73 lines
3.1 KiB
Python
73 lines
3.1 KiB
Python
model_name = "ChatGLM-ONNX"
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cmd_to_install = "`pip install -r request_llm/requirements_chatglm_onnx.txt`"
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from transformers import AutoModel, AutoTokenizer
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import time
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import threading
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import importlib
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from toolbox import update_ui, get_conf
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from multiprocessing import Process, Pipe
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from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns, SingletonLocalLLM
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from .chatglmoonx import ChatGLMModel, chat_template
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# ------------------------------------------------------------------------------------------------------------------------
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# 🔌💻 Local Model
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# ------------------------------------------------------------------------------------------------------------------------
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@SingletonLocalLLM
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class GetONNXGLMHandle(LocalLLMHandle):
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def load_model_info(self):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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self.model_name = model_name
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self.cmd_to_install = cmd_to_install
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def load_model_and_tokenizer(self):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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import os, glob
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if not len(glob.glob("./request_llm/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/*.bin")) >= 7: # 该模型有七个 bin 文件
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from huggingface_hub import snapshot_download
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snapshot_download(repo_id="K024/ChatGLM-6b-onnx-u8s8", local_dir="./request_llm/ChatGLM-6b-onnx-u8s8")
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def create_model():
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return ChatGLMModel(
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tokenizer_path = "./request_llm/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/sentencepiece.model",
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onnx_model_path = "./request_llm/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/chatglm-6b-int8.onnx"
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)
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self._model = create_model()
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return self._model, None
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def llm_stream_generator(self, **kwargs):
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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def adaptor(kwargs):
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query = kwargs['query']
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max_length = kwargs['max_length']
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top_p = kwargs['top_p']
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temperature = kwargs['temperature']
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history = kwargs['history']
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return query, max_length, top_p, temperature, history
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query, max_length, top_p, temperature, history = adaptor(kwargs)
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prompt = chat_template(history, query)
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for answer in self._model.generate_iterate(
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prompt,
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max_generated_tokens=max_length,
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top_k=1,
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top_p=top_p,
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temperature=temperature,
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):
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yield answer
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def try_to_import_special_deps(self, **kwargs):
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# import something that will raise error if the user does not install requirement_*.txt
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# 🏃♂️🏃♂️🏃♂️ 子进程执行
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pass
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# ------------------------------------------------------------------------------------------------------------------------
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# 🔌💻 GPT-Academic Interface
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# ------------------------------------------------------------------------------------------------------------------------
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predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetONNXGLMHandle, model_name) |