# Tailwinds - The UI for AI

## Tailwinds - The UI for AI

- [Welcome to Tailwinds](https://tailwindsdocs.innovativesol.com/readme.md): Tailwinds is the "UI for AI" platform designed to simplify the creation of AI-powered applications, workflows, chatbots, and APIs.
- [Chatflows](https://tailwindsdocs.innovativesol.com/readme/chatflows.md)
- [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.
- [Agentflows](https://tailwindsdocs.innovativesol.com/readme/agentflows.md): Learn about the different agentic system architectures incorporated in Tailwinds.
- [Multi-Agents (Supervisor/Worker)](https://tailwindsdocs.innovativesol.com/readme/agentflows/multi-agents.md): Learn how to use Multi-Agents in Tailwinds
- [Sequential Agents](https://tailwindsdocs.innovativesol.com/readme/agentflows/sequential-agents.md)
- [API](https://tailwindsdocs.innovativesol.com/readme/api.md): Learn how to use the Prediction, Vector Upsert and Message API
- [Chatflows and APIs](https://tailwindsdocs.innovativesol.com/readme/api/chatflow-level.md): Learn how to set up chatflow-level access control for your Tailwinds instance
- [Document Stores](https://tailwindsdocs.innovativesol.com/readme/document-stores.md): Learn how to use the Tailwinds Document Stores
- [Embed](https://tailwindsdocs.innovativesol.com/readme/embed.md): Learn how to embed our in-house chat widget
- [Rate Limit](https://tailwindsdocs.innovativesol.com/readme/embed/rate-limit.md): Learn how to managing API requests in Tailwinds
- [API Streaming](https://tailwindsdocs.innovativesol.com/readme/streaming.md): Learn when you can stream back to your front end
- [Analytics](https://tailwindsdocs.innovativesol.com/readme/analytic.md): Learn how to analyze and troubleshoot your chatflows and agentflows
- [Credentials](https://tailwindsdocs.innovativesol.com/readme/credentials.md): Tailwinds natively integrates with a number of out of the box ISVs, AI providers and more
- [Amazon Bedrock Credential Setup](https://tailwindsdocs.innovativesol.com/readme/credentials/amazon-bedrock-credential-setup.md)
- [IBM Watsonx.AI Credential Setup](https://tailwindsdocs.innovativesol.com/readme/credentials/ibm-watsonx.ai-credential-setup.md)
- [Variables](https://tailwindsdocs.innovativesol.com/readme/variables.md): Learn how to use variables in Tailwinds
- [Utilities](https://tailwindsdocs.innovativesol.com/readme/utilities.md): Learn how to use Tailwinds utility nodes
- [Custom JS Function](https://tailwindsdocs.innovativesol.com/readme/utilities/custom-js-function.md): Similar to a Tool, you can write custom JS functions that can be executed as independent nodes withing Tailwinds.
- [Set/Get Variable](https://tailwindsdocs.innovativesol.com/readme/utilities/set-get-variable.md)
- [If Else](https://tailwindsdocs.innovativesol.com/readme/utilities/if-else.md)
- [Sticky Note](https://tailwindsdocs.innovativesol.com/readme/utilities/sticky-note.md): Add a sticky note to the flow.
- [Example Flows](https://tailwindsdocs.innovativesol.com/readme/use-cases.md): Learn to build your own Tailwinds solutions through practical examples
- [Calling Children Flows](https://tailwindsdocs.innovativesol.com/readme/use-cases/calling-children-flows.md): Learn how to effectively use the Chatflow Tool and the Custom Tool
- [Calling Webhook](https://tailwindsdocs.innovativesol.com/readme/use-cases/webhook-tool.md): Learn how to call a webhook on Make
- [Interacting with API](https://tailwindsdocs.innovativesol.com/readme/use-cases/interacting-with-api.md): Learn how to use external API integrations with Tailwinds
- [Multiple Documents QnA](https://tailwindsdocs.innovativesol.com/readme/use-cases/multiple-documents-qna.md): Learn how to query multiple documents correctly
- [SQL QnA](https://tailwindsdocs.innovativesol.com/readme/use-cases/sql-qna.md): Learn how to query structured data
- [Upserting Data](https://tailwindsdocs.innovativesol.com/readme/use-cases/upserting-data.md): Learn how to upsert data to Vector Stores with Tailwinds
- [Web Scrape QnA](https://tailwindsdocs.innovativesol.com/readme/use-cases/web-scrape-qna.md): Learn how to scrape, upsert, and query a website
- [Monitoring & Auditing](https://tailwindsdocs.innovativesol.com/readme/monitoring-and-auditing.md)
- [Configuring Monitoring and Traces](https://tailwindsdocs.innovativesol.com/readme/monitoring-and-auditing/configuring-monitoring-and-traces.md)
- [Tailwinds Security and Deployment](https://tailwindsdocs.innovativesol.com/readme/tailwinds-security-and-deployment.md): This article details the deployment model of Tailwinds, data security posture and other relevant material.
- [Release Notes](https://tailwindsdocs.innovativesol.com/release-notes.md)
- [12/17/2024 - v2.2.1](https://tailwindsdocs.innovativesol.com/release-notes/12-17-2024-v2.2.1.md)
- [10/11/2024 - v2.1.2](https://tailwindsdocs.innovativesol.com/release-notes/10-11-2024-v2.1.2.md)
- [9/27/2024- v2.1](https://tailwindsdocs.innovativesol.com/release-notes/9-27-2024-v2.1.md)
- [8/16/2024 - v2.0.5](https://tailwindsdocs.innovativesol.com/release-notes/8-16-2024-v2.0.5.md): Tailwinds 2.0.5 Release Notes
- [Demos and Use-cases](https://tailwindsdocs.innovativesol.com/demos.md): Here are a number of demos leveraging Tailwinds to solve practical problems.
- [Create a Basic Chatbot](https://tailwindsdocs.innovativesol.com/demos/create-a-basic-chatbot.md)
- [Build an AI-Powered Translator](https://tailwindsdocs.innovativesol.com/demos/build-an-ai-powered-translator.md)
- [Create research-powered call scripts](https://tailwindsdocs.innovativesol.com/demos/create-research-powered-call-scripts.md)
- [Extract information from Medical Documents](https://tailwindsdocs.innovativesol.com/demos/extract-information-from-medical-documents.md)
- [Identify ICD10 medical codes](https://tailwindsdocs.innovativesol.com/demos/identify-icd10-medical-codes.md)
- [Syllabus](https://tailwindsdocs.innovativesol.com/genai-university/syllabus.md)
- [101-Prompt Engineering](https://tailwindsdocs.innovativesol.com/genai-university/101-prompt-engineering.md): And related techniques
- [101-System Prompts](https://tailwindsdocs.innovativesol.com/genai-university/101-system-prompts.md)
- [101-Human (User) Prompts](https://tailwindsdocs.innovativesol.com/genai-university/101-human-user-prompts.md)
- [101-Context Window](https://tailwindsdocs.innovativesol.com/genai-university/101-context-window.md)
- [101-Prompt Chains](https://tailwindsdocs.innovativesol.com/genai-university/101-prompt-chains.md)
- [201-Documents and Vector Databases (RAG)](https://tailwindsdocs.innovativesol.com/genai-university/201-documents-and-vector-databases-rag.md)
- [301-AI Agents](https://tailwindsdocs.innovativesol.com/genai-university/301-ai-agents.md)
- [301-Agent Tools](https://tailwindsdocs.innovativesol.com/genai-university/301-agent-tools.md)
- [401-Multi-Agent](https://tailwindsdocs.innovativesol.com/genai-university/401-multi-agent.md)