---
id: aip-agents-binary
version: "0.6.140"
license: unclear
license_treatment: unclear
maintenance: active
---

# aip-agents-binary — A library for managing agents in Gen AI applications.

License: unclear · Maintenance: active · Downloads: 84.6K/mo

## What it is and what it does

aip-agents-binary is the core local execution library for GL AIP, an ecosystem for building AI agents with LLM backends. It provides a LangGraph-based agent runtime with tool calling, guardrails, human-in-the-loop support, skill loading from GitHub, and A2UI payload emission for structured UI rendering. The library is designed to be used directly for local execution or wrapped by other packages in the ecosystem for seamless local/remote mode switching.

The package integrates deeply with dependencies including langchain, langchain-openai, langgraph, langchain-experimental, and internal GL libraries (gllm-core-binary, gllm-inference-binary, gllm-tools-binary, gllm-datastore-binary, gl-observability-binary, gl-connectors-sdk). It exposes a public integration facade for cross-package consumers, while marking many internal modules as non-contract surfaces subject to change. Skills can be installed from GitHub sources and staged into a configured backend; multiple skill sources are attempted before failing, with a summary error if any fail.

Use it for:

- Build a local AI agent that calls tools and LLMs without deploying to a remote server.
- Integrate guardrails and human-in-the-loop workflows into agent decision-making for safety-critical tasks.
- Load and stage reusable skills from GitHub repositories into a configured backend.
- Emit A2UI payloads to render structured UI elements in agent responses.
- Develop and test agents locally before pushing to a remote platform for production.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

A local execution agent library for building and running AI agents with LLM integration, tool calling, guardrails, and skill management as part of the GL AIP ecosystem.

Yes, with conditions. The package is actively maintained, has low install friction, and fills a clear role in the GL AIP ecosystem for local agent development. However, it depends on an internal registry that may not be accessible without special setup, and its license is undeclared. Verify registry access and license terms before production use.

## Install

pip install aip-agents-binary
uv add aip-agents-binary
poetry add aip-agents-binary

## Installing aip-agents-binary

Before you install: Low install friction with a pure-Python wheel. Active maintenance (released 3 days ago). Requires Python 3.11–3.12 and pulls 29 runtime dependencies including langchain, langgraph, fastapi, and several internal GL binary packages, which may add setup complexity depending on registry access.

License in practice: License status is unclear—no SPDX identifier or raw license text is recorded. Verify the actual license terms before committing to production use.

Quickstart:

pip install aip-agents-binary

from aip_agents.agent.langgraph_react_agent import LangGraphReactAgent

agent = LangGraphReactAgent(
    name="example-agent",
    instruction="Help with tasks.",
)


Requires Python 3.11–3.12. Package is published to an internal registry; ensure your pip/Poetry config includes the registry URL or install via glaip-sdk instead.

Verify before relying:

- Whether the internal registry is accessible without special credentials or VPN setup.
- Whether all 29 runtime dependencies are available in the same registry.
- Actual license terms and any commercial or internal-use restrictions.
- Whether optional extras (google, google-adk, memory, privacy, skills) are documented and stable.

## Package facts

- License: not declared (unclear)
- Python support: capped_below_current
- Install friction: low
- Maintenance: active
- Downloads: 84.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

local AI agent framework, LLM agent library Python, agent tool calling guardrails, gen AI application agents, agentic AI framework, agent-framework, langgraph-based, internal-registry

[View on SkillFed](https://skillfed.io/packages/aip-agents-binary) · [View on PyPI](https://pypi.org/project/aip-agents-binary/)