+ relative_path = (
+ os.path.relpath(file, _DOCS_DIR).replace(".mdx", "").replace(".md", "")
+ )
+
+ doc_url = f"https://python.langchain.com/docs/{relative_path}"
for import_info in file_imports:
doc_title = import_info["title"]
class_name = import_info["imported"]
@@ -77,7 +100,8 @@ def _get_doc_title(data: str, file_name: str) -> str:
def replace_imports(file):
- """Replace imports in each Python code block with links to their documentation and append the import info in a comment"""
+ """Replace imports in each Python code block with links to their
+ documentation and append the import info in a comment"""
all_imports = []
with open(file, "r") as f:
data = f.read()
@@ -97,37 +121,45 @@ def replace_imports(file):
# Process imports in the code block
imports = []
for import_match in _IMPORT_RE.finditer(code):
- class_name = import_match.group(4)
- try:
- module_path = get_full_module_name(import_match.group(2), class_name)
- except AttributeError as e:
- logger.warning(f"Could not find module for {class_name}, {e}")
- continue
- except ImportError as e:
- # Some CentOS OpenSSL issues can cause this to fail
- logger.warning(f"Failed to load for class {class_name}, {e}")
- continue
+ module = import_match.group(1)
+ imports_str = (
+ import_match.group(3).replace("(\n", "").replace("\n)", "")
+ ) # Handle newlines within parentheses
+ # remove any newline and spaces, then split by comma
+ imported_classes = [
+ imp.strip()
+ for imp in re.split(r",\s*", imports_str.replace("\n", ""))
+ if imp.strip()
+ ]
+ for class_name in imported_classes:
+ try:
+ module_path = get_full_module_name(module, class_name)
+ except AttributeError as e:
+ logger.warning(f"Could not find module for {class_name}, {e}")
+ continue
+ except ImportError as e:
+ logger.warning(f"Failed to load for class {class_name}, {e}")
+ continue
- url = (
- _BASE_URL
- + "/"
- + module_path.split(".")[1]
- + "/"
- + module_path
- + "."
- + class_name
- + ".html"
- )
+ url = (
+ _BASE_URL
+ + module_path.split(".")[1]
+ + "/"
+ + module_path
+ + "."
+ + class_name
+ + ".html"
+ )
- # Add the import information to our list
- imports.append(
- {
- "imported": class_name,
- "source": import_match.group(2),
- "docs": url,
- "title": _DOC_TITLE,
- }
- )
+ # Add the import information to our list
+ imports.append(
+ {
+ "imported": class_name,
+ "source": module,
+ "docs": url,
+ "title": _DOC_TITLE,
+ }
+ )
if imports:
all_imports.extend(imports)
diff --git a/docs/extras/integrations/llms/jsonformer_experimental.ipynb b/docs/extras/integrations/llms/jsonformer_experimental.ipynb
index d7dae68bca1..189de072d12 100644
--- a/docs/extras/integrations/llms/jsonformer_experimental.ipynb
+++ b/docs/extras/integrations/llms/jsonformer_experimental.ipynb
@@ -216,7 +216,7 @@
},
"outputs": [],
"source": [
- "from langchain.experimental.llms import JsonFormer\n",
+ "from langchain_experimental.llms import JsonFormer\n",
"\n",
"json_former = JsonFormer(json_schema=decoder_schema, pipeline=hf_model)"
]
diff --git a/docs/extras/integrations/llms/rellm_experimental.ipynb b/docs/extras/integrations/llms/rellm_experimental.ipynb
index 0849449cfb4..8cc3e00465f 100644
--- a/docs/extras/integrations/llms/rellm_experimental.ipynb
+++ b/docs/extras/integrations/llms/rellm_experimental.ipynb
@@ -162,7 +162,7 @@
}
],
"source": [
- "from langchain.experimental.llms import RELLM\n",
+ "from langchain_experimental.llms import RELLM\n",
"\n",
"model = RELLM(pipeline=hf_model, regex=pattern, max_new_tokens=200)\n",
"\n",
diff --git a/docs/extras/integrations/providers/dataforseo.mdx b/docs/extras/integrations/providers/dataforseo.mdx
index 9dcde2e4edc..71ab4bdeefe 100644
--- a/docs/extras/integrations/providers/dataforseo.mdx
+++ b/docs/extras/integrations/providers/dataforseo.mdx
@@ -13,7 +13,7 @@ This page provides instructions on how to use the DataForSEO search APIs within
The DataForSEO utility wraps the API. To import this utility, use:
```python
-from langchain.utilities import DataForSeoAPIWrapper
+from langchain.utilities.dataforseo_api_search import DataForSeoAPIWrapper
```
For a detailed walkthrough of this wrapper, see [this notebook](/docs/integrations/tools/dataforseo.ipynb).
diff --git a/docs/extras/integrations/providers/rebuff.ipynb b/docs/extras/integrations/providers/rebuff.ipynb
index a4123682e5c..991985886fe 100644
--- a/docs/extras/integrations/providers/rebuff.ipynb
+++ b/docs/extras/integrations/providers/rebuff.ipynb
@@ -177,8 +177,9 @@
"metadata": {},
"outputs": [],
"source": [
- "from langchain.chains import TransformChain, SQLDatabaseChain, SimpleSequentialChain\n",
- "from langchain.sql_database import SQLDatabase"
+ "from langchain.chains import TransformChain, SimpleSequentialChain\n",
+ "from langchain.sql_database import SQLDatabase\n",
+ "from langchain_experimental.sql import SQLDatabaseChain"
]
},
{
diff --git a/docs/extras/integrations/providers/rockset.mdx b/docs/extras/integrations/providers/rockset.mdx
index 4dd5431dc1c..1b9ba565903 100644
--- a/docs/extras/integrations/providers/rockset.mdx
+++ b/docs/extras/integrations/providers/rockset.mdx
@@ -15,7 +15,7 @@ pip install rockset
See a [usage example](/docs/integrations/vectorstores/rockset).
```python
-from langchain.vectorstores import RocksetDB
+from langchain.vectorstores import Rockset
```
## Document Loader
diff --git a/docs/extras/integrations/providers/spacy.mdx b/docs/extras/integrations/providers/spacy.mdx
index f526e21efe1..f4d49497dd5 100644
--- a/docs/extras/integrations/providers/spacy.mdx
+++ b/docs/extras/integrations/providers/spacy.mdx
@@ -16,5 +16,5 @@ pip install spacy
See a [usage example](/docs/modules/data_connection/document_transformers/text_splitters/split_by_token.html#spacy).
```python
-from langchain.llms import SpacyTextSplitter
+from langchain.text_splitter import SpacyTextSplitter
```
diff --git a/docs/extras/integrations/text_embedding/localai.ipynb b/docs/extras/integrations/text_embedding/localai.ipynb
index 0cbd171426a..6294b65ff9f 100644
--- a/docs/extras/integrations/text_embedding/localai.ipynb
+++ b/docs/extras/integrations/text_embedding/localai.ipynb
@@ -77,7 +77,7 @@
"metadata": {},
"outputs": [],
"source": [
- "from langchain.embeddings.openai import LocalAIEmbeddings"
+ "from langchain.embeddings import LocalAIEmbeddings"
]
},
{
diff --git a/docs/extras/integrations/tools/dataforseo.ipynb b/docs/extras/integrations/tools/dataforseo.ipynb
index 3aed7f28fc3..8093aea2b25 100644
--- a/docs/extras/integrations/tools/dataforseo.ipynb
+++ b/docs/extras/integrations/tools/dataforseo.ipynb
@@ -15,7 +15,7 @@
"metadata": {},
"outputs": [],
"source": [
- "from langchain.utilities import DataForSeoAPIWrapper"
+ "from langchain.utilities.dataforseo_api_search import DataForSeoAPIWrapper"
]
},
{
diff --git a/docs/extras/integrations/vectorstores/rockset.ipynb b/docs/extras/integrations/vectorstores/rockset.ipynb
index 426f42e31b0..fde25b40140 100644
--- a/docs/extras/integrations/vectorstores/rockset.ipynb
+++ b/docs/extras/integrations/vectorstores/rockset.ipynb
@@ -124,7 +124,7 @@
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain.document_loaders import TextLoader\n",
- "from langchain.vectorstores.rocksetdb import RocksetDB\n",
+ "from langchain.vectorstores import Rockset\n",
"\n",
"loader = TextLoader(\"../../../state_of_the_union.txt\")\n",
"documents = loader.load()\n",
@@ -150,7 +150,7 @@
"# Make sure the environment variable OPENAI_API_KEY is set up\n",
"embeddings = OpenAIEmbeddings()\n",
"\n",
- "docsearch = RocksetDB(\n",
+ "docsearch = Rockset(\n",
" client=rockset_client,\n",
" embeddings=embeddings,\n",
" collection_name=COLLECTION_NAME,\n",
@@ -185,7 +185,7 @@
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"output = docsearch.similarity_search_with_relevance_scores(\n",
- " query, 4, RocksetDB.DistanceFunction.COSINE_SIM\n",
+ " query, 4, Rockset.DistanceFunction.COSINE_SIM\n",
")\n",
"print(\"output length:\", len(output))\n",
"for d, dist in output:\n",
@@ -221,7 +221,7 @@
"output = docsearch.similarity_search_with_relevance_scores(\n",
" query,\n",
" 4,\n",
- " RocksetDB.DistanceFunction.COSINE_SIM,\n",
+ " Rockset.DistanceFunction.COSINE_SIM,\n",
" where_str=\"{} NOT LIKE '%citizens%'\".format(TEXT_KEY),\n",
")\n",
"print(\"output length:\", len(output))\n",
@@ -237,15 +237,16 @@
]
},
{
+ "attachments": {},
"cell_type": "markdown",
"id": "0765b822",
"metadata": {},
"source": [
"### 3. [Optional] Drop all inserted documents\n",
"\n",
- "In order to delete texts from the Rockset collection, you need to know the unique ID associated with each document inside Rockset. These ids can either be supplied directly by the user while inserting the texts (in the `RocksetDB.add_texts()` function), else Rockset will generate a unique ID or each document. Either way, `Rockset.add_texts()` returns the ids for the inserted documents.\n",
+ "In order to delete texts from the Rockset collection, you need to know the unique ID associated with each document inside Rockset. These ids can either be supplied directly by the user while inserting the texts (in the `Rockset.add_texts()` function), else Rockset will generate a unique ID or each document. Either way, `Rockset.add_texts()` returns the ids for the inserted documents.\n",
"\n",
- "To delete these docs, simply use the `RocksetDB.delete_texts()` function."
+ "To delete these docs, simply use the `Rockset.delete_texts()` function."
]
},
{
diff --git a/docs/extras/modules/chains/how_to/custom_chain.ipynb b/docs/extras/modules/chains/how_to/custom_chain.ipynb
index 59ce061fe9c..2e4f4e4115d 100644
--- a/docs/extras/modules/chains/how_to/custom_chain.ipynb
+++ b/docs/extras/modules/chains/how_to/custom_chain.ipynb
@@ -15,10 +15,7 @@
"execution_count": 11,
"id": "c19c736e-ca74-4726-bb77-0a849bcc2960",
"metadata": {
- "tags": [],
- "vscode": {
- "languageId": "python"
- }
+ "tags": []
},
"outputs": [],
"source": [
@@ -28,7 +25,7 @@
"\n",
"from pydantic import Extra\n",
"\n",
- "from langchain.schema import BaseLanguageModel\n",
+ "from langchain.schema.language_model import BaseLanguageModel\n",
"from langchain.callbacks.manager import (\n",
" AsyncCallbackManagerForChainRun,\n",
" CallbackManagerForChainRun,\n",
@@ -130,11 +127,7 @@
"cell_type": "code",
"execution_count": 12,
"id": "18361f89",
- "metadata": {
- "vscode": {
- "languageId": "python"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
diff --git a/docs/extras/modules/model_io/prompts/prompt_templates/few_shot_examples_chat.ipynb b/docs/extras/modules/model_io/prompts/prompt_templates/few_shot_examples_chat.ipynb
index 0ea9a3728aa..6e88c015707 100644
--- a/docs/extras/modules/model_io/prompts/prompt_templates/few_shot_examples_chat.ipynb
+++ b/docs/extras/modules/model_io/prompts/prompt_templates/few_shot_examples_chat.ipynb
@@ -35,19 +35,16 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 2,
"id": "91f1ca7f-a748-44c7-a1c6-a89a2d1414ba",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "from langchain.schema import SystemMessage\n",
"from langchain.prompts import (\n",
" FewShotChatMessagePromptTemplate,\n",
- " HumanMessagePromptTemplate,\n",
- " AIMessagePromptTemplate,\n",
- " SystemMessagePromptTemplate,\n",
+ " ChatPromptTemplate,\n",
")"
]
},
@@ -61,7 +58,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 3,
"id": "0fc5a02a-6249-4e92-95c3-30fff9671e8b",
"metadata": {
"tags": []
@@ -84,7 +81,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 4,
"id": "65e72ad1-9060-47d0-91a1-bc130c8b98ac",
"metadata": {
"tags": []
@@ -103,9 +100,12 @@
],
"source": [
"# This is a prompt template used to format each individual example.\n",
- "example_prompt = HumanMessagePromptTemplate.from_template(\n",
- " \"{input}\"\n",
- ") + AIMessagePromptTemplate.from_template(\"{output}\")\n",
+ "example_prompt = ChatPromptTemplate.from_messages(\n",
+ " [\n",
+ " (\"human\", \"{input}\"),\n",
+ " (\"ai\", \"{output}\"),\n",
+ " ]\n",
+ ")\n",
"few_shot_prompt = FewShotChatMessagePromptTemplate(\n",
" example_prompt=example_prompt,\n",
" examples=examples,\n",
@@ -124,23 +124,25 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 5,
"id": "9f86d6d9-50de-41b6-b6c7-0f9980cc0187",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "final_prompt = (\n",
- " SystemMessagePromptTemplate.from_template(\"You are wonderous wizard of math.\")\n",
- " + few_shot_prompt\n",
- " + HumanMessagePromptTemplate.from_template(\"{input}\")\n",
+ "final_prompt = ChatPromptTemplate.from_messages(\n",
+ " [\n",
+ " (\"system\", \"You are wonderous wizard of math.\"),\n",
+ " few_shot_prompt,\n",
+ " (\"human\", \"{input}\"),\n",
+ " ]\n",
")"
]
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 6,
"id": "97d443b1-6fae-4b36-bede-3ff7306288a3",
"metadata": {
"tags": []
@@ -149,10 +151,10 @@
{
"data": {
"text/plain": [
- "AIMessage(content=' Triangles do not have a \"square\". A square refers to a shape with 4 equal sides and 4 right angles. Triangles have 3 sides and 3 angles.\\n\\nThe area of a triangle can be calculated using the formula:\\n\\nA = 1/2 * b * h\\n\\nWhere:\\n\\nA is the area \\nb is the base (the length of one of the sides)\\nh is the height (the length from the base to the opposite vertex)\\n\\nSo the area depends on the specific dimensions of the triangle. There is no single \"square of a triangle\". The area can vary greatly between different triangles.', additional_kwargs={}, example=False)"
+ "AIMessage(content=' Triangles do not have a \"square\". A square refers to a shape with 4 equal sides and 4 right angles. Triangles have 3 sides and 3 angles.\\n\\nThe area of a triangle can be calculated using the formula:\\n\\nA = 1/2 * b * h\\n\\nWhere:\\n\\nA is the area \\nb is the base (the length of one of the sides)\\nh is the height (the length from the base to the opposite vertex)\\n\\nSo the area depends on the specific dimensions of the triangle. There is no single \"square of a triangle\". The area can vary greatly depending on the base and height measurements.', additional_kwargs={}, example=False)"
]
},
- "execution_count": 14,
+ "execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@@ -182,7 +184,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 7,
"id": "6f7b5e86-4ca7-4edd-bf2b-9663030b2393",
"metadata": {
"tags": []
@@ -204,7 +206,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 8,
"id": "ad66f06a-66fd-4fcc-8166-5d0e3c801e57",
"metadata": {
"tags": []
@@ -239,7 +241,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 9,
"id": "7790303a-f722-452e-8921-b14bdf20bdff",
"metadata": {
"tags": []
@@ -252,7 +254,7 @@
" {'input': '2+4', 'output': '6'}]"
]
},
- "execution_count": 17,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -279,17 +281,17 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 10,
"id": "253c255e-41d7-45f6-9d88-c7a0ced4b1bd",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "from langchain.schema import SystemMessage\n",
- "from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate\n",
- "from langchain.prompts.few_shot import FewShotChatMessagePromptTemplate\n",
- "\n",
+ "from langchain.prompts import (\n",
+ " FewShotChatMessagePromptTemplate,\n",
+ " ChatPromptTemplate,\n",
+ ")\n",
"\n",
"# Define the few-shot prompt.\n",
"few_shot_prompt = FewShotChatMessagePromptTemplate(\n",
@@ -299,9 +301,8 @@
" # Define how each example will be formatted.\n",
" # In this case, each example will become 2 messages:\n",
" # 1 human, and 1 AI\n",
- " example_prompt=(\n",
- " HumanMessagePromptTemplate.from_template(\"{input}\")\n",
- " + AIMessagePromptTemplate.from_template(\"{output}\")\n",
+ " example_prompt=ChatPromptTemplate.from_messages(\n",
+ " [(\"human\", \"{input}\"), (\"ai\", \"{output}\")]\n",
" ),\n",
")"
]
@@ -316,7 +317,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 11,
"id": "860bf682-c469-40e9-b657-27bfe7026099",
"metadata": {
"tags": []
@@ -347,23 +348,25 @@
},
{
"cell_type": "code",
- "execution_count": 24,
+ "execution_count": 12,
"id": "e731cb45-f0ea-422c-be37-42af2a6cb2c4",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
- "final_prompt = (\n",
- " SystemMessagePromptTemplate.from_template(\"You are wonderous wizard of math.\")\n",
- " + few_shot_prompt\n",
- " + HumanMessagePromptTemplate.from_template(\"{input}\")\n",
+ "final_prompt = ChatPromptTemplate.from_messages(\n",
+ " [\n",
+ " (\"system\", \"You are wonderous wizard of math.\"),\n",
+ " few_shot_prompt,\n",
+ " (\"human\", \"{input}\"),\n",
+ " ]\n",
")"
]
},
{
"cell_type": "code",
- "execution_count": 25,
+ "execution_count": 13,
"id": "e6cc4199-8947-42d7-91f0-375de1e15bd9",
"metadata": {
"tags": []
@@ -396,7 +399,7 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 14,
"id": "0568cbc6-5354-47f1-ab4d-dfcc616cf583",
"metadata": {
"tags": []
@@ -408,7 +411,7 @@
"AIMessage(content=' 3 + 3 = 6', additional_kwargs={}, example=False)"
]
},
- "execution_count": 26,
+ "execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
diff --git a/docs/extras/use_cases/agent_simulations/characters.ipynb b/docs/extras/use_cases/agent_simulations/characters.ipynb
index 2cb423fed80..406a546f45a 100644
--- a/docs/extras/use_cases/agent_simulations/characters.ipynb
+++ b/docs/extras/use_cases/agent_simulations/characters.ipynb
@@ -101,7 +101,7 @@
},
"outputs": [],
"source": [
- "from langchain.experimental.generative_agents import (\n",
+ "from langchain_experimental.generative_agents import (\n",
" GenerativeAgent,\n",
" GenerativeAgentMemory,\n",
")"
diff --git a/docs/extras/use_cases/autonomous_agents/autogpt.ipynb b/docs/extras/use_cases/autonomous_agents/autogpt.ipynb
index 2b3e9c2f637..afe994cdfca 100644
--- a/docs/extras/use_cases/autonomous_agents/autogpt.ipynb
+++ b/docs/extras/use_cases/autonomous_agents/autogpt.ipynb
@@ -100,7 +100,7 @@
"metadata": {},
"outputs": [],
"source": [
- "from langchain.experimental import AutoGPT\n",
+ "from langchain_experimental.autonomous_agents import AutoGPT\n",
"from langchain.chat_models import ChatOpenAI"
]
},
@@ -124,43 +124,47 @@
},
{
"cell_type": "markdown",
+ "id": "f0f208d9",
+ "metadata": {
+ "collapsed": false
+ },
"source": [
"## Run an example\n",
"\n",
"Here we will make it write a weather report for SF"
- ],
- "metadata": {
- "collapsed": false
- },
- "id": "f0f208d9"
+ ]
},
{
"cell_type": "code",
"execution_count": null,
- "outputs": [],
- "source": [
- "agent.run([\"write a weather report for SF today\"])"
- ],
+ "id": "d119d788",
"metadata": {
"collapsed": false
},
- "id": "d119d788"
+ "outputs": [],
+ "source": [
+ "agent.run([\"write a weather report for SF today\"])"
+ ]
},
{
"cell_type": "markdown",
+ "id": "f13f8322",
+ "metadata": {
+ "collapsed": false
+ },
"source": [
"## Chat History Memory\n",
"\n",
"In addition to the memory that holds the agent immediate steps, we also have a chat history memory. By default, the agent will use 'ChatMessageHistory' and it can be changed. This is useful when you want to use a different type of memory for example 'FileChatHistoryMemory'"
- ],
- "metadata": {
- "collapsed": false
- },
- "id": "f13f8322"
+ ]
},
{
"cell_type": "code",
"execution_count": null,
+ "id": "2a81f5ad",
+ "metadata": {
+ "collapsed": false
+ },
"outputs": [],
"source": [
"from langchain.memory.chat_message_histories import FileChatMessageHistory\n",
@@ -173,19 +177,15 @@
" memory=vectorstore.as_retriever(),\n",
" chat_history_memory=FileChatMessageHistory(\"chat_history.txt\"),\n",
")"
- ],
- "metadata": {
- "collapsed": false
- },
- "id": "2a81f5ad"
+ ]
},
{
"cell_type": "markdown",
- "source": [],
+ "id": "b1403008",
"metadata": {
"collapsed": false
},
- "id": "b1403008"
+ "source": []
}
],
"metadata": {
@@ -209,4 +209,4 @@
},
"nbformat": 4,
"nbformat_minor": 5
-}
\ No newline at end of file
+}
diff --git a/docs/extras/use_cases/autonomous_agents/baby_agi.ipynb b/docs/extras/use_cases/autonomous_agents/baby_agi.ipynb
index 5e4bff5f2c9..ae7668acb4d 100644
--- a/docs/extras/use_cases/autonomous_agents/baby_agi.ipynb
+++ b/docs/extras/use_cases/autonomous_agents/baby_agi.ipynb
@@ -39,7 +39,7 @@
"from langchain.vectorstores.base import VectorStore\n",
"from pydantic import BaseModel, Field\n",
"from langchain.chains.base import Chain\n",
- "from langchain.experimental import BabyAGI"
+ "from langchain_experimental.autonomous_agents import BabyAGI"
]
},
{
diff --git a/docs/extras/use_cases/autonomous_agents/baby_agi_with_agent.ipynb b/docs/extras/use_cases/autonomous_agents/baby_agi_with_agent.ipynb
index 2fb3f905d64..dc4c4f0974d 100644
--- a/docs/extras/use_cases/autonomous_agents/baby_agi_with_agent.ipynb
+++ b/docs/extras/use_cases/autonomous_agents/baby_agi_with_agent.ipynb
@@ -35,7 +35,7 @@
"from langchain.vectorstores.base import VectorStore\n",
"from pydantic import BaseModel, Field\n",
"from langchain.chains.base import Chain\n",
- "from langchain.experimental import BabyAGI"
+ "from langchain_experimental.autonomous_agents import BabyAGI"
]
},
{
diff --git a/docs/extras/use_cases/autonomous_agents/marathon_times.ipynb b/docs/extras/use_cases/autonomous_agents/marathon_times.ipynb
index 45777e4dac0..aaaa3a64517 100644
--- a/docs/extras/use_cases/autonomous_agents/marathon_times.ipynb
+++ b/docs/extras/use_cases/autonomous_agents/marathon_times.ipynb
@@ -36,7 +36,7 @@
"# General\n",
"import os\n",
"import pandas as pd\n",
- "from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT\n",
+ "from langchain_experimental.autonomous_agents import AutoGPT\n",
"from langchain.chat_models import ChatOpenAI\n",
"\n",
"from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent\n",
diff --git a/docs/extras/use_cases/code_writing/cpal.ipynb b/docs/extras/use_cases/code_writing/cpal.ipynb
index 2ee78c205e3..47e2decbfd3 100644
--- a/docs/extras/use_cases/code_writing/cpal.ipynb
+++ b/docs/extras/use_cases/code_writing/cpal.ipynb
@@ -48,8 +48,8 @@
"source": [
"from IPython.display import SVG\n",
"\n",
- "from langchain.experimental.cpal.base import CPALChain\n",
- "from langchain.chains import PALChain\n",
+ "from langchain_experimental.cpal.base import CPALChain\n",
+ "from langchain_experimental.pal_chain import PALChain\n",
"from langchain import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0, max_tokens=512)\n",
@@ -200,121 +200,7 @@
"outputs": [
{
"data": {
- "image/svg+xml": [
- ""
- ],
+ "image/svg+xml": "",
"text/plain": [
""
]
@@ -573,43 +459,7 @@
"outputs": [
{
"data": {
- "image/svg+xml": [
- ""
- ],
+ "image/svg+xml": "",
"text/plain": [
""
]
@@ -700,43 +550,7 @@
"outputs": [
{
"data": {
- "image/svg+xml": [
- ""
- ],
+ "image/svg+xml": "",
"text/plain": [
""
]
@@ -827,49 +641,7 @@
"outputs": [
{
"data": {
- "image/svg+xml": [
- ""
- ],
+ "image/svg+xml": "",
"text/plain": [
""
]
diff --git a/docs/snippets/modules/agents/agent_types/plan_and_execute.mdx b/docs/snippets/modules/agents/agent_types/plan_and_execute.mdx
index bba43e37d8d..06035896889 100644
--- a/docs/snippets/modules/agents/agent_types/plan_and_execute.mdx
+++ b/docs/snippets/modules/agents/agent_types/plan_and_execute.mdx
@@ -3,7 +3,7 @@
```python
from langchain.chat_models import ChatOpenAI
-from langchain.experimental.plan_and_execute import PlanAndExecute, load_agent_executor, load_chat_planner
+from langchain_experimental.plan_and_execute import PlanAndExecute, load_agent_executor, load_chat_planner
from langchain.llms import OpenAI
from langchain import SerpAPIWrapper
from langchain.agents.tools import Tool
diff --git a/libs/langchain/langchain/agents/agent_toolkits/__init__.py b/libs/langchain/langchain/agents/agent_toolkits/__init__.py
index 0e1680e1e07..74d170dc21f 100644
--- a/libs/langchain/langchain/agents/agent_toolkits/__init__.py
+++ b/libs/langchain/langchain/agents/agent_toolkits/__init__.py
@@ -11,6 +11,7 @@ from langchain.agents.agent_toolkits.gmail.toolkit import GmailToolkit
from langchain.agents.agent_toolkits.jira.toolkit import JiraToolkit
from langchain.agents.agent_toolkits.json.base import create_json_agent
from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
+from langchain.agents.agent_toolkits.multion.base import create_multion_agent
from langchain.agents.agent_toolkits.nla.toolkit import NLAToolkit
from langchain.agents.agent_toolkits.office365.toolkit import O365Toolkit
from langchain.agents.agent_toolkits.openapi.base import create_openapi_agent
@@ -63,6 +64,7 @@ __all__ = [
"create_pbi_agent",
"create_pbi_chat_agent",
"create_python_agent",
+ "create_multion_agent",
"create_spark_dataframe_agent",
"create_spark_sql_agent",
"create_sql_agent",
diff --git a/libs/langchain/langchain/prompts/chat.py b/libs/langchain/langchain/prompts/chat.py
index f9b64ec24e9..2a24a745237 100644
--- a/libs/langchain/langchain/prompts/chat.py
+++ b/libs/langchain/langchain/prompts/chat.py
@@ -457,6 +457,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate, ABC):
messages: Sequence[
Union[
BaseMessagePromptTemplate,
+ BaseChatPromptTemplate,
BaseMessage,
Tuple[str, str],
Tuple[Type, str],
@@ -515,7 +516,9 @@ class ChatPromptTemplate(BaseChatPromptTemplate, ABC):
# Automatically infer input variables from messages
input_vars = set()
for _message in _messages:
- if isinstance(_message, BaseMessagePromptTemplate):
+ if isinstance(
+ _message, (BaseChatPromptTemplate, BaseMessagePromptTemplate)
+ ):
input_vars.update(_message.input_variables)
return cls(input_variables=sorted(input_vars), messages=_messages)
@@ -643,12 +646,13 @@ def _create_template_from_message_type(
def _convert_to_message(
message: Union[
BaseMessagePromptTemplate,
+ BaseChatPromptTemplate,
BaseMessage,
Tuple[str, str],
Tuple[Type, str],
str,
]
-) -> Union[BaseMessage, BaseMessagePromptTemplate]:
+) -> Union[BaseMessage, BaseMessagePromptTemplate, BaseChatPromptTemplate]:
"""Instantiate a message from a variety of message formats.
The message format can be one of the following:
@@ -665,8 +669,10 @@ def _convert_to_message(
Returns:
an instance of a message or a message template
"""
- if isinstance(message, BaseMessagePromptTemplate):
- _message: Union[BaseMessage, BaseMessagePromptTemplate] = message
+ if isinstance(message, (BaseMessagePromptTemplate, BaseChatPromptTemplate)):
+ _message: Union[
+ BaseMessage, BaseMessagePromptTemplate, BaseChatPromptTemplate
+ ] = message
elif isinstance(message, BaseMessage):
_message = message
elif isinstance(message, str):
diff --git a/libs/langchain/tests/integration_tests/chains/test_cpal.py b/libs/langchain/tests/integration_tests/chains/test_cpal.py
index adb3a6ae5fc..35b00bb0e8a 100644
--- a/libs/langchain/tests/integration_tests/chains/test_cpal.py
+++ b/libs/langchain/tests/integration_tests/chains/test_cpal.py
@@ -7,17 +7,15 @@ from unittest import mock
import pydantic
import pytest
-
-from langchain import OpenAI
-from langchain.experimental.cpal.base import (
+from langchain_experimental.cpal.base import (
CausalChain,
CPALChain,
InterventionChain,
NarrativeChain,
QueryChain,
)
-from langchain.experimental.cpal.constants import Constant
-from langchain.experimental.cpal.models import (
+from langchain_experimental.cpal.constants import Constant
+from langchain_experimental.cpal.models import (
CausalModel,
EntityModel,
EntitySettingModel,
@@ -25,18 +23,20 @@ from langchain.experimental.cpal.models import (
NarrativeModel,
QueryModel,
)
-from langchain.experimental.cpal.templates.univariate.causal import (
+from langchain_experimental.cpal.templates.univariate.causal import (
template as causal_template,
)
-from langchain.experimental.cpal.templates.univariate.intervention import (
+from langchain_experimental.cpal.templates.univariate.intervention import (
template as intervention_template,
)
-from langchain.experimental.cpal.templates.univariate.narrative import (
+from langchain_experimental.cpal.templates.univariate.narrative import (
template as narrative_template,
)
-from langchain.experimental.cpal.templates.univariate.query import (
+from langchain_experimental.cpal.templates.univariate.query import (
template as query_template,
)
+
+from langchain import OpenAI
from langchain.output_parsers import PydanticOutputParser
from langchain.prompts.prompt import PromptTemplate
from tests.unit_tests.llms.fake_llm import FakeLLM
@@ -274,7 +274,7 @@ class TestUnitCPALChain_MathWordProblems(unittest.TestCase):
patch required since `networkx` package is not part of unit test environment
"""
with mock.patch(
- "langchain.experimental.cpal.models.NetworkxEntityGraph"
+ "langchain_experimental.cpal.models.NetworkxEntityGraph"
) as mock_networkx:
graph_instance = mock_networkx.return_value
graph_instance.get_topological_sort.return_value = [