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