handle local llm dependency error properly
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@ -58,8 +58,8 @@ class GetONNXGLMHandle(LocalLLMHandle):
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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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# 🏃♂️🏃♂️🏃♂️ 主进程执行
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# from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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pass
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import importlib
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importlib.import_module('modelscope')
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# ------------------------------------------------------------------------------------------------------------------------
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@ -124,6 +124,7 @@ def get_local_llm_predict_fns(LLMSingletonClass, model_name):
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"""
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_llm_handle = LLMSingletonClass()
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if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + _llm_handle.info
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if not _llm_handle.running: raise RuntimeError(_llm_handle.info)
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# chatglm 没有 sys_prompt 接口,因此把prompt加入 history
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history_feedin = []
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@ -152,6 +153,7 @@ def get_local_llm_predict_fns(LLMSingletonClass, model_name):
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_llm_handle = LLMSingletonClass()
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chatbot[-1] = (inputs, load_message + "\n\n" + _llm_handle.info)
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yield from update_ui(chatbot=chatbot, history=[])
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if not _llm_handle.running: raise RuntimeError(_llm_handle.info)
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if additional_fn is not None:
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from core_functional import handle_core_functionality
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