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* feat(config): add model artifact source contract Assisted-by: Codex:GPT-5 [Codex] * feat(downloader): add authenticated raw-byte progress Assisted-by: Codex:GPT-5 [Codex] * feat(huggingface): resolve immutable snapshot manifests Assisted-by: Codex:GPT-5 [Codex] * feat(models): add artifact storage primitives Assisted-by: Codex:GPT-5 [Codex] * feat(models): materialize pinned Hugging Face snapshots Assisted-by: Codex:GPT-5 [Codex] * feat(models): bind managed snapshots at runtime Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): materialize model artifacts during install Assisted-by: Codex:GPT-5 [Codex] * feat(gallery): declare managed Hugging Face artifacts Assisted-by: Codex:GPT-5 [Codex] * feat(models): preload managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * fix(gallery): retain shared artifact caches on delete Assisted-by: Codex:GPT-5 [Codex] * feat(models): report artifact acquisition progress Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load managed models from ModelFile Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): load staged speech model snapshots Assisted-by: Codex:GPT-5 [Codex] * refactor(backends): use staged snapshots in engine backends Assisted-by: Codex:GPT-5 [Codex] * test(distributed): cover staged artifact snapshots Assisted-by: Codex:GPT-5 [Codex] * docs: explain managed model artifacts Assisted-by: Codex:GPT-5 [Codex] * docs: add product design context Assisted-by: Codex:GPT-5 [Codex] * feat(ui): show model artifact download progress Assisted-by: Codex:GPT-5 [Codex] * Eagerly materialize Hugging Face artifacts Materialize HF-backed model references as managed GGUF artifacts during load, with lazy download retained only as fallback. Assisted-by: Codex:GPT-5 [shell] * Refactor HF downloads through a shared executor Assisted-by: Codex:GPT-5 [shell] * drop Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
47 lines
1.5 KiB
YAML
47 lines
1.5 KiB
YAML
---
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name: "liquid-audio"
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description: |
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LiquidAI LFM2 / LFM2.5 Audio models served by the Python `liquid-audio` backend.
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Supports four roles via the `mode:` option:
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- chat text-only chat completion (generate_sequential, no audio)
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- asr speech-to-text (Perform ASR. system prompt)
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- tts text-to-speech in 4 baked voices (us_male/us_female/uk_male/uk_female)
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- s2s interleaved speech-to-speech (the realtime any-to-any path)
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license: "LFM Open License v1.0"
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urls:
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- https://huggingface.co/LiquidAI/LFM2.5-Audio-1.5B
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- https://github.com/Liquid4All/liquid-audio
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config_file: |
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backend: liquid-audio
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context_size: 32768
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f16: true
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mmap: true
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# realtime_audio surfaces the model on the Talk page; chat/tts/transcript
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# let it also serve the standalone /v1/chat/completions, /v1/audio/speech,
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# and /v1/audio/transcriptions endpoints (backend implements all three).
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known_usecases:
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- realtime_audio
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- chat
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- tts
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- transcript
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- vad
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parameters:
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model: LiquidAI/LFM2.5-Audio-1.5B
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artifacts:
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- name: model
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target: model
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source:
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type: huggingface
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repo: LiquidAI/LFM2.5-Audio-1.5B
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# Special tokens emitted in the text track during interleaved generation.
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# Included so a future client-side parser can spot them; the LFM2 tool-call
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# format itself is auto-detected by the upstream llama.cpp parser when the
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# model loads under that backend.
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stopwords:
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- <|im_end|>
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- <|endoftext|>
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