Retriever TavilyWebSearch

Retriever TavilyWebSearch

Certified

Retrieve web results with Tavily

Uses Tavily Search to fetch live web context for RAG. Requires API key; maxResults caps returned snippets and defaults to 3. Requests count against Tavily quotas.

yaml
type: io.kestra.plugin.ai.retriever.TavilyWebSearch

Chat with your data using Retrieval Augmented Generation (RAG) and a WebSearch content retriever. The Chat with RAG retrieves contents from a WebSearch client and provides a response grounded in data rather than hallucinating.

yaml
id: rag
namespace: company.ai

tasks:
  - id: chat_with_rag_and_websearch_content_retriever
    type: io.kestra.plugin.ai.rag.ChatCompletion
    chatProvider:
      type: io.kestra.plugin.ai.provider.GoogleGemini
      modelName: gemini-3.5-flash-lite
      apiKey: "{{ secret('GEMINI_API_KEY') }}"
    contentRetrievers:
      - type: io.kestra.plugin.ai.retriever.TavilyWebSearch
        apiKey: "{{ secret('TAVILY_API_KEY') }}"
    prompt: What is the latest release of Kestra?
Installation

Our standard Docker images already include this plugin. If you use a -slim image or another setup, install it with the following command: 

kestractl plugins get io.kestra.plugin:plugin-ai --compatible-for $KESTRA_VERSION

For kestractl, use your Kestra version with --compatible-for, or specify an exact plugin version.

For Kestra CLI, replace LATEST with a specific version or version range to pin the plugin version.

Properties

API Key

Tavily API key used to authenticate search requests. Store it as a Kestra secret rather than inline. No default: this property is required.

Default3

Maximum results

Number of search results retrieved for each query. Defaults to 3.

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