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from .Linly import Linly |
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from .Qwen import Qwen |
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from .Qwen2 import Qwen2 |
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try: |
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from .Gemini import Gemini |
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except Exception as e: |
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print("Gemini模型加载失败，可能是因为没有google-generativeai库，但是Gemini模型不是必顂的，可以忽略") |
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from .ChatGPT import ChatGPT |
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from .ChatGLM import ChatGLM |
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from .Llama2Chinese import Llama2Chinese |
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from .GPT4Free import GPT4FREE |
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def test_Linly(question = "如何应对压力？", mode='offline', model_path="Linly-AI/Chinese-LLaMA-2-7B-hf"): |
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llm = Linly(mode, model_path) |
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answer = llm.generate(question) |
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print(answer) |
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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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def test_ChatGPT(question = "如何应对压力？", model_path = 'gpt-3.5-turbo', api_key = None, proxy_url = None): |
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llm = ChatGPT(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, prefix_prompt='''请用少于25个字回答以下问题\n\n'''): |
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if model_name not in ['Linly', 'Qwen', 'Qwen2', 'Gemini', 'ChatGLM', 'ChatGPT', 'Llama2Chinese', 'GPT4Free', '直接回复 Direct Reply']: |
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raise ValueError("model_name must be one of ['Linly', 'Qwen', 'Gemini', 'ChatGLM', 'ChatGPT', 'Llama2Chinese', 'GPT4Free']") |
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if model_name == 'Linly': |
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llm = Linly(self.mode, model_path) |
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elif model_name == 'Qwen': |
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llm = Qwen(self.mode, model_path) |
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elif model_name == 'Qwen2': |
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llm = Qwen2(self.mode, model_path) |
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elif model_name == 'Gemini': |
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llm = Gemini(model_path, api_key, proxy_url) |
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elif model_name == 'ChatGLM': |
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llm = ChatGLM(self.mode, model_path) |
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elif model_name == 'ChatGPT': |
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llm = ChatGPT(model_path, api_key, proxy_url) |
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elif model_name == 'Llama2Chinese': |
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llm = Llama2Chinese(model_path, self.mode) |
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elif model_name == 'GPT4Free': |
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llm = GPT4FREE() |
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elif model_name == '直接回复 Direct Reply': |
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llm = self |
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llm.prefix_prompt = prefix_prompt |
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return llm |
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def generate(self, question, system_prompt = 'system无效'): |
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return question |
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def test_Linly(self, question="如何应对压力？", model_path="Linly-AI/Chinese-LLaMA-2-7B-hf"): |
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llm = Linly(self.mode, model_path) |
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answer = llm.generate(question) |
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print(answer) |
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def test_Qwen(self, question="如何应对压力？", model_path="Qwen/Qwen-1_8B-Chat"): |
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llm = Qwen(self.mode, model_path) |
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answer = llm.generate(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.generate(question) |
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print(answer) |
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def test_ChatGPT(self, question="如何应对压力？", model_path = 'gpt-3.5-turbo', api_key = None, proxy_url = None): |
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llm = ChatGPT(model_path, api_key, proxy_url) |
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answer = llm.generate(question) |
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print(answer) |
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def test_ChatGLM(self, question="如何应对压力？", model_path="THUDM/chatglm-6b"): |
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llm = ChatGLM(mode=self.mode, model_name_or_path=model_path) |
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answer = llm.generate(question) |
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print(answer) |
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if __name__ == '__main__': |
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llm_class = LLM(mode='offline') |
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llm_class.init_model('直接回复 Direct Reply') |
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question = '如何应对压力？' |
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answer = llm_class.generate(question) |
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