24f04b67db
New modules shipped (from Linnet integration): - acoustic.py: AST (MIT/ast-finetuned-audioset-10-10-0.4593) replaces YAMNet stub; 527 AudioSet classes mapped to queue/speaker/environ/scene labels; _LABEL_MAP includes hold_music, ringback, DTMF, background_shift, AMD signal chain - accent.py: facebook/mms-lid-126 language ID → regional accent labels (en_gb, en_us, en_au, fr, es, de, zh, …); lazy-loaded, gated by CF_VOICE_ACCENT - privacy.py: compound privacy risk scorer — public_env, background_voices, nature scene, accent signals; returns 0–3 score without storing any audio - prosody.py: openSMILE-backed prosody extractor (sarcasm_risk, flat_f0_score, speech_rate, pitch_range); mock mode returns neutral values - dimensional.py: audeering/wav2vec2-large-robust-12-ft-emotion-msp-dim valence/arousal/dominance scorer; gated by CF_VOICE_DIMENSIONAL - trajectory.py: rolling buffer for arousal/valence deltas, trend detection (escalating/suppressed/stable), coherence scoring, suppression/reframe flags - telephony.py: TelephonyBackend Protocol + MockTelephonyBackend + SignalWireBackend + FreeSWITCHBackend; CallSession dataclass; make_telephony() factory - app.py: FastAPI service (port 8007) — /health + /classify; accepts base64 PCM chunks, returns full AudioEventOut including dimensional/prosody/accent fields - prefs.py: voice preference helpers (elcor_mode, confidence_threshold, whisper_model, elcor_prior_frames); cf-core and env-var fallback Tests: fix stale tests (YAMNetAcousticBackend → ASTAcousticBackend, scene field added to AcousticResult, speaker_at gap now resolves dominant speaker not UNKNOWN, make_io real path returns MicVoiceIO when sounddevice installed). 78 tests passing. Closes #2, #3.
59 lines
3.6 KiB
Text
59 lines
3.6 KiB
Text
# cf-voice environment — copy to .env and fill in values
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# cf-voice itself does not auto-load .env; consumers (Linnet, Osprey, etc.)
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# load it via python-dotenv in their own startup. For standalone cf-voice
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# dev/testing, source this file manually or install python-dotenv.
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# ── HuggingFace — free tier / local use ──────────────────────────────────────
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# Used by the local diarization path (free tier, user's own machine).
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# Each user must:
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# 1. Create a free account at huggingface.co
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# 2. Accept the gated model terms at:
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# https://huggingface.co/pyannote/speaker-diarization-3.1
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# https://huggingface.co/pyannote/segmentation-3.0
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# 3. Generate a read token at huggingface.co/settings/tokens
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HF_TOKEN=
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# ── HuggingFace — paid tier / cf-orch backend ─────────────────────────────────
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# Used by cf-orch when running diarization as a managed service on Heimdall.
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# This is a CircuitForge org token — NOT the user's personal token.
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#
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# Prerequisites (one-time, manual — tracked in circuitforge-orch#27):
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# 1. Create CircuitForge org on huggingface.co
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# 2. Accept pyannote/speaker-diarization-3.1 terms under the org account
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# 3. Accept pyannote/segmentation-3.0 terms under the org account
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# 4. Generate a read-only org token and set it here
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#
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# Leave blank on local installs — HF_TOKEN above is used instead.
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CF_HF_TOKEN=
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# ── Whisper STT ───────────────────────────────────────────────────────────────
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# Model size: tiny | base | small | medium | large-v2 | large-v3
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# Smaller = faster / less VRAM; larger = more accurate.
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# Recommended: small (500MB VRAM) for real-time use.
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CF_VOICE_WHISPER_MODEL=small
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# ── Compute ───────────────────────────────────────────────────────────────────
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# auto (detect GPU), cuda, cpu
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CF_VOICE_DEVICE=auto
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# ── Mock mode ─────────────────────────────────────────────────────────────────
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# Set to 1 to use synthetic VoiceFrames — no GPU, mic, or HF token required.
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# Unset or 0 for real audio capture.
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CF_VOICE_MOCK=
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# ── Tone classifier ───────────────────────────────────────────────────────────
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# Minimum confidence to emit a VoiceFrame (below this = frame skipped).
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CF_VOICE_CONFIDENCE_THRESHOLD=0.55
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# ── Elcor annotation mode ─────────────────────────────────────────────────────
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# Accessibility feature for autistic and ND users. Switches tone subtext from
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# generic format ("Tone: Frustrated") to Elcor-style prefix format
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# ("With barely concealed frustration:"). Opt-in, local-only.
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# Overridden by cf-core preferences store when circuitforge_core is installed.
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# 1 = enabled, 0 or unset = disabled (default).
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CF_VOICE_ELCOR=0
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# Number of prior VoiceFrames to include as context for Elcor label generation.
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# Larger windows = more contextually aware annotations, higher LLM prompt cost.
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# Default: 4 frames (~10 seconds of rolling context at 2.5s intervals).
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CF_VOICE_ELCOR_PRIOR_FRAMES=4
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