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|
| import os
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|
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| from openai import OpenAI
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|
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| os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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|
|
|
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| def get_infer_request():
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| messages = [{'role': 'user', 'content': "How's the weather in Beijing today?"}]
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| tools = [{
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| 'name': 'get_current_weather',
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| 'description': 'Get the current weather in a given location',
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| 'parameters': {
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| 'type': 'object',
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| 'properties': {
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| 'location': {
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| 'type': 'string',
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| 'description': 'The city and state, e.g. San Francisco, CA'
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| },
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| 'unit': {
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| 'type': 'string',
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| 'enum': ['celsius', 'fahrenheit']
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| }
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| },
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| 'required': ['location']
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| }
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| }]
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| return messages, tools
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|
|
|
|
| def infer(client, model: str, messages, tools):
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| messages = messages.copy()
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| query = messages[0]['content']
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| resp = client.chat.completions.create(model=model, messages=messages, tools=tools, max_tokens=512, temperature=0)
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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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| print(f'tool_calls: {resp.choices[0].message.tool_calls}')
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|
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| tool = '{"temperature": 32, "condition": "Sunny", "humidity": 50}'
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| print(f'tool_response: {tool}')
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| messages += [{'role': 'assistant', 'content': response}, {'role': 'tool', 'content': tool}]
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| resp = client.chat.completions.create(model=model, messages=messages, tools=tools, max_tokens=512, temperature=0)
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| response2 = resp.choices[0].message.content
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| print(f'response2: {response2}')
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|
|
|
|
|
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| def infer_stream(client, model: str, messages, tools):
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| messages = messages.copy()
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| query = messages[0]['content']
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| gen = client.chat.completions.create(
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| model=model, messages=messages, tools=tools, max_tokens=512, temperature=0, stream=True)
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| response = ''
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| print(f'query: {query}\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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| delta = chunk.choices[0].delta.content
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| response += delta
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| print(delta, end='', flush=True)
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| print()
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| print(f'tool_calls: {chunk.choices[0].delta.tool_calls}')
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|
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| tool = '{"temperature": 32, "condition": "Sunny", "humidity": 50}'
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| print(f'tool_response: {tool}')
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| messages += [{'role': 'assistant', 'content': response}, {'role': 'tool', 'content': tool}]
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| gen = client.chat.completions.create(
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| model=model, messages=messages, tools=tools, max_tokens=512, temperature=0, stream=True)
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| print(f'query: {query}\nresponse2: ', 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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|
|
|
|
| if __name__ == '__main__':
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| host: str = '127.0.0.1'
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| 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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|
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| messages, tools = get_infer_request()
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| infer(client, model, messages, tools)
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| infer_stream(client, model, messages, tools)
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|
|
