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rustytorch/crates/models/rtx-csm/Cargo.toml
T
osobhandClaude Opus 4.7 af45e1b58e rtx-csm: Phase 6b — LlmClient trait + OpenAI-compatible streaming impl
Generic LLM client abstraction for the conversational stack:

- LlmClient trait with generate_stream(messages, config) -> TokenStream.
  Default generate() impl folds the stream for non-streaming callers.
- ChatMessage / Role / GenConfig types with sensible defaults.
- OpenAiCompatibleClient: HTTP impl with SSE streaming. Works against
  OpenAI, Z.AI, vLLM, llama.cpp's HTTP server, LiteLLM — any endpoint
  serving the Chat Completions schema.
- examples/llm_chat: demo CLI that prints token-by-token to stdout
  with TTFT + total-time + char-count metrics.

Promotes tokio + reqwest + futures-util to regular dependencies (no
longer dev-only) so the trait is part of the public library surface.
Adds async-trait + eventsource-stream for the SSE streaming.

3 unit tests (constructors, role serialization, default config); 82
lib tests total green.

Phase 6 progress:
- 6a Kyutai STT: integration scaffolded; output bridge needs Python
  reference diff (deferred)
- 6b LLM client: shipped (this commit)
- 6c session glue (axum WS + duplex audio loop): next
- 6d productionization: deferred

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>
2026-04-26 04:47:48 -07:00

196 lines
5.6 KiB
TOML

[package]
name = "rtx-csm"
version.workspace = true
edition.workspace = true
authors.workspace = true
license.workspace = true
repository.workspace = true
description = "Rust-native port of Sesame CSM-1B (Conversational Speech Model) on candle + moshi"
# NOTE: candle-transformers 0.8 (workspace pin) does NOT contain the `csm`
# model module — it was added in 0.9.0. We deliberately pull candle 0.9 + moshi
# 0.6 directly here, NOT via workspace deps. Cargo will compile candle 0.8 (for
# the rest of rustytorch) and candle 0.9 (for rtx-csm) side-by-side. No Tensor
# types are shared across that boundary today.
[dependencies]
# Candle 0.9 — required for the csm model module
candle-core = { version = "0.9.1", default-features = false }
candle-nn = { version = "0.9.1", default-features = false }
candle-transformers = { version = "0.9.1", default-features = false }
# Kyutai's moshi crate: provides streaming STT (asr.rs + lm.rs) on top of
# candle 0.9.1. We use moshi::{asr, lm, mimi} for STT integration. Note:
# moshi::mimi uses a different weight-key naming than HF's kyutai/mimi
# (older Kyutai split-format with weight_g/weight_v); we keep our existing
# Mimi loader on candle_transformers::models::mimi for the HF format. The
# STT path uses Kyutai's pytorch_mimi file which IS in moshi's expected
# naming, so they coexist cleanly in different model instances.
moshi = { version = "0.6.4", default-features = false }
# Mimi neural audio codec: we use the HF-compatible `candle-transformers::models::mimi`
# (not the `moshi` crate, which expects different weight-key naming).
# Tokenizer (Llama-3.2 BPE)
tokenizers = { version = "0.20", default-features = false, features = ["onig"] }
# HF Hub asset resolution (synchronous via ureq + rustls)
hf-hub = { version = "0.5", default-features = false, features = ["ureq", "rustls-tls"] }
# Audio I/O
hound = "3.5"
symphonia = { version = "0.5", features = ["all"] }
rubato = "0.15"
# Loudness normalization (EBU R128 / ITU-R BS.1770-4)
ebur128 = "0.1"
# In-process ASR via whisper.cpp bindings. Optional via the `asr` feature
# because it pulls a C++ build (cmake + clang). Provides Metal acceleration.
whisper-rs = { version = "0.16", default-features = false, optional = true }
# Text normalization
unicode-normalization = "0.1"
regex = "1"
# Weight loading
safetensors = "0.4"
# Errors / logging / serde
anyhow.workspace = true
thiserror.workspace = true
tracing.workspace = true
serde.workspace = true
serde_json.workspace = true
# Numerics
half = "2.3"
rand = "0.8"
bytemuck = { version = "1.14", features = ["derive"] }
# Async + HTTP for the LlmClient abstraction (Phase 6b). Promoted from
# dev-dependency to regular dependency so the trait is part of the public
# library surface.
tokio = { version = "1", features = ["macros", "rt-multi-thread", "sync"] }
futures-util = "0.3"
reqwest = { version = "0.12", default-features = false, features = ["json", "stream", "rustls-tls"] }
async-trait = "0.1"
eventsource-stream = "0.2"
[dev-dependencies]
clap = { version = "4.5", features = ["derive"] }
tempfile = "3.0"
approx = "0.5"
tracing-subscriber = "0.3"
# For the TTS HTTP server example.
axum = { version = "0.7", features = ["multipart"] }
# tokio with extra features (signal handler) needed by tts_server.
tokio = { version = "1", features = ["macros", "rt-multi-thread", "signal", "sync"] }
tower = "0.5"
tower-http = { version = "0.6", features = ["trace"] }
# Multipart support added on top of the public reqwest dep for tts_server_bench.
reqwest = { version = "0.12", default-features = false, features = ["json", "multipart", "rustls-tls"] }
[features]
default = ["cpu"]
cpu = []
cuda = ["candle-core/cuda", "candle-nn/cuda", "candle-transformers/cuda"]
metal = ["candle-core/metal", "candle-nn/metal", "candle-transformers/metal"]
accelerate = ["candle-core/accelerate", "candle-nn/accelerate"]
mkl = ["candle-core/mkl", "candle-nn/mkl"]
# In-process Whisper ASR via whisper.cpp bindings. Brings in C++ build deps.
asr = ["dep:whisper-rs"]
asr-metal = ["asr", "whisper-rs/metal"]
asr-cuda = ["asr", "whisper-rs/cuda"]
[[example]]
name = "generate"
path = "examples/generate.rs"
[[example]]
name = "bench"
path = "examples/bench.rs"
[[example]]
name = "quantize"
path = "examples/quantize.rs"
[[example]]
name = "inspect_gguf"
path = "examples/inspect_gguf.rs"
[[example]]
name = "qmatmul_repro"
path = "examples/qmatmul_repro.rs"
[[example]]
name = "qmm_layer_diff"
path = "examples/qmm_layer_diff.rs"
[[example]]
name = "lora_train_step"
path = "examples/lora_train_step.rs"
[[example]]
name = "forward_loss_demo"
path = "examples/forward_loss_demo.rs"
[[example]]
name = "lora_finetune_step"
path = "examples/lora_finetune_step.rs"
[[example]]
name = "tts_server"
path = "examples/tts_server.rs"
[[example]]
name = "lora_train"
path = "examples/lora_train.rs"
[[example]]
name = "audioseal_inspect"
path = "examples/audioseal_inspect.rs"
[[example]]
name = "audioseal_convert"
path = "examples/audioseal_convert.rs"
[[example]]
name = "audioseal_demo"
path = "examples/audioseal_demo.rs"
[[example]]
name = "audioseal_apply"
path = "examples/audioseal_apply.rs"
[[example]]
name = "wavlm_sv_convert"
path = "examples/wavlm_sv_convert.rs"
[[example]]
name = "wavlm_sv_demo"
path = "examples/wavlm_sv_demo.rs"
[[example]]
name = "wavlm_sv_inspect"
path = "examples/wavlm_sv_inspect.rs"
[[example]]
name = "pipeline"
path = "examples/pipeline.rs"
[[example]]
name = "generate_long"
path = "examples/generate_long.rs"
[[example]]
name = "tts_server_bench"
path = "examples/tts_server_bench.rs"
[[example]]
name = "stt_demo"
path = "examples/stt_demo.rs"
[[example]]
name = "llm_chat"
path = "examples/llm_chat.rs"