# -*- coding: utf-8 -*-
"""Use DashScope API to generate images,
convert text to audio, and convert images to text.
Please refer to the official documentation for more details:
https://dashscope.aliyun.com/
"""
from typing import Union, Optional, Literal, Sequence
import os
from ...models import (
DashScopeImageSynthesisWrapper,
DashScopeMultiModalWrapper,
)
from ..service_response import (
ServiceResponse,
ServiceExecStatus,
)
from ...utils.common import _download_file
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def dashscope_text_to_image(
prompt: str,
api_key: str,
n: int = 1,
size: Literal["1024*1024", "720*1280", "1280*720"] = "1024*1024",
model: str = "wanx-v1",
save_dir: Optional[str] = None,
) -> ServiceResponse:
"""Generate image(s) based on the given prompt, and return image url(s).
Args:
prompt (`str`):
The text prompt to generate image.
api_key (`str`):
The api key for the dashscope api.
n (`int`, defaults to `1`):
The number of images to generate.
size (`Literal["1024*1024", "720*1280", "1280*720"]`, defaults to
`"1024*1024"`):
Size of the image.
model (`str`, defaults to '"wanx-v1"'):
The model to use.
save_dir (`Optional[str]`, defaults to 'None'):
The directory to save the generated images. If not specified,
will return the web urls.
Returns:
ServiceResponse:
A dictionary with two variables: `status` and`content`.
If `status` is ServiceExecStatus.SUCCESS,
the `content` is a dict with key 'fig_paths" and
value is a list of the paths to the generated images.
Example:
.. code-block:: python
prompt = "A beautiful sunset in the mountains"
print(dashscope_text_to_image(prompt, "{api_key}"))
> {
> 'status': 'SUCCESS',
> 'content': {'image_urls': ['IMAGE_URL1', 'IMAGE_URL2']}
> }
"""
text2img = DashScopeImageSynthesisWrapper(
config_name="dashscope-text-to-image-service", # Just a placeholder
model_name=model,
api_key=api_key,
)
try:
res = text2img(
prompt=prompt,
n=n,
size=size,
)
urls = res.image_urls
# save images to save_dir
if urls is not None:
if save_dir:
os.makedirs(save_dir, exist_ok=True)
urls_local = []
# Obtain the image file names in the url
for url in urls:
image_name = url.split("/")[-1]
image_path = os.path.abspath(
os.path.join(save_dir, image_name),
)
# Download the image
_download_file(url, image_path)
urls_local.append(image_path)
return ServiceResponse(
ServiceExecStatus.SUCCESS,
{"image_urls": urls_local},
)
else:
# Return the web urls
return ServiceResponse(
ServiceExecStatus.SUCCESS,
{"image_urls": urls},
)
else:
return ServiceResponse(
ServiceExecStatus.ERROR,
"Error: Failed to generate images",
)
except Exception as e:
return ServiceResponse(
ServiceExecStatus.ERROR,
str(e),
)
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def dashscope_image_to_text(
image_urls: Union[str, Sequence[str]],
api_key: str,
prompt: str = "Describe the image",
model: str = "qwen-vl-plus",
) -> ServiceResponse:
"""Generate text based on the given images.
Args:
image_urls (`Union[str, Sequence[str]]`):
The url of single or multiple images.
api_key (`str`):
The api key for the dashscope api.
prompt (`str`, defaults to 'Describe the image' ):
The text prompt.
model (`str`, defaults to 'qwen-vl-plus'):
The model to use in DashScope MultiModal API.
Returns:
`ServiceResponse`:
A dictionary with two variables: `status` and`content`.
If `status` is ServiceExecStatus.SUCCESS, the `content` is the
generated text.
Example:
.. code-block:: python
image_url = "image.jpg"
prompt = "Describe the image"
print(image_to_text(image_url, prompt))
> {'status': 'SUCCESS', 'content': 'A beautiful sunset in the mountains'}
"""
img2text = DashScopeMultiModalWrapper(
config_name="dashscope-image-to-text-service", # Just a placeholder
model_name=model,
api_key=api_key,
)
if isinstance(image_urls, str):
image_urls = [image_urls]
# Check if the local url is valid
img_abs_urls = []
for url in image_urls:
if os.path.exists(url):
if os.path.isfile(url):
img_abs_urls.append(os.path.abspath(url))
else:
return ServiceResponse(
ServiceExecStatus.ERROR,
f'Error: The input image url "{url}" is not a file.',
)
else:
# Maybe a web url or an invalid url, we leave it to the API
# to handle
img_abs_urls.append(url)
# Convert image paths according to the model requirements
contents = img2text.convert_url(img_abs_urls)
contents.append({"text": prompt})
# currently only support one round of conversation
# if multiple rounds of conversation are needed,
# it would be better to implement an Agent class
sys_message = {
"role": "system",
"content": [{"text": "You are a helpful assistant."}],
}
user_message = {
"role": "user",
"content": contents,
}
messages = [sys_message, user_message]
try:
res = img2text(messages, stream=False)
description = res.text
if description is not None:
return ServiceResponse(
ServiceExecStatus.SUCCESS,
description,
)
else:
return ServiceResponse(
ServiceExecStatus.ERROR,
"Error: Failed to generate text",
)
except Exception as e:
return ServiceResponse(
ServiceExecStatus.ERROR,
str(e),
)
[文档]
def dashscope_text_to_audio(
text: str,
api_key: str,
save_dir: str,
model: str = "sambert-zhichu-v1",
sample_rate: int = 48000,
) -> ServiceResponse:
"""Convert the given text to audio.
Args:
text (`str`):
The text to be converted into audio.
api_key (`str`):
The api key for the dashscope API.
save_dir (`str`):
The directory to save the generated audio.
model (`str`, defaults to 'sambert-zhichu-v1'):
The model to use. Full model list can be found in
https://help.aliyun.com/zh/dashscope/model-list
sample_rate (`int`, defaults to 48000):
Samplerate of the audio.
Returns:
`ServiceResponse`:
A dictionary with two variables: `status` and`content`. If
`status` is ServiceExecStatus.SUCCESS, the `content` contains
a dictionary with key "audio_path" and value is the path to
the generated audio.
Example:
.. code-block:: python
text = "How is the weather today?"
print(text_to_audio(text)) gives:
> {'status': 'SUCCESS', 'content': {"audio_path": "AUDIO_PATH"}}
"""
try:
import dashscope
except ImportError as e:
raise ImportError(
"The package 'dashscope' is not installed. Please install it by "
"running `pip install dashscope>=1.19.0`",
) from e
dashscope.api_key = api_key
res = dashscope.audio.tts.SpeechSynthesizer.call(
model=model,
text=text,
sample_rate=sample_rate,
format="wav",
)
audio_data = res.get_audio_data()
if audio_data is not None:
if save_dir is not None:
os.makedirs(save_dir, exist_ok=True)
# Save locally
text = text[0:15] if len(text) > 15 else text
audio_path = os.path.join(save_dir, f"{text.strip()}.wav")
with open(audio_path, "wb") as f:
f.write(audio_data)
return ServiceResponse(
ServiceExecStatus.SUCCESS,
{"audio_path": audio_path},
)
else:
return ServiceResponse(
ServiceExecStatus.ERROR,
"Error: Failed to generate audio",
)