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3.18 kB
| # Copyright (c) Alibaba, Inc. and its affiliates. | |
| import os | |
| from openai import OpenAI | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '0' | |
| def get_infer_request(): | |
| messages = [{'role': 'user', 'content': "How's the weather in Beijing today?"}] | |
| tools = [{ | |
| 'name': 'get_current_weather', | |
| 'description': 'Get the current weather in a given location', | |
| 'parameters': { | |
| 'type': 'object', | |
| 'properties': { | |
| 'location': { | |
| 'type': 'string', | |
| 'description': 'The city and state, e.g. San Francisco, CA' | |
| }, | |
| 'unit': { | |
| 'type': 'string', | |
| 'enum': ['celsius', 'fahrenheit'] | |
| } | |
| }, | |
| 'required': ['location'] | |
| } | |
| }] | |
| return messages, tools | |
| def infer(client, model: str, messages, tools): | |
| messages = messages.copy() | |
| query = messages[0]['content'] | |
| resp = client.chat.completions.create(model=model, messages=messages, tools=tools, max_tokens=512, temperature=0) | |
| response = resp.choices[0].message.content | |
| print(f'query: {query}') | |
| print(f'response: {response}') | |
| print(f'tool_calls: {resp.choices[0].message.tool_calls}') | |
| tool = '{"temperature": 32, "condition": "Sunny", "humidity": 50}' | |
| print(f'tool_response: {tool}') | |
| messages += [{'role': 'assistant', 'content': response}, {'role': 'tool', 'content': tool}] | |
| resp = client.chat.completions.create(model=model, messages=messages, tools=tools, max_tokens=512, temperature=0) | |
| response2 = resp.choices[0].message.content | |
| print(f'response2: {response2}') | |
| # streaming | |
| def infer_stream(client, model: str, messages, tools): | |
| messages = messages.copy() | |
| query = messages[0]['content'] | |
| gen = client.chat.completions.create( | |
| model=model, messages=messages, tools=tools, max_tokens=512, temperature=0, stream=True) | |
| response = '' | |
| print(f'query: {query}\nresponse: ', end='') | |
| for chunk in gen: | |
| if chunk is None: | |
| continue | |
| delta = chunk.choices[0].delta.content | |
| response += delta | |
| print(delta, end='', flush=True) | |
| print() | |
| print(f'tool_calls: {chunk.choices[0].delta.tool_calls}') | |
| tool = '{"temperature": 32, "condition": "Sunny", "humidity": 50}' | |
| print(f'tool_response: {tool}') | |
| messages += [{'role': 'assistant', 'content': response}, {'role': 'tool', 'content': tool}] | |
| gen = client.chat.completions.create( | |
| model=model, messages=messages, tools=tools, max_tokens=512, temperature=0, stream=True) | |
| print(f'query: {query}\nresponse2: ', end='') | |
| for chunk in gen: | |
| if chunk is None: | |
| continue | |
| print(chunk.choices[0].delta.content, end='', flush=True) | |
| print() | |
| if __name__ == '__main__': | |
| 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}') | |
| messages, tools = get_infer_request() | |
| infer(client, model, messages, tools) | |
| infer_stream(client, model, messages, tools) | |