67 lines
2.0 KiB
Python
67 lines
2.0 KiB
Python
import json
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import mz_prompt_utils
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import mz_llama_cpp
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import importlib
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phi3_models = [
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"Phi-3-mini-4k-instruct-q4.gguf"
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]
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def get_exist_model(model_name):
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modelscope_model_path = mz_prompt_utils.Utils.modelscope_download_model(
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model_type="phi3",
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model_name=model_name,
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only_get_path=True,
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)
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if modelscope_model_path is not None:
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return modelscope_model_path
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model_url = f"https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf/resolve/main/{model_name}"
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hf_model_path = mz_prompt_utils.Utils.hf_download_model(model_url, only_get_path=True)
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if hf_model_path is not None:
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return hf_model_path
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return None
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def query_beautify_prompt_text(args_dict):
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model_name = args_dict.get("llama_cpp_model", "")
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download_source = args_dict.get("download_source", None)
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import mz_prompts
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importlib.reload(mz_prompts)
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importlib.reload(mz_llama_cpp)
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try:
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model_file = get_exist_model(model_name)
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if model_file is None:
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if download_source == "modelscope":
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model_file = mz_prompt_utils.Utils.modelscope_download_model(
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model_type="phi3",
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model_name=model_name,
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)
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else:
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model_url = f"https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf/resolve/main/{model_name}"
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if download_source == "hf-mirror.com":
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model_url = f"https://hf-mirror.com/microsoft/Phi-3-mini-4k-instruct-gguf/resolve/main/{model_name}"
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model_file = mz_prompt_utils.Utils.hf_download_model(model_url)
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args_dict["llama_cpp_model"] = model_file
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full_response = mz_llama_cpp.base_query_beautify_prompt_text(args_dict=args_dict)
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return full_response
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except Exception as e:
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mz_llama_cpp.freed_gpu_memory(model_file=model_file)
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# mz_utils.Utils.print_log(f"Error in auto_prompt_text: {e}")
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raise e |