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| """ | |
| deploy-as-bot\gradio_chatbot.py | |
| A system, method for deploying to Gradio. Gradio is a basic "deploy" interface which allows for other users to test your model from a web URL. It also enables some basic functionality like user flagging for weird responses. | |
| Note that the URL is displayed once the script is run. | |
| Set the working directory to */deploy-as-bot in terminal before running. | |
| """ | |
| import os | |
| import sys | |
| from os.path import dirname | |
| sys.path.append(dirname(dirname(os.path.abspath(__file__)))) | |
| import gradio as gr | |
| import logging | |
| import argparse | |
| import time | |
| import warnings | |
| from pathlib import Path | |
| from cleantext import clean | |
| from transformers import pipeline | |
| from datetime import datetime | |
| from ai_single_response import query_gpt_model | |
| #from gradio.networking import get_state, set_state | |
| from flask import Flask, request, session, jsonify, abort, send_file, render_template, redirect | |
| import nltk | |
| nltk.download('stopwords') | |
| warnings.filterwarnings(action="ignore", message=".*gradient_checkpointing*") | |
| logging.basicConfig() | |
| cwd = Path.cwd() | |
| my_cwd = str(cwd.resolve()) # string so it can be passed to os.path() objects | |
| def gramformer_correct(corrector, qphrase: str): | |
| """ | |
| gramformer_correct - correct a string using a text2textgen pipeline model from transformers | |
| Args: | |
| corrector (transformers.pipeline): [transformers pipeline object, already created w/ relevant model] | |
| qphrase (str): [text to be corrected] | |
| Returns: | |
| [str]: [corrected text] | |
| """ | |
| try: | |
| corrected = corrector( | |
| clean(qphrase), return_text=True, clean_up_tokenization_spaces=True | |
| ) | |
| return corrected[0]["generated_text"] | |
| except: | |
| print("NOTE - failed to correct with gramformer") | |
| return clean(qphrase) | |
| def ask_gpt(message: str, sender: str = ""): | |
| """ | |
| ask_gpt - queries the relevant model with a prompt message and (optional) speaker name | |
| Args: | |
| message (str): prompt message to respond to | |
| sender (str, optional): speaker aka who said the message. Defaults to "". | |
| Returns: | |
| [str]: [model response as a string] | |
| """ | |
| st = time.time() | |
| prompt = clean(message) # clean user input | |
| prompt = prompt.strip() # get rid of any extra whitespace | |
| if len(prompt) > 200: | |
| prompt = prompt[-200:] # truncate | |
| sender = clean(sender.strip()) | |
| if len(sender) > 2: | |
| try: | |
| prompt_speaker = clean(sender) | |
| except: | |
| # there was some issue getting that info, whatever | |
| prompt_speaker = None | |
| else: | |
| prompt_speaker = None | |
| resp = query_gpt_model( | |
| folder_path=model_loc, | |
| prompt_msg=prompt, | |
| speaker=prompt_speaker, | |
| kparam=150, | |
| temp=0.75, | |
| top_p=0.65, # optimize this with hyperparam search | |
| ) | |
| bot_resp = gramformer_correct(corrector, qphrase=resp["out_text"]) | |
| rt = round(time.time() - st, 2) | |
| print(f"took {rt} sec to respond") | |
| return bot_resp | |
| def chat(first_and_last_name, message): | |
| """ | |
| chat - helper function that makes the whole gradio thing work. | |
| Args: | |
| first_and_last_name (str or None): [speaker of the prompt, if provided] | |
| message (str): [description] | |
| Returns: | |
| [str]: [returns an html string to display] | |
| """ | |
| history = [] | |
| response = ask_gpt(message, sender=first_and_last_name) | |
| history.append((f"{first_and_last_name}: " + message, " GPT-Model: " + response)) #+ " [end] ")) | |
| #html = "<div class='chatbot'>" | |
| #for user_msg, resp_msg in history: | |
| # html += f"<div class='user_msg'>{user_msg}</div>" | |
| # html += f"<div class='resp_msg' style='color: black'>{resp_msg}</div>" | |
| #html += "</div>" | |
| return history | |
| def get_parser(): | |
| """ | |
| get_parser - a helper function for the argparse module | |
| Returns: | |
| [argparse.ArgumentParser]: [the argparser relevant for this script] | |
| """ | |
| parser = argparse.ArgumentParser( | |
| description="submit a message and have a 774M parameter GPT model respond" | |
| ) | |
| parser.add_argument( | |
| "--model", | |
| required=False, | |
| type=str, | |
| # "gp2_DDandPeterTexts_774M_73Ksteps", - from GPT-Peter | |
| default="GPT2_trivNatQAdailydia_774M_175Ksteps", | |
| help="folder - with respect to git directory of your repo that has the model files in it (pytorch.bin + " | |
| "config.json). No models? Run the script download_models.py", | |
| ) | |
| parser.add_argument( | |
| "--gram-model", | |
| required=False, | |
| type=str, | |
| default="pszemraj/t5-v1_1-base-ft-jflAUG", | |
| help="text2text generation model ID from huggingface for the model to correct grammar", | |
| ) | |
| return parser | |
| if __name__ == "__main__": | |
| args = get_parser().parse_args() | |
| default_model = str(args.model) | |
| model_loc = cwd.parent / default_model | |
| model_loc = str(model_loc.resolve()) | |
| gram_model = args.gram_model | |
| print(f"using model stored here: \n {model_loc} \n") | |
| corrector = pipeline("text2text-generation", model=gram_model, device=-1) | |
| print("Finished loading the gramformer model - ", datetime.now()) | |
| iface = gr.Interface( | |
| chat, | |
| inputs=["text", "text"], | |
| outputs="html", | |
| title="Real-Impact English Chat Demo 英语聊天演示", | |
| description="A basic interface with a neural network model trained on general Q&A and conversation. Treat it like a friend! 带有模型的基本界面，进行了一般问答和对话训练。 请像朋友一样与他对话！ \n first and last name 姓名 \n message 信息 \n Clear 清除 \nSubmit 确认 \n Screenshot 截屏", | |
| article="**Important Notes & About: 重要说明 & 关于我们**\n" | |
| "1. the model can take up to 200 seconds to respond sometimes, patience is a virtue. 该模型有时可能需要长达 60 秒的响应时间，请耐心等待。\n" | |
| "2. entering a username is completely optional. 姓名输入是可选的。\n " | |
| "3. the model was trained on several different datasets. Anything it says should be fact-checked before being regarded as a true statement. 该模型在几个不同的数据集上训练而成，它所说的任何内容都应该经过事实核查，然后才能被视为真实陈述。\n ", | |
| css=""" | |
| .chatbox {display:flex;flex-direction:column} | |
| .user_msg, .resp_msg {padding:4px;margin-bottom:4px;border-radius:4px;width:80%} | |
| .user_msg {background-color:cornflowerblue;color:white;align-self:start} | |
| .resp_msg {background-color:lightgray;align-self:self-end} | |
| """, | |
| allow_screenshot=True, | |
| allow_flagging=False, | |
| flagging_dir="gradio_data", | |
| flagging_options=[ | |
| "great response", | |
| "doesn't make sense", | |
| "bad/offensive response", | |
| ], | |
| enable_queue=True, # allows for dealing with multiple users simultaneously | |
| #theme="darkhuggingface", | |
| #server_name="0.0.0.0", | |
| ) | |
| iface.launch(share=True) | |