diff --git a/docs/api_reference/guide_imports.json b/docs/api_reference/guide_imports.json
index 8a3f485e0d..4da5366e27 100644
--- a/docs/api_reference/guide_imports.json
+++ b/docs/api_reference/guide_imports.json
@@ -1 +1 @@
-{"SingleFileFacebookMessengerChatLoader": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook"}, "FolderFacebookMessengerChatLoader": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Chat loaders": "https://python.langchain.com/docs/integrations/chat_loaders/index"}, "merge_chat_runs": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Slack": "https://python.langchain.com/docs/integrations/chat_loaders/slack", "WhatsApp": "https://python.langchain.com/docs/integrations/chat_loaders/whatsapp", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "Telegram": "https://python.langchain.com/docs/integrations/chat_loaders/telegram", "Discord": "https://python.langchain.com/docs/integrations/chat_loaders/discord"}, "map_ai_messages": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "GMail": "https://python.langchain.com/docs/integrations/chat_loaders/gmail", "Slack": "https://python.langchain.com/docs/integrations/chat_loaders/slack", "WhatsApp": "https://python.langchain.com/docs/integrations/chat_loaders/whatsapp", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "Telegram": "https://python.langchain.com/docs/integrations/chat_loaders/telegram", "Discord": "https://python.langchain.com/docs/integrations/chat_loaders/discord"}, "convert_messages_for_finetuning": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Chat loaders": "https://python.langchain.com/docs/integrations/chat_loaders/index", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage"}, "ChatOpenAI": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Slack": "https://python.langchain.com/docs/integrations/chat_loaders/slack", "WhatsApp": "https://python.langchain.com/docs/integrations/chat_loaders/whatsapp", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "Telegram": "https://python.langchain.com/docs/integrations/chat_loaders/telegram", "Discord": "https://python.langchain.com/docs/integrations/chat_loaders/discord", "RePhraseQueryRetriever": "https://python.langchain.com/docs/integrations/retrievers/re_phrase", "Wikipedia": "https://python.langchain.com/docs/integrations/retrievers/wikipedia", "Arxiv": "https://python.langchain.com/docs/integrations/retrievers/arxiv", "ChatGPT Plugins": "https://python.langchain.com/docs/integrations/tools/chatgpt_plugins", "Human as a tool": "https://python.langchain.com/docs/integrations/tools/human_tools", "Yahoo Finance News": "https://python.langchain.com/docs/integrations/tools/yahoo_finance_news", "ArXiv": "https://python.langchain.com/docs/integrations/tools/arxiv", "Metaphor Search": "https://python.langchain.com/docs/integrations/tools/metaphor_search", "Shell (bash)": "https://python.langchain.com/docs/integrations/tools/bash", "Xata chat memory": "https://python.langchain.com/docs/integrations/memory/xata_chat_message_history", "Dynamodb Chat Message History": "https://python.langchain.com/docs/integrations/memory/dynamodb_chat_message_history", "OpenAI": "https://python.langchain.com/docs/integrations/chat/openai", "LLMonitor": "https://python.langchain.com/docs/integrations/callbacks/llmonitor", "Context": "https://python.langchain.com/docs/integrations/callbacks/context", "Label Studio": "https://python.langchain.com/docs/integrations/callbacks/labelstudio", "PromptLayer": "https://python.langchain.com/docs/integrations/callbacks/promptlayer", "CnosDB": "https://python.langchain.com/docs/integrations/providers/cnosdb", "Log10": "https://python.langchain.com/docs/integrations/providers/log10", "Flyte": "https://python.langchain.com/docs/integrations/providers/flyte", "Arthur": "https://python.langchain.com/docs/integrations/providers/arthur_tracking", "CSV": "https://python.langchain.com/docs/integrations/toolkits/csv", "Document Comparison": "https://python.langchain.com/docs/integrations/toolkits/document_comparison_toolkit", "Python": "https://python.langchain.com/docs/integrations/toolkits/python", "PowerBI Dataset": "https://python.langchain.com/docs/integrations/toolkits/powerbi", "SQL Database": "https://python.langchain.com/docs/integrations/toolkits/sql_database", "Airbyte Question Answering": "https://python.langchain.com/docs/integrations/toolkits/airbyte_structured_qa", "Github": "https://python.langchain.com/docs/integrations/toolkits/github", "Spark SQL": "https://python.langchain.com/docs/integrations/toolkits/spark_sql", "AINetwork": "https://python.langchain.com/docs/integrations/toolkits/ainetwork", "Pandas Dataframe": "https://python.langchain.com/docs/integrations/toolkits/pandas", "Neo4j Vector Index": "https://python.langchain.com/docs/integrations/vectorstores/neo4jvector", "OpenAI Functions Metadata Tagger": "https://python.langchain.com/docs/integrations/document_transformers/openai_metadata_tagger", "Loading documents from a YouTube url": "https://python.langchain.com/docs/integrations/document_loaders/youtube_audio", "Figma": "https://python.langchain.com/docs/integrations/document_loaders/figma", "Fallbacks": "https://python.langchain.com/docs/guides/fallbacks", "Debugging": "https://python.langchain.com/docs/guides/debugging", "LangSmith Walkthrough": "https://python.langchain.com/docs/guides/langsmith/walkthrough", "Reversible data anonymization with Microsoft Presidio": "https://python.langchain.com/docs/guides/privacy/presidio_data_anonymization/reversible", "Data anonymization with Microsoft Presidio": "https://python.langchain.com/docs/guides/privacy/presidio_data_anonymization/index", "Comparing Chain Outputs": "https://python.langchain.com/docs/guides/evaluation/examples/comparisons", "Agent Trajectory": "https://python.langchain.com/docs/guides/evaluation/trajectory/trajectory_eval", "Custom Trajectory Evaluator": "https://python.langchain.com/docs/guides/evaluation/trajectory/custom", "Set env var OPENAI_API_KEY or load from a .env file:": "https://python.langchain.com/docs/use_cases/tagging", "Set env var OPENAI_API_KEY or load from a .env file": "https://python.langchain.com/docs/use_cases/qa_structured/sql", "Question Answering": "https://python.langchain.com/docs/use_cases/question_answering/question_answering", "Perform context-aware text splitting": "https://python.langchain.com/docs/use_cases/question_answering/how_to/document-context-aware-QA", "Conversational Retrieval Agent": "https://python.langchain.com/docs/use_cases/question_answering/how_to/conversational_retrieval_agents", "Multiple Retrieval Sources": "https://python.langchain.com/docs/use_cases/question_answering/how_to/multiple_retrieval", "Cite sources": "https://python.langchain.com/docs/use_cases/question_answering/how_to/qa_citations", "Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "Analysis of Twitter the-algorithm source code with LangChain, GPT4 and Activeloop's Deep Lake": "https://python.langchain.com/docs/use_cases/question_answering/how_to/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/question_answering/how_to/code/code-analysis-deeplake", "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", "Neptune Open Cypher QA Chain": "https://python.langchain.com/docs/use_cases/more/graph/neptune_cypher_qa", "NebulaGraphQAChain": "https://python.langchain.com/docs/use_cases/more/graph/graph_nebula_qa", "Memgraph QA chain": "https://python.langchain.com/docs/use_cases/more/graph/graph_memgraph_qa", "KuzuQAChain": "https://python.langchain.com/docs/use_cases/more/graph/graph_kuzu_qa", "HugeGraph QA Chain": "https://python.langchain.com/docs/use_cases/more/graph/graph_hugegraph_qa", "GraphSparqlQAChain": "https://python.langchain.com/docs/use_cases/more/graph/graph_sparql_qa", "Diffbot Graph Transformer": "https://python.langchain.com/docs/use_cases/more/graph/diffbot_graphtransformer", "ArangoDB QA chain": "https://python.langchain.com/docs/use_cases/more/graph/graph_arangodb_qa", "Neo4j DB QA chain": "https://python.langchain.com/docs/use_cases/more/graph/graph_cypher_qa", "FalkorDBQAChain": "https://python.langchain.com/docs/use_cases/more/graph/graph_falkordb_qa", "Agents": "https://python.langchain.com/docs/use_cases/more/agents/agents", "AutoGPT": "https://python.langchain.com/docs/use_cases/more/agents/autonomous_agents/autogpt", "!pip install bs4": "https://python.langchain.com/docs/use_cases/more/agents/autonomous_agents/marathon_times", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/more/agents/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/more/agents/agents/sales_agent_with_context", "CAMEL Role-Playing Autonomous Cooperative Agents": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/camel_role_playing", "Multi-Agent Simulated Environment: Petting Zoo": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/petting_zoo", "Multi-agent decentralized speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_bidding", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_authoritarian", "Generative Agents in LangChain": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/characters", "Two-Player Dungeons & Dragons": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/two_player_dnd", "Multi-Player Dungeons & Dragons": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multi_player_dnd", "Simulated Environment: Gymnasium": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/gymnasium", "Agent Debates with Tools": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/two_agent_debate_tools", "How to use a SmartLLMChain": "https://python.langchain.com/docs/use_cases/more/self_check/smart_llm", "Vector SQL Retriever with MyScale": "https://python.langchain.com/docs/use_cases/qa_structured/integrations/myscale_vector_sql", "Elasticsearch": "https://python.langchain.com/docs/use_cases/qa_structured/integrations/elasticsearch", "SQL": "https://python.langchain.com/docs/use_cases/sql/sql", "MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "MultiQueryRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/MultiQueryRetriever", "WebResearchRetriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/web_research", "Memory in LLMChain": "https://python.langchain.com/docs/modules/memory/adding_memory", "Custom callback handlers": "https://python.langchain.com/docs/modules/callbacks/custom_callbacks", "Async callbacks": "https://python.langchain.com/docs/modules/callbacks/async_callbacks", "Defining Custom Tools": "https://python.langchain.com/docs/modules/agents/tools/custom_tools", "Tools as OpenAI Functions": "https://python.langchain.com/docs/modules/agents/tools/tools_as_openai_functions", "OpenAI Multi Functions Agent": "https://python.langchain.com/docs/modules/agents/agent_types/openai_multi_functions_agent", "Handle parsing errors": "https://python.langchain.com/docs/modules/agents/how_to/handle_parsing_errors", "Running Agent as an Iterator": "https://python.langchain.com/docs/modules/agents/how_to/agent_iter", "Add Memory to OpenAI Functions Agent": "https://python.langchain.com/docs/modules/agents/how_to/add_memory_openai_functions", "Custom functions with OpenAI Functions Agent": "https://python.langchain.com/docs/modules/agents/how_to/custom-functions-with-openai-functions-agent", "Use ToolKits with OpenAI Functions": "https://python.langchain.com/docs/modules/agents/how_to/use_toolkits_with_openai_functions", "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", "Prompt pipelining": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/prompts_pipelining", "Connecting to a Feature Store": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/connecting_to_a_feature_store", "Custom chain": "https://python.langchain.com/docs/modules/chains/how_to/custom_chain", "Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/how_to/openai_functions", "interface.md": "https://python.langchain.com/docs/expression_language/interface", "First we add a step to load memory": "https://python.langchain.com/docs/expression_language/cookbook/retrieval", "sql_db.md": "https://python.langchain.com/docs/expression_language/cookbook/sql_db", "prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser", "Adding memory": "https://python.langchain.com/docs/expression_language/cookbook/memory", "multiple_chains.md": "https://python.langchain.com/docs/expression_language/cookbook/multiple_chains", "Code writing": "https://python.langchain.com/docs/expression_language/cookbook/code_writing", "Using tools": "https://python.langchain.com/docs/expression_language/cookbook/tools", "Configure Runnable traces": "https://python.langchain.com/docs/expression_language/how_to/trace_config"}, "ChatPromptTemplate": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Chat loaders": "https://python.langchain.com/docs/integrations/chat_loaders/index", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "Anthropic": "https://python.langchain.com/docs/integrations/chat/anthropic", "\ud83d\ude85 LiteLLM": "https://python.langchain.com/docs/integrations/chat/litellm", "Konko": "https://python.langchain.com/docs/integrations/chat/konko", "OpenAI": "https://python.langchain.com/docs/integrations/chat/openai", "Google Cloud Platform Vertex AI PaLM ": "https://python.langchain.com/docs/integrations/chat/google_vertex_ai_palm", "JinaChat": "https://python.langchain.com/docs/integrations/chat/jinachat", "Context": "https://python.langchain.com/docs/integrations/callbacks/context", "OpenAI Functions Metadata Tagger": "https://python.langchain.com/docs/integrations/document_transformers/openai_metadata_tagger", "Figma": "https://python.langchain.com/docs/integrations/document_loaders/figma", "Fireworks": "https://python.langchain.com/docs/integrations/llms/fireworks", "Fallbacks": "https://python.langchain.com/docs/guides/fallbacks", "Set env var OPENAI_API_KEY or load from a .env file:": "https://python.langchain.com/docs/use_cases/tagging", "Multiple Retrieval Sources": "https://python.langchain.com/docs/use_cases/question_answering/how_to/multiple_retrieval", "Structure answers with OpenAI functions": "https://python.langchain.com/docs/use_cases/question_answering/integrations/openai_functions_retrieval_qa", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_authoritarian", "MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "Memory in LLMChain": "https://python.langchain.com/docs/modules/memory/adding_memory", "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", "Few-shot examples for chat models": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/few_shot_examples_chat", "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/how_to/openai_functions", "interface.md": "https://python.langchain.com/docs/expression_language/interface", "First we add a step to load memory": "https://python.langchain.com/docs/expression_language/cookbook/retrieval", "sql_db.md": "https://python.langchain.com/docs/expression_language/cookbook/sql_db", "prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser", "Adding memory": "https://python.langchain.com/docs/expression_language/cookbook/memory", "multiple_chains.md": "https://python.langchain.com/docs/expression_language/cookbook/multiple_chains", "Code writing": "https://python.langchain.com/docs/expression_language/cookbook/code_writing", "Using tools": "https://python.langchain.com/docs/expression_language/cookbook/tools", "Adding moderation": "https://python.langchain.com/docs/expression_language/cookbook/moderation"}, "StrOutputParser": {"Facebook Messenger": "https://python.langchain.com/docs/integrations/chat_loaders/facebook", "Chat loaders": "https://python.langchain.com/docs/integrations/chat_loaders/index", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "OpaquePrompts": "https://python.langchain.com/docs/integrations/llms/opaqueprompts", "Fallbacks": "https://python.langchain.com/docs/guides/fallbacks", "MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "First we add a step to load memory": "https://python.langchain.com/docs/expression_language/cookbook/retrieval", "sql_db.md": "https://python.langchain.com/docs/expression_language/cookbook/sql_db", "prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser", "multiple_chains.md": "https://python.langchain.com/docs/expression_language/cookbook/multiple_chains", "Code writing": "https://python.langchain.com/docs/expression_language/cookbook/code_writing", "Using tools": "https://python.langchain.com/docs/expression_language/cookbook/tools", "Configure Runnable traces": "https://python.langchain.com/docs/expression_language/how_to/trace_config"}, "AIMessage": {"Twitter (via Apify)": "https://python.langchain.com/docs/integrations/chat_loaders/twitter", "Zep": "https://python.langchain.com/docs/integrations/retrievers/zep_memorystore", "Zep Memory": "https://python.langchain.com/docs/integrations/memory/zep_memory", "SQL Chat Message History": "https://python.langchain.com/docs/integrations/memory/sql_chat_message_history", "Anthropic": "https://python.langchain.com/docs/integrations/chat/anthropic", "\ud83d\ude85 LiteLLM": "https://python.langchain.com/docs/integrations/chat/litellm", "Konko": "https://python.langchain.com/docs/integrations/chat/konko", "OpenAI": "https://python.langchain.com/docs/integrations/chat/openai", "JinaChat": "https://python.langchain.com/docs/integrations/chat/jinachat", "Set env var OPENAI_API_KEY or load from a .env file:": "https://python.langchain.com/docs/use_cases/chatbots", "CAMEL Role-Playing Autonomous Cooperative Agents": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/camel_role_playing", "Multi-agent decentralized speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_bidding", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_authoritarian", "Multi-Player Dungeons & Dragons": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multi_player_dnd", "Simulated Environment: Gymnasium": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/gymnasium", "Agent Debates with Tools": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/two_agent_debate_tools", "Prompt pipelining": "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/prompts_pipelining"}, "convert_message_to_dict": {"Twitter (via Apify)": "https://python.langchain.com/docs/integrations/chat_loaders/twitter"}, "GMailLoader": {"GMail": "https://python.langchain.com/docs/integrations/chat_loaders/gmail"}, "SlackChatLoader": {"Slack": "https://python.langchain.com/docs/integrations/chat_loaders/slack"}, "ChatSession": {"Slack": "https://python.langchain.com/docs/integrations/chat_loaders/slack", "WhatsApp": "https://python.langchain.com/docs/integrations/chat_loaders/whatsapp", "iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage", "Telegram": "https://python.langchain.com/docs/integrations/chat_loaders/telegram", "Discord": "https://python.langchain.com/docs/integrations/chat_loaders/discord"}, "WhatsAppChatLoader": {"WhatsApp": "https://python.langchain.com/docs/integrations/providers/whatsapp", "WhatsApp Chat": "https://python.langchain.com/docs/integrations/document_loaders/whatsapp_chat"}, "IMessageChatLoader": {"iMessage": "https://python.langchain.com/docs/integrations/chat_loaders/imessage"}, "TelegramChatLoader": {"Telegram": "https://python.langchain.com/docs/integrations/chat_loaders/telegram"}, "base": {"Discord": "https://python.langchain.com/docs/integrations/chat_loaders/discord"}, "HuggingFaceBgeEmbeddings": {"BGE on Hugging Face": "https://python.langchain.com/docs/integrations/text_embedding/bge_huggingface"}, "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": "https://python.langchain.com/docs/integrations/providers/huggingface", "Sentence Transformers": "https://python.langchain.com/docs/integrations/text_embedding/sentence_transformers", "LOTR (Merger Retriever)": "https://python.langchain.com/docs/integrations/retrievers/merger_retriever", "ScaNN": "https://python.langchain.com/docs/integrations/vectorstores/scann", "Annoy": "https://python.langchain.com/docs/integrations/vectorstores/annoy", "your local model path": "https://python.langchain.com/docs/integrations/vectorstores/vearch", "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", 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"https://python.langchain.com/docs/modules/agents/how_to/agent_vectorstore", "Access intermediate steps": "https://python.langchain.com/docs/modules/agents/how_to/intermediate_steps", "Timeouts for agents": "https://python.langchain.com/docs/modules/agents/how_to/max_time_limit", "Streaming final agent output": "https://python.langchain.com/docs/modules/agents/how_to/streaming_stdout_final_only", "Cap the max number of iterations": "https://python.langchain.com/docs/modules/agents/how_to/max_iterations", "Async API": "https://python.langchain.com/docs/modules/chains/how_to/async_chain", "Tracking token usage": "https://python.langchain.com/docs/modules/model_io/models/llms/token_usage_tracking", "Serialization": "https://python.langchain.com/docs/modules/model_io/models/llms/llm_serialization", "Retry parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/retry", "Datetime parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/datetime", "Pydantic (JSON) parser": "https://python.langchain.com/docs/modules/model_io/output_parsers/pydantic", "Router": "https://python.langchain.com/docs/modules/chains/foundational/router", "Transformation": "https://python.langchain.com/docs/modules/chains/foundational/transformation", "Adding moderation": "https://python.langchain.com/docs/expression_language/cookbook/moderation"}, "ContextualCompressionRetriever": {"Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "LOTR (Merger Retriever)": "https://python.langchain.com/docs/integrations/retrievers/merger_retriever"}, "CohereRerank": {"Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "Cohere": "https://python.langchain.com/docs/integrations/providers/cohere"}, "RetrievalQA": {"Cohere Reranker": "https://python.langchain.com/docs/integrations/retrievers/cohere-reranker", "Ollama": "https://python.langchain.com/docs/integrations/llms/ollama", "Confident": "https://python.langchain.com/docs/integrations/callbacks/confident", "Document Comparison": "https://python.langchain.com/docs/integrations/toolkits/document_comparison_toolkit", "ScaNN": "https://python.langchain.com/docs/integrations/vectorstores/scann", "Activeloop Deep Lake": "https://python.langchain.com/docs/integrations/vectorstores/activeloop_deeplake", "StarRocks": "https://python.langchain.com/docs/integrations/vectorstores/starrocks", "your local model path": "https://python.langchain.com/docs/integrations/vectorstores/vearch", "Loading documents from a YouTube url": "https://python.langchain.com/docs/integrations/document_loaders/youtube_audio", "Docugami": "https://python.langchain.com/docs/integrations/document_loaders/docugami", "Question Answering": "https://python.langchain.com/docs/use_cases/question_answering/question_answering", "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", "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", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/more/agents/agents/sales_agent_with_context", "Combine agents and vector stores": "https://python.langchain.com/docs/modules/agents/how_to/agent_vectorstore"}, "KNNRetriever": {"kNN": "https://python.langchain.com/docs/integrations/retrievers/knn"}, "WikipediaRetriever": {"Wikipedia": "https://python.langchain.com/docs/integrations/providers/wikipedia"}, "ConversationalRetrievalChain": {"Wikipedia": "https://python.langchain.com/docs/integrations/retrievers/wikipedia", "Arxiv": "https://python.langchain.com/docs/integrations/retrievers/arxiv", "Chat Over Documents with Vectara": "https://python.langchain.com/docs/integrations/providers/vectara/vectara_chat", "Vectara": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/vectara_self_query", "Set env var OPENAI_API_KEY or load from a .env file:": "https://python.langchain.com/docs/use_cases/chatbots", "Set env var OPENAI_API_KEY or load from a .env file": "https://python.langchain.com/docs/use_cases/code_understanding", "Analysis of Twitter the-algorithm source code with LangChain, GPT4 and Activeloop's Deep Lake": "https://python.langchain.com/docs/use_cases/question_answering/how_to/code/twitter-the-algorithm-analysis-deeplake", "Use LangChain, GPT and Activeloop's Deep Lake to work with code base": 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"https://python.langchain.com/docs/use_cases/question_answering/how_to/multiple_retrieval", "Retrieve as you generate with FLARE": "https://python.langchain.com/docs/use_cases/question_answering/how_to/flare", "!pip install bs4": "https://python.langchain.com/docs/use_cases/more/agents/autonomous_agents/marathon_times", "Plug-and-Plai": "https://python.langchain.com/docs/use_cases/more/agents/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/more/agents/agents/custom_agent_with_plugin_retrieval", "Set env var OPENAI_API_KEY or load from a .env file": "https://python.langchain.com/docs/use_cases/qa_structured/sql", "SQL": "https://python.langchain.com/docs/use_cases/sql/sql", "Indexing": "https://python.langchain.com/docs/modules/data_connection/indexing", "MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "Milvus": 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"MyScale": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/myscale_self_query", "Deep Lake": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/activeloop_deeplake_self_query", "Qdrant": "https://python.langchain.com/docs/modules/data_connection/retrievers/self_query/qdrant_self_query", "Memory in the Multi-Input Chain": "https://python.langchain.com/docs/modules/memory/adding_memory_chain_multiple_inputs", "Custom agent with tool retrieval": "https://python.langchain.com/docs/modules/agents/how_to/custom_agent_with_tool_retrieval"}, "ChatGPTPluginRetriever": {"ChatGPT Plugin": "https://python.langchain.com/docs/integrations/retrievers/chatgpt-plugin", "OpenAI": "https://python.langchain.com/docs/integrations/providers/openai"}, "GoogleVertexAISearchRetriever": {"Google Vertex AI Search": "https://python.langchain.com/docs/integrations/retrievers/google_vertex_ai_search"}, "DocArrayRetriever": {"DocArray Retriever": 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"Vectara Text Generation": "https://python.langchain.com/docs/integrations/providers/vectara/vectara_text_generation", "Natural Language APIs": "https://python.langchain.com/docs/integrations/toolkits/openapi_nla", "JSON": "https://python.langchain.com/docs/integrations/toolkits/json", "Figma": "https://python.langchain.com/docs/integrations/document_loaders/figma", "Predibase": "https://python.langchain.com/docs/integrations/llms/predibase", "Eden AI": "https://python.langchain.com/docs/integrations/llms/edenai", "Azure ML": "https://python.langchain.com/docs/integrations/llms/azure_ml", "Removing logical fallacies from model output": "https://python.langchain.com/docs/guides/safety/logical_fallacy_chain", "Amazon Comprehend Moderation Chain": "https://python.langchain.com/docs/guides/safety/amazon_comprehend_chain", "Custom Trajectory Evaluator": "https://python.langchain.com/docs/guides/evaluation/trajectory/custom", "Custom Pairwise Evaluator": 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"\ud83d\ude85 LiteLLM": "https://python.langchain.com/docs/integrations/chat/litellm", "Konko": "https://python.langchain.com/docs/integrations/chat/konko", "OpenAI": "https://python.langchain.com/docs/integrations/chat/openai", "Google Cloud Platform Vertex AI PaLM ": "https://python.langchain.com/docs/integrations/chat/google_vertex_ai_palm", "JinaChat": "https://python.langchain.com/docs/integrations/chat/jinachat", "Anyscale": "https://python.langchain.com/docs/integrations/chat/anyscale", "LLMonitor": "https://python.langchain.com/docs/integrations/callbacks/llmonitor", "Context": "https://python.langchain.com/docs/integrations/callbacks/context", "Label Studio": "https://python.langchain.com/docs/integrations/callbacks/labelstudio", "MLflow AI Gateway": "https://python.langchain.com/docs/integrations/providers/mlflow_ai_gateway", "Set env var OPENAI_API_KEY or load from a .env file:": "https://python.langchain.com/docs/use_cases/chatbots", "Conversational Retrieval Agent": 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"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/more/agents/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/more/agents/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/more/agents/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/more/agents/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/more/agents/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Wikibase Agent": "https://python.langchain.com/docs/use_cases/more/agents/agents/wikibase_agent", "SalesGPT - Your Context-Aware AI Sales Assistant With Knowledge Base": "https://python.langchain.com/docs/use_cases/more/agents/agents/sales_agent_with_context", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/more/agents/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"}, "AIPlugin": {"Plug-and-Plai": "https://python.langchain.com/docs/use_cases/more/agents/agents/custom_agent_with_plugin_retrieval_using_plugnplai", "Custom Agent with PlugIn Retrieval": "https://python.langchain.com/docs/use_cases/more/agents/agents/custom_agent_with_plugin_retrieval"}, "SteamshipImageGenerationTool": {"Multi-modal outputs: Image & Text": "https://python.langchain.com/docs/use_cases/more/agents/multi_modal/multi_modal_output_agent"}, "RegexParser": {"Multi-Agent Simulated Environment: Petting Zoo": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/petting_zoo", "Multi-agent decentralized speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_bidding", "Multi-agent authoritarian speaker selection": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/multiagent_authoritarian", "Simulated Environment: Gymnasium": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/gymnasium"}, "TimeWeightedVectorStoreRetriever": {"Generative Agents in LangChain": "https://python.langchain.com/docs/use_cases/more/agents/agent_simulations/characters"}, "LLMBashChain": {"Bash chain": "https://python.langchain.com/docs/use_cases/more/code_writing/llm_bash"}, "BashOutputParser": {"Bash chain": "https://python.langchain.com/docs/use_cases/more/code_writing/llm_bash"}, "BashProcess": {"Bash chain": "https://python.langchain.com/docs/use_cases/more/code_writing/llm_bash"}, "LLMSymbolicMathChain": {"LLM Symbolic Math ": "https://python.langchain.com/docs/use_cases/more/code_writing/llm_symbolic_math"}, "LLMSummarizationCheckerChain": {"Summarization checker chain": "https://python.langchain.com/docs/use_cases/more/self_check/llm_summarization_checker"}, "LLMCheckerChain": {"Self-checking chain": "https://python.langchain.com/docs/use_cases/more/self_check/llm_checker"}, "ElasticsearchDatabaseChain": {"Set env var OPENAI_API_KEY or load from a .env file": "https://python.langchain.com/docs/use_cases/qa_structured/sql", "Elasticsearch": "https://python.langchain.com/docs/use_cases/qa_structured/integrations/elasticsearch", "SQL": "https://python.langchain.com/docs/use_cases/sql/sql"}, "SQLRecordManager": {"Indexing": "https://python.langchain.com/docs/modules/data_connection/indexing"}, "index": {"Indexing": "https://python.langchain.com/docs/modules/data_connection/indexing"}, "BaseLoader": {"Indexing": "https://python.langchain.com/docs/modules/data_connection/indexing"}, "InMemoryStore": {"Caching": "https://python.langchain.com/docs/modules/data_connection/text_embedding/caching_embeddings", "MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "Parent Document Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/parent_document_retriever"}, "LocalFileStore": {"Caching": "https://python.langchain.com/docs/modules/data_connection/text_embedding/caching_embeddings"}, "RedisStore": {"Caching": "https://python.langchain.com/docs/modules/data_connection/text_embedding/caching_embeddings"}, "CacheBackedEmbeddings": {"Caching": "https://python.langchain.com/docs/modules/data_connection/text_embedding/caching_embeddings"}, "EnsembleRetriever": {"Ensemble Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/ensemble"}, "MultiVectorRetriever": {"MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector"}, "JsonKeyOutputFunctionsParser": {"MultiVector Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/multi_vector", "prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser"}, "ParentDocumentRetriever": {"Parent Document Retriever": "https://python.langchain.com/docs/modules/data_connection/retrievers/parent_document_retriever"}, "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": {"Message Memory in Agent backed by a database": "https://python.langchain.com/docs/modules/memory/agent_with_memory_in_db"}, "BaseMemory": {"Custom Memory": "https://python.langchain.com/docs/modules/memory/custom_memory"}, "ConversationKGMemory": {"Conversation Knowledge Graph": "https://python.langchain.com/docs/modules/memory/types/kg"}, "ConversationTokenBufferMemory": {"Conversation Token Buffer": "https://python.langchain.com/docs/modules/memory/types/token_buffer"}, "tracing_enabled": {"Multiple callback handlers": "https://python.langchain.com/docs/modules/callbacks/multiple_callbacks"}, "FileCallbackHandler": {"Logging to file": "https://python.langchain.com/docs/modules/callbacks/filecallbackhandler"}, "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"}, "XMLAgent": {"XML Agent": "https://python.langchain.com/docs/modules/agents/agent_types/xml_agent", "Agents": "https://python.langchain.com/docs/expression_language/cookbook/agent"}, "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"}, "HumanInputChatModel": {"Human input chat model": "https://python.langchain.com/docs/modules/model_io/models/chat/human_input_chat_model"}, "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"}, "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"}, "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"}, "create_openai_fn_chain": {"Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/how_to/openai_functions"}, "create_structured_output_chain": {"Using OpenAI functions": "https://python.langchain.com/docs/modules/chains/how_to/openai_functions"}, "RunnablePassthrough": {"First we add a step to load memory": "https://python.langchain.com/docs/expression_language/cookbook/retrieval", "prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser", "multiple_chains.md": "https://python.langchain.com/docs/expression_language/cookbook/multiple_chains"}, "format_document": {"First we add a step to load memory": "https://python.langchain.com/docs/expression_language/cookbook/retrieval"}, "RunnableLambda": {"sql_db.md": "https://python.langchain.com/docs/expression_language/cookbook/sql_db", "Run arbitrary functions": "https://python.langchain.com/docs/expression_language/how_to/functions"}, "JsonOutputFunctionsParser": {"prompt_llm_parser.md": "https://python.langchain.com/docs/expression_language/cookbook/prompt_llm_parser"}, "RunnableConfig": {"Run arbitrary functions": "https://python.langchain.com/docs/expression_language/how_to/functions"}, "GoogleSpeechToTextLoader": {"Google Cloud Speech-to-Text": "https://python.langchain.com/docs/integrations/document_loaders/google_speech_to_text"},  "GoogleTranslateTransformer": {"Google Cloud Translation": "https://python.langchain.com/docs/integrations/document_loaders/google_translate"}}
diff --git a/docs/docs/integrations/document_transformers/google_translate.ipynb b/docs/docs/integrations/document_transformers/google_translate.ipynb
new file mode 100644
index 0000000000..07a0299dd4
--- /dev/null
+++ b/docs/docs/integrations/document_transformers/google_translate.ipynb
@@ -0,0 +1,215 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Google Translate\n",
+    "\n",
+    "[Google Translate](https://translate.google.com/) is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another.\n",
+    "\n",
+    "The `GoogleTranslateTransformer` allows you to translate text and HTML with the [Google Cloud Translation API](https://cloud.google.com/translate).\n",
+    "\n",
+    "To use it, you should have the `google-cloud-translate` python package installed, and a Google Cloud project with the [Translation API enabled](https://cloud.google.com/translate/docs/setup). This transformer uses the [Advanced edition (v3)](https://cloud.google.com/translate/docs/intro-to-v3).\n",
+    "\n",
+    "- [Google Neural Machine Translation](https://en.wikipedia.org/wiki/Google_Neural_Machine_Translation)\n",
+    "- [A Neural Network for Machine Translation, at Production Scale](https://blog.research.google/2016/09/a-neural-network-for-machine.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install google-cloud-translate\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.schema import Document\n",
+    "from langchain.document_transformers import GoogleTranslateTransformer\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Input\n",
+    "\n",
+    "This is the document we'll translate"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sample_text = \"\"\"[Generated with Google Bard]\n",
+    "Subject: Key Business Process Updates\n",
+    "\n",
+    "Date: Friday, 27 October 2023\n",
+    "\n",
+    "Dear team,\n",
+    "\n",
+    "I am writing to provide an update on some of our key business processes.\n",
+    "\n",
+    "Sales process\n",
+    "\n",
+    "We have recently implemented a new sales process that is designed to help us close more deals and grow our revenue. The new process includes a more rigorous qualification process, a more streamlined proposal process, and a more effective customer relationship management (CRM) system.\n",
+    "\n",
+    "Marketing process\n",
+    "\n",
+    "We have also revamped our marketing process to focus on creating more targeted and engaging content. We are also using more social media and paid advertising to reach a wider audience.\n",
+    "\n",
+    "Customer service process\n",
+    "\n",
+    "We have also made some improvements to our customer service process. We have implemented a new customer support system that makes it easier for customers to get help with their problems. We have also hired more customer support representatives to reduce wait times.\n",
+    "\n",
+    "Overall, we are very pleased with the progress we have made on improving our key business processes. We believe that these changes will help us to achieve our goals of growing our business and providing our customers with the best possible experience.\n",
+    "\n",
+    "If you have any questions or feedback about any of these changes, please feel free to contact me directly.\n",
+    "\n",
+    "Thank you,\n",
+    "\n",
+    "Lewis Cymbal\n",
+    "CEO, Cymbal Bank\n",
+    "\"\"\"\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When initializing the `GoogleTranslateTransformer`, you can include the following parameters to configure the requests.\n",
+    "\n",
+    "- `project_id`: Google Cloud Project ID.\n",
+    "- `location`: (Optional) Translate model location.\n",
+    "  - Default: `global` \n",
+    "- `model_id`: (Optional) Translate [model ID][models] to use.\n",
+    "- `glossary_id`: (Optional) Translate [glossary ID][glossaries] to use.\n",
+    "- `api_endpoint`: (Optional) [Regional endpoint][endpoints] to use.\n",
+    "\n",
+    "[models]: https://cloud.google.com/translate/docs/advanced/translating-text-v3#comparing-models\n",
+    "[glossaries]: https://cloud.google.com/translate/docs/advanced/glossary\n",
+    "[endpoints]: https://cloud.google.com/translate/docs/advanced/endpoints"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "documents = [Document(page_content=sample_text)]\n",
+    "translator = GoogleTranslateTransformer(project_id=\"<YOUR_PROJECT_ID>\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Output\n",
+    "\n",
+    "After translating a document, the result will be returned as a new document with the `page_content` translated into the target language.\n",
+    "\n",
+    "You can provide the following keyword parameters to the `transform_documents()` method:\n",
+    "\n",
+    "- `target_language_code`: [ISO 639][iso-639] language code of the output document.\n",
+    "    - For supported languages, refer to [Language support][supported-languages].\n",
+    "- `source_language_code`: (Optional) [ISO 639][iso-639] language code of the input document.\n",
+    "    - If not provided, language will be auto-detected.\n",
+    "- `mime_type`: (Optional) [Media Type][media-type] of the input text.\n",
+    "    - Options: `text/plain` (Default), `text/html`.\n",
+    "\n",
+    "[iso-639]: https://en.wikipedia.org/wiki/ISO_639\n",
+    "[supported-languages]: https://cloud.google.com/translate/docs/languages\n",
+    "[media-type]: https://en.wikipedia.org/wiki/Media_type"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "translated_documents = translator.transform_documents(documents, target_language_code=\"es\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'model': '', 'detected_language_code': 'en'}\n",
+      "[Generado con Google Bard]\n",
+      "Asunto: Actualizaciones clave de procesos comerciales\n",
+      "\n",
+      "Fecha: viernes 27 de octubre de 2023\n",
+      "\n",
+      "Estimado equipo,\n",
+      "\n",
+      "Le escribo para brindarle una actualización sobre algunos de nuestros procesos comerciales clave.\n",
+      "\n",
+      "Proceso de ventas\n",
+      "\n",
+      "Recientemente implementamos un nuevo proceso de ventas que está diseñado para ayudarnos a cerrar más acuerdos y aumentar nuestros ingresos. El nuevo proceso incluye un proceso de calificación más riguroso, un proceso de propuesta más simplificado y un sistema de gestión de relaciones con el cliente (CRM) más eficaz.\n",
+      "\n",
+      "Proceso de mercadeo\n",
+      "\n",
+      "También hemos renovado nuestro proceso de marketing para centrarnos en crear contenido más específico y atractivo. También estamos utilizando más redes sociales y publicidad paga para llegar a una audiencia más amplia.\n",
+      "\n",
+      "proceso de atención al cliente\n",
+      "\n",
+      "También hemos realizado algunas mejoras en nuestro proceso de atención al cliente. Hemos implementado un nuevo sistema de atención al cliente que facilita que los clientes obtengan ayuda con sus problemas. También hemos contratado más representantes de atención al cliente para reducir los tiempos de espera.\n",
+      "\n",
+      "En general, estamos muy satisfechos con el progreso que hemos logrado en la mejora de nuestros procesos comerciales clave. Creemos que estos cambios nos ayudarán a lograr nuestros objetivos de hacer crecer nuestro negocio y brindar a nuestros clientes la mejor experiencia posible.\n",
+      "\n",
+      "Si tiene alguna pregunta o comentario sobre cualquiera de estos cambios, no dude en ponerse en contacto conmigo directamente.\n",
+      "\n",
+      "Gracias,\n",
+      "\n",
+      "Platillo Lewis\n",
+      "Director ejecutivo, banco de platillos\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for doc in translated_documents:\n",
+    "    print(doc.metadata)\n",
+    "    print(doc.page_content)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/docs/docs/integrations/platforms/google.mdx b/docs/docs/integrations/platforms/google.mdx
index 3cdb7e88d5..5fbb941ec7 100644
--- a/docs/docs/integrations/platforms/google.mdx
+++ b/docs/docs/integrations/platforms/google.mdx
@@ -83,7 +83,7 @@ First, we need to install several python packages.
 pip install google-api-python-client google-auth-httplib2 google-auth-oauthlib
 ```
 
-See a [usage example and authorizing instructions](/docs/integrations/document_loaders/google_drive).
+See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_drive).
 
 ```python
 from langchain.document_loaders import GoogleDriveLoader
@@ -101,7 +101,7 @@ First, we need to install the python package.
 pip install google-cloud-speech
 ```
 
-See a [usage example and authorizing instructions](/docs/integrations/document_loaders/google_speech_to_text).
+See a [usage example and authorization instructions](/docs/integrations/document_loaders/google_speech_to_text).
 
 ```python
 from langchain.document_loaders import GoogleSpeechToTextLoader
@@ -221,15 +221,14 @@ pip install googlemaps
 from langchain.tools import GooglePlacesTool
 ```
 
-## Document Transformer
+## Document Transformers
+
 ### Google Document AI
 
 >[Document AI](https://cloud.google.com/document-ai/docs/overview) is a `Google Cloud Platform` 
 > service to transform unstructured data from documents into structured data, making it easier 
 > to understand, analyze, and consume.  
 
-
-
 We need to set up a [`GCS` bucket and create your own OCR processor](https://cloud.google.com/document-ai/docs/create-processor)  
 The `GCS_OUTPUT_PATH` should be a path to a folder on GCS (starting with `gs://`) 
 and a processor name should look like `projects/PROJECT_NUMBER/locations/LOCATION/processors/PROCESSOR_ID`.
@@ -241,7 +240,6 @@ pip install google-cloud-documentai
 pip install google-cloud-documentai-toolbox
 ```
 
-
 See a [usage example](/docs/integrations/document_transformers/docai).
 
 ```python
@@ -249,6 +247,28 @@ from langchain.document_loaders.blob_loaders import Blob
 from langchain.document_loaders.parsers import DocAIParser
 ```
 
+### Google Translate
+
+> [Google Translate](https://translate.google.com/) is a multilingual neural machine
+> translation service developed by Google to translate text, documents and websites
+> from one language into another.
+
+The `GoogleTranslateTransformer` allows you to translate text and HTML with the [Google Cloud Translation API](https://cloud.google.com/translate).
+
+To use it, you should have the `google-cloud-translate` python package installed, and a Google Cloud project with the [Translation API enabled](https://cloud.google.com/translate/docs/setup). This transformer uses the [Advanced edition (v3)](https://cloud.google.com/translate/docs/intro-to-v3).
+
+First, we need to install the python package.
+
+```bash
+pip install google-cloud-translate
+```
+
+See a [usage example and authorization instructions](/docs/integrations/document_transformers/google_translate).
+
+```python
+from langchain.document_transformers import GoogleTranslateTransformer
+```
+
 ## Chat loaders
 ### Gmail
 
@@ -260,7 +280,7 @@ First, we need to install several python packages.
 pip install --upgrade google-auth google-auth-oauthlib google-auth-httplib2 google-api-python-client
 ```
 
-See a [usage example and authorizing instructions](/docs/integrations/chat_loaders/gmail).
+See a [usage example and authorization instructions](/docs/integrations/chat_loaders/gmail).
 
 ```python
 from langchain.chat_loaders.gmail import GMailLoader
@@ -269,7 +289,7 @@ from langchain.chat_loaders.gmail import GMailLoader
 ## Agents and Toolkits
 ### Gmail
 
-See a [usage example and authorizing instructions](/docs/integrations/toolkits/gmail).
+See a [usage example and authorization instructions](/docs/integrations/toolkits/gmail).
 
 ```python
 from langchain.agents.agent_toolkits import GmailToolkit
@@ -279,7 +299,7 @@ toolkit = GmailToolkit()
 
 ### Google Drive
 
-See a [usage example and authorizing instructions](/docs/integrations/toolkits/google_drive).
+See a [usage example and authorization instructions](/docs/integrations/toolkits/google_drive).
 
 ```python
 from langchain_googledrive.utilities.google_drive import GoogleDriveAPIWrapper
diff --git a/libs/langchain/langchain/document_transformers/__init__.py b/libs/langchain/langchain/document_transformers/__init__.py
index e7a51e0445..abaed3894c 100644
--- a/libs/langchain/langchain/document_transformers/__init__.py
+++ b/libs/langchain/langchain/document_transformers/__init__.py
@@ -28,6 +28,7 @@ from langchain.document_transformers.embeddings_redundant_filter import (
     EmbeddingsRedundantFilter,
     get_stateful_documents,
 )
+from langchain.document_transformers.google_translate import GoogleTranslateTransformer
 from langchain.document_transformers.html2text import Html2TextTransformer
 from langchain.document_transformers.long_context_reorder import LongContextReorder
 from langchain.document_transformers.nuclia_text_transform import NucliaTextTransformer
@@ -40,6 +41,7 @@ __all__ = [
     "DoctranPropertyExtractor",
     "EmbeddingsClusteringFilter",
     "EmbeddingsRedundantFilter",
+    "GoogleTranslateTransformer",
     "get_stateful_documents",
     "LongContextReorder",
     "NucliaTextTransformer",
diff --git a/libs/langchain/langchain/document_transformers/google_translate.py b/libs/langchain/langchain/document_transformers/google_translate.py
new file mode 100644
index 0000000000..f52e618230
--- /dev/null
+++ b/libs/langchain/langchain/document_transformers/google_translate.py
@@ -0,0 +1,106 @@
+from typing import Any, Optional, Sequence
+
+from langchain.schema import BaseDocumentTransformer, Document
+from langchain.utilities.vertexai import get_client_info
+
+
+class GoogleTranslateTransformer(BaseDocumentTransformer):
+    """Translate text documents using Google Cloud Translation."""
+
+    def __init__(
+        self,
+        project_id: str,
+        *,
+        location: str = "global",
+        model_id: Optional[str] = None,
+        glossary_id: Optional[str] = None,
+        api_endpoint: Optional[str] = None,
+    ) -> None:
+        """
+        Arguments:
+            project_id: Google Cloud Project ID.
+            location: (Optional) Translate model location.
+            model_id: (Optional) Translate model ID to use.
+            glossary_id: (Optional) Translate glossary ID to use.
+            api_endpoint: (Optional) Regional endpoint to use.
+        """
+        try:
+            from google.api_core.client_options import ClientOptions
+            from google.cloud import translate
+        except ImportError as exc:
+            raise ImportError(
+                "Install Google Cloud Translate to use this parser."
+                "(pip install google-cloud-translate)"
+            ) from exc
+
+        self.project_id = project_id
+        self.location = location
+        self.model_id = model_id
+        self.glossary_id = glossary_id
+
+        self._client = translate.TranslationServiceClient(
+            client_info=get_client_info("translate"),
+            client_options=(
+                ClientOptions(api_endpoint=api_endpoint) if api_endpoint else None
+            ),
+        )
+        self._parent_path = self._client.common_location_path(project_id, location)
+        # For some reason, there's no `model_path()` method for the client.
+        self._model_path = (
+            f"{self._parent_path}/models/{model_id}" if model_id else None
+        )
+        self._glossary_path = (
+            self._client.glossary_path(project_id, location, glossary_id)
+            if glossary_id
+            else None
+        )
+
+    def transform_documents(
+        self, documents: Sequence[Document], **kwargs: Any
+    ) -> Sequence[Document]:
+        """Translate text documents using Google Translate.
+
+        Arguments:
+            source_language_code: ISO 639 language code of the input document.
+            target_language_code: ISO 639 language code of the output document.
+                For supported languages, refer to:
+                https://cloud.google.com/translate/docs/languages
+            mime_type: (Optional) Media Type of input text.
+                Options: `text/plain`, `text/html`
+        """
+        try:
+            from google.cloud import translate
+        except ImportError as exc:
+            raise ImportError(
+                "Install Google Cloud Translate to use this parser."
+                "(pip install google-cloud-translate)"
+            ) from exc
+
+        response = self._client.translate_text(
+            request=translate.TranslateTextRequest(
+                contents=[doc.page_content for doc in documents],
+                parent=self._parent_path,
+                model=self._model_path,
+                glossary_config=translate.TranslateTextGlossaryConfig(
+                    glossary=self._glossary_path
+                ),
+                source_language_code=kwargs.get("source_language_code", None),
+                target_language_code=kwargs.get("target_language_code"),
+                mime_type=kwargs.get("mime_type", "text/plain"),
+            )
+        )
+
+        # If using a glossary, the translations will be in `glossary_translations`.
+        translations = response.glossary_translations or response.translations
+
+        return [
+            Document(
+                page_content=translation.translated_text,
+                metadata={
+                    **doc.metadata,
+                    "model": translation.model,
+                    "detected_language_code": translation.detected_language_code,
+                },
+            )
+            for doc, translation in zip(documents, translations)
+        ]