JOSE ANASTACIO ESQUIVEL SALAS
496ce190ef
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| .. | ||
| mcp_client | ||
| memory | ||
| model | ||
| skills | ||
| .gitignore | ||
| README.md | ||
| main.py | ||
| pyproject.toml | ||
| uv.lock | ||
README.md
This is a project generated by the AgentCore CLI!
Layout
The generated application code lives at the agent root directory. At the root, there is a .gitignore file, an
agentcore/ folder which represents the configurations and state associated with this project. Other agentcore
commands like deploy, dev, and invoke rely on the configuration stored here.
Agent Root
The main entrypoint to your app is defined in main.py. Using the AgentCore SDK @app.entrypoint decorator, this
file defines a Starlette ASGI app with the chosen Agent framework SDK running within.
model/load.py instantiates your chosen model provider.
Input Validation
Validate invocation input before forwarding it to Strands. Keep plain prompts typed as strings. If the app accepts a
caller-supplied message history, retain strip_trailing_tool_use(), which normalizes the history tail before
invoking the agent.
Environment Variables
| Variable | Required | Description |
|---|---|---|
LOCAL_DEV |
No | Set to 1 to use .env.local instead of AgentCore Identity |
Developing locally
If installation was successful, a virtual environment is already created with dependencies installed.
Activate the environment with source .venv/bin/activate on macOS/Linux, .venv\Scripts\activate.bat in Windows
Command Prompt, or .\.venv\Scripts\activate.ps1 in Windows PowerShell.
agentcore dev will start a local server on 0.0.0.0:8080.
In a new terminal, you can invoke that server with:
agentcore invoke --dev "What can you do"
Deployment
After providing credentials, agentcore deploy will deploy your project into Amazon Bedrock AgentCore.
Use agentcore invoke to invoke your deployed agent.