Strands Compose Chat

A ready-to-run web chat application for agents built with strands-compose.

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Overview

Strands Compose lets you describe an agent system in a single YAML file, and Strands Compose Agentcore runs that system on AWS Bedrock AgentCore Runtime.

Strands Compose Chat is the front door: a complete web application where people sign in, open a conversation, and chat with the agents you have built. It handles everything around them - user accounts, conversations, history, access control, and usage tracking.

Focus on building agents, and this app makes them accessible to your users.

Where it fits in the ecosystem:

Chat UI for any strands-compose agent

Admin Panel - manage access, users and resources

https://github.com/user-attachments/assets/4ecafdce-16e9-488b-b389-71be92d23aa3

What's included

The application comes complete — there is nothing to assemble:

Who it's for

• Freelancers and small teams who have built an agent and need to put it in front of clients or colleagues quickly, with a polished interface and proper sign-in.
• Organisations that want an internal AI assistant or department-specific agents, gated behind company SSO, with usage and cost visibility for budgeting.
• Anyone delivering an agent as a product or internal service who would rather configure a chat app than build and maintain one.

Getting started

The application is published on PyPI as strands-compose-chat and includes the web interface bundled in. Installing it gives you a command-line tool available as strands-compose-chat or its short alias scc.

pip install strands-compose-chat

A minimal local run:

scc migrate     # create the database
scc serve       # start the web server on http://127.0.0.1:8000

Two worked setups are in the examples directory:

• 01-local-dev — run on your own machine with a local database. The fastest way to try the app.
• 02-docker — a production-like stack (the app plus a PostgreSQL database) with Docker Compose. Recommended for production, and the basis for deploying to orchestrators such as ECS or Kubernetes.

Each example has step-by-step instructions and a configuration template.

Technical overview

The intent here is a brief map, not a deep reference — detailed documentation lives in separate documents.

Architecture.

A single deployable application made of two parts: a Python backend and a web frontend that ships bundled inside it. The backend exposes the API and serves the interface; the frontend is what users see in the browser. The backend talks to your agents only through the strands-compose SDK, so anything agent-related stays consistent with the rest of the ecosystem.

Tech stack.

Built on a modern, high-performance stack selected for streaming and multi-tenant workloads. The async backend handles concurrent SSE streams without blocking, the database layer uses async SQLAlchemy 2.0 with eager-loaded relationships and parameterised queries throughout, and the frontend delivers a responsive interface with real-time updates via an event-driven store.

Security.

Authentication, authorisation, and transport security are implemented to production standards with no shortcuts. Every endpoint is gated, every credential is hashed or redacted, and production mode enforces a strict baseline at startup — refusing misconfiguration rather than running with it silently.