deploy-hf

meta-pytorch/OpenEnv/.claude/skills/deploy-hf/SKILL.md

Deploy an OpenEnv environment to Hugging Face Spaces. Use when asked to deploy, push to Hugging Face, or update a space.

Skill2.7k starsChanged 6 months ago
  • Installs packages
  • Sends data out

What's in it

  1. Deploy to Hugging Face Spaces
  2. When to Use This Skill
  3. Prerequisites
  4. Instructions
  5. 1. Identify the Environment
  6. 2. Determine the Repository ID
  7. 3. Pre-Deployment Setup
  8. 4. Run the Deployment Command
  9. 5. Verify Deployment
  10. Example Usage
  11. Deploy carlaenv to existing space
  12. Deploy echoenv as private space
  13. Deploy with GPU hardware
  14. Deploy with custom base image
  15. Output Format
  16. Health check
  17. Reset environment
  18. Step action
  19. Troubleshooting
  20. Error: "ModuleNotFoundError: No module named 'openenv'"
  21. Error: "does not appear to be a Python project"
  22. Error: "Directory does not exist"
  23. Error: "Authentication required"
  24. Space build fails
  25. Common Environments
  26. Notes
  27. Related Documentation

Tools it asks for

  • Bash
  • Read
---
name: deploy-hf
description: Deploy an OpenEnv environment to Hugging Face Spaces. Use when asked to deploy, push to Hugging Face, or update a space.
allowed-tools: Bash, Read
---

# Deploy to Hugging Face Spaces

Deploy an OpenEnv environment to Hugging Face Spaces using the OpenEnv CLI.

## When to Use This Skill

- User asks to "deploy to Hugging Face"
- User says "push to Hugging Face Spaces"
- User wants to update an existing space
- After implementing new features that need to be tested in production

## Prerequisites

Before deploying, ensure:
1. The environment has an `openenv.yaml` file
2. The environment has a `server/Dockerfile`
3. You have Hugging Face credentials configured (automatic via huggingface-cli)

## Instructions

### 1. Identify the Environment

Determine which environment to deploy:
- If user specifies: use that environment (e.g., "carla_env", "browser_env")
- If in environment directory: use current directory
- Otherwise: ask the user

### 2. Determine the Repository ID

Repository ID format: `username/space-name`

- If user provides full ID: use it (e.g., "sergiopaniego/carla-env-real-updated")
- If user provides only space name: construct ID with their username
- Check `openenv.yaml` for default repo-id
- Otherwise: ask the user

### 3. Pre-Deployment Setup

**IMPORTANT**: Always run from the project root directory.

Before deploying, ensure OpenEnv is installed:

```bash
cd /path/to/OpenEnv  # Navigate to project root if needed
uv pip install -e .
```

If this fails with "does not appear to be a Python project", you're not in the project root.

### 4. Run the Deployment Command

Execute the deployment:

```bash
PYTHONPATH=src uv run python -m openenv.cli push <environment-dir> --repo-id <username/space-name>
```

**Parameters**:
- `<environment-dir>`: Path to environment (e.g., `envs/carla_env`)
- `--repo-id`: Hugging Face Spaces repository ID (e.g., `sergiopaniego/carla-env-real-updated`)

**Optional flags**:
- `--private`: Deploy as a private space
- `--no-interface`: Disable the web interface (deploy API-only)
- `--base-image <image>`: Override the base Docker image
- `--hardware <hw>` / `-H <hw>`: Request Hugging Face Space hardware (e.g. `t4-medium`, `a10g-small`, `cpu-basic`)

### 5. Verify Deployment

After successful deployment:
1. Note the Space URL returned by the command
2. **Wait for build to complete:**
   - CPU environments: ~5 minutes
   - GPU environments (CARLA): ~30-60 minutes
3. Check the space status at the URL
4. Test with a simple health check once build completes:
   ```bash
   curl https://<username>-<space-name>.hf.space/health
   ```

## Example Usage

### Deploy carla_env to existing space

```bash
PYTHONPATH=src uv run python -m openenv.cli push envs/carla_env --repo-id sergiopaniego/carla-env-real-updated
```

### Deploy echo_env as private space

```bash
PYTHONPATH=src uv run python -m openenv.cli push envs/echo_env --repo-id username/my-echo-env --private
```

### Deploy with GPU hardware

```bash
PYTHONPATH=src uv run python -m openenv.cli push envs/carla_env --repo-id username/carla-env --hardware t4-medium
```

### Deploy with custom base image

```bash
PYTHONPATH=src uv run python -m openenv.cli push envs/browser_env --repo-id username/browser-env --base-image nvidia/cuda:11.8.0-runtime-ubuntu22.04
```

## Output Format

Report deployment status:

```
## Hugging Face Deployment

### Environment
- Environment: <env-name>
- Directory: <path>
- Dockerfile: <path-to-dockerfile>

### Deployment
- Repository ID: <username/space-name>
- Space URL: <https://huggingface.co/spaces/username/space-name>
- Status: ✓ Deployed successfully

### Next Steps
1. Wait for space to build (5 min for CPU, 30-60 min for GPU/CARLA)
2. Visit space URL to check build status
3. Test environment once build completes

### Testing Commands
```bash
# Health check
curl https://<username>-<space-name>.hf.space/health

# Reset environment
curl -X POST https://<username>-<space-name>.hf.space/reset

# Step action
curl -X POST https://<username>-<space-name>.hf.space/step \
  -H "Content-Type: application/json" \
  -d '{"action_type": "observe"}'
```
```

## Troubleshooting

### Error: "ModuleNotFoundError: No module named 'openenv'"

**Solution**: Install OpenEnv first (must be run from project root):
```bash
cd /path/to/OpenEnv  # Navigate to project root
uv pip install -e .
```

### Error: "does not appear to be a Python project"

**Cause**: You're not in the project root directory.

**Solution**: Navigate to the OpenEnv project root where `pyproject.toml` exists:
```bash
cd /Users/sergiopaniegoblanco/Documents/Projects/OpenEnv  # Adjust path
uv pip install -e .
```

### Error: "Directory does not exist"

**Solution**: Ensure you're passing the correct environment directory path:
```bash
# Correct
PYTHONPATH=src uv run python -m openenv.cli push envs/carla_env --repo-id ...

# Incorrect
PYTHONPATH=src uv run python -m openenv.cli push carla_env --repo-id ...
```

### Error: "Authentication required"

**Solution**: Login to Hugging Face CLI first:
```bash
huggingface-cli login
```

### Space build fails

**Solutions**:
1. Check Dockerfile syntax and dependencies
2. Verify hardware requirements (GPU spaces need `--hardware` setting on HF)
3. Check space logs on Hugging Face for detailed errors
4. Ensure `openenv.yaml` is valid

## Common Environments

| Environment | Path | Typical Repo ID | Hardware |
|-------------|------|-----------------|----------|
| carla_env (standalone) | envs/carla_env | username/carla-env-real | GPU (T4/A10G) |
| carla_env (mock) | envs/carla_env | username/carla-env-mock | CPU |
| echo_env | envs/echo_env | username/echo-env | CPU |
| browser_env | envs/browser_env | username/browser-env | CPU |
| tbench2_env | envs/tbench2_env | username/tbench2-env | CPU |

## Notes

- Deployment requires Hugging Face authentication (automatic if `huggingface-cli` is logged in)
- By default, spaces are **public** (use `--private` for private spaces)
- By default, **web interface is enabled** (use `--no-interface` for API-only)
- GPU spaces can request hardware via `--hardware` (e.g. `--hardware t4-medium`)
- Build times vary: CPU (~5 min), GPU with CARLA (~30-60 min)
- The CLI automatically moves Dockerfile to repository root for Hugging Face compatibility

## Related Documentation

- [DEPLOYMENT_GUIDE.md](../../envs/carla_env/DEPLOYMENT_GUIDE.md) - Detailed deployment modes
- [README.md](../../README.md) - OpenEnv overview
- Hugging Face Spaces Docs: https://huggingface.co/docs/hub/spaces

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