wehub-resource-sync
99 lines
3.1 KiB
Python
99 lines
3.1 KiB
Python
# Copyright (c) ModelScope Contributors. All rights reserved.
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import os
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from openai import OpenAI
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from typing import Literal
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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def infer(client, model: str, messages):
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resp = client.chat.completions.create(model=model, messages=messages, max_tokens=512, temperature=0)
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query = messages[0]['content']
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response = resp.choices[0].message.content
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print(f'query: {query}')
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print(f'response: {response}')
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return response
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# streaming
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def infer_stream(client, model: str, messages):
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gen = client.chat.completions.create(model=model, messages=messages, stream=True, temperature=0)
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print(f'messages: {messages}\nresponse: ', end='')
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for chunk in gen:
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if chunk is None:
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continue
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print(chunk.choices[0].delta.content, end='', flush=True)
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print()
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def get_message(mm_type: Literal['text', 'image', 'video', 'audio']):
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if mm_type == 'text':
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message = {'role': 'user', 'content': 'who are you?'}
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elif mm_type == 'image':
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message = {
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'role':
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'user',
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'content': [{
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'type': 'image',
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'image': 'http://modelscope-open.oss-cn-hangzhou.aliyuncs.com/images/animal.png'
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}, {
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'type': 'text',
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'text': 'How many sheep are there in the picture?'
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}]
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}
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elif mm_type == 'video':
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# # use base64
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# import base64
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# with open('baby.mp4', 'rb') as f:
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# vid_base64 = base64.b64encode(f.read()).decode('utf-8')
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# video = f'data:video/mp4;base64,{vid_base64}'
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# use url
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video = 'https://modelscope-open.oss-cn-hangzhou.aliyuncs.com/images/baby.mp4'
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message = {
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'role': 'user',
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'content': [{
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'type': 'video',
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'video': video
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}, {
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'type': 'text',
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'text': 'Describe this video.'
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}]
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}
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elif mm_type == 'audio':
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message = {
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'role':
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'user',
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'content': [{
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'type': 'audio',
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'audio': 'http://modelscope-open.oss-cn-hangzhou.aliyuncs.com/images/weather.wav'
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}, {
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'type': 'text',
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'text': 'What does this audio say?'
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}]
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}
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return message
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def run_client(host: str = '127.0.0.1', port: int = 8000):
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client = OpenAI(
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api_key='EMPTY',
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base_url=f'http://{host}:{port}/v1',
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)
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model = client.models.list().data[0].id
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print(f'model: {model}')
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query = 'who are you?'
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messages = [{'role': 'user', 'content': query}]
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response = infer(client, model, messages)
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messages.append({'role': 'assistant', 'content': response})
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messages.append(get_message(mm_type='video'))
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infer_stream(client, model, messages)
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if __name__ == '__main__':
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from swift import DeployArguments, run_deploy
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with run_deploy(DeployArguments(model='Qwen/Qwen2.5-VL-3B-Instruct', verbose=False, log_interval=-1)) as port:
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run_client(port=port)
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