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aha/Cargo.toml
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[package]
name = "aha"
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version = "0.1.7"
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edition = "2024"
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repository = "https://github.com/jhqxxx/aha"
license = "Apache-2.0"
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description = "aha model inference library, now supports Qwen2.5VL, MiniCPM4, VoxCPM, Qwen3VL, DeepSeek-OCR, Hunyuan-OCR, PaddleOCR-VL, VoxCPM1.5, RMBG2.0, GLM-ASR-Nano-2512"
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[dependencies]
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candle-core = { version = "0.9.1"}
candle-nn = { version = "0.9.1"}
candle-transformers = { version = "0.9.1"}
candle-flash-attn = { version = "0.9.1", optional = true }
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serde = "1.0.226"
serde_json = "1.0.145"
anyhow = "1.0.100"
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ffmpeg-next = { version = "8.0.0", optional = true }
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image = "0.25.8"
reqwest = { version = "0.12.23", features = ["blocking"] }
base64 = "0.22.1"
num = "0.4.3"
minijinja = "2.12.0"
tokenizers = "0.22.1"
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aha_openai_dive = { version = "1.4", features = ["stream"]}
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uuid = { version = "1.18.1", features = ["v4"]}
chrono = "0.4.42"
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rocket = { version = "0.5.1", features = ["serde_json", "json"] }
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tokio = "1.47.1"
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hound = "3.5.1"
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clap = { version = "4.5.51", features = ["derive"] }
modelscope = "0.1.0"
dirs = "6.0.0"
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url = "2.5.7"
rayon = "1.10"
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# rubato = "1.0.0"
# audioadapter-buffers = "2.0.0"
realfft = "3.5.0"
symphonia = { version = "0.5.5", features = ["mp3", "wav"] }
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[features]
flash-attn=["candle-flash-attn"]
cuda=["candle-nn/cuda", "candle-core/cuda", "candle-transformers/cuda"]
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ffmpeg=["ffmpeg-next"]
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[lints.clippy]
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needless_range_loop = "allow"
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single_range_in_vec_init = "allow"
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manual_div_ceil = "allow"