import os import gradio as gr from transformers import T5Tokenizer, T5ForConditionalGeneration tokenizer = T5Tokenizer.from_pretrained("ClueAI/ChatYuan-large-v2") model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v2") # 使用 device='cpu' def preprocess(text): text = text.replace("\n", "\\n").replace("\t", "\\t") return text def postprocess(text): return text.replace("\\n", "\n").replace("\\t", "\t").replace('%20',' ') def answer(text, sample=True, top_p=1, temperature=0.7): '''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=768, return_tensors="pt").to(device) if not sample: out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=512, num_beams=1, length_penalty=0.6) else: out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=512, do_sample=True, top_p=top_p, temperature=temperature, no_repeat_ngram_size=3) 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:" output_text = answer(input_text) history.append((input, output_text)) print(history) return history, history block = gr.Blocks() with block as demo: gr.Markdown("""

元语智能——ChatYuan

""") 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 = gr.Button('🧹 清除发送框') send = gr.Button("🚀 发送") 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:" # output_text = ChatYuan(api_key, input_text) # history.append((input, output_text)) # print(history) # return history, history block = gr.Blocks() with block as demo_1: gr.Markdown("""

元语智能——ChatYuan

在使用此功能前,你需要有个API key. API key 可以通过这个平台获取 """) 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, inputs=[message, state], outputs=[chatbot, state]) with gr.Row(): clear_history = gr.Button("👋 清除历史对话") clear = gr.Button('🧹 清除发送框') send = gr.Button("🚀 发送") 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) block = gr.Blocks() with block as introduction: gr.Markdown("""

元语智能——ChatYuan

😉ChatYuan: 元语功能型对话大模型

👏这个模型可以用于问答、结合上下文做对话、做各种生成任务, 包括创意性写作, 也能回答一些像法律、新冠等领域问题. 它基于PromptCLUE-large结合数亿条功能对话多轮对话数据进一步训练得到.

👀PromptCLUE-large在1000亿token中文语料上预训练, 累计学习1.5万亿中文token, 并且在数百种任务上进行Prompt任务式训练. 针对理解类任务, 如分类、情感分析、抽取等, 可以自定义标签体系; 针对多种生成任务, 可以进行采样自由生成.

🚀在线Demo   |   ModelScope   |   Huggingface   |   官网体验场   |   ChatYuan-API   |   Github项目地址   |   OpenI免费试用  
""") gui = gr.TabbedInterface(interface_list=[introduction,demo, demo_1], tab_names=["相关介绍","开源模型", "API调用"]) gui.launch(quiet=True,show_api=False, share = False)