177 lines
5.9 KiB
Python
177 lines
5.9 KiB
Python
import gradio as gr
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import os
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import torch
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from transformers import GemmaTokenizer, AutoModelForCausalLM
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
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from threading import Thread
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DESCRIPTION = '''
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<div>
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<h1 style="text-align: center;">EmoLLM Llama3 心理咨询室 V4.0</h1>
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<p align="center">
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<a href="https://github.com/SmartFlowAI/EmoLLM/">
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<img src="https://st-app-center-006861-9746-jlroxvg.openxlab.space/media/cda6c1a05dc8ba5b19ad3e7a24920fdf3750c917751202385a6dbc51.png" alt="Logo" width="20%">
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</a>
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</p>
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<div align="center">
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<!-- PROJECT SHIELDS -->
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[![OpenXLab_Model][OpenXLab_Model-image]][OpenXLab_Model-url]
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<h2 style="text-align: center;"> EmoLLM是一系列能够支持 理解用户-支持用户-帮助用户 心理健康辅导链路的 心理健康大模型 ，欢迎大家star~⭐⭐</h2>
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<p>https://github.com/SmartFlowAI/EmoLLM</p>
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</div>
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</div>
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[OpenXLab_Model-image]: https://cdn-static.openxlab.org.cn/header/openxlab_models.svg
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[OpenXLab_Model-url]: https://openxlab.org.cn/models/detail/chg0901/EmoLLM-Llama3-8B-Instruct3.0
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'''
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LICENSE = """
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<p align="center"> Built with Meta Llama 3 </>
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"""
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PLACEHOLDER = """
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<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
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</div>
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"""
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css = """
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h1 {
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text-align: center;
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display: block;
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}
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<!--
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#duplicate-button {
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margin: auto;
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color: white;
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background: #1565c0;
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border-radius: 100vh;
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}
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-->
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"""
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# download internlm2 to the base_path directory using git tool
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base_path = './EmoLLM-Llama3-8B-Instruct3.0'
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os.system(f'git clone https://code.openxlab.org.cn/chg0901/EmoLLM-Llama3-8B-Instruct3.0.git {base_path}')
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os.system(f'cd {base_path} && git lfs pull')
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# Load the tokenizer and model
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tokenizer = AutoTokenizer.from_pretrained(base_path,trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(base_path,trust_remote_code=True, device_map="auto", torch_dtype=torch.float16).eval() # to("cuda:0")
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terminators = [
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tokenizer.eos_token_id,
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tokenizer.convert_tokens_to_ids("<|eot_id|>")
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]
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def chat_llama3_8b(message: str,
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history: list,
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temperature: float,
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max_new_tokens: int,
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top_p: float
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) -> str:
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"""
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Generate a streaming response using the llama3-8b model.
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Args:
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message (str): The input message.
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history (list): The conversation history used by ChatInterface.
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temperature (float): The temperature for generating the response.
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max_new_tokens (int): The maximum number of new tokens to generate.
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Returns:
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str: The generated response.
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"""
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conversation = []
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for user, assistant in history:
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conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
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conversation.append({"role": "user", "content": message})
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input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt").to(model.device)
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streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
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generate_kwargs = dict(
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input_ids= input_ids,
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streamer=streamer,
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max_new_tokens=max_new_tokens,
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do_sample=True,
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temperature=temperature,
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top_p = top_p,
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eos_token_id=terminators,
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)
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# This will enforce greedy generation (do_sample=False) when the temperature is passed 0, avoiding the crash.
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if temperature == 0:
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generate_kwargs['do_sample'] = False
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t = Thread(target=model.generate, kwargs=generate_kwargs)
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t.start()
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outputs = []
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for text in streamer:
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outputs.append(text)
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yield "".join(outputs)
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# Gradio block
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chatbot=gr.Chatbot(height=450, placeholder=PLACEHOLDER, label='EmoLLM Chat')
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with gr.Blocks(fill_height=True, css=css) as demo:
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gr.Markdown(DESCRIPTION)
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# gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
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gr.ChatInterface(
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fn=chat_llama3_8b,
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chatbot=chatbot,
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fill_height=True,
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additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
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additional_inputs=[
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gr.Slider(minimum=0,
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maximum=1,
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step=0.1,
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value=0.95,
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label="Temperature",
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render=False),
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gr.Slider(minimum=128,
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maximum=4096,
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step=1,
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value=4096,
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label="Max new tokens",
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render=False ),
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gr.Slider(minimum=0.0,
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maximum=1,
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step=0.01,
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value=0.8,
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label="Top P",
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render=False ),
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# gr.Slider(minimum=128,
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# maximum=4096,
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# step=1,
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# value=512,
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# label="Max new tokens",
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# render=False ),
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],
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examples=[
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['请介绍你自己。'],
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['我觉得我在学校的学习压力好大啊，虽然我真的很喜欢我的专业，但最近总是担心自己无法达到自己的期望，这让我有点焦虑。'],
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['我最近总觉得自己在感情上陷入了困境，我喜欢上了我的朋友，但又害怕表达出来会破坏我们现在的关系...'],
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['我感觉自己像是被困在一个无尽的循环中。每天醒来都感到身体沉重，对日常活动提不起兴趣，工作、锻炼甚至是我曾经喜欢的事物都让我觉得厌倦'],
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['最近工作压力特别大，还有一些家庭矛盾']
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],
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cache_examples=False,
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)
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gr.Markdown(LICENSE)
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if __name__ == "__main__":
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demo.launch()
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