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import os |
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from openai import OpenAI |
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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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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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print(chunk.choices[0].delta.content, end='', flush=True) |
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print() |
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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 = 'Where is the capital of Zhejiang?' |
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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({'role': 'user', 'content': 'What delicious food is there?'}) |
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infer_stream(client, model, messages) |
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if __name__ == '__main__': |
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from swift.llm import run_deploy, DeployArguments |
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with run_deploy(DeployArguments(model='Qwen/Qwen2.5-1.5B-Instruct', verbose=False, log_interval=-1)) as port: |
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run_client(port=port) |
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