End-to-end SilentCipher: bit-perfect round-trip on real LibriSpeech
audio. Sesame's actual production watermarker now works in pure
candle 0.9 + Metal.
New components in src/silentcipher.rs:
detect(samples_16k) -> DetectResult
1. RMS-normalize to VCTK baseline (matches embed pre-conditioning)
2. STFT -> magnitude
3. dec_m_0(magnitude) -> (B, message_dim, 1, T) logits
4. argmax along message_dim -> (T,) per-frame predictions
5. Truncate to multiple of message_len
6. Reshape to (n_patches, message_len), per-column mode
7. Find terminator (value 0), rotate so payload follows it
8. Subtract +1 offset -> original codes
encode_bits / decode_bits (Phase 10.4 fix)
Switched from base-4 (2 bits per code) to base-`(message_dim - 1)`.
The 16 kHz model has message_dim=4 = 3 carrier values (1,2,3) +
terminator (0), NOT 4 carrier values. Original base-4 packing
occasionally produced value 3, which Python's
`np.identity(4)[index+1]` would have crashed on. Real capacity:
15 codes x log2(3) ~= 23.78 bits per patch.
SilentCipherWatermark (impl Watermarker)
Wraps a SilentCipherWatermarker with a fixed default_payload so
it satisfies the existing Watermarker trait. Maps confidence ->
DetectionResult.mean_presence and the lower-16-bits of the
decoded payload -> DetectionResult.message (None below confidence
0.7 to suppress false positives).
examples/silentcipher_apply
Mirrors audioseal_apply: --in / --out / --payload / --detect-only.
Loads from sony/silentcipher HF repo, embeds, optionally
resamples back to source rate, optionally re-detects to verify.
Verified end-to-end (LibriSpeech /tmp/asr_test.flac, 10.42 s @ 16 kHz):
Build: 29 ms (3 .ckpt files from HF cache)
Embed: 1213 ms = 0.116x realtime
Detect: 1838 ms = 0.18x realtime
payload: 0x00BC614E (in)
recovered: 0x00BC614E (out)
codes match: 15 / 15
confidence: 1.0000
Clean (un-watermarked) audio: confidence 0.475, codes mostly 0 -
strong signal-vs-noise discrimination at the 0.7 threshold.
This closes the most surprising gap from the Sesame stack analysis:
rtx-csm now has the *literal* Sesame watermarker (not Meta's
AudioSeal) working in pure candle. AudioSeal stays available for
callers that prefer it.
Phase 10.5 (next): wire as a third option in converse_server alongside
AudioSeal, and a 24/16 kHz ResampledWatermarker for the CSM path.
Plus an A/B bench (SilentCipher vs AudioSeal).
Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
280 lines
7.8 KiB
TOML
280 lines
7.8 KiB
TOML
[package]
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name = "rtx-csm"
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version.workspace = true
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edition.workspace = true
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authors.workspace = true
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license.workspace = true
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repository.workspace = true
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description = "Rust-native port of Sesame CSM-1B (Conversational Speech Model) on candle + moshi"
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# NOTE: candle-transformers 0.8 (workspace pin) does NOT contain the `csm`
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# model module — it was added in 0.9.0. We deliberately pull candle 0.9 + moshi
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# 0.6 directly here, NOT via workspace deps. Cargo will compile candle 0.8 (for
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# the rest of rustytorch) and candle 0.9 (for rtx-csm) side-by-side. No Tensor
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# types are shared across that boundary today.
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[dependencies]
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# Candle 0.9 — required for the csm model module
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candle-core = { version = "0.9.1", default-features = false }
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candle-nn = { version = "0.9.1", default-features = false }
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candle-transformers = { version = "0.9.1", default-features = false }
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# Kyutai's moshi crate: provides streaming STT (asr.rs + lm.rs) on top of
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# candle 0.9.1. We use moshi::{asr, lm, mimi} for STT integration. Note:
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# moshi::mimi uses a different weight-key naming than HF's kyutai/mimi
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# (older Kyutai split-format with weight_g/weight_v); we keep our existing
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# Mimi loader on candle_transformers::models::mimi for the HF format. The
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# STT path uses Kyutai's pytorch_mimi file which IS in moshi's expected
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# naming, so they coexist cleanly in different model instances.
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moshi = { version = "0.6.4", default-features = false }
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# SentencePiece tokenizer for Kyutai STT detokenization (token IDs → text).
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sentencepiece = "0.13"
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# Mimi neural audio codec: we use the HF-compatible `candle-transformers::models::mimi`
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# (not the `moshi` crate, which expects different weight-key naming).
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# Tokenizer (Llama-3.2 BPE)
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tokenizers = { version = "0.20", default-features = false, features = ["onig"] }
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# HF Hub asset resolution (synchronous via ureq + rustls)
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hf-hub = { version = "0.5", default-features = false, features = ["ureq", "rustls-tls"] }
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# Audio I/O
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hound = "3.5"
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symphonia = { version = "0.5", features = ["all"] }
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rubato = "0.15"
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# FFT primitives for the SilentCipher STFT (Phase 10). Pure Rust,
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# zero C linkage. Ships in the default build because it's <100 KB
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# of compiled code.
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rustfft = "6.2"
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# Loudness normalization (EBU R128 / ITU-R BS.1770-4)
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ebur128 = "0.1"
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# In-process ASR via whisper.cpp bindings. Optional via the `asr` feature
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# because it pulls a C++ build (cmake + clang). Provides Metal acceleration.
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whisper-rs = { version = "0.16", default-features = false, optional = true }
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# Silero V5 VAD via ONNX Runtime (`ort` crate). Optional via the `vad`
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# feature because it introduces a second ML inference runtime alongside
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# candle — Phase 8.1.2's `ort_conflict_probe` binary verifies it doesn't
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# regress CSM Metal inference the way whisper-rs (ggml) did.
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voice_activity_detector = { version = "0.2", optional = true }
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# Text normalization
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unicode-normalization = "0.1"
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regex = "1"
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# Weight loading
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safetensors = "0.4"
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# Errors / logging / serde
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anyhow.workspace = true
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thiserror.workspace = true
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tracing.workspace = true
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serde.workspace = true
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serde_json.workspace = true
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# Numerics
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half = "2.3"
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rand = "0.8"
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bytemuck = { version = "1.14", features = ["derive"] }
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# Async + HTTP for the LlmClient abstraction (Phase 6b). Promoted from
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# dev-dependency to regular dependency so the trait is part of the public
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# library surface.
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tokio = { version = "1", features = ["macros", "rt-multi-thread", "sync"] }
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futures-util = "0.3"
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reqwest = { version = "0.12", default-features = false, features = ["json", "stream", "rustls-tls"] }
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async-trait = "0.1"
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eventsource-stream = "0.2"
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[dev-dependencies]
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clap = { version = "4.5", features = ["derive"] }
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tempfile = "3.0"
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approx = "0.5"
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tracing-subscriber = "0.3"
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# For the TTS HTTP server + converse_server WebSocket examples.
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axum = { version = "0.7", features = ["multipart", "ws"] }
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# WebSocket client for examples/converse_client.
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tokio-tungstenite = { version = "0.24", default-features = false, features = ["connect", "rustls-tls-webpki-roots"] }
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# tokio with extra features (signal handler) needed by tts_server.
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tokio = { version = "1", features = ["macros", "rt-multi-thread", "signal", "sync"] }
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tower = "0.5"
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tower-http = { version = "0.6", features = ["trace"] }
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# Multipart support added on top of the public reqwest dep for tts_server_bench.
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reqwest = { version = "0.12", default-features = false, features = ["json", "multipart", "rustls-tls"] }
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[features]
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default = ["cpu"]
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cpu = []
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cuda = ["candle-core/cuda", "candle-nn/cuda", "candle-transformers/cuda"]
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metal = ["candle-core/metal", "candle-nn/metal", "candle-transformers/metal"]
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accelerate = ["candle-core/accelerate", "candle-nn/accelerate"]
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mkl = ["candle-core/mkl", "candle-nn/mkl"]
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# In-process Whisper ASR via whisper.cpp bindings. Brings in C++ build deps.
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asr = ["dep:whisper-rs"]
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asr-metal = ["asr", "whisper-rs/metal"]
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asr-cuda = ["asr", "whisper-rs/cuda"]
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# Silero V5 VAD via ONNX Runtime. Use `--features metal,vad` to enable
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# alongside CSM. Phase 8.1.2 must pass before relying on this in
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# production.
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vad = ["dep:voice_activity_detector"]
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[[example]]
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name = "generate"
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path = "examples/generate.rs"
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[[example]]
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name = "bench"
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path = "examples/bench.rs"
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[[example]]
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name = "quantize"
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path = "examples/quantize.rs"
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[[example]]
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name = "inspect_gguf"
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path = "examples/inspect_gguf.rs"
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[[example]]
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name = "qmatmul_repro"
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path = "examples/qmatmul_repro.rs"
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[[example]]
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name = "qmm_layer_diff"
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path = "examples/qmm_layer_diff.rs"
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[[example]]
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name = "lora_train_step"
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path = "examples/lora_train_step.rs"
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[[example]]
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name = "forward_loss_demo"
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path = "examples/forward_loss_demo.rs"
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[[example]]
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name = "lora_finetune_step"
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path = "examples/lora_finetune_step.rs"
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[[example]]
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name = "tts_server"
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path = "examples/tts_server.rs"
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[[example]]
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name = "lora_train"
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path = "examples/lora_train.rs"
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[[example]]
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name = "audioseal_inspect"
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path = "examples/audioseal_inspect.rs"
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[[example]]
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name = "audioseal_convert"
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path = "examples/audioseal_convert.rs"
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[[example]]
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name = "audioseal_demo"
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path = "examples/audioseal_demo.rs"
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[[example]]
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name = "audioseal_apply"
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path = "examples/audioseal_apply.rs"
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[[example]]
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name = "wavlm_sv_convert"
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path = "examples/wavlm_sv_convert.rs"
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[[example]]
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name = "wavlm_sv_demo"
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path = "examples/wavlm_sv_demo.rs"
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[[example]]
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name = "wavlm_sv_inspect"
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path = "examples/wavlm_sv_inspect.rs"
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[[example]]
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name = "pipeline"
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path = "examples/pipeline.rs"
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[[example]]
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name = "generate_long"
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path = "examples/generate_long.rs"
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[[example]]
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name = "tts_server_bench"
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path = "examples/tts_server_bench.rs"
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[[example]]
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name = "stt_demo"
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path = "examples/stt_demo.rs"
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[[example]]
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name = "llm_chat"
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path = "examples/llm_chat.rs"
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[[example]]
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name = "converse"
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path = "examples/converse.rs"
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[[example]]
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name = "converse_server"
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path = "examples/converse_server.rs"
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[[example]]
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name = "converse_client"
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path = "examples/converse_client.rs"
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[[example]]
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name = "converse_server_bench"
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path = "examples/converse_server_bench.rs"
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[[example]]
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name = "llm_extra_body_smoke"
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path = "examples/llm_extra_body_smoke.rs"
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[[example]]
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name = "stt_profile"
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path = "examples/stt_profile.rs"
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[[example]]
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name = "whisper_profile"
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path = "examples/whisper_profile.rs"
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required-features = ["asr"]
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[[example]]
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name = "ort_conflict_probe"
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path = "examples/ort_conflict_probe.rs"
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required-features = ["vad"]
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[[example]]
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name = "make_silence_test"
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path = "examples/make_silence_test.rs"
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[[example]]
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name = "moonshine_inspect"
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path = "examples/moonshine_inspect.rs"
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[[example]]
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name = "moonshine_smoke"
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path = "examples/moonshine_smoke.rs"
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[[example]]
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name = "moonshine_transcribe"
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path = "examples/moonshine_transcribe.rs"
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[[example]]
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name = "moonshine_profile"
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path = "examples/moonshine_profile.rs"
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[[example]]
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name = "silentcipher_inspect"
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path = "examples/silentcipher_inspect.rs"
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[[example]]
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name = "silentcipher_smoke"
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path = "examples/silentcipher_smoke.rs"
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[[example]]
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name = "silentcipher_apply"
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path = "examples/silentcipher_apply.rs"
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