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Merge pull request #1678 from vinodkiran/FEATURE/marketplace-revamp
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Marketplace: Revamped UI
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vinodkiran committed Feb 8, 2024
2 parents f758800 + 08c0780 commit 64018b7
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/API Agent OpenAI.json
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{
"description": "Use OpenAI Function Agent and Chain to automatically decide which API to call, generating url and body request from conversation",
"categories": "Buffer Memory,ChainTool,API Chain,ChatOpenAI,OpenAI Function Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/API Agent.json
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{
"description": "Given API docs, agent automatically decide which API to call, generating url and body request from conversation",
"categories": "Buffer Memory,ChainTool,API Chain,ChatOpenAI,Conversational Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Antonym.json
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{
"description": "Output antonym of given user input using few-shot prompt template built with examples",
"categories": "Few Shot Prompt,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/AutoGPT.json
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{
"description": "Use AutoGPT - Autonomous agent with chain of thoughts for self-guided task completion",
"categories": "AutoGPT,SERP Tool,File Read/Write,ChatOpenAI,Pinecone,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/BabyAGI.json
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{
"description": "Use BabyAGI to create tasks and reprioritize for a given objective",
"categories": "BabyAGI,ChatOpenAI,Pinecone,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/CSV Agent.json
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{
"description": "Analyse and summarize CSV data",
"categories": "CSV Agent,ChatOpenAI,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Engage with data sources such as YouTube Transcripts, Google, and more through intelligent Q&A interactions",
"categories": "Memory Vector Store,SearchAPI,ChatOpenAI,Conversational Retrieval QA Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/ChatGPTPlugin.json
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{
"description": "Use ChatGPT Plugins within LangChain abstractions with GET and POST Tools",
"categories": "ChatGPT Plugin,HTTP GET/POST,ChatOpenAI,MRKL Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Claude LLM.json
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{
"description": "Use Anthropic Claude with 200k context window to ingest whole document for QnA",
"categories": "Buffer Memory,Prompt Template,Conversation Chain,ChatAnthropic,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Answer question based on retrieved documents (context) with built-in memory to remember conversation using LlamaIndex",
"categories": "Text File,Prompt Template,ChatOpenAI,Conversation Chain,Pinecone,LlamaIndex,Redis",
"framework": "LlamaIndex",
"badge": "NEW",
"nodes": [
{
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{
"description": "A conversational agent for a chat model which utilize chat specific prompts",
"categories": "Calculator Tool,Buffer Memory,SerpAPI,ChatOpenAI,Conversational Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Agent optimized for vector retrieval during conversation and answering questions based on previous dialogue.",
"categories": "Retriever Tool,Buffer Memory,ChatOpenAI,Conversational Retrieval Agent, Pinecone,Langchain",
"badge": "POPULAR",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Text file QnA using conversational retrieval QA chain",
"categories": "TextFile,ChatOpenAI,Conversational Retrieval QA Chain,Pinecone,Langchain",
"badge": "POPULAR",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Flowise Docs QnA.json
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{
"description": "Flowise Docs Github QnA using conversational retrieval QA chain",
"categories": "Memory Vector Store,Github Loader,ChatOpenAI,Conversational Retrieval QA Chain,Langchain",
"badge": "POPULAR",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Simple LLM Chain using HuggingFace Inference API on falcon-7b-instruct model",
"categories": "HuggingFace,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/IfElse.json
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{
"description": "Split flows based on if else condition",
"categories": "IfElse Function,ChatOpenAI,OpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"badge": "new",
"nodes": [
{
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Image Generation.json
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{
"description": "Generate image using Replicate Stability text-to-image generative AI model",
"badge": "NEW",
"categories": "Replicate,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Input Moderation.json
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{
"description": "Detect text that could generate harmful output and prevent it from being sent to the language model",
"badge": "NEW",
"categories": "Moderation,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Return response as a list (array) instead of a string/text",
"badge": "NEW",
"categories": "CSV Output Parser,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Local QnA.json
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{
"description": "QnA chain using Ollama local LLM, LocalAI embedding model, and Faiss local vector store",
"badge": "POPULAR",
"categories": "Text File,ChatOllama,Conversational Retrieval QA Chain,Faiss,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Long Term Memory.json
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{
"description": "Use long term memory like Zep to differentiate conversations between users with sessionId",
"categories": "ChatOpenAI,Conversational Retrieval QA Chain,Zep Memory,Qdrant,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Metadata Filter.json
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{
"description": "Upsert multiple files with metadata and filter by it using conversational retrieval QA chain",
"categories": "Text File,PDF File,ChatOpenAI,Conversational Retrieval QA Chain,Pinecone,Langchain",
"badge": "POPULAR",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "A chain that automatically picks an appropriate prompt from multiple prompts",
"categories": "ChatOpenAI,Multi Prompt Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "A chain that automatically picks an appropriate retriever from multiple different vector databases",
"categories": "ChatOpenAI,Multi Retrieval QA Chain,Pinecone,Chroma,Supabase,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Multiple VectorDB.json
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{
"description": "Use the agent to choose between multiple different vector databases, with the ability to use other tools",
"categories": "Buffer Memory,ChatOpenAI,Chain Tool,Retrieval QA Chain,Redis,Faiss,Conversational Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/OpenAI Agent.json
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{
"description": "An agent that uses OpenAI's Function Calling functionality to pick the tool and args to call",
"categories": "Buffer Memory,Custom Tool, SerpAPI,OpenAI Function,Calculator Tool,ChatOpenAI,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/OpenAI Assistant.json
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{
"description": "OpenAI Assistant that has instructions and can leverage models, tools, and knowledge to respond to user queries",
"categories": "Custom Tool, SerpAPI,OpenAI Assistant,Calculator Tool,Langchain",
"framework": "Langchain",
"badge": "NEW",
"nodes": [
{
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{
"description": "Use chat history to rephrase user question, and answer the rephrased question using retrieved docs from vector store",
"categories": "ChatOpenAI,LLM Chain,SingleStore,Langchain",
"badge": "POPULAR",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Prompt Chaining.json
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{
"description": "Use output from a chain as prompt for another chain",
"categories": "Custom Tool,OpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Query Engine.json
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{
"description": "Stateless query engine designed to answer question over your data using LlamaIndex",
"categories": "ChatAnthropic,Compact and Refine,Pinecone,LlamaIndex",
"badge": "NEW",
"framework": "LlamaIndex",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/ReAct Agent.json
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{
"description": "An agent that uses ReAct logic to decide what action to take",
"categories": "Calculator Tool,SerpAPI,ChatOpenAI,MRKL Agent,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Replicate LLM.json
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{
"description": "Use Replicate API that runs Llama 13b v2 model with LLMChain",
"categories": "Replicate,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/SQL DB Chain.json
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{
"description": "Answer questions over a SQL database",
"categories": "ChatOpenAI,Sql Database Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/SQL Prompt.json
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{
"description": "Manually construct prompts to query a SQL database",
"categories": "IfElse Function,Variable Set/Get,Custom JS Function,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"badge": "new",
"nodes": [
{
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{
"description": "Simple chat engine to handle back and forth conversations using LlamaIndex",
"categories": "BufferMemory,AzureChatOpenAI,LlamaIndex",
"framework": "LlamaIndex",
"badge": "NEW",
"nodes": [
{
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{
"description": "Basic example of Conversation Chain with built-in memory - works exactly like ChatGPT",
"categories": "Buffer Memory,ChatOpenAI,Conversation Chain,Langchain",
"framework": "Langchain",
"badge": "POPULAR",
"nodes": [
{
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Simple LLM Chain.json
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{
"description": "Basic example of stateless (no memory) LLM Chain with a Prompt Template and LLM Model",
"categories": "OpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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{
"description": "Return response as a specified JSON structure instead of a string/text",
"categories": "Structured Output Parser,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"badge": "NEW",
"nodes": [
{
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{
"description": "Breaks down query into sub questions for each relevant data source, then combine into final response",
"categories": "Sub Question Query Engine,Sticky Note,QueryEngine Tool,Compact and Refine,ChatOpenAI,Pinecone,LlamaIndex",
"framework": "LlamaIndex",
"badge": "NEW",
"nodes": [
{
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/Translator.json
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{
"description": "Language translation using LLM Chain with a Chat Prompt Template and Chat Model",
"categories": "Chat Prompt Template,ChatOpenAI,LLM Chain,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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3 changes: 3 additions & 0 deletions packages/server/marketplaces/chatflows/Vectara RAG Chain.json
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{
"description": "QA chain for Vectara",
"categories": "Vectara QA Chain,Vectara,Langchain",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/WebBrowser.json
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{
"description": "Conversational Agent with ability to visit a website and extract information",
"categories": "Buffer Memory,Web Browser,ChatOpenAI,Conversational Agent",
"framework": "Langchain",
"nodes": [
{
"width": 300,
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2 changes: 2 additions & 0 deletions packages/server/marketplaces/chatflows/WebPage QnA.json
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{
"description": "Scrape web pages for QnA with long term memory Motorhead and return source documents",
"categories": "HtmlToMarkdown,Cheerio Web Scraper,ChatOpenAI,Redis,Pinecone,Langchain",
"framework": "Langchain",
"badge": "POPULAR",
"nodes": [
{
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{
"name": "add_contact_hubspot",
"framework": "Langchain",
"description": "Add new contact to Hubspot",
"color": "linear-gradient(rgb(85,198,123), rgb(0,230,99))",
"iconSrc": "https://cdn.worldvectorlogo.com/logos/hubspot-1.svg",
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{
"name": "add_airtable",
"framework": "Langchain",
"description": "Add column1, column2 to Airtable",
"color": "linear-gradient(rgb(125,71,222), rgb(128,102,23))",
"iconSrc": "https://raw.githubusercontent.com/gilbarbara/logos/main/logos/airtable.svg",
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{
"name": "todays_date_time",
"framework": "Langchain",
"description": "Useful to get todays day, date and time.",
"color": "linear-gradient(rgb(117,118,129), rgb(230,10,250))",
"iconSrc": "https://raw.githubusercontent.com/gilbarbara/logos/main/logos/javascript.svg",
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1 change: 1 addition & 0 deletions packages/server/marketplaces/tools/Get Stock Mover.json
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{
"name": "get_stock_movers",
"framework": "Langchain",
"description": "Get the stocks that has biggest price/volume moves, e.g. actives, gainers, losers, etc.",
"iconSrc": "https://rapidapi.com/cdn/images?url=https://rapidapi-prod-apis.s3.amazonaws.com/9c/e743343bdd41edad39a3fdffd5b974/016c33699f51603ae6fe4420c439124b.png",
"color": "linear-gradient(rgb(191,202,167), rgb(143,202,246))",
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1 change: 1 addition & 0 deletions packages/server/marketplaces/tools/Make Webhook.json
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{
"name": "make_webhook",
"framework": "Langchain",
"description": "Useful when you need to send message to Discord",
"color": "linear-gradient(rgb(19,94,2), rgb(19,124,59))",
"iconSrc": "https://github.com/FlowiseAI/Flowise/assets/26460777/517fdab2-8a6e-4781-b3c8-fb92cc78aa0b",
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{
"name": "send_message_to_discord_channel",
"framework": "Langchain",
"description": "Send message to Discord channel",
"color": "linear-gradient(rgb(155,190,84), rgb(176,69,245))",
"iconSrc": "https://raw.githubusercontent.com/gilbarbara/logos/main/logos/discord-icon.svg",
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