Skip to main content

Agent Utilities for Pydantic AI Agents

Project description

Agent Utilities - Pydantic AI Utilities

PyPI - Version MCP Server PyPI - Downloads GitHub Repo stars GitHub forks GitHub contributors PyPI - License GitHub

GitHub last commit (by committer) GitHub pull requests GitHub closed pull requests GitHub issues

GitHub top language GitHub language count GitHub repo size GitHub repo file count (file type) PyPI - Wheel PyPI - Implementation

Version: 0.2.29

Overview

Agent Utilities provides a robust foundation for building production-ready Pydantic AI Agents. It simplifies agent creation, adds multi-agent supervisor patterns, and provides essential "operating system" tools for agents, including workspace management, scheduling, and discovery.

Key Features

  • Agent Creation: Streamlined create_agent function that handles MCP servers, skills, and model configuration automatically.
  • Multi-Agent Support: Native support for the supervisor pattern, allowing complex tasks to be delegated to specialized child agents.
  • Agent Server: Built-in FastAPI server (create_agent_server) with SSE support for easy integration into web UIs and A2A networks.
  • Elicitation Support: Built-in flow for handling structured user input requests from MCP servers, seamlessly integrated with the Web UI.
  • Workspace Management: Automated management of agent state through standard markdown files (IDENTITY.md, MEMORY.md, USER.md).
  • A2A Integration: Seamless discovery and communication between agents in a distributed network.
  • Periodic Scheduler: In-memory task scheduler for running background agent jobs.
  • Lightweight & Lazy: Core utilities are lightweight. Heavy dependencies like FastAPI or LlamaIndex are lazy-loaded only when requested via optional extras.

Installation

# Core utilities only
pip install agent-utilities

# With full agent support (recommended)
pip install agent-utilities[agent]

# With MCP server support
pip install agent-utilities[mcp]

# With embedding/vector support
pip install agent-utilities[embeddings]

Quick Start

from agent_utilities import create_agent

# Create a simple agent with workspace tools
agent = create_agent(name="MyAgent")

# Or create a multi-agent supervisor
agent = create_agent(
    name="Supervisor",
    agent_definitions=[{"name": "Researcher", "description": "Search the web"}]
)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agent_utilities-0.2.29.tar.gz (51.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agent_utilities-0.2.29-py3-none-any.whl (56.0 kB view details)

Uploaded Python 3

File details

Details for the file agent_utilities-0.2.29.tar.gz.

File metadata

  • Download URL: agent_utilities-0.2.29.tar.gz
  • Upload date:
  • Size: 51.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for agent_utilities-0.2.29.tar.gz
Algorithm Hash digest
SHA256 c5654c119080280f314d18ad8f77c0a69a335cf57ec250ca399ce7a0f044b1ae
MD5 39ac3826847d984aa4b01a0b8345639c
BLAKE2b-256 4186a5167e5e7e317f31ba1a5a4348add93b2af69bae18933572b7f702e8b171

See more details on using hashes here.

File details

Details for the file agent_utilities-0.2.29-py3-none-any.whl.

File metadata

File hashes

Hashes for agent_utilities-0.2.29-py3-none-any.whl
Algorithm Hash digest
SHA256 69f6e2239533f3b7767237dbe2ac3a07b8ca982c1df85b4a258cdb52ae0f28ee
MD5 a5cc88dd9eb46e3378dd3c3691d1ba91
BLAKE2b-256 ddf518e63c9ccb3f85b9980c85d304d5b5899b4730aba05599c64b4a6e4c6996

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page