55 lines
2.2 KiB
Python
55 lines
2.2 KiB
Python
from llm.Qwen import Qwen
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from llm.Gemini import Gemini
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from llm.ChatGPT import ChatGPT
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from llm.VllmGPT import VllmGPT
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def test_Qwen(question = "如何应对压力？", mode='offline', model_path="Qwen/Qwen-1_8B-Chat"):
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llm = Qwen(mode, model_path)
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answer = llm.generate(question)
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print(answer)
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def test_Gemini(question = "如何应对压力？", model_path='gemini-pro', api_key=None, proxy_url=None):
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llm = Gemini(model_path, api_key, proxy_url)
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answer = llm.generate(question)
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print(answer)
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class LLM:
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def __init__(self, mode='offline'):
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self.mode = mode
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def init_model(self, model_name, model_path, api_key=None, proxy_url=None):
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if model_name not in ['Qwen', 'Gemini', 'ChatGPT', 'VllmGPT']:
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raise ValueError("model_name must be 'ChatGPT', 'VllmGPT', 'Qwen', or 'Gemini'(其他模型还未集成)")
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if model_name == 'Gemini':
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llm = Gemini(model_path, api_key, proxy_url)
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elif model_name == 'ChatGPT':
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llm = ChatGPT(model_path, api_key=api_key)
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elif model_name == 'Qwen':
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llm = Qwen(model_path=model_path, api_key=api_key, api_base=proxy_url)
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elif model_name == 'VllmGPT':
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llm = VllmGPT()
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return llm
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def test_Qwen(self, question="如何应对压力？", model_path="Qwen/Qwen-1_8B-Chat", api_key=None, proxy_url=None):
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llm = Qwen(model_path=model_path, api_key=api_key, api_base=proxy_url)
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answer = llm.chat(question)
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print(answer)
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def test_Gemini(self, question="如何应对压力？", model_path='gemini-pro', api_key=None, proxy_url=None):
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llm = Gemini(model_path, api_key, proxy_url)
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answer = llm.chat(question)
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print(answer)
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if __name__ == '__main__':
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llm = LLM()
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# llm.test_Gemini(api_key='你的API Key', proxy_url=None)
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# llm = LLM().init_model('Gemini', model_path= 'gemini-pro',api_key='AIzaSyBWAWfT8zsyAZcRIXLS5Vzlw8KKCN9qsAg', proxy_url='http://172.31.71.58:7890')
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# response = llm.chat("如何应对压力？")
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# llm = LLM().init_model('VllmGPT', model_path= 'THUDM/chatglm3-6b')
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# response = llm.chat("如何应对压力？")
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# print(response)
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llm.test_Qwen(api_key="none", proxy_url="http://10.1.1.113:18000/v1")
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