v1.4.1

Warning

⚠️ Installing inference in Google Colab? Read this first

Starting with this release, pip install inference in a fresh Google Colab runtime can crash on import inference with RuntimeError: Detected that PyTorch and TorchAudio were compiled with different CUDA versions. Colab preinstalls a torchaudio built for an older CUDA than the torch that dependency resolution installs, and new transformers imports torchaudio when present in env.
Fix: remove the stale torchaudio before importing — it takes one cell:

!pip uninstall -y torchaudio

Run it right before pip install inference and before the first import — then no restart is needed. If you already hit the error, uninstall and restart the runtime (Runtime → Restart session) so the failed import is not cached. If you actually use torchaudio in the same notebook, reinstall a build matching your torch version instead of removing it.

🚀 Added

🤖 SpaceXAI Grok workflow block (Grok 4.6 / 4.5)

The new roboflow_core/spacexai@v1 block brings xAI's Grok vision models into Workflows, with Grok 4.6 as the default and Grok 4.5 selectable. It speaks xAI's OpenAI-compatible Responses API and supports the full VLM task lineup — unconstrained prompting, VQA, OCR, captioning, classification and structured answering — plus object detection using the percent-of-image box_2d contract that won the vlm-exam benchmark for Grok, with vlm_as_detector@v2 shipping the matching model_type="spacexai" parser. (@SkalskiP, #2799).

⚡ Gemini 3.7 Flash in the Google Gemini blocks

Google released Gemini 3.7 Flash on Aug 13 and it is selectable in google_gemini@v3 and google_gemini@v4 the day after, with thinking-level control and native code execution enabled — validated by full-benchmark runs across all six VLM tasks before flipping the switch (@SkalskiP, #2794).

📊 Deeper usage and cache telemetry

Usage rows can now be attributed by model architecture (resource_details.model_type, e.g. rfdetr-seg-nano) and by the input resolution the model actually ran at, bucketed in megapixels — resolved from a process-local cache at model load so the hot path never does a registry lookup (@SolomonLake, #2782). SAM3's visual-segment encoder fast path also gains a bounded Prometheus counter reporting embedding-cache hit / miss / not_attempted outcomes (@hansent, #2779).

🔧 Fixed

• Vision Events sink no longer drops assume-identity headers — the sink built its own request headers instead of going through build_roboflow_api_headers(), so deployments authenticating via ROBOFLOW_API_EXTRA_HEADERS had their event writes silently rejected upstream while the block reported success (@rvirani1, #2774).
• MemoryCache.acquire_lock actually serialises on one key now — a check-then-act race let two callers racing on a missing key each build their own lock and both enter the protected section, and the lock refresh reused Lock.acquire's -1 "block forever" sentinel as a cache expiry, storing the entry one second in the past and poisoning its own cache slot (@adhavan18, #2795).
• WebRTC callback shutdown deadlock removed — WebRTCSession.close() called from on_data/on_error callbacks blocked the session event loop waiting on cleanup scheduled onto that same loop; loop-initiated cleanup is now dispatched to a helper thread without blocking (@voropaevv, #2778).
• TrOCR works under transformers 5.15 — the new transformers force-routes vision-encoder-decoder checkpoints to its generic tokenizer backend, which cannot read the sentencepiece-only serialization Roboflow model packages ship; the TrOCR loader now builds its processor from the tokenizer class declared in the package instead (@PawelPeczek-Roboflow, #2798).
• pip install inference in Google Colab no longer crashes on import — Colab preinstalls a torchaudio whose CUDA build no longer matches the torch that dependency resolution installs, and transformers 5.x imports torchaudio whenever it is present; the Colab verification images drop the stale torchaudio, and Colab users hitting the crash can do the same with pip uninstall -y torchaudio (@PawelPeczek-Roboflow, #2798).
• GPU image dependency resolution fixed for torch 2.6+cu124 builds (@PawelPeczek-Roboflow, #2796).

🚧 Maintenance

🧵 transformers unpinned — one GPU build again

The dependency structure now allows transformers up to the 5.15 line across the repo and inference-models (@PawelPeczek-Roboflow, #2797, #2798). Since transformers 5.15.0 ships the NVIDIA Cosmos 3 Edge model code, the GPU image installs it straight from PyPI and the git-pin override step is gone — which retires the dual GPU build from v1.3.8/v1.3.9: there is no separate -cosmos3 tag anymore, the standard roboflow/roboflow-inference-server-gpu:1.4.1 image runs Cosmos 3 Edge out of the box.

• MQTT Writer sink gets a block namespace — roboflow_enterprise/mqtt_writer_sink@v1 is the primary identifier (it was the only block among 201 without a namespace), and the bare mqtt_writer_sink@v1 stays on as a legacy alias so existing workflows keep working (@shntu, #2783).
• Regression coverage for pipeline stream controls — pause_stream(), mute_stream() and resume_stream() are now exercised across all-sources, matching-source and unknown-source cases (@arubittu, #2790).
• PR-review skill suite updated after the tensor-native Workflows merge (@PawelPeczek-Roboflow, #2791).

🏅 New Contributors

• @arubittu made their first contribution in #2790
• @adhavan18 made their first contribution in #2795

Full Changelog: v1.4.0...v1.4.1