semvec/pypi-packages huggingface dataset:
llamactl 0.4.12
A command-line interface for managing LlamaDeploy projects and deployments
License: MIT
Requires Python: <4,>=3.10

# llamactl


A command-line interface for managing LlamaDeploy projects and deployments.

For an end-to-end introduction, see [Getting started with LlamaAgents](https://developers.llamaindex.ai/python/cloud/llamaagents/getting-started).

## Installation

Install from PyPI:

```bash
pip install llamactl
```

Or using uv:

```bash
uv add llamactl
```

## Quick Start

1. **Configure your profile**: Set up connection to your LlamaDeploy control plane
   ```bash
   llamactl profile configure
   ```

2. **Check health**: Verify connection to the control plane
   ```bash
   llamactl health
   ```

3. **Create a project**: Initialize a new deployment project
   ```bash
   llamactl project create my-project
   ```

4. **Deploy**: Deploy your project to the control plane
   ```bash
   llamactl deployment create my-deployment --project-name my-project
   ```

## Commands

### Profile Management
- `llamactl profile configure` - Configure connection to control plane
- `llamactl profile show` - Show current profile configuration
- `llamactl profile list` - List all configured profiles

### Project Management
- `llamactl project create <name>` - Create a new project
- `llamactl project list` - List all projects
- `llamactl project show <name>` - Show project details
- `llamactl project delete <name>` - Delete a project

### Deployment Management
- `llamactl deployment create <name>` - Create a new deployment
- `llamactl deployment list` - List all deployments
- `llamactl deployment show <name>` - Show deployment details
- `llamactl deployment delete <name>` - Delete a deployment
- `llamactl deployment logs <name>` - View deployment logs

### Health & Status
- `llamactl health` - Check control plane health
- `llamactl serve` - Start local development server

## Configuration

llamactl stores configuration in your home directory at `~/.llamactl/`.

### Profile Configuration
Profiles allow you to manage multiple control plane connections:

```bash
# Configure default profile
llamactl profile configure

# Configure named profile
llamactl profile configure --profile production

# Use specific profile for commands
llamactl --profile production deployment list
```

## Development

This CLI is part of the LlamaDeploy ecosystem. For development setup:

1. Clone the repository
2. Install dependencies: `uv sync`
3. Run tests: `uv run pytest`

## Requirements

- Python 3.12+
- Access to a LlamaDeploy control plane

## License

This project is licensed under the MIT License.
llama-deploy-core 0.4.12
Core models and schemas for LlamaDeploy
License: MIT
Requires Python: <4,>=3.10

# llama-deploy-core

Core models and schemas for LlamaDeploy.

For an end-to-end introduction, see [Getting started with LlamaAgents](https://developers.llamaindex.ai/python/cloud/llamaagents/getting-started).
llama-deploy-appserver 0.4.12
Application server components for LlamaDeploy
License: MIT
Requires Python: <4,>=3.10

# llama-deploy-appserver

Application server components for LlamaDeploy.

For an end-to-end introduction, see [Getting started with LlamaAgents](https://developers.llamaindex.ai/python/cloud/llamaagents/getting-started).
e2b 2.13.3
E2B SDK that give agents cloud environments
License: MIT
Requires Python: <4.0,>=3.10

<p align="center">
  <img width="100" src="https://raw.githubusercontent.com/e2b-dev/E2B/refs/heads/main/readme-assets/logo-circle.png" alt="e2b logo">
</p>

<h4 align="center">
  <a href="https://pypi.org/project/e2b/">
    <img alt="Last 1 month downloads for the Python SDK" loading="lazy" decoding="async" style="color:transparent;width:170px;height:18px" src="https://static.pepy.tech/personalized-badge/e2b?period=monthly&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=PyPi%20Monthly%20Downloads">
  </a>  
</h4>


## What is E2B?
[E2B](https://www.e2b.dev/) is an open-source infrastructure that allows you to run AI-generated code in secure isolated sandboxes in the cloud. To start and control sandboxes, use our [JavaScript SDK](https://www.npmjs.com/package/@e2b/code-interpreter) or [Python SDK](https://pypi.org/project/e2b_code_interpreter).

## Run your first Sandbox

### 1. Install SDK

```
pip install e2b-code-interpreter
```

### 2. Get your E2B API key
1. Sign up to E2B [here](https://e2b.dev).
2. Get your API key [here](https://e2b.dev/dashboard?tab=keys).
3. Set environment variable with your API key
```
E2B_API_KEY=e2b_***
```     

### 3. Execute code with code interpreter inside Sandbox

```py
from e2b_code_interpreter import Sandbox

with Sandbox.create() as sandbox:
    sandbox.run_code("x = 1")
    execution = sandbox.run_code("x+=1; x")
    print(execution.text)  # outputs 2
```

### 4. Check docs
Visit [E2B documentation](https://e2b.dev/docs).

### 5. E2B cookbook
Visit our [Cookbook](https://github.com/e2b-dev/e2b-cookbook/tree/main) to get inspired by examples with different LLMs and AI frameworks.