rocm_vllm_deployment

# ROCm vLLM Deployment Skill

Production-ready automation for deploying vLLM inference services on AMD ROCm GPUs using Docker Compose.

## Features

- Environment Auto-Check - Detects and repairs missing dependencies
- Model Parameter Detection - Auto-reads config.json for optimal settings
- VRAM Estimation - Calculates memory requirements before deployment
- Secure Token Handling - Never writes tokens to compose files
- **Structured Output** - All logs and test results saved per-model
- **Deployment Reports** - Human-readable summary for each deployment
- Health Verification - Automated health checks and functional tests
- Troubleshooting Guide - Common issues and solutions

## Environment Prerequisites

**Recommended (for production):** Add to `~/.bash_profile`:

```bash
# HuggingFace authentication token (required for gated models)
export HF_TOKEN="hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"

# Model cache directory (optional)
export HF_HOME="$HOME/models"

# Apply changes
source ~/.bash_profile
```

**Not required for testing:** The skill will proceed without these set:
- **HF_TOKEN**: Optional — public models work without it; gated models fail at download with clear error
- **HF_HOME**: Optional — defaults to `/root/.cache/huggingface/hub`

### Environment Variable Detection

**Priority Order:**
1. **Explicit parameter** (highest) — Provided in task/request (e.g., `hf_token: "xxx"`)
2. **Environment variable** — Already set in shell or from parent process
3. **~/.bash_profile** — Source to load variables
4. **Default value** (lowest) — HF_HOME defaults to `/root/.cache/huggingface/hub`

| Variable | Required | If Missing |
|----------|----------|------------|
| `HF_TOKEN` | **Conditional** | Continue without token (public models work; gated models fail at download with clear error) |
| `HF_HOME` | No | **Warning + Default** — Use `/root/.cache/huggingface/hub` |

**Philosophy:** Fail fast for configuration errors, fail at download time for authentication errors.

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