FunClip v2.2.0: Long-Form Speaker-Aware Video Clipping with MOSS

August 31, 2026 · FunClip Release

FunClip local video, subtitle recognition, and intelligent clipping interface

FunClip v2.2.0 adds an opt-in MOSS path: send long audio to a vLLM service, normalize text, speaker identities, and time ranges through FunASR, then generate SRT or clip by spkS01, spkS02, and later speaker IDs.

MOSS-Transcribe-Diarize is a third-party model maintained by OpenMOSS, not a FunASR or FunClip-owned checkpoint. The integration pins OpenMOSS-Team/MOSS-Transcribe-Diarize revision e8681d68e7042738ffca8ac8212bc8fcb1131ab8 and keeps ownership and support boundaries explicit.

Data path

Stage	Responsibility
vLLM	Loads the pinned MOSS revision and serves timestamped speaker markup through `/v1/audio/transcriptions`.
FunASR 1.4.9+	Parses the response into common `text`, `timestamp`, and `sentence_info` fields.
FunClip 2.2.0	Renders speaker-labeled SRT and sends selected speaker ranges into the existing audio/video clipping workflow.

1. Start vLLM at the pinned revision

python -m venv .venv-moss
. .venv-moss/bin/activate
pip install -U vllm

vllm serve OpenMOSS-Team/MOSS-Transcribe-Diarize \
  --revision e8681d68e7042738ffca8ac8212bc8fcb1131ab8 \
  --served-model-name moss-transcribe-diarize \
  --trust-remote-code --host 127.0.0.1 --port 8898

Verify the service with real audio before starting FunClip. The tested contract uses response_format=json:

curl -fsS http://127.0.0.1:8898/v1/audio/transcriptions \
  -F file=@sample.wav \
  -F model=moss-transcribe-diarize \
  -F response_format=json \
  -F max_completion_tokens=8192

2. Start FunClip

python -m pip install -U -r requirements.txt
python funclip/launch.py \
  --model moss \
  --moss-backend vllm \
  --moss-base-url http://127.0.0.1:8898/v1 \
  --moss-max-tokens 8192

For an authenticated remote service, put the bearer credential in the MOSS_API_KEY environment variable. FunClip does not require putting the token in the command line or repository.

Capabilities and boundaries

Long-form ASR, speaker identity, SRT, and speaker-based clipping are supported, including valid speaker turns shorter than one second.
MOSS provides segment-level timestamps. Use it for whole-segment or speaker clipping; keep Paraformer for precise arbitrary character-level text clipping.
Global speaker identity depends on continuous context, so the MOSS path attaches no external VAD or speaker model that would pre-chunk the recording.
If the final segment is missing its ending timestamp after token exhaustion, FunClip raises an explicit truncation error and asks for a higher --moss-max-tokens value instead of silently dropping the tail.

See the bilingual MOSS production guide for health checks, runtime choices, and capacity boundaries.

Download and verify v2.2.0

FunClip-2.2.0.tar.gz
SHA256 994c5d9cf392b74b36284d526eca8bada1560a3e7825ab7baa9c673a1b4ef216

FunClip-2.2.0.zip
SHA256 4f5a7d33d9ea65467f29b55b15ed5be18e64de7e57e2f9f36fe51a23b40557e7

Download the archives and SHA256SUMS from the FunClip v2.2.0 release.

Release content resolves to commit c205bf32a8b11226ff5e8acb9a3c7a1f00cd3b06. The repository suite completed with 84 passed and 1 skipped. A live H100 + vLLM two-speaker run returned S01/S02, valid SRT, and the expected S02 clip. This verifies the release path, not every language, audio condition, or production concurrency level.

Run one real two-speaker recording through the production guide, then bring the same service into FunClip.

Open the FunClip v2.2.0 release and downloads