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| import gradio as gr | |
| from compressor import PromptCompressor | |
| import os | |
| res = os.popen('python -m spacy download en_core_web_sm').read() | |
| print(res) | |
| def compressit(original_text, compressor1, ratio, maxlength): | |
| if compressor1=="Selective Context": | |
| compressor = PromptCompressor(type='SCCompressor', lang='en', model='gpt2', device='cpu') | |
| elif compressor1=="LLMLingua": | |
| return "Sorry, currently we cannot provide services for LLMLingua due to the Huggingface Token issue. Please try other compressors." | |
| elif compressor1=="LongLLMLingua": | |
| return "Sorry, currently we cannot provide services for LongLLMLingua due to the Huggingface Token issue. Please try other compressors." | |
| elif compressor1=="SCRL": | |
| compressor = PromptCompressor(type='SCRLCompressor', model_dir="models/gigaword-L8/", device="cpu", tokenizer_dir="sentence-transformers/paraphrase-distilroberta-base-v2") | |
| elif compressor1=="KiS": | |
| compressor = PromptCompressor(type='KiSCompressor', device="cpu", model_dir="philippelaban/keep_it_simple") | |
| else: | |
| compressor = PromptCompressor(type='SCCompressor', lang='en', model='gpt2', device='cpu') | |
| if compressor1 == "Selective Context": | |
| compressed_prompt = compressor.compressgo(original_prompt=original_text, ratio=float(ratio)) | |
| else: | |
| if maxlength: | |
| compressed_prompt = compressor.compressgo(original_prompt=original_text, ratio=float(ratio), max_length=int(maxlength)) | |
| else: | |
| gr.Warning("max_length is needed for this type of compressor. Please fill in and try again.") | |
| return "max_length is missing.", 0 | |
| gr.Warning("The prompt is generating, please wait patiently as it may take a long time to generate during busy hours.") | |
| return compressed_prompt["compressed_prompt"], compressed_prompt["ratio"] | |
| demo = gr.Interface( | |
| fn=compressit, | |
| inputs=[ | |
| gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="input", info="Enter the original prompt here."), | |
| gr.Dropdown( | |
| ["Selective Context", "LLMLingua", "LongLLMLingua", "SCRL", "KiS"], label="compressor", info="Choose your compressor here. \n Currently, we cannot support the online demo for LLMLingua and LongLLMLingua due to the Huggingface Token issue." | |
| ), | |
| gr.Textbox(lines=1, placeholder="Enter the compression ratio here...", info="Ratio only works for Selective Context, LLMLingua and LongLLMLingua."), | |
| gr.Textbox(lines=1, placeholder="Enter the max_length parameter (integer) if you are using SCRL or KiS", label="max_length", info="If you are using SCRL or KiS, fill in the parameter, if not, just ignore this.\n Hint: For SCRL, max_length should be shorter than the lenght of original prompt; For KiS, max_length should be longer than it.") | |
| ], | |
| outputs=[ | |
| gr.Textbox(lines=1, label="output", info="Please wait patiently when proceeding it may take more than 2 minutes to generate since we are using CPUs for free."), | |
| gr.Textbox(lines=1, label="ratio", info="With the compression ratio of: ") | |
| ], | |
| examples=[ | |
| ["Read the following poem and summarize it: O Captain! My Captain! our fearful trip is done; The ship has weather'd every rack, the prize we sought is won; The port is near, the bells I hear, the people all exulting, While follow eyes the steady keel, the vessel grim and daring.", "Selective Context", 0.5, 0], | |
| ["Read the following poem and summarize it: O Captain! My Captain! our fearful trip is done; The ship has weather'd every rack, the prize we sought is won; The port is near, the bells I hear, the people all exulting, While follow eyes the steady keel, the vessel grim and daring.", "SCRL", 0, 16], | |
| ] | |
| ) | |
| demo.launch(share=False) | |