portugalfuturista/z-ai-sdk-python
2
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

feat: update tts asr api and samples (#58)

Browse source
This commit is contained in:
666ycy 2026-01-12 18:33:42 +08:00 committed by GitHub
parent 55646149ff
commit 3a21569744
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
6 changed files with 205 additions and 20 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

82
examples/audio_speech_example.py Normal file
View file

@ -0,0 +1,82 @@
from zai import ZaiClient
import os
import traceback
import uuid
# Change working directory to project root
script_dir = os.path.dirname(os.path.abspath(__file__))
project_root = os.path.dirname(script_dir)
os.chdir(project_root)
def text_to_speech_non_stream():
# Initialize client
client = ZaiClient()
# Audio format
# Supported response formats: wav, pcm (default)
response_format = 'pcm'
try:
# Generate speech audio from text
response = client.audio.speech(
model='glm-tts',
input='Hello, this is a test for text-to-speech functionality.',
voice='tongtong',
response_format=response_format,
stream=False
)
# Save audio to file with unique name
output_file = f"audio_speech_{uuid.uuid4()}.{response_format}"
with open(output_file, 'wb') as f:
f.write(response.content)
print(f"Audio saved to {os.path.abspath(output_file)}")
except Exception as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
raise
def text_to_speech_stream():
# Initialize client
client = ZaiClient()
# Audio format
# Streaming only supports pcm format
response_format = 'pcm'
try:
# Generate speech audio with streaming
response = client.audio.speech(
model='glm-tts',
input='Hello, this is a test for text-to-speech functionality.',
voice='tongtong',
response_format=response_format,
stream=True
)
# Process streaming response
chunk_index = 0
for chunk in response:
try:
choice = chunk.choices[0]
if choice.delta is None:
break
if choice.delta.content:
print(f"[Chunk {chunk_index}] {choice.delta.content}")
chunk_index += 1
except (AttributeError, IndexError) as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
except Exception as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
raise
if __name__ == '__main__':
# Non-streaming text to speech
text_to_speech_non_stream()
# Streaming text to speech
# text_to_speech_stream()

83
examples/audio_transcriptions_example.py Normal file
View file

@ -0,0 +1,83 @@
from zai import ZaiClient
import os
import traceback
# Change working directory to project root
script_dir = os.path.dirname(os.path.abspath(__file__))
project_root = os.path.dirname(script_dir)
os.chdir(project_root)
def audio_transcription_non_stream():
# Initialize client
client = ZaiClient()
# Audio file path
# Supported formats: .wav, .mp3
# File size limit: <= 25 MB, Duration limit: <= 30 seconds
audio_file_path = "tests/integration_tests/asr.wav"
# Check if file exists
if not os.path.exists(audio_file_path):
print(f"Audio file not found: {audio_file_path}")
return
try:
# Open the audio file and create transcription
with open(audio_file_path, 'rb') as audio_file:
response = client.audio.transcriptions.create(
model='glm-asr-2512',
file=audio_file,
stream=False
)
# Print transcription result
print(response.text)
except Exception as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
raise
def audio_transcription_stream():
# Initialize client
client = ZaiClient()
# Audio file path
# Supported formats: .wav, .mp3
# File size limit: <= 25 MB, Duration limit: <= 30 seconds
audio_file_path = "tests/integration_tests/asr.wav"
# Check if file exists
if not os.path.exists(audio_file_path):
print(f"Audio file not found: {audio_file_path}")
return
try:
# Open the audio file and create transcription with streaming
with open(audio_file_path, 'rb') as audio_file:
response = client.audio.transcriptions.create(
model='glm-asr-2512',
file=audio_file,
stream=True
)
# Process streaming response
print("Streaming transcription:")
for chunk in response:
try:
if hasattr(chunk, 'delta') and chunk.delta:
print(chunk.delta, flush=True)
except (AttributeError, IndexError) as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
except Exception as e:
print(f"Exception: {e}\nTraceback: {traceback.format_exc()}")
raise
if __name__ == '__main__':
# Non-streaming audio transcription
audio_transcription_non_stream()
# Streaming audio transcription
# audio_transcription_stream()

16
src/zai/api_resource/audio/audio.py
View file

@ -51,6 +51,7 @@ class Audio(BaseAPI):
input: str = None,
voice: str = None,
response_format: str = None,
watermark_enabled: Optional[bool] | NotGiven = NOT_GIVEN,
sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN,
request_id: str = None,
user_id: str = None,
@ -66,13 +67,18 @@ class Audio(BaseAPI):
Generate speech audio from text input
Arguments:
model (str): The model to use for speech generation
input (str): The text to convert to speech
voice (str): The voice to use for speech generation
response_format (str): The format of the response audio
model (str): The model to use for speech generation (e.g., 'glm-tts')
input (str): The text to convert to speech (max length: 1024 characters)
voice (str): The voice to use for speech generation (e.g., 'tongtong', 'chuichui', 'xiaochen', etc.)
response_format (str): The format of the response audio ('wav' or 'pcm', default 'pcm')
watermark_enabled (Optional[bool]): Whether to enable watermark on generated audio
sensitive_word_check (Optional[SensitiveWordCheckRequest]): Sensitive word check configuration
request_id (str): Unique identifier for the request
user_id (str): User identifier
encode_format (str): Encoding format for streaming response ('base64' or 'hex', default 'base64')
speed (float): Speech speed, default 1.0, valid range [0.5, 2]
volume (float): Audio volume, default 1.0, valid range (0, 10]
stream (bool): Whether to use streaming output (default False)
extra_headers (Headers): Additional headers to send
extra_body (Body): Additional body parameters
timeout (float | httpx.Timeout): Request timeout
@ -83,6 +89,8 @@ class Audio(BaseAPI):
'input': input,
'voice': voice,
'response_format': response_format,
'watermark_enabled': watermark_enabled,
'sensitive_word_check': sensitive_word_check,
'encode_format': encode_format,
'request_id': request_id,
'user_id': user_id,

20
src/zai/api_resource/audio/transcriptions.py
View file

@ -1,7 +1,7 @@
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Mapping, Optional, cast
from typing import TYPE_CHECKING, List, Mapping, Optional, cast
import httpx
from typing_extensions import Literal
@ -43,10 +43,12 @@ class Transcriptions(BaseAPI):
*,
file: FileTypes,
model: str,
file_base64: Optional[str] | NotGiven = NOT_GIVEN,
prompt: Optional[str] | NotGiven = NOT_GIVEN,
hotwords: Optional[List[str]] | NotGiven = NOT_GIVEN,
request_id: Optional[str] | NotGiven = NOT_GIVEN,
user_id: Optional[str] | NotGiven = NOT_GIVEN,
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
temperature: Optional[float] | NotGiven = NOT_GIVEN,
sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN,
extra_headers: Headers | None = None,
extra_body: Body | None = None,
@ -58,28 +60,26 @@ class Transcriptions(BaseAPI):
Arguments:
file (FileTypes): Audio file to transcribe
model (str): The model to use for transcription
file_base64 (Optional[str]): Base64 encoded audio file (alternative to file)
prompt (Optional[str]): Previous transcription result for context
hotwords (Optional[List[str]]): Hot words to improve recognition rate
request_id (Optional[str]): Unique identifier for the request
user_id (Optional[str]): User identifier
stream (Optional[Literal[False]] | Literal[True]): Whether to stream the response
temperature (Optional[float]): Sampling temperature for transcription
sensitive_word_check (Optional[SensitiveWordCheckRequest]): Sensitive word check configuration
extra_headers (Headers): Additional headers to send
extra_body (Body): Additional body parameters
timeout (float | httpx.Timeout): Request timeout
"""
if temperature is not None and temperature != NOT_GIVEN:
if temperature <= 0:
temperature = 0.01
if temperature >= 1:
temperature = 0.99
body = deepcopy_minimal(
{
'model': model,
'file': file,
'file_base64': file_base64,
'prompt': prompt,
'hotwords': hotwords,
'request_id': request_id,
'user_id': user_id,
'temperature': temperature,
'sensitive_word_check': sensitive_word_check,
'stream': stream,
}

12
src/zai/types/audio/audio_speech_params.py
View file

@ -16,6 +16,11 @@ class AudioSpeechParams(TypedDict, total=False):
input (str): Text to be converted to speech
voice (str): Voice tone for speech generation
response_format (str): Format of the generated audio file
watermark_enabled (Optional[bool]): Whether to enable watermark on generated audio
encode_format (str): Encoding format for streaming response (base64 or hex)
speed (float): Speech speed, default 1.0, range [0.5, 2]
volume (float): Audio volume, default 1.0, range (0, 10]
stream (bool): Whether to use streaming output
sensitive_word_check (Optional[SensitiveWordCheckRequest]): Sensitive word check configuration
request_id (str): Request ID passed by client, must be unique; used to distinguish each request,
platform will generate default if not provided by client
@ -26,10 +31,11 @@ class AudioSpeechParams(TypedDict, total=False):
input: str
voice: str
response_format: str
sensitive_word_check: Optional[SensitiveWordCheckRequest]
request_id: str
user_id: str
watermark_enabled: Optional[bool]
encode_format: str
speed: float
volume: float
stream: bool
sensitive_word_check: Optional[SensitiveWordCheckRequest]
request_id: str
user_id: str

12
src/zai/types/audio/transcriptions_create_param.py
View file

@ -1,6 +1,6 @@
from __future__ import annotations
from typing import Optional
from typing import List, Optional
from typing_extensions import TypedDict
@ -13,7 +13,10 @@ class TranscriptionsParam(TypedDict, total=False):
Attributes:
model (str): Model encoding.
temperature (float): Sampling temperature.
file (str): Audio file to transcribe.
file_base64 (str): Base64 encoded audio file (alternative to file).
prompt (str): Previous transcription result for context in long text scenarios.
hotwords (List[str]): Hot words to improve recognition rate for specific domain vocabulary.
stream (bool): Whether to use streaming output.
sensitive_word_check (Optional[SensitiveWordCheckRequest]): Sensitive word check configuration.
request_id (str): Passed by the client, must ensure uniqueness; used to distinguish
@ -23,7 +26,10 @@ class TranscriptionsParam(TypedDict, total=False):
"""
model: str
temperature: float
file: str
file_base64: str
prompt: str
hotwords: List[str]
stream: bool
sensitive_word_check: Optional[SensitiveWordCheckRequest]
request_id: str