# Chatflows - [LangChain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain.md): LangChain Agent Nodes - [Agents](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents.md): LangChain Agent Nodes - [Airtable Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/airtable-agent.md): Agent used to to answer queries on Airtable table. - [AutoGPT](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/autogpt.md): Autonomous agent with chain of thoughts for self-guided task completion. - [BabyAGI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/babyagi.md): Task Driven Autonomous Agent which creates new task and reprioritizes task list based on objective - [CSV Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/csv-agent.md): Agent used to answer queries on CSV data. - [Conversational Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/conversational-agent.md): Conversational agent for a chat model. It will utilize chat specific prompts. - [OpenAI Assistant](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/openai-assistant.md): An agent that uses OpenAI Assistant API to pick the tool and args to call. - [Threads](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/openai-assistant/threads.md) - [ReAct Agent Chat](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/react-agent-chat.md) - [ReAct Agent LLM](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/react-agent-llm.md) - [Tool Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/tool-agent.md): Agent that uses Function Calling to pick the tools and args to call. - [XML Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/agents/xml-agent.md): Agent that is designed for LLMs that are good for reasoning/writing XML (e.g: Anthropic Claude). - [Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache.md): LangChain Cache Nodes - [InMemory Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/in-memory-cache.md): Caches LLM response in local memory, will be cleared when app is restarted. - [InMemory Embedding Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/inmemory-embedding-cache.md): Cache generated Embeddings in memory to avoid needing to recompute them. - [Momento Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/momento-cache.md): Cache LLM response using Momento, a distributed, serverless cache. - [Redis Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/redis-cache.md): Cache LLM response in Redis, useful for sharing cache across multiple processes or servers. - [Redis Embeddings Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/redis-embeddings-cache.md): Cache LLM response in Redis, useful for sharing cache across multiple processes or servers. - [Upstash Redis Cache](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/cache/upstash-redis-cache.md): Cache LLM response in Upstash Redis, serverless data for Redis and Kafka. - [Chains](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains.md): LangChain Chain Nodes - [GET API Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/get-api-chain.md): Chain to run queries against GET API. - [OpenAPI Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/openapi-chain.md): Chain that automatically select and call APIs based only on an OpenAPI spec. - [POST API Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/post-api-chain.md): Chain to run queries against POST API. - [Conversation Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/conversation-chain.md): Chat models specific conversational chain with memory. - [Conversational Retrieval QA Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/conversational-retrieval-qa-chain.md) - [LLM Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/llm-chain.md): Chain to run queries against LLMs. - [Multi Prompt Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/multi-prompt-chain.md): Chain automatically picks an appropriate prompt from multiple prompt templates. - [Multi Retrieval QA Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/multi-retrieval-qa-chain.md): QA Chain that automatically picks an appropriate vector store from multiple retrievers. - [Retrieval QA Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/retrieval-qa-chain.md): QA chain to answer a question based on the retrieved documents. - [Sql Database Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/sql-database-chain.md): Answer questions over a SQL database. - [Vectara QA Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/vectara-chain.md) - [VectorDB QA Chain](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chains/vectordb-qa-chain.md): QA chain for vector databases. - [Chat Models](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models.md): LangChain Chat Model Nodes - [AWS ChatBedrock](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/aws-chatbedrock.md): Wrapper around AWS Bedrock large language models that use the Chat endpoint. - [Azure ChatOpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/azure-chatopenai-1.md) - [NIBittensorChat](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/nibittensorchat.md): Wrapper around Bittensor subnet 1 large language models. - [ChatAnthropic](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatanthropic.md): Wrapper around ChatAnthropic large language models that use the Chat endpoint. - [ChatCohere](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatcohere.md): Wrapper around Cohere Chat Endpoints. - [Chat Fireworks](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chat-fireworks.md): Wrapper around Fireworks Chat Endpoints. - [ChatGoogleGenerativeAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/google-ai.md) - [ChatGooglePaLM](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatgooglepalm.md): Wrapper around Google MakerSuite PaLM large language models using the Chat endpoint. - [Google VertexAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/google-vertexai.md) - [ChatHuggingFace](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chathuggingface.md): Wrapper around HuggingFace large language models. - [ChatMistralAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/mistral-ai.md) - [ChatOllama](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatollama.md) - [ChatOllama Funtion](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatollama-funtion.md): Run open-source function-calling compatible LLM on Ollama. - [ChatOpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/azure-chatopenai.md) - [ChatOpenAI Custom](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chatopenai-custom.md): Custom/FineTuned model using OpenAI Chat compatible API. - [ChatTogetherAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/chattogetherai.md): Wrapper around TogetherAI large language models - [GroqChat](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/chat-models/groqchat.md): Wrapper around Groq API with LPU Inference Engine. - [Document Loaders](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders.md): LangChain Document Loader Nodes - [API Loader](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/api-loader.md): Load data from an API. - [Airtable](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/airtable.md): Load data from Airtable table. - [Apify Website Content Crawler](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/apify-website-content-crawler.md): Load data from Apify Website Content Crawler. - [Cheerio Web Scraper](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/cheerio-web-scraper.md) - [Confluence](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/confluence.md): Load data from a Confluence Document - [Csv File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/csv-file.md): Load data from CSV files. - [Custom Document Loader](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/custom-document-loader.md): Custom function for loading documents. - [Document Store](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/document-store.md): Load data from pre-configured document stores. - [Docx File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/docx-file.md): Load data from DOCX files. - [Figma](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/figma.md): Load data from a Figma file. - [FireCrawl](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/firecrawl.md): Load data from URL using FireCrawl. - [Folder with Files](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/folder-with-files.md): Load data from folder with multiple files. - [GitBook](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/gitbook.md): Load data from GitBook. - [Github](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/github.md): Load data from a GitHub repository. - [Json File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/json-file.md): Load data from JSON files. - [Json Lines File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/json-lines-file.md): Load data from JSON Lines files. - [Notion Database](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/notion-database.md): Load data from Notion Database (each row is a separate document with all properties as metadata). - [Notion Folder](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/notion-folder.md): Load data from the exported and unzipped Notion folder. - [Notion Page](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/notion-page.md): Load data from Notion Page (including child pages all as separate documents). - [PDF Files](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/pdf-file.md) - [Plain Text](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/plain-text.md): Load data from plain text. - [Playwright Web Scraper](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/playwright-web-scraper.md) - [Puppeteer Web Scraper](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/puppeteer-web-scraper.md) - [AWS S3 File Loader](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/s3-file-loader.md) - [SearchApi For Web Search](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/searchapi-for-web-search.md): Load data from real-time search results. - [SerpApi For Web Search](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/serpapi-for-web-search.md): Load and process data from web search results. - [Spider Web Scraper/Crawler](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/spider-web-scraper-crawler.md): Scrape & Crawl the web with Spider. - [Text File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/text-file.md): Load data from text files. - [Unstructured File Loader](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/unstructured-file-loader.md): Use Unstructured.io to load data from a file path. - [Unstructured Folder Loader](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/unstructured-folder-loader.md): Use Unstructured.io to load data from a folder. Note: Currently doesn't support .png and .heic until unstructured is updated. - [VectorStore To Document](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/document-loaders/vectorstore-to-document.md): Search documents with scores from vector store. - [Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings.md): LangChain Embedding Nodes - [AWS Bedrock Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/aws-bedrock-embeddings.md): AWSBedrock embedding models to generate embeddings for a given text. - [Azure OpenAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/azure-openai-embeddings.md) - [Cohere Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/cohere-embeddings.md): Cohere API to generate embeddings for a given text - [Google GenerativeAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/googlegenerativeai-embeddings.md): Google Generative API to generate embeddings for a given text. - [Google PaLM Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/google-palm-embeddings.md): Google MakerSuite PaLM API to generate embeddings for a given text. - [Google VertexAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/googlevertexai-embeddings.md): Google vertexAI API to generate embeddings for a given text. - [HuggingFace Inference Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/huggingface-inference-embeddings.md): HuggingFace Inference API to generate embeddings for a given text. - [MistralAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/mistralai-embeddings.md): MistralAI API to generate embeddings for a given text. - [Ollama Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/ollama-embeddings.md): Generate embeddings for a given text using open source model on Ollama. - [OpenAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/openai-embeddings.md): OpenAI API to generate embeddings for a given text. - [OpenAI Embeddings Custom](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/openai-embeddings-custom.md): OpenAI API to generate embeddings for a given text. - [TogetherAI Embedding](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/togetherai-embedding.md): TogetherAI Embedding models to generate embeddings for a given text. - [VoyageAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/embeddings/voyageai-embeddings.md): Voyage AI API to generate embeddings for a given text. - [LLMs](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms.md): LangChain LLM Nodes - [AWS Bedrock](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/aws-bedrock.md): Wrapper around AWS Bedrock large language models. - [Azure OpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/azure-openai.md): Wrapper around Azure OpenAI large language models. - [NIBittensorLLM](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/nibittensorllm.md): Wrapper around Bittensor subnet 1 large language models. - [Cohere](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/cohere.md): Wrapper around Cohere large language models. - [GooglePaLM](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/googlepalm.md): Wrapper around Google MakerSuite PaLM large language models. - [GoogleVertex AI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/googlevertex-ai.md): Wrapper around GoogleVertexAI large language models. - [HuggingFace Inference](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/huggingface-inference.md): Wrapper around HuggingFace large language models. - [Ollama](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/ollama.md): Wrapper around open source large language models on Ollama. - [OpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/openai.md): Wrapper around OpenAI large language models. - [Replicate](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/llms/replicate.md): Use Replicate to run open source models on cloud. - [Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory.md): LangChain Memory Nodes - [Buffer Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/buffer-memory.md) - [Buffer Window Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/buffer-window-memory.md) - [Conversation Summary Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/conversation-summary-memory.md) - [Conversation Summary Buffer Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/conversation-summary-buffer-memory.md) - [DynamoDB Chat Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/dynamodb-chat-memory.md): Stores the conversation in dynamo db table. - [MongoDB Atlas Chat Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/mongodb-atlas-chat-memory.md): Stores the conversation in MongoDB Atlas. - [Redis-Backed Chat Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/redis-backed-chat-memory.md): Summarizes the conversation and stores the memory in Redis server. - [Upstash Redis-Backed Chat Memory](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/memory/upstash-redis-backed-chat-memory.md): Summarizes the conversation and stores the memory in Upstash Redis server. - [Moderation](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/moderation.md): LangChain Moderation Nodes - [OpenAI Moderation](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/moderation/openai-moderation.md): Check whether content complies with OpenAI usage policies. - [Simple Prompt Moderation](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/moderation/simple-prompt-moderation.md): Check whether input consists of any text from Deny list, and prevent being sent to LLM. - [Output Parsers](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/output-parsers.md): LangChain Output Parser Nodes - [CSV Output Parser](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/output-parsers/csv-output-parser.md): Parse the output of an LLM call as a comma-separated list of values. - [Custom List Output Parser](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/output-parsers/custom-list-output-parser.md): Parse the output of an LLM call as a list of values. - [Structured Output Parser](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/output-parsers/structured-output-parser.md): Parse the output of an LLM call into a given (JSON) structure. - [Advanced Structured Output Parser](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/output-parsers/advanced-structured-output-parser.md): Parse the output of an LLM call into a given structure by providing a Zod schema. - [Prompts](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/prompts.md): LangChain Prompt Nodes - [Chat Prompt Template](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/prompts/chat-prompt-template.md): Schema to represent a chat prompt. - [Few Shot Prompt Template](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/prompts/few-shot-prompt-template.md): Prompt template you can build with examples. - [Prompt Template](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/prompts/prompt-template.md): Schema to represent a basic prompt for an LLM. - [Record Managers](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/record-managers.md): LangChain Record Manager Nodes - [Retrievers](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers.md): LangChain Retriever Nodes - [Cohere Rerank Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/cohere-rerank-retriever.md): Cohere Rerank indexes the documents from most to least semantically relevant to the query. - [Embeddings Filter Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/embeddings-filter-retriever.md): A document compressor that uses embeddings to drop documents unrelated to the query. - [HyDE Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/hyde-retriever.md): Use HyDE retriever to retrieve from a vector store. - [LLM Filter Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/llm-filter-retriever.md): Iterate over the initially returned documents and extract, from each, only the content that is relevant to the query. - [Multi Query Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/multi-query-retriever.md): Generate multiple queries from different perspectives for a given user input query. - [Prompt Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/prompt-retriever.md): Store prompt template with name & description to be later queried by MultiPromptChain. - [Reciprocal Rank Fusion Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/reciprocal-rank-fusion-retriever.md): Reciprocal Rank Fusion to re-rank search results by multiple query generation. - [Similarity Score Threshold Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/similarity-score-threshold-retriever.md): Return results based on the minimum similarity percentage. - [Vector Store Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/vector-store-retriever.md): Store vector store as retriever to be later queried by MultiRetrievalQAChain. - [Voyage AI Rerank Retriever](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/retrievers/page.md): Voyage AI Rerank indexes the documents from most to least semantically relevant to the query. - [Text Splitters](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters.md): LangChain Text Splitter Nodes - [Character Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/character-text-splitter.md): Splits only on one type of character (defaults to "\n\n"). - [Code Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/code-text-splitter.md): Split documents based on language-specific syntax. - [Html-To-Markdown Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/html-to-markdown-text-splitter.md): Converts Html to Markdown and then split your content into documents based on the Markdown headers. - [Markdown Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/markdown-text-splitter.md): Split your content into documents based on the Markdown headers. - [Recursive Character Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/recursive-character-text-splitter.md): Split documents recursively by different characters - starting with "\n\n", then "\n", then " ". - [Token Text Splitter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/text-splitters/token-text-splitter.md): Splits a raw text string by first converting the text into BPE tokens, then split these tokens into chunks and convert the tokens within a single chunk back into text. - [Tools](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools.md): LangChain Tool Nodes - [BraveSearch API](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/bravesearch-api.md): Wrapper around BraveSearch API - a real-time API to access Brave search results. - [Calculator](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/calculator.md): Perform calculations on response. - [Chain Tool](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/chain-tool.md): Use a chain as allowed tool for agent. - [Chatflow Tool](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/chatflow-tool.md): Execute another chatflow and get the response. - [Custom Tool](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/custom-tool.md) - [Exa Search](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/exa-search.md): Wrapper around Exa Search API - search engine fully designed for use by LLMs. - [Google Custom Search](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/google-custom-search.md): Wrapper around Google Custom Search API - a real-time API to access Google search results. - [OpenAPI Toolkit](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/openapi-toolkit.md): Load OpenAPI specification. - [Python Interpreter](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/python-interpreter.md): Execute python code in Pyodide sandbox environment. - [Read File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/read-file.md): Read file from disk. - [Request Get](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/request-get.md): Execute HTTP GET requests. - [Request Post](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/request-post.md): Execute HTTP POST requests. - [Retriever Tool](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/retriever-tool.md): Use a retriever as allowed tool for agent. - [SearchApi](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/searchapi.md): Real-time API for accessing Google Search data. - [SearXNG](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/searxng.md): Wrapper around SearXNG - a free internet metasearch engine. - [Serp API](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/serp-api.md): Wrapper around SerpAPI - a real-time API to access Google search results. - [Serper](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/serper.md): Wrapper around Serper.dev - Google Search API. - [Web Browser](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/web-browser.md): Gives agent the ability to visit a website and extract information. - [Write File](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/tools/write-file.md): Write file to disk. - [Vector Stores](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores.md): LangChain Vector Store Nodes - [AstraDB](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/astradb.md) - [Chroma](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/chroma.md) - [Elastic](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/elastic.md) - [Faiss](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/faiss.md): Upsert embedded data and perform similarity search upon query using Faiss library from Meta. - [In-Memory Vector Store](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/in-memory-vector-store.md): In-memory vectorstore that stores embeddings and does an exact, linear search for the most similar embeddings. - [Milvus](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/milvus.md): Upsert embedded data and perform similarity search upon query using Milvus, world's most advanced open-source vector database. - [MongoDB Atlas](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/mongodb-atlas.md): Upsert embedded data and perform similarity or mmr search upon query using MongoDB Atlas, a managed cloud mongodb database. - [OpenSearch](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/opensearch.md): Upsert embedded data and perform similarity search upon query using OpenSearch, an open-source, all-in-one vector database. - [Pinecone](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/pinecone.md): Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database. - [Postgres](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/postgres.md): Upsert embedded data and perform similarity search upon query using pgvector on Postgres. - [Qdrant](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/qdrant.md) - [Redis](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/redis.md) - [SingleStore](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/singlestore.md) - [Supabase](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/supabase.md) - [Upstash Vector](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/upstash-vector.md) - [Vectara](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/vectara.md) - [Weaviate](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/weaviate.md): Upsert embedded data and perform similarity or mmr search using Weaviate, a scalable open-source vector database. - [Zep Collection - Open Source](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/zep-collection-open-source.md): Upsert embedded data and perform similarity or mmr search upon query using Zep, a fast and scalable building block for LLM apps. - [Zep Collection - Cloud](https://tailwindsdocs.innovativesol.com/readme/chatflows/langchain/vector-stores/zep-collection-cloud.md): Upsert embedded data and perform similarity or mmr search upon query using Zep, a fast and scalable building block for LLM apps. - [LlamaIndex](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex.md): Learn how Tailwinds integrates with the LlamaIndex framework - [Agents](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/agents.md): LlamaIndex Agent Nodes - [OpenAI Tool Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/agents/openai-tool-agent.md): Agent that uses OpenAI Function Calling to pick the tools and args to call using LlamaIndex. - [Anthropic Tool Agent](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/agents/openai-tool-agent-1.md): Agent that uses Anthropic Function Calling to pick the tools and args to call using LlamaIndex. - [Chat Models](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models.md): LlamaIndex Chat Model Nodes - [AzureChatOpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/azurechatopenai.md): Wrapper around Azure OpenAI Chat LLM specific for LlamaIndex. - [ChatAnthropic](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chatanthropic.md): Wrapper around ChatAnthropic LLM specific for LlamaIndex. - [ChatMistral](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chatmistral.md): Wrapper around ChatMistral LLM specific for LlamaIndex. - [ChatOllama](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chatollama.md): Wrapper around ChatOllama LLM specific for LlamaIndex. - [ChatOpenAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chatopenai.md): Wrapper around OpenAI Chat LLM specific for LlamaIndex. - [ChatTogetherAI](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chattogetherai.md): Wrapper around ChatTogetherAI LLM specific for LlamaIndex. - [ChatGroq](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/chat-models/chatgroq.md): Wrapper around Groq LLM specific for LlamaIndex. - [Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/embeddings.md): LlamaIndex Embeddings Nodes - [Azure OpenAI Embeddings](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/embeddings/azure-openai-embeddings.md): Azure OpenAI API embeddings specific for LlamaIndex. - [OpenAI Embedding](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/embeddings/openai-embedding.md): OpenAI Embedding specific for LlamaIndex. - [Engine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/engine.md): LlamaIndex Engine Nodes - [Query Engine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/engine/query-engine.md) - [Simple Chat Engine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/engine/simple-chat-engine.md) - [Context Chat Engine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/engine/context-chat-engine.md) - [Sub-Question Query Engine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/engine/sub-question-query-engine.md) - [Response Synthesizer](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/response-synthesizer.md): LlamaIndex Response Synthesizer Nodes - [Refine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/response-synthesizer/refine.md) - [Compact And Refine](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/response-synthesizer/compact-and-refine.md) - [Simple Response Builder](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/response-synthesizer/simple-response-builder.md) - [Tree Summarize](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/response-synthesizer/tree-summarize.md) - [Tools](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/tools.md): LlamaIndex Agent Nodes - [Query Engine Tool](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/tools/query-engine-tool.md) - [Vector Stores](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/vector-stores.md): LlamaIndex Vector Store Nodes - [Pinecone](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/vector-stores/pinecone.md): Upsert embedded data and perform similarity search upon query using Pinecone, a leading fully managed hosted vector database. - [SimpleStore](https://tailwindsdocs.innovativesol.com/readme/chatflows/llamaindex/vector-stores/queryengine-tool.md): Upsert embedded data to local path and perform similarity search. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://tailwindsdocs.innovativesol.com/readme/chatflows.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.