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feat(annotate): use cached HF token from huggingface-cli login

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Fall back to huggingface_hub.get_token() when HF_TOKEN/HUGGINGFACE_API_KEY
env vars aren't set. That picks up the token cached by
'huggingface-cli login' so users don't need to export it on every shell.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Pepijn
2026-04-28 19:36:24 +02:00
parent cd495a3a9d
commit c06c8d594a
1 changed files with 9 additions and 2 deletions
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src/lerobot/annotations/steerable_pipeline/vlm_client.py
+9 -2
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@@ -283,10 +283,17 @@ def _make_openai_client(config: VlmConfig) -> VlmClient:
if config.use_hf_inference_providers: if config.use_hf_inference_providers:
api_base = "https://router.huggingface.co/v1" api_base = "https://router.huggingface.co/v1"
token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACE_API_KEY") or "" token = os.environ.get("HF_TOKEN") or os.environ.get("HUGGINGFACE_API_KEY") or ""
if not token:
try:
from huggingface_hub import get_token # noqa: PLC0415
token = get_token() or ""
except Exception: # noqa: BLE001
token = ""
if not token: if not token:
raise RuntimeError( raise RuntimeError(
"use_hf_inference_providers=True requires HF_TOKEN (or " "use_hf_inference_providers=True needs an HF token. Either set "
"HUGGINGFACE_API_KEY) in the environment." "HF_TOKEN in the environment, or run `huggingface-cli login` once."
) )
api_key = token api_key = token
auto_serve = False auto_serve = False