FlowiseAI
English
English
  • Introduction
  • Get Started
  • Contribution Guide
    • Building Node
  • API Reference
    • Assistants
    • Attachments
    • Chat Message
    • Chatflows
    • Document Store
    • Feedback
    • Leads
    • Ping
    • Prediction
    • Tools
    • Upsert History
    • Variables
    • Vector Upsert
  • Using Flowise
    • Agentflow V2
    • Agentflow V1 (Deprecating)
      • Multi-Agents
      • Sequential Agents
        • Video Tutorials
    • API
    • Analytic
      • Arize
      • Langfuse
      • Lunary
      • Opik
      • Phoenix
    • Document Stores
    • Embed
    • Monitoring
    • Streaming
    • Uploads
    • Variables
    • Workspaces
    • Evaluations
  • Configuration
    • Auth
      • App Level
      • Chatflow Level
    • Databases
    • Deployment
      • AWS
      • Azure
      • Alibaba Cloud
      • Digital Ocean
      • Elestio
      • GCP
      • Hugging Face
      • Kubernetes using Helm
      • Railway
      • Render
      • Replit
      • RepoCloud
      • Sealos
      • Zeabur
    • Environment Variables
    • Rate Limit
    • Running Flowise behind company proxy
    • SSO
    • Running Flowise using Queue
    • Running in Production
  • Integrations
    • LangChain
      • Agents
        • Airtable Agent
        • AutoGPT
        • BabyAGI
        • CSV Agent
        • Conversational Agent
        • Conversational Retrieval Agent
        • MistralAI Tool Agent
        • OpenAI Assistant
          • Threads
        • OpenAI Function Agent
        • OpenAI Tool Agent
        • ReAct Agent Chat
        • ReAct Agent LLM
        • Tool Agent
        • XML Agent
      • Cache
        • InMemory Cache
        • InMemory Embedding Cache
        • Momento Cache
        • Redis Cache
        • Redis Embeddings Cache
        • Upstash Redis Cache
      • Chains
        • GET API Chain
        • OpenAPI Chain
        • POST API Chain
        • Conversation Chain
        • Conversational Retrieval QA Chain
        • LLM Chain
        • Multi Prompt Chain
        • Multi Retrieval QA Chain
        • Retrieval QA Chain
        • Sql Database Chain
        • Vectara QA Chain
        • VectorDB QA Chain
      • Chat Models
        • AWS ChatBedrock
        • Azure ChatOpenAI
        • NVIDIA NIM
        • ChatAnthropic
        • ChatCohere
        • Chat Fireworks
        • ChatGoogleGenerativeAI
        • Google VertexAI
        • ChatHuggingFace
        • ChatLocalAI
        • ChatMistralAI
        • IBM Watsonx
        • ChatOllama
        • ChatOpenAI
        • ChatTogetherAI
        • GroqChat
      • Document Loaders
        • API Loader
        • Airtable
        • Apify Website Content Crawler
        • Cheerio Web Scraper
        • Confluence
        • Csv File
        • Custom Document Loader
        • Document Store
        • Docx File
        • File Loader
        • Figma
        • FireCrawl
        • Folder with Files
        • GitBook
        • Github
        • Json File
        • Json Lines File
        • Notion Database
        • Notion Folder
        • Notion Page
        • PDF Files
        • Plain Text
        • Playwright Web Scraper
        • Puppeteer Web Scraper
        • S3 File Loader
        • SearchApi For Web Search
        • SerpApi For Web Search
        • Spider Web Scraper/Crawler
        • Text File
        • Unstructured File Loader
        • Unstructured Folder Loader
        • VectorStore To Document
      • Embeddings
        • AWS Bedrock Embeddings
        • Azure OpenAI Embeddings
        • Cohere Embeddings
        • Google GenerativeAI Embeddings
        • Google VertexAI Embeddings
        • HuggingFace Inference Embeddings
        • LocalAI Embeddings
        • MistralAI Embeddings
        • Ollama Embeddings
        • OpenAI Embeddings
        • OpenAI Embeddings Custom
        • TogetherAI Embedding
        • VoyageAI Embeddings
      • LLMs
        • AWS Bedrock
        • Azure OpenAI
        • Cohere
        • GoogleVertex AI
        • HuggingFace Inference
        • Ollama
        • OpenAI
        • Replicate
      • Memory
        • Buffer Memory
        • Buffer Window Memory
        • Conversation Summary Memory
        • Conversation Summary Buffer Memory
        • DynamoDB Chat Memory
        • MongoDB Atlas Chat Memory
        • Redis-Backed Chat Memory
        • Upstash Redis-Backed Chat Memory
        • Zep Memory
      • Moderation
        • OpenAI Moderation
        • Simple Prompt Moderation
      • Output Parsers
        • CSV Output Parser
        • Custom List Output Parser
        • Structured Output Parser
        • Advanced Structured Output Parser
      • Prompts
        • Chat Prompt Template
        • Few Shot Prompt Template
        • Prompt Template
      • Record Managers
      • Retrievers
        • Extract Metadata Retriever
        • Custom Retriever
        • Cohere Rerank Retriever
        • Embeddings Filter Retriever
        • HyDE Retriever
        • LLM Filter Retriever
        • Multi Query Retriever
        • Prompt Retriever
        • Reciprocal Rank Fusion Retriever
        • Similarity Score Threshold Retriever
        • Vector Store Retriever
        • Voyage AI Rerank Retriever
      • Text Splitters
        • Character Text Splitter
        • Code Text Splitter
        • Html-To-Markdown Text Splitter
        • Markdown Text Splitter
        • Recursive Character Text Splitter
        • Token Text Splitter
      • Tools
        • BraveSearch API
        • Calculator
        • Chain Tool
        • Chatflow Tool
        • Custom Tool
        • Exa Search
        • Google Custom Search
        • OpenAPI Toolkit
        • Code Interpreter by E2B
        • Read File
        • Request Get
        • Request Post
        • Retriever Tool
        • SearchApi
        • SearXNG
        • Serp API
        • Serper
        • Tavily
        • Web Browser
        • Write File
      • Vector Stores
        • AstraDB
        • Chroma
        • Couchbase
        • Elastic
        • Faiss
        • In-Memory Vector Store
        • Milvus
        • MongoDB Atlas
        • OpenSearch
        • Pinecone
        • Postgres
        • Qdrant
        • Redis
        • SingleStore
        • Supabase
        • Upstash Vector
        • Vectara
        • Weaviate
        • Zep Collection - Open Source
        • Zep Collection - Cloud
    • LiteLLM Proxy
    • LlamaIndex
      • Agents
        • OpenAI Tool Agent
        • Anthropic Tool Agent
      • Chat Models
        • AzureChatOpenAI
        • ChatAnthropic
        • ChatMistral
        • ChatOllama
        • ChatOpenAI
        • ChatTogetherAI
        • ChatGroq
      • Embeddings
        • Azure OpenAI Embeddings
        • OpenAI Embedding
      • Engine
        • Query Engine
        • Simple Chat Engine
        • Context Chat Engine
        • Sub-Question Query Engine
      • Response Synthesizer
        • Refine
        • Compact And Refine
        • Simple Response Builder
        • Tree Summarize
      • Tools
        • Query Engine Tool
      • Vector Stores
        • Pinecone
        • SimpleStore
    • Utilities
      • Custom JS Function
      • Set/Get Variable
      • If Else
      • Sticky Note
    • External Integrations
      • Zapier Zaps
  • Migration Guide
    • Cloud Migration
    • v1.3.0 Migration Guide
    • v1.4.3 Migration Guide
    • v2.1.4 Migration Guide
  • Use Cases
    • Calling Children Flows
    • Calling Webhook
    • Interacting with API
    • Multiple Documents QnA
    • SQL QnA
    • Upserting Data
    • Web Scrape QnA
  • Flowise
    • Flowise GitHub
    • Flowise Cloud
Powered by GitBook
On this page
  • Quickstart Tutorial
  • Prerequisite
  • Setup
  • Vectara Query Parameters
  • Resources
Edit on GitHub
  1. Integrations
  2. LangChain
  3. Vector Stores

Vectara

PreviousUpstash VectorNextWeaviate

Last updated 3 months ago

Quickstart Tutorial

Prerequisite

  1. Click Create Corpus

Name the corpus to be created and click Create Corpus then wait for the corpus to finish setting up.

Setup

  1. Click on the "Access Control" tab in the corpus view

  1. Click on the "Create API Key" button, choose a name for the API key and pick the QueryService & IndexService option

  1. Click Create to create the API key

  2. Get your Corpus ID, API Key, and Customer ID by clicking the down-arrow under "copy" for your new API key:

  1. Back to Flowise canvas, and create your chatflow. Click Create New from the Credentials dropdown ane enter your Vectara credentials.

  1. Enjoy!

Vectara Query Parameters

For finer control over the Vectara query parameters, click on "Additional Parameters" and then you can update the following parameters from their default:

  • "Sentences before" and "Sentences after": these control how many sentences before/after the matching text are returned as results from the Vectara retrieval engine

  • Top-K: how many results to return from Vectara for the query

Resources

Register an account for

Metadata Filter: Vectara supports meta-data filtering. To use , ensure that metadata fields you want to filter by are defined in your Vectara corpus.

Lambda: defines the behavior of in Vectara

MMR-K: number of results to use for (max marginal relvance)

Vectara
filtering
hybrid search
MMR
LangChain JS Vectara Blog Post
5 Reasons to Use Vectara's Langchain Integration Blog Post
Max Marginal Relevance in Vectara
Vectara Boomerang embedding model Blog Post
Detecting Hallucination with Vectara's HHEM