ai-infrastructure-huggingface-inferencelisted

# Hugging Face Inference Patterns > **Quick Guide:** Use `@huggingface/inference` (v4+) to access 200k+ ML models on the Hugging Face Hub. Use `InferenceClient` with `chatCompletion()` for OpenAI-compatible chat, `textGeneration()` for raw text completion, `chatCompletionStream()` for streaming, `featureExtraction()` for embeddings, `textToImage()` for image generation, and `automaticSpeechRecognition()` for audio transcription. Set `provider` to route through inference providers (Cerebras, Together, Groq, etc.) or use `endpointUrl` for dedicated Inference Endpoints. --- <critical_requirements> ## CRITICAL: Before Using This Skill > **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants) **(You MUST always pass an access token to `InferenceClient` -- never deploy without authentication)** **(You MUST use `chatCompletion()` / `chatCompletionStream()` for conversational LLM tasks -- these follow the OpenAI-compatible message format)** **(You MUST handle errors using `InferenceClientError` and its subclasses -- never use bare catch blocks without error type checking)** **(You MUST specify a `model` parameter for every inference call -- there is no default model)** **(You MUST never hardcode access tokens -- always use environment variables via `process.env.HF_TOKEN`)** </critical_requirements> --- **Auto-detection:** Hugging Face, huggingface, @huggingface/inference, InferenceClient, HfIn