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[update] Update model name

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This commit is contained in:
LittleMouse
2025-04-21 11:51:16 +08:00
parent 23cc53d9ef
commit 66a47708d1
13 changed files with 123 additions and 54 deletions
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benchmark/utils/llm.py
+1 -9
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@@ -30,7 +30,6 @@ class LLMClient:
while True:
chunk = self.sock.recv(4096)
logging.info(f"Received chunk: {chunk}")
response += chunk
while b'\n' in response:
@@ -149,21 +148,14 @@ class LLMClient:
def test(self, model, input_text):
logging.info("Setting up...")
setup_response = self.setup(model)
logging.info("Setup response: %s", setup_response)
logging.info("Running inference...")
inference_result = self.inference(input_text)
logging.info("Inference result: %s", inference_result)
logging.info("Exiting...")
exit_response = self.exit()
logging.info("Exit response: %s", exit_response)
return {
"setup_response": setup_response,
"inference_result": inference_result,
"exit_response": exit_response
}
return {}
if __name__ == "__main__":
host = "192.168.20.186"
doc/projects_llm_framework_doc/llm_depth_anything_en.md
+1 -1
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@@ -27,7 +27,7 @@ Send JSON:
- work_id: When configuring the unit, it is `depth_anything`.
- action: The method called is `setup`.
- object: The data type being transmitted is `depth_anything.setup`.
- model: The model used is the `depth_anything` model.
- model: The model used is the `depth-anything-ax630c` model.
- response_format: The return result is `jpeg.base64.stream`.
- input: The input is `camera.1001`, which refers to the input from the camera unit, as detailed in the camera unit
documentation.
doc/projects_llm_framework_doc/llm_depth_anything_zh.md
+1 -1
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@@ -27,7 +27,7 @@ depth_anything 视觉单元，用于提供图片深度信息。
- work_id：配置单元时，为 `depth_anything`。
- action：调用的方法为 `setup`。
- object：传输的数据类型为 `depth_anything.setup`。
- model：使用的模型为 `depth_anything` 模型。
- model：使用的模型为 `depth-anything-ax630c` 模型。
- response_format：返回结果为 `jpeg.base64.stream`。
- input：输入的为 `camera.1001`，代表的是从 camera 单元内部输入，详见 camera 单位文档。
- enoutput：是否启用用户结果输出。
doc/projects_llm_framework_doc/llm_melotts_en.md
+4 -4
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@@ -16,7 +16,7 @@ Send JSON:
"action": "setup",
"object": "melotts.setup",
"data": {
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm",
"input": "tts.utf-8",
"enoutput": false
@@ -28,7 +28,7 @@ Send JSON:
- work_id: For configuration, it is `melotts`.
- action: The method to be called is `setup`.
- object: The data type being transmitted is `melotts.setup`.
- model: The model being used is the Chinese model `melotts_zh-cn`.
- model: The model being used is the Chinese model `melotts-zh-cn`.
- response_format: The result is returned as `sys.pcm`, system audio data, which is directly sent to the llm-audio
module for playback.
- input: The input is `tts.utf-8`, representing user input.
@@ -139,7 +139,7 @@ Example:
"action": "setup",
"object": "melotts.setup",
"data": {
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm",
"input": [
"tts.utf-8",
@@ -335,7 +335,7 @@ Response JSON:
"inputs_": [
"tts.utf-8"
],
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm"
},
"error": {
doc/projects_llm_framework_doc/llm_melotts_zh.md
+4 -4
View File
@@ -15,7 +15,7 @@
"action": "setup",
"object": "melotts.setup",
"data": {
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm",
"input": "tts.utf-8",
"enoutput": false
@@ -27,7 +27,7 @@
- work_id：配置单元时，为 `melotts`。
- action：调用的方法为 `setup`。
- object：传输的数据类型为 `melotts.setup`。
- model：使用的模型为 `melotts_zh-cn` 中文模型。
- model：使用的模型为 `melotts-zh-cn` 中文模型。
- response_format：返回结果为 `sys.pcm`, 系统音频数据，并直接发送到 llm-audio 模块进行播放。
- input：输入的为 `tts.utf-8`,代表的是从用户输入。
- enoutput：是否起用用户结果输出。
@@ -134,7 +134,7 @@ error::code 为 0 表示执行成功。
"action": "setup",
"object": "melotts.setup",
"data": {
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm",
"input": [
"tts.utf-8",
@@ -328,7 +328,7 @@ error::code 为 0 表示执行成功。
"inputs_": [
"tts.utf-8"
],
"model": "melotts_zh-cn",
"model": "melotts-zh-cn",
"response_format": "sys.pcm"
},
"error": {
doc/projects_llm_framework_doc/llm_tts_en.md
+42 -5
View File
@@ -16,7 +16,7 @@ Send JSON:
"action": "setup",
"object": "tts.setup",
"data": {
"model": "single_speaker_fast",
"model": "single-speaker-english-fast",
"response_format": "sys.pcm",
"input": "tts.utf-8",
"enoutput": false
@@ -28,7 +28,7 @@ Send JSON:
- work_id: For configuring the unit, it is `tts`.
- action: The method to call is `setup`.
- object: The type of data being transmitted is `tts.setup`.
- model: The model used is the `single_speaker_fast` Chinese model.
- model: The model used is the `single-speaker-english-fast` English model.
- response_format: The returned result is `sys.pcm`, system audio data, which is directly sent to the llm-audio module
for playback.
- input: Input is `tts.utf-8`, representing user input.
@@ -46,13 +46,50 @@ Response JSON:
},
"object": "None",
"request_id": "2",
"work_id": "llm.1003"
"work_id": "tts.1003"
}
```
- created: Message creation time, in Unix time.
- work_id: The successfully created work_id unit.
## inference
### streaming input
```json
{
"request_id": "2",
"work_id": "tts.1003",
"action": "inference",
"object": "tts.utf-8.stream",
"data": {
"delta": "What's ur name?",
"index": 0,
"finish": true
}
}
```
- object: The data type transmitted is tts.utf-8.stream, indicating a streaming input from the user's UTF-8.
- delta: Segment data of the streaming input.
- index: Index of the segment in the streaming input.
- finish: A flag indicating whether the streaming input has completed.
### non-streaming input
```json
{
"request_id": "2",
"work_id": "tts.1003",
"action": "inference",
"object": "tts.utf-8",
"data": "What's ur name?"
}
```
- object: The data type transmitted is tts.utf-8, indicating a non-streaming input from the user's UTF-8.
- data: Data for non-streaming input.
## link
Link the output of the upper unit.
@@ -102,7 +139,7 @@ Example:
"action": "setup",
"object": "tts.setup",
"data": {
"model": "single_speaker_fast",
"model": "single-speaker-fast",
"response_format": "sys.pcm",
"input": [
"tts.utf-8",
@@ -298,7 +335,7 @@ Response JSON:
"inputs_": [
"tts.utf-8"
],
"model": "single_speaker_fast",
"model": "single-speaker-fast",
"response_format": "sys.pcm"
},
"error": {
doc/projects_llm_framework_doc/llm_tts_zh.md
+41 -5
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@@ -15,7 +15,7 @@
"action": "setup",
"object": "tts.setup",
"data": {
"model": "single_speaker_fast",
"model": "single-speaker-fast",
"response_format": "sys.pcm",
"input": "tts.utf-8",
"enoutput": false
@@ -27,7 +27,7 @@
- work_id：配置单元时，为 `tts`。
- action：调用的方法为 `setup`。
- object：传输的数据类型为 `tts.setup`。
- model：使用的模型为 `single_speaker_fast` 中文模型。
- model：使用的模型为 `single-speaker-fast` 中文模型。
- response_format：返回结果为 `sys.pcm`, 系统音频数据，并直接发送到 llm-audio 模块进行播放。
- input：输入的为 `tts.utf-8`,代表的是从用户输入。
- enoutput：是否起用用户结果输出。
@@ -44,13 +44,49 @@
},
"object": "None",
"request_id": "2",
"work_id": "llm.1003"
"work_id": "tts.1003"
}
```
- created：消息创建时间，unix 时间。
- work_id：返回成功创建的 work_id 单元。
## inference
### 流式输入
```json
{
"request_id": "2",
"work_id": "tts.1003",
"action": "inference",
"object": "tts.utf-8.stream",
"data": {
"delta": "今天天气真好！",
"index": 0,
"finish": true
}
}
```
- object：传输的数据类型为 `tts.utf-8.stream` 代表的是从用户 utf-8 的流式输入
- delta：流式输入的分段数据
- index：流式输入的分段索引
- finish:流式输入是否完成的标志位
### 非流式输入
```json
{
"request_id": "2",
"work_id": "tts.1003",
"action": "inference",
"object": "tts.utf-8",
"data": "今天天气真好！"
}
```
- object：传输的数据类型为 `tts.utf-8` 代表的是从用户 utf-8 的非流式输入
- data：非流式输入的数据
## link
链接上级单元的输出。
@@ -98,7 +134,7 @@ error::code 为 0 表示执行成功。
"action": "setup",
"object": "tts.setup",
"data": {
"model": "single_speaker_fast",
"model": "single-speaker-fast",
"response_format": "sys.pcm",
"input": [
"tts.utf-8",
@@ -294,7 +330,7 @@ error::code 为 0 表示执行成功。
"inputs_": [
"tts.utf-8"
],
"model": "single_speaker_fast",
"model": "single-speaker-fast",
"response_format": "sys.pcm"
},
"error": {
projects/llm_framework/main_depth_anything/mode_depth-anything-ax630c.json
+3 -1
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@@ -1,7 +1,9 @@
{
"mode":"depth_anything",
"mode":"depth-anything-ax630c",
"type":"cv",
"homepage":"https://github.com/DepthAnything/Depth-Anything-V2",
"compile_flage":"pulsar2 build --input depth_anything.onnx --config config.json --output_dir output --output_name depth_anything.axmodel --target_hardware AX620E",
"pulsar_version":"2.5-2d5d0fa3",
"capabilities":[
"Segmentation"
],
projects/llm_framework/main_melotts/mode_melotts-zh-cn.json
+3 -1
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@@ -1,7 +1,9 @@
{
"mode": "melotts_zh-cn",
"mode": "melotts-zh-cn",
"type": "tts",
"homepage":"https://huggingface.co/myshell-ai/MeloTTS-Chinese",
"compile_flage":"pulsar2 build --input decoder.onnx --config config_decoder_u16.json --output_dir decoder --output_name decoder.axmodel --target_hardware AX620E --npu_mode NPU2 --compiler.check 0",
"pulsar_version":"3.2-99f14d0a",
"capabilities": [
"tts",
"Chinese"
projects/llm_framework/main_tts/mode_single-speaker-english-fast.json
+1 -1
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@@ -1,5 +1,5 @@
{
"mode": "single_speaker_english_fast",
"mode": "single-speaker-english-fast",
"type": "tts",
"homepage":"https://github.com/huakunyang/SummerTTS",
"capabilities": [
projects/llm_framework/main_tts/mode_single-speaker-fast.json
+1 -1
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@@ -1,5 +1,5 @@
{
"mode": "single_speaker_fast",
"mode": "single-speaker-fast",
"type": "tts",
"homepage":"https://github.com/huakunyang/SummerTTS",
"capabilities": [
projects/llm_framework/main_vad/mode_silero-vad.json
+1 -1
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@@ -1,5 +1,5 @@
{
"mode": "silero_vad",
"mode": "silero-vad",
"type": "vad",
"homepage":"https://github.com/snakers4/silero-vad",
"capabilities": [
projects/llm_framework/tools/llm_pack.py
+20 -20
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@@ -69,23 +69,23 @@ def create_lib_deb(package_name, version, src_folder, revision = 'm5stack1'):
# if os.path.exists(zip_file_extrpath):
# shutil.copytree(zip_file_extrpath, os.path.join(deb_folder, 'opt/m5stack/scripts'))
# zip_file = 'm5stack_dist-packages.tar.gz'
# down_url = 'https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/llm/m5stack_dist-packages.tar.gz'
# zip_file_extrpath = 'm5stack_dist-packages'
# if not os.path.exists(zip_file_extrpath):
# # Downloading via HTTP (more common)
# if not os.path.exists(zip_file):
# response = requests.get(down_url)
# if response.status_code == 200:
# with open(zip_file, 'wb') as file:
# file.write(response.content)
# else:
# print("{} down failed".format(down_url))
# with tarfile.open(zip_file, 'r:gz') as tar:
# tar.extractall(path=zip_file_extrpath)
# print("The {} download successful.".format(down_url))
# if os.path.exists(zip_file_extrpath):
# shutil.copytree(zip_file_extrpath, os.path.join(deb_folder, 'usr/local/lib/python3.10/dist-packages'))
zip_file = 'm5stack_dist-packages.tar.gz'
down_url = 'https://m5stack.oss-cn-shenzhen.aliyuncs.com/resource/linux/llm/m5stack_dist-packages.tar.gz'
zip_file_extrpath = 'm5stack_dist-packages'
if not os.path.exists(zip_file_extrpath):
# Downloading via HTTP (more common)
if not os.path.exists(zip_file):
response = requests.get(down_url)
if response.status_code == 200:
with open(zip_file, 'wb') as file:
file.write(response.content)
else:
print("{} down failed".format(down_url))
with tarfile.open(zip_file, 'r:gz') as tar:
tar.extractall(path=zip_file_extrpath)
print("The {} download successful.".format(down_url))
if os.path.exists(zip_file_extrpath):
shutil.copytree(zip_file_extrpath, os.path.join(deb_folder, 'usr/local/lib/python3.10/dist-packages'))
os.makedirs(os.path.join(deb_folder, 'DEBIAN'), exist_ok = True)
with open(os.path.join(deb_folder, 'DEBIAN/control'),'w') as f:
@@ -374,9 +374,9 @@ if __name__ == "__main__":
'llm-model-sherpa-ncnn-streaming-zipformer-zh-14M-2023-02-23':[create_data_deb,'llm-model-sherpa-ncnn-streaming-zipformer-zh-14M-2023-02-23', data_version, src_folder, revision],
'llm-model-sherpa-onnx-kws-zipformer-gigaspeech-3.3M-2024-01-01':[create_data_deb,'llm-model-sherpa-onnx-kws-zipformer-gigaspeech-3.3M-2024-01-01', '0.3', src_folder, revision],
'llm-model-sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01':[create_data_deb,'llm-model-sherpa-onnx-kws-zipformer-wenetspeech-3.3M-2024-01-01', '0.3', src_folder, revision],
'llm-model-single-speaker-english-fast':[create_data_deb,'llm-model-single-speaker-english-fast', data_version, src_folder, revision],
'llm-model-single-speaker-fast':[create_data_deb,'llm-model-single-speaker-fast', data_version, src_folder, revision],
'llm-model-melotts-zh-cn':[create_data_deb,'llm-model-melotts-zh-cn', '0.4', src_folder, revision],
'llm-model-single-speaker-english-fast':[create_data_deb,'llm-model-single-speaker-english-fast', '0.3', src_folder, revision],
'llm-model-single-speaker-fast':[create_data_deb,'llm-model-single-speaker-fast', '0.3', src_folder, revision],
'llm-model-melotts-zh-cn':[create_data_deb,'llm-model-melotts-zh-cn', '0.5', src_folder, revision],
'llm-model-yolo11n':[create_data_deb,'llm-model-yolo11n', data_version, src_folder, revision],
'llm-model-yolo11n-pose':[create_data_deb,'llm-model-yolo11n-pose', '0.3', src_folder, revision],
'llm-model-yolo11n-hand-pose':[create_data_deb,'llm-model-yolo11n-hand-pose', '0.3', src_folder, revision],