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agent builder

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Multi-Agent Platforms & Frameworks
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Basic Information

Strands Agent Builder is an interactive, model-driven toolkit for building, testing, and extending custom AI agents and tools from the terminal. The repository provides a CLI called strands, a Python package installable via pipx, sample commands for creating tools and agents, and integration points for knowledge bases and model providers. It is designed to let developers compose focused agents, hot-reload tools during development, and iterate on agent behavior and toolsets. The project includes documentation, a set of built-in tools, environment variable configuration, and examples for loading and extending tools from persistent knowledge bases. The README explains quick start usage, environment variables, model configuration defaults, and instructions for plugging in custom model providers under a local .models directory. The repo is intended for interactive agent development rather than a single monolithic application.

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Stars
225
App URL
https://github.com/strands-agents/agent-builder
Github Repository
https://github.com/strands-agents/agent-builder/blob/main/README.md

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App Details

Features
The README documents a wide set of built-in tools and capabilities plus CLI convenience. Key features include instant hot-reloading for custom tools, CLI-driven interactive development with rich console output, nested agent creation and tool delegation, and support for coordinating multiple agents via a swarm feature. Integrated tools cover shell and Python REPL execution (with platform caveats), HTTP requests, image generation and reading, scheduling with cron, environment management, memory persistence, retrieval from knowledge bases, Slack integration, speech output, and workflow orchestration. The project exposes optimized model configuration defaults for large models, the ability to choose different model providers including bedrock and ollama, and hooks for custom providers. Environment variables allow customization of tokens, thinking budgets, system prompts, tool caching, and default knowledge base.
Use Cases
This repository helps developers rapidly prototype and iterate on specialized AI agents and toolchains from a familiar terminal workflow. It simplifies creating, testing, and extending tools that agents can call, and it provides persistence via Amazon Bedrock Knowledge Bases so tools and configurations can be stored, retrieved, and improved over time. The strands CLI and integrated tools reduce setup friction for common agent tasks like web requests, file editing, math, scheduling, and multimedia generation. Model configuration defaults and support for multiple model providers let teams run high-capacity models with sensible timeouts and retry behavior while still allowing customization. Nested agents, swarms, and workflow orchestration support building more complex multi-agent behaviors and delegating responsibilities across tools and sub-agents.

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