70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
# coding=utf-8
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# Implements stream chat in command line for fine-tuned models.
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# Usage: python cli_demo.py --model_name_or_path path_to_model --checkpoint_dir path_to_checkpoint
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from threading import Thread
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from transformers import TextIteratorStreamer
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from llmtuner import Template, get_infer_args, load_model_and_tokenizer, get_logits_processor
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def main():
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model_args, data_args, finetuning_args, generating_args = get_infer_args()
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model, tokenizer = load_model_and_tokenizer(model_args, finetuning_args)
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prompt_template = Template(data_args.prompt_template)
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source_prefix = data_args.source_prefix if data_args.source_prefix else ""
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def predict_and_print(query, history: list) -> list:
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input_ids = tokenizer([prompt_template.get_prompt(query, history, source_prefix)], return_tensors="pt")["input_ids"]
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input_ids = input_ids.to(model.device)
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streamer = TextIteratorStreamer(tokenizer, timeout=60.0, skip_prompt=True, skip_special_tokens=True)
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gen_kwargs = generating_args.to_dict()
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gen_kwargs.update({
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"input_ids": input_ids,
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"logits_processor": get_logits_processor(),
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"streamer": streamer
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})
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thread = Thread(target=model.generate, kwargs=gen_kwargs)
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thread.start()
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print("Assistant: ", end="", flush=True)
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response = ""
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for new_text in streamer:
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print(new_text, end="", flush=True)
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response += new_text
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print()
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history = history + [(query, response)]
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return history
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history = []
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print("Welcome to the CLI application, use `clear` to remove the history, use `exit` to exit the application.")
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while True:
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try:
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query = input("\nUser: ")
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except UnicodeDecodeError:
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print("Detected decoding error at the inputs, please set the terminal encoding to utf-8.")
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continue
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except Exception:
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raise
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if query.strip() == "exit":
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break
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if query.strip() == "clear":
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history = []
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print("History has been removed.")
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continue
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history = predict_and_print(query, history)
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if __name__ == "__main__":
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main()
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