qwenlm--qwen-agent
wehub-resource-sync
110 行
3.6 KiB
Python
110 行
3.6 KiB
Python
# Copyright 2023 The Qwen team, Alibaba Group. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import pytest
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from qwen_agent.llm import get_chat_model
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@pytest.mark.parametrize('cfg', [0, 1])
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@pytest.mark.parametrize('gen_cfg1', [
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None,
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dict(parallel_function_calls=True),
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dict(function_choice='auto'),
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dict(function_choice='none'),
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dict(function_choice='get_current_weather'),
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])
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@pytest.mark.parametrize('gen_cfg2', [
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None,
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dict(function_choice='none'),
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dict(function_choice='get_current_weather'),
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])
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def test_function_content(cfg, gen_cfg1, gen_cfg2):
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if cfg == 0:
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llm = get_chat_model({
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# Use the model service provided by DashScope:
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'model': 'qwen2.5-7b-instruct',
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'model_server': 'dashscope',
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'api_key': os.getenv('DASHSCOPE_API_KEY'),
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'generate_cfg': {
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'fncall_prompt_type': 'qwen'
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},
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})
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else:
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llm = get_chat_model({
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'model': 'qwen2.5-7b-instruct',
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'model_server': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
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'api_key': os.getenv('DASHSCOPE_API_KEY', 'none'),
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'generate_cfg': {
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'fncall_prompt_type': 'qwen'
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},
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})
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# Step 1: send the conversation and available functions to the model
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messages = [{'role': 'user', 'content': "What's the weather like in San Francisco?"}]
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functions = [{
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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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print('# Assistant Response 1:')
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responses = []
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for responses in llm.chat(messages=messages, functions=functions, stream=True, extra_generate_cfg=gen_cfg1):
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print(responses)
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messages.extend(responses) # extend conversation with assistant's reply
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if gen_cfg1 and (gen_cfg1.get('function_choice') == 'none'):
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assert all([('function_call' not in rsp) for rsp in responses])
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return
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# Step 2: check if the model wanted to call a function
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last_response = messages[-1]
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assert last_response.get('function_call')
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messages.append({
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'role': 'function',
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'name': last_response['function_call']['name'],
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'content': '',
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})
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print('# Assistant Response 2:')
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for responses in llm.chat(
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messages=messages,
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functions=functions,
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stream=True,
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extra_generate_cfg=gen_cfg2,
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): # get a new response from the model where it can see the function response
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print(responses)
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if __name__ == '__main__':
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test_function_content(0)
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test_function_content(1)
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