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| import os | |
| import gradio as gr | |
| import clueai | |
| import torch | |
| from transformers import T5Tokenizer, T5ForConditionalGeneration | |
| tokenizer = T5Tokenizer.from_pretrained("huolongguo10/HR_Chat") | |
| model = T5ForConditionalGeneration.from_pretrained("huolongguo10/HR_Chat") | |
| # 使用 | |
| device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') | |
| model.to(device) | |
| base_info = "用户：你是谁？\n小元：我是huolongguo10助手智能助手。\n" | |
| def preprocess(text): | |
| text = f"{base_info}{text}" | |
| text = text.replace("\n", "\\n").replace("\t", "\\t") | |
| return text | |
| def postprocess(text): | |
| return text.replace("\\n", "\n").replace("\\t", "\t").replace('%20',' ')#.replace(" ", " ") | |
| generate_config = {'do_sample': True, 'top_p': 0.9, 'top_k': 50, 'temperature': 0.9, | |
| 'num_beams': 1, 'max_length': 1024, 'min_length': 3, 'no_repeat_ngram_size': 5, | |
| 'length_penalty': 0.6, 'return_dict_in_generate': True, 'output_scores': True} | |
| def answer(text, sample=True, top_p=0.9, temperature=0.9): | |
| '''sample：是否抽样。生成任务，可以设置为True; | |
| top_p：0-1之间，生成的内容越多样''' | |
| text = preprocess(text) | |
| encoding = tokenizer(text=[text], truncation=True, padding=True, max_length=1024, return_tensors="pt").to(device) | |
| if not sample: | |
| out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=1024, num_beams=1, length_penalty=0.6) | |
| else: | |
| out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=1024, do_sample=True, top_p=top_p, temperature=temperature, no_repeat_ngram_size=12) | |
| #out=model.generate(**encoding, **generate_config) | |
| out_text = tokenizer.batch_decode(out["sequences"], skip_special_tokens=True) | |
| return postprocess(out_text[0]) | |
| def clear_session(): | |
| return '', None | |
| def chatyuan_bot(input, history): | |
| history = history or [] | |
| if len(history) > 5: | |
| history = history[-5:] | |
| context = "\n".join([f"用户：{input_text}\n小元：{answer_text}" for input_text, answer_text in history]) | |
| #print(context) | |
| input_text = context + "\n用户：" + input + "\n小元：" | |
| input_text = input_text.strip() | |
| output_text = answer(input_text) | |
| print("open_model".center(20, "=")) | |
| print(f"{input_text}\n{output_text}") | |
| #print("="*20) | |
| history.append((input, output_text)) | |
| #print(history) | |
| return history, history | |
| def chatyuan_bot_regenerate(input, history): | |
| history = history or [] | |
| if history: | |
| input=history[-1][0] | |
| history=history[:-1] | |
| if len(history) > 1: | |
| history = history[-1:] | |
| context = "\n".join([f"用户：{input_text}\n小元：{answer_text}" for input_text, answer_text in history]) | |
| #print(context) | |
| input_text = context + "\n用户：" + input + "\n小元：" | |
| input_text = input_text.strip() | |
| output_text = answer(input_text) | |
| print("open_model".center(20, "=")) | |
| print(f"{input_text}\n{output_text}") | |
| history.append((input, output_text)) | |
| #print(history) | |
| return history, history | |
| block = gr.Blocks() | |
| with block as demo: | |
| gr.Markdown("""<h1><center>huolongguo10助手</center></h1> | |
| """) | |
| chatbot = gr.Chatbot(label='ChatYuan') | |
| message = gr.Textbox() | |
| state = gr.State() | |
| message.submit(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state]) | |
| with gr.Row(): | |
| clear_history = gr.Button("👋 清除历史对话 | Clear History") | |
| clear = gr.Button('🧹 清除发送框 | Clear Input') | |
| send = gr.Button("🚀 发送 | Send") | |
| regenerate = gr.Button("🚀 重新生成本次结果 | regenerate") | |
| regenerate.click(chatyuan_bot_regenerate, inputs=[message, state], outputs=[chatbot, state]) | |
| send.click(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state]) | |
| clear.click(lambda: None, None, message, queue=False) | |
| clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False) | |
| def ChatYuan(api_key, text_prompt): | |
| cl = clueai.Client(api_key, | |
| check_api_key=True) | |
| # generate a prediction for a prompt | |
| # 需要返回得分的话，指定return_likelihoods="GENERATION" | |
| prediction = cl.generate(model_name='ChatYuan-large', prompt=text_prompt) | |
| # print the predicted text | |
| #print('prediction: {}'.format(prediction.generations[0].text)) | |
| response = prediction.generations[0].text | |
| if response == '': | |
| response = "很抱歉，我无法回答这个问题" | |
| return response | |
| def chatyuan_bot_api(api_key, input, history): | |
| history = history or [] | |
| if len(history) > 5: | |
| history = history[-5:] | |
| context = "\n".join([f"用户：{input_text}\n小元：{answer_text}" for input_text, answer_text in history]) | |
| #print(context) | |
| input_text = context + "\n用户：" + input + "\n小元：" | |
| input_text = input_text.strip() | |
| output_text = ChatYuan(api_key, input_text) | |
| print("api".center(20, "=")) | |
| print(f"api_key:{api_key}\n{input_text}\n{output_text}") | |
| #print("="*20) | |
| history.append((input, output_text)) | |
| #print(history) | |
| return history, history | |
| block = gr.Blocks() | |
| with block as demo_1: | |
| gr.Markdown(""" | |
| """) | |
| api_key = gr.inputs.Textbox(label="请输入你的api-key(必填)", default="", type='password') | |
| chatbot = gr.Chatbot(label='ChatYuan') | |
| message = gr.Textbox() | |
| state = gr.State() | |
| message.submit(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state]) | |
| with gr.Row(): | |
| clear_history = gr.Button("👋 清除历史对话 | Clear Context") | |
| clear = gr.Button('🧹 清除发送框 | Clear Input') | |
| send = gr.Button("🚀 发送 | Send") | |
| send.click(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state],api_name='send') | |
| clear.click(lambda: None, None, message, queue=False) | |
| clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False) | |
| block = gr.Blocks() | |
| with block as introduction: | |
| gr.Markdown("""啥也没有 | |
| """) | |
| gui = gr.TabbedInterface(interface_list=[demo], tab_names=["开源模型"]) | |
| gui.launch(quiet=True,show_api=True, share = False) |