Generative AI Toolkit - AI SDKs and Libraries Tool

Overview

Generative AI Toolkit is an open-source Python library from AWS Labs that helps developers build, test, evaluate, and operate LLM-backed agents with production-grade observability and automated evaluation. The toolkit provides a lightweight agent implementation (BedrockConverseAgent) that integrates with the Amazon Bedrock Converse API, supports streaming responses, tool registration, multi-agent supervision, and local development without a full AWS deployment. The library emphasizes traces (OpenTelemetry-compatible) and metrics as first-class artifacts: traces capture LLM prompts, tool calls, token usage and metadata, which are used to compute evaluation metrics such as latency, cost, cosine similarity and conciseness. ([github.com](https://github.com/awslabs/generative-ai-toolkit)) The project includes helpers for mocking the Bedrock Converse API (for deterministic unit tests), an interactive local web UI for conversation and trace debugging, built-in tracers (DynamoDB and AWS X-Ray), and utilities to emit CloudWatch custom metrics for continuous monitoring in production. The toolkit is described in an accompanying research paper that outlines its lifecycle approach to improving LLM-based application quality. Releases and packaging are available on PyPI (latest release 0.23.0 at time of writing). ([github.com](https://github.com/awslabs/generative-ai-toolkit))

GitHub Statistics

• Stars: 43
• Forks: 13
• Contributors: 8
• License: Apache-2.0
• Primary Language: Python
• Last Updated: 2025-11-12T12:22:22Z
• Latest Release: v0.23.0

Repository activity shows a modest but active open-source project: the GitHub repository lists 43 stars and 13 forks, with around 165 commits and a small number of open PRs (3) and no open issues at the time of inspection. The project is Apache-2.0 licensed and packaged on PyPI (latest release 0.23.0 published November 12, 2025), indicating ongoing maintenance and releases. The PyPI project page also lists named maintainers and dependency extras (run-agent, evaluate, all). Overall community signals point to a focused engineering project maintained by AWS Labs with a small contributor base and targeted user audience. ([github.com](https://github.com/awslabs/generative-ai-toolkit))

Installation

Install via pip:

pip install "generative-ai-toolkit[all]"  # installs optional extras (UI, evaluate, run-agent).

pip install generative-ai-toolkit==0.23.0  # install the release published Nov 12, 2025.

pip install generative-ai-toolkit  # minimal installation without extras.

Key Features

• BedrockConverseAgent implementation for Amazon Bedrock model access and streaming responses.
• First-class traces capturing prompts, model outputs, tool calls, token usage, and metadata.
• OpenTelemetry-compatible tracers with out-of-the-box DynamoDB and AWS X-Ray support.
• Repeatable test Cases, Expect assertions, and Bedrock API mocks for deterministic unit tests.
• Built-in evaluation metrics (latency, cost, cosine similarity, conciseness) and custom metric hooks.
• Local web UI to inspect conversations, traces, and evaluation results (runs at localhost:7860).
• Support for multi-agent setups and registering functions/tools as callable agent tools.

Community

Community engagement is focused and engineering-oriented: the repository (43 stars, 13 forks) is maintained by AWS Labs with regular releases (PyPI 0.23.0, Nov 12, 2025). The project is described in a December 2024 research paper and has been mentioned in developer posts and write-ups, but public third‑party user reviews are limited. The codebase is Apache-2.0 licensed and suitable for teams adopting Amazon Bedrock and AWS observability patterns. ([github.com](https://github.com/awslabs/generative-ai-toolkit))

Key Information

• Category: SDKs and Libraries
• Type: AI SDKs and Libraries Tool