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Relevance AI SDK

Relevance AI SDK is a Python library for connecting to Relevance AI projects and interacting with their agents, tools, tasks, and knowledge sets.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Relevance AI SDK — OpenViST project profile in Agent Frameworks.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it when a Python application or utility needs to call and manage resources in a Relevance AI project, rather than when looking for a standalone agent runtime.

Who it is for

  • Python developers integrating Relevance AI project resources into code.
  • Teams building internal utilities to browse project agents and tools or inspect task progress.

Documented uses

  • List and retrieve project agents, then trigger an agent task with a message.
  • Retrieve task steps and metadata, or delete a completed task.
  • List and retrieve tools, inspect a tool's parameter schema, and trigger it with parameters.
  • List knowledge sets and retrieve stored data.
Before you choose

Requirements & limits

The README requires a Relevance AI account and a secret key with Admin permissions for SDK use. The repository is licensed under Apache-2.0.

  • Client configuration requires an API key, region, and project identifier.
  • The examples cover agent task triggering and progress retrieval, as well as tool and knowledge-set operations.
  • A command-line wrapper or task-progress dashboard would need to be built around the SDK; neither is shown as an included interface.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Set up a Python client for a Relevance AI project

Install the SDK and configure a client with project credentials.

Before you start

  • Python 3 environment
  • Relevance AI account
  • Secret key with Admin permissions
  • API key, region, and project identifier

Steps

  1. Install the library with the command below.

    Documented command
    pip install relevanceai

  2. Create an account and generate a secret key with Admin permissions through the SDK Login flow.

  3. Configure the client using the API key, region, and project identifier, either as environment variables or as client arguments.

Expected outcome

A configured Python client for interacting with agents, tools, tasks, and knowledge in the project.

Guide limitations

  • This guide covers client setup; it does not verify successful connection or describe deployment.
Documentation 1 ↗
Source-based practical guide

Trigger an agent task and inspect its progress

Use the Python SDK to start a task with a project agent and retrieve its task steps.

Before you start

  • Python 3 environment with the RelevanceAI library installed
  • Configured client credentials
  • Agent ID for an agent in the project

Steps

  1. Retrieve the agent with client.agents.retrieve_agent(agent_id=...).

  2. Call trigger_task with a message and retain the returned conversation ID.

  3. Pass the conversation ID to view_task_steps to retrieve task progress.

Expected outcome

The SDK returns a task conversation ID and provides a method to retrieve the task steps.

Guide limitations

  • The README demonstrates starting a task and viewing steps; it does not describe a dashboard or guarantee task results.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
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Sources checked
14 October 2026
Original website title
RelevanceAI/relevanceai · Official homepage title · retained in its source language
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