Metadata-Version: 2.4
Name: agent-engine-cli
Version: 0.1.3
Summary: Command-line interface for managing Google Cloud Vertex AI Agent Engine deployments
Project-URL: Homepage, https://github.com/mmontan/agent-engine-cli
Project-URL: Bug Tracker, https://github.com/mmontan/agent-engine-cli/issues
Author: Mirko Montanari
License-Expression: MIT
License-File: LICENSE
Keywords: agent,agent-engine,agents,ai,automation,cli,gcp,google-cloud,llm,vertex,vertex-ai
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.10
Requires-Dist: google-cloud-aiplatform>=1.133.0
Requires-Dist: requests>=2.31.0
Requires-Dist: typer>=0.9.0
Description-Content-Type: text/markdown

# Agent Engine CLI

A command-line interface to manage Agent Engine.

## Installation with uv

This project is set up to work seamlessly with `uv`.

1.  **Install uv** (if you haven't already):
    ```bash
    curl -LsSf https://astral.sh/uv/install.sh | sh
    ```

2.  **Create a virtual environment and install dependencies**:
    ```bash
    uv venv
    source .venv/bin/activate
    uv pip install -e .
    ```

3.  **Run the CLI**:
    ```bash
    ae --help
    ```

## Running Without Installation

You can run the CLI directly without installing it:

```bash
# Using uv (recommended)
uv run python -m agent_engine_cli.main --help

# Or with plain Python (after installing dependencies)
python -m agent_engine_cli.main --help
```

Example commands:
```bash
uv run python -m agent_engine_cli.main list -p PROJECT_ID -l us-central1
uv run python -m agent_engine_cli.main get AGENT_ID -p PROJECT_ID -l us-central1
```

## Chat with an Agent

Start an interactive chat session with a deployed agent:

```bash
# Basic usage
ae chat AGENT_ID -p PROJECT_ID -l us-central1

# With custom user ID
ae chat AGENT_ID -p PROJECT_ID -l us-central1 --user my-user-id

# With debug logging enabled
ae chat AGENT_ID -p PROJECT_ID -l us-central1 --debug
```

## Development

To run tests:

```bash
uv pip install -e ".[dev]" # or just use the dev-dependencies if using a uv-managed lockfile workflow
# If using pure uv sync:
uv sync
uv run pytest
```
