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Basic Information

This repository provides the Relevance AI Python SDK, a client library for developers to interact with the Relevance AI platform and manage AI agents, tools, tasks, and knowledge sets. It is intended for use in Python 3 environments and includes instructions for installation via pip and for configuring client credentials using environment variables or direct parameters. The README demonstrates how to instantiate a client, validate credentials, list and retrieve agents and tools, trigger agent tasks and tools, view task progress, and work with knowledge sets. Example workflows include starting agent tasks and inspecting task steps. The SDK exposes methods to manage ongoing tasks and metadata so developers can programmatically orchestrate an AI workforce from their applications.

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App Details

Features
The SDK offers programmatic access to core platform capabilities. Installation is available through pip and the client supports credential configuration via environment variables or direct arguments. Agent features include listing agents, retrieving agent details, triggering tasks, and viewing task steps to monitor progress. Tool features include listing tools, retrieving tool parameter schemas, and triggering tools with parameters. Knowledge management features include listing knowledge sets and retrieving stored data. Task management includes fetching task metadata and deleting completed tasks. The README documents usage examples and basic client setup to help developers integrate these features into applications and scripts.
Use Cases
This SDK helps developers and teams integrate Relevance AI capabilities into their codebase to build, orchestrate, and monitor AI-driven workflows. It enables automation of agent-run tasks and tool invocations, simplifies credential handling for secure access, and provides methods to manage knowledge stores used by agents. By exposing task metadata and step inspection, it supports observability and debugging of agent workflows. The library lets developers programmatically trigger and control agents for use cases such as lead qualification and other automated processes described in examples, reducing the effort to connect application logic to the Relevance AI platform.

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