Merge branch 'vad'

* vad:
[fix]: readme.
[fix]: add.
[feature]: remove experimental models.
[fix]: web bugfix.
update prompt for en
[feature]: add session history.
restore min_silence_duration_ms to 100
add hotwords config to mapping
add hotwords
add hotwords config to mapping
add hotwords
update vad threshold
remove english words, add more Chinese hotwords
rename processing pipe
rename filenames

README.md

@@ -84,3 +84,4 @@ license: mit
 ## 运行
 > 1. 运行命令 `python main.py` 启动应用程序。
 > 2. 打开浏览器并访问 `http://localhost:9191/` 以使用该应用。
+> 3. 推荐是用 Chrome 浏览器，Safari/Firefox 可能会出现一些问题。

config/hotwords.json

@@ -6,6 +6,7 @@
     "go same": "GOSIM",
     "GoSync": "GOSIM",
     "Go Son": "GOSIM",
+    "GOSIMe": "GOSIM",
     "CSN": "CSDN",
     "CSDF": "CSDN",
     "CSTN": "CSDN",
@@ -20,8 +21,60 @@
     "它跟face": "huggingface",
     "拉么index": "LlamaIndex",
     "lama index": "LlamaIndex",
+    "feature为": "futurewei",
+    "future为": "futurewei",
+    "future维": "futurewei",
+    "feature维": "futurewei",
     "rug": "RAG",
     "defive": "Dify",
     "define": "Dify",
-    "open minus":"open manus"
+    "open minus":"open manus",
+    "Open minus":"open manus",
+    "美塔GPT": "metagpt",
+    "Open manners": "open manus",
+    "Deep wisdom":"DeepWisdom",
+    "meta GPT": "MetaGPT",
+    "rag flu": "RAGFlow",
+    "rug flu": "RAGFlow",
+    "RAG flow": "RAGFlow",
+    "RAG floor": "RAGFlow",
+    "rig floor": "RAGFlow",
+    "rik flow": "RAGFlow",
+    "Rik flow": "RAGFlow",
+    "Raj flow": "RAGFlow",
+    "Read flow": "RAGFlow",
+    "二AJ flow": "RAGFlow",
+    "Rig flow": "RAGFlow",
+    "Rig": "RAG",
+    "二AG flow": "RAGFlow",
+    "Rick flow": "RAGFlow",
+    "ick flow": "RAGFlow",
+    "二AJ": "RAG",
+    "rig": "RAG",
+    "美他GBT": "MetaGPT",
+    "没他GPT": "MetaGPT",
+    "GBT": "GPT",
+    "美他": "Meta",
+    "英飞流": "InfinFlow",
+    "H一百": "H100",
+    "v一百": "V100",
+    "h两百": "H200",
+    "H两百": "H200",
+    "隐扣的": "encoder",
+    "抵扣的": "decoder",
+    "耳机": "RAG",
+    "头坑": "token",
+    "麦TGPT": "MetaGPT",
+    "三点四b": "3.4b",
+    "七b": "7b",
+    "可拍了的": "Copilot",
+    "spore": "score",
+    "KV cash": "KV cache",
+    "拉玛": "Llama",
+    "拉玛三": "Llama3",
+    "拉玛三二": "Llama3.2",
+    "拉玛三二七零": "Llama3.2-70b",
+    "拉玛三二七零b": "Llama3.2-70b",
+    "follow三十二": "fp32"
+
 }

config/hotwords.txt

@@ -1,37 +1,79 @@
-GOSIM
-CSDN
-Rust
-git
-lib
-HUAWEI
-Futurewei
-Cloud
-OpenAI
-PYTHON
+阿里
+通义实验室
+通义灵码
+通义晓蜜
+通义听悟
+通义星尘
 千问
 鸿蒙
-vLLM
-MiniCPM
-ChatGPT
-GPT
-GPT2
-GPT3
-GPT4
-Llama
-Llama2
-Llama3
-MISTRAL
-Large
-Mistral
-Small
-LoRA
-finetune
-quantization
-pruning
-MoXIN
-Function
-Func
-Lava
-C++
-阿里
-pipeline
+范式
+泛化
+用例
+模型
+预训练
+无监督
+先验
+注意力
+编程
+订阅
+智能体
+头数
+基座模型
+激活值
+隐藏层
+注意力头数
+开源
+微调
+指令微调
+具身智能
+声学建模
+边缘计算
+昇腾
+训推
+强化学习
+近端策略优化
+奖励建模
+分词
+幻觉
+代码补全
+代码生成
+上下文感知
+上下文学习
+任务分解
+需求理解
+自然语言处理
+检索增强生成
+多模态
+拉玛
+美他
+英飞流
+向量
+稀疏向量
+张量
+稠密
+海涵
+重构
+语义
+语义鸿沟
+隐扣的
+抵扣的
+索引
+次级索引
+融合
+召回
+复现
+知识图谱
+源
+图数据库
+图搜索
+命名体
+补全
+数量级
+耳机
+头坑
+工程
+多语言
+词袋
+可拍了的
+转置
+八比特

config/keywords.txt

@@ -1,4 +1,3 @@
 OpenAGI
 LLaMA Factory
-OPENGL
-Web3
+OPENGL

config/prompt.py

@@ -19,11 +19,11 @@ keywords_list = [i.strip() for i in (CONFIG_DIR / 'keywords.txt').read_text().sp
 keywords_mapping_string = '\n'.join([f'  * {value}: {value}' for value in keywords_list ])
 
 LLM_SYS_7B_PROMPT_EN= """
-你是一名专业的同声传译员，正在为 GOSIM 会议提供中英/英中翻译服务。你的任务是准确、流畅地翻译发言内容。
+你是一名专业的同声传译员，正在为 GOSIM 会议提供英中翻译服务。你的任务是准确、流畅地翻译发言内容。
 
 请遵循以下要求：
 1. 语言风格：翻译成中文时，请使用自然、流畅、符合现代汉语口语习惯的表达方式。避免生硬、逐字翻译的痕迹，要让听众容易理解。
-2. 专业术语：**请优先参考下方提供的术语对照表进行翻译。** 对于对照表中未包含的术语，如果该术语有公认的标准翻译，请使用标准翻译；如果没有或不确定，可以保留英文原文或提供最贴切的翻译。不要用通俗词汇替代专业术语。
+2. 专业术语：**请优先参考下方提供的术语对照表进行翻译。** 对于对照表中未包含的术语，如果该术语有公认的标准翻译，请使用标准翻译；如果没有或不确定，请保留英文原文。不要用通俗词汇替代专业术语。
 3. 专有名词：对于专有名词，如会议名称 "GOSIM"、人名、公司名、项目名、特定技术名称等，请保留其原始英文不做翻译。
 4. 流畅性与准确性：在追求口语化的同时，务必保证信息传达的准确性。
 5. 输出：请直接输出翻译结果，不要添加任何额外的解释或说明。

config/settings.py

@@ -23,7 +23,7 @@ console_handler.setFormatter(console_formatter)
 logging.getLogger().addHandler(console_handler)
 
 # 音频段的决策时间
-FRAME_SCOPE_TIME_THRESHOLD = 4
+FRAME_SCOPE_TIME_THRESHOLD = 6
 # 最长语音时长
 MAX_SPEECH_DURATION_S = 15
 

frontend/assets/{index-f4166384.css → index-b1f15c01.css}

@@ -1 +1 @@
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438px)}.content-wrapper .content-box[data-v-d41c9ce7]{padding:24px;height:240px;background-color:#e8e8e8;border-radius:16px;width:50%;margin:48px auto;min-width:300px}.content-wrapper .video-box[data-v-d41c9ce7]{max-width:800px;min-width:320px;width:90vw;height:auto}

frontend/index.html

@@ -5,8 +5,8 @@
     <link rel="icon" type="image/svg+xml" href="./favicon.ico" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Translator</title>
-    <script type="module" crossorigin src="./assets/index-a389e3a7.js"></script>
-    <link rel="stylesheet" href="./assets/index-f4166384.css">
+    <script type="module" crossorigin src="./assets/index-fc3a0f87.js"></script>
+    <link rel="stylesheet" href="./assets/index-b1f15c01.css">
   </head>
   <body>
     <div id="app"></div>

main.py

@@ -3,7 +3,7 @@ from transcribe.serve import WhisperTranscriptionService
 from uuid import uuid1
 from logging import getLogger
 import numpy as np
-from transcribe.translatepipes import TranslatePipes
+from transcribe.processing import ProcessingPipes
 from contextlib import asynccontextmanager
 from multiprocessing import Process, freeze_support
 from fastapi.staticfiles import StaticFiles
@@ -33,7 +33,7 @@ async def get_audio_from_websocket(websocket)->np.array:
 @asynccontextmanager
 async def lifespan(app:FastAPI):
     global pipe
-    pipe = TranslatePipes()
+    pipe = ProcessingPipes()
     pipe.wait_ready()
     logger.info("Pipeline is ready.")
     yield

moyoyo_asr_models/ggml-medium-encoder.mlmodelc/analytics/coremldata.bin

@@ -1,3 +0,0 @@
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moyoyo_asr_models/ggml-medium-encoder.mlmodelc/coremldata.bin

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moyoyo_asr_models/ggml-medium-encoder.mlmodelc/metadata.json

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-        "shortDescription" : "",
-        "shape" : "[]",
-        "name" : "output",
-        "type" : "MultiArray"
-      }
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-
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-    "mlProgramOperationTypeHistogram" : {
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-      "Gelu" : 26,
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-    "computePrecision" : "Mixed (Float16, Float32, Int32)",
-    "isUpdatable" : "0",
-    "availability" : {
-      "macOS" : "12.0",
-      "tvOS" : "15.0",
-      "watchOS" : "8.0",
-      "iOS" : "15.0",
-      "macCatalyst" : "15.0"
-    },
-    "modelType" : {
-      "name" : "MLModelType_mlProgram"
-    },
-    "userDefinedMetadata" : {
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-        "isOptional" : "0",
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-        "formattedType" : "MultiArray (Float32 1 × 80 × 3000)",
-        "shortDescription" : "",
-        "shape" : "[1, 80, 3000]",
-        "name" : "logmel_data",
-        "type" : "MultiArray"
-      }
-    ],
-    "generatedClassName" : "coreml_encoder_medium",
-    "method" : "predict"
-  }
-]

moyoyo_asr_models/ggml-medium-encoder.mlmodelc/weights/weight.bin

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moyoyo_asr_models/ggml-medium-q5_0.bin

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moyoyo_asr_models/ggml-small-encoder.mlmodelc/analytics/coremldata.bin

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moyoyo_asr_models/ggml-small-encoder.mlmodelc/coremldata.bin

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moyoyo_asr_models/ggml-small-encoder.mlmodelc/metadata.json

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-[
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-      "Gelu" : 14,
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-    "isUpdatable" : "0",
-    "availability" : {
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-      "tvOS" : "15.0",
-      "watchOS" : "8.0",
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-    },
-    "modelType" : {
-      "name" : "MLModelType_mlProgram"
-    },
-    "userDefinedMetadata" : {
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-        "name" : "logmel_data",
-        "type" : "MultiArray"
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-    "method" : "predict"
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moyoyo_asr_models/ggml-small-encoder.mlmodelc/weights/weight.bin

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moyoyo_asr_models/ggml-small.bin

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moyoyo_asr_models/qwen2.5-7b-instruct-q5_0-00001-of-00002.gguf

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moyoyo_asr_models/qwen2.5-7b-instruct-q5_0-00002-of-00002.gguf

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-size 1314064416

transcribe/helpers/vadprocessor.py

@@ -1,5 +1,4 @@
 from copy import deepcopy
-from queue import Queue, Empty
 from time import time
 from config import VAD_MODEL_PATH
 from silero_vad import load_silero_vad

transcribe/{translatepipes.py → processing.py}

@@ -1,7 +1,7 @@
 from .pipelines import WhisperPipe, MetaItem, WhisperChinese, Translate7BPipe, FunASRPipe, VadPipe, TranslatePipe
 from .utils import timer
 
-class TranslatePipes:
+class ProcessingPipes:
     def __init__(self) -> None:
 
         self._process = []

transcribe/serve.py

@@ -10,9 +10,8 @@ import collections
 from api_model import TransResult, Message
 
 from .utils import log_block, start_thread, get_text_separator, filter_words
-from .translatepipes import TranslatePipes
-
-from transcribe.pipelines import MetaItem
+from .processing import ProcessingPipes
+from .pipelines import MetaItem
 
 
 logger = getLogger("TranscriptionService")
@@ -25,7 +24,7 @@ class WhisperTranscriptionService:
     """
 
 
-    def __init__(self, websocket, pipe: TranslatePipes, language=None, dst_lang=None, client_uid=None):
+    def __init__(self, websocket, pipe: ProcessingPipes, language=None, dst_lang=None, client_uid=None):
         print('>>>>>>>>>>>>>>>> init service >>>>>>>>>>>>>>>>>>>>>>')
         print('src_lang:', language)
         self.source_language = language  # 源语言