AWS Generative AI Toolkit - AI SDKs and Libraries Tool

Overview

The AWS Generative AI Toolkit is an open-source Python library for building, testing, and operating LLM-based agents that use models accessible via the Amazon Bedrock Converse API. It emphasizes production observability and continuous evaluation: every agent action (LLM call, tool invocation, subagent run) is traced and can be emitted to OpenTelemetry-compatible backends such as AWS X-Ray or persisted for later analysis. The toolkit supports streaming responses, conversation history backends (in-memory, SQLite, DynamoDB), and simple registration of Python functions as callable tools for agents. Beyond runtime features, the toolkit provides a developer-oriented testing and evaluation stack: deterministic Bedrock mocks for unit tests, a Case/Expect DSL to express repeatable conversations and assertions, built-in evaluation metrics (latency, token usage, cost, cosine similarity, conciseness), and a lightweight web UI to inspect traces and evaluation results. The project is oriented toward deployments on AWS (Lambda, ECS, EKS) and integrates metric publishing to CloudWatch, making it suitable for teams who want to operationalize agent behavior and detect regressions in production. The project is documented, includes sample notebooks and examples, and is released under Apache-2.0. ([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

According to the GitHub repository, the project is maintained by awslabs and shows 43 stars and 13 forks, with an active commit history and 165 commits in the default branch. Recent releases include v0.23.0 (released 12 Nov) which added multi-line tool parameter descriptions and parallel subagent invocations, indicating ongoing development and feature additions. The repository currently shows a small core contributor base and a low public issue count (0 open issues at the time of this check), suggesting a relatively small but focused community around the toolkit. Full repository details and the release notes are available on the project GitHub. ([github.com](https://github.com/awslabs/generative-ai-toolkit))

Installation

Install via pip:

pip install "generative-ai-toolkit[all]"

pip install "generative-ai-toolkit[run-agent]"

pip install generative-ai-toolkit

Key Features

• OpenTelemetry-compatible tracing for LLM calls, tool invocations, and subagent executions.
• Built-in evaluation metrics (cost, latency, token usage, cosine similarity) with CloudWatch export.
• BedrockConverseAgent supporting streaming responses and simple Python tool registration.
• Deterministic Bedrock mock and Case/Expect test DSL for repeatable unit and integration tests.
• Multi-agent support with subcontexts, parallel subagent invocations, and a web UI for debugging.

Community

The toolkit is an AWS Labs open-source project with modest but steady community activity: 43 stars, 13 forks, and ongoing releases (v0.23.0). Documentation, sample notebooks, and an associated arXiv paper describe the design and goals, but public issue activity is low, indicating a smaller user base or enterprise-focused usage. Contributors and PR activity exist but are limited, so users should expect good AWS-aligned integration and patterns, while community support channels are primarily GitHub and related AWS documentation. ([github.com](https://github.com/awslabs/generative-ai-toolkit))

Key Information

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