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Browse files- README.md +8 -6
- app.py +172 -0
- requirements.txt +4 -0
README.md
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---
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title:
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sdk:
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app_file: app.py
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pinned: false
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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title: ChatYuan Large V2
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emoji: 📊
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colorFrom: red
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colorTo: pink
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sdk: gradio
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sdk_version: 3.23.0
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app_file: app.py
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pinned: false
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license: creativeml-openrail-m
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duplicated_from: ClueAI/ChatYuan-large-v2
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import os
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import gradio as gr
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import clueai
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import torch
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from transformers import T5Tokenizer, T5ForConditionalGeneration
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tokenizer = T5Tokenizer.from_pretrained("ClueAI/ChatYuan-large-v2")
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model = T5ForConditionalGeneration.from_pretrained("ClueAI/ChatYuan-large-v2")
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# 使用
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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model.to(device)
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base_info = "用户:你是谁?\n小元:我是元语智能公司研发的AI智能助手, 在不违反原则的情况下,我可以回答你的任何问题。\n"
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def preprocess(text):
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text = f"{base_info}{text}"
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text = text.replace("\n", "\\n").replace("\t", "\\t")
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return text
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def postprocess(text):
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return text.replace("\\n", "\n").replace("\\t", "\t").replace('%20',' ')#.replace(" ", " ")
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generate_config = {'do_sample': True, 'top_p': 0.9, 'top_k': 50, 'temperature': 0.7,
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'num_beams': 1, 'max_length': 1024, 'min_length': 3, 'no_repeat_ngram_size': 5,
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'length_penalty': 0.6, 'return_dict_in_generate': True, 'output_scores': True}
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def answer(text, sample=True, top_p=0.9, temperature=0.7):
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'''sample:是否抽样。生成任务,可以设置为True;
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top_p:0-1之间,生成的内容越多样'''
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text = preprocess(text)
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encoding = tokenizer(text=[text], truncation=True, padding=True, max_length=1024, return_tensors="pt").to(device)
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if not sample:
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out = model.generate(**encoding, return_dict_in_generate=True, output_scores=False, max_new_tokens=1024, num_beams=1, length_penalty=0.6)
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else:
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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)
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#out=model.generate(**encoding, **generate_config)
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out_text = tokenizer.batch_decode(out["sequences"], skip_special_tokens=True)
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return postprocess(out_text[0])
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def clear_session():
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return '', None
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def chatyuan_bot(input, history):
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history = history or []
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if len(history) > 5:
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history = history[-5:]
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context = "\n".join([f"用户:{input_text}\n小元:{answer_text}" for input_text, answer_text in history])
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#print(context)
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input_text = context + "\n用户:" + input + "\n小元:"
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input_text = input_text.strip()
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output_text = answer(input_text)
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print("open_model".center(20, "="))
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print(f"{input_text}\n{output_text}")
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#print("="*20)
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history.append((input, output_text))
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#print(history)
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return history, history
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def chatyuan_bot_regenerate(input, history):
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history = history or []
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if history:
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input=history[-1][0]
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history=history[:-1]
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if len(history) > 5:
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history = history[-5:]
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context = "\n".join([f"用户:{input_text}\n小元:{answer_text}" for input_text, answer_text in history])
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#print(context)
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input_text = context + "\n用户:" + input + "\n小元:"
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input_text = input_text.strip()
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output_text = answer(input_text)
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print("open_model".center(20, "="))
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print(f"{input_text}\n{output_text}")
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history.append((input, output_text))
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#print(history)
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return history, history
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block = gr.Blocks()
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with block as demo:
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gr.Markdown("""<h1><center>元语智能——ChatYuan</center></h1>
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<font size=4>回答来自ChatYuan, 是模型生成的结果, 请谨慎辨别和参考, 不代表任何人观点 | Answer generated by ChatYuan model</font>
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<font size=4>注意:gradio对markdown代码格式展示有限</font>
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""")
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chatbot = gr.Chatbot(label='ChatYuan')
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message = gr.Textbox()
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state = gr.State()
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message.submit(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state])
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with gr.Row():
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clear_history = gr.Button("👋 清除历史对话 | Clear History")
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clear = gr.Button('🧹 清除发送框 | Clear Input')
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send = gr.Button("🚀 发送 | Send")
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regenerate = gr.Button("🚀 重新生成本次结果 | regenerate")
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regenerate.click(chatyuan_bot_regenerate, inputs=[message, state], outputs=[chatbot, state])
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send.click(chatyuan_bot, inputs=[message, state], outputs=[chatbot, state])
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clear.click(lambda: None, None, message, queue=False)
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clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False)
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def ChatYuan(api_key, text_prompt):
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cl = clueai.Client(api_key,
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check_api_key=True)
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# generate a prediction for a prompt
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# 需要返回得分的话,指定return_likelihoods="GENERATION"
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prediction = cl.generate(model_name='ChatYuan-large', prompt=text_prompt)
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# print the predicted text
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#print('prediction: {}'.format(prediction.generations[0].text))
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response = prediction.generations[0].text
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if response == '':
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response = "很抱歉,我无法回答这个问题"
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return response
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def chatyuan_bot_api(api_key, input, history):
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history = history or []
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if len(history) > 5:
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history = history[-5:]
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context = "\n".join([f"用户:{input_text}\n小元:{answer_text}" for input_text, answer_text in history])
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#print(context)
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input_text = context + "\n用户:" + input + "\n小元:"
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input_text = input_text.strip()
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output_text = ChatYuan(api_key, input_text)
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print("api".center(20, "="))
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print(f"api_key:{api_key}\n{input_text}\n{output_text}")
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#print("="*20)
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history.append((input, output_text))
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#print(history)
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return history, history
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block = gr.Blocks()
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with block as demo_1:
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gr.Markdown("""<h1><center>元语智能——ChatYuan</center></h1>
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<font size=4>回答来自ChatYuan, 以上是模型生成的结果, 请谨慎辨别和参考, 不代表任何人观点 | Answer generated by ChatYuan model</font>
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<font size=4>注意:gradio对markdown代码格式展示有限</font>
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<font size=4>在使用此功能前,你需要有个API key. API key 可以通过这个<a href='https://www.clueai.cn/' target="_blank">平台</a>获取</font>
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""")
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api_key = gr.inputs.Textbox(label="请输入你的api-key(必填)", default="", type='password')
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chatbot = gr.Chatbot(label='ChatYuan')
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message = gr.Textbox()
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state = gr.State()
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message.submit(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state])
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with gr.Row():
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clear_history = gr.Button("👋 清除历史对话 | Clear Context")
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clear = gr.Button('🧹 清除发送框 | Clear Input')
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send = gr.Button("🚀 发送 | Send")
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send.click(chatyuan_bot_api, inputs=[api_key,message, state], outputs=[chatbot, state],api_name='send')
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clear.click(lambda: None, None, message, queue=False)
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clear_history.click(fn=clear_session , inputs=[], outputs=[chatbot, state], queue=False)
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block = gr.Blocks()
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with block as introduction:
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gr.Markdown("""啥也没有
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""")
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gui = gr.TabbedInterface(interface_list=[demo], tab_names=["开源模型"])
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gui.launch(quiet=True,show_api=True, share = False)
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requirements.txt
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transformers
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torch
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SentencePiece
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clueai
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