接入TGUI
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@ -34,7 +34,7 @@ WEB_PORT = -1
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MAX_RETRY = 2
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# OpenAI模型选择是(gpt4现在只对申请成功的人开放)
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LLM_MODEL = "pygmalion-1.3b@localhost@7860" # "gpt-3.5-turbo"
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LLM_MODEL = "TGUI:galactica-1.3b@localhost:7860" # "gpt-3.5-turbo"
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# OpenAI的API_URL
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API_URL = "https://api.openai.com/v1/chat/completions"
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@ -2,7 +2,7 @@
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## 1. 先运行text-generation
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``` sh
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# 下载模型
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# 下载模型( text-generation 这么牛的项目,别忘了给人家star )
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git clone https://github.com/oobabooga/text-generation-webui.git
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# 安装text-generation的额外依赖
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@ -12,28 +12,25 @@ pip install accelerate bitsandbytes flexgen gradio llamacpp markdown numpy peft
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cd text-generation-webui
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# 下载模型
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python download-model.py facebook/opt-1.3b
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# 其他可选如 facebook/galactica-1.3b
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python download-model.py facebook/galactica-1.3b
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# 其他可选如 facebook/opt-1.3b
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# facebook/galactica-6.7b
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# facebook/galactica-120b
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# Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's GPT-J-6B.
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# facebook/pygmalion-1.3b
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# facebook/pygmalion-1.3b 等
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# 详情见 https://github.com/oobabooga/text-generation-webui
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# 启动text-generation,注意把模型的斜杠改成下划线
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python server.py --cpu --listen --listen-port 7860 --model facebook_galactica-1.3b
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```
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## 2. 修改config.py
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``` sh
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# LLM_MODEL格式较复杂 TGUI:[模型]@[ws地址]:[ws端口] , 端口要和上面给定的端口一致
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LLM_MODEL = "TGUI:galactica-1.3b@localhost:7860"
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```
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# LLM_MODEL格式为 [模型]@[ws地址] @[ws端口]
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LLM_MODEL = "pygmalion-1.3b@localhost@7860"
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```
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## 3. 运行!
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```
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``` sh
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cd chatgpt-academic
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python main.py
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```
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@ -15,7 +15,10 @@ import importlib
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from toolbox import get_conf
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LLM_MODEL, = get_conf('LLM_MODEL')
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model_name, addr, port = LLM_MODEL.split('@')
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# "TGUI:galactica-1.3b@localhost:7860"
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model_name, addr_port = LLM_MODEL.split('@')
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assert ':' in addr_port, "LLM_MODEL 格式不正确!" + LLM_MODEL
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addr, port = addr_port.split(':')
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def random_hash():
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letters = string.ascii_lowercase + string.digits
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@ -117,11 +120,11 @@ def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prom
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def run_coorotine(mutable):
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async def get_result(mutable):
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async for response in run(prompt):
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# Print intermediate steps
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print(response[len(mutable[0]):])
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mutable[0] = response
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asyncio.run(get_result(mutable))
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thread_listen = threading.Thread(target=run_coorotine, args=(mutable,))
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thread_listen = threading.Thread(target=run_coorotine, args=(mutable,), daemon=True)
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thread_listen.start()
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while thread_listen.is_alive():
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@ -145,7 +148,7 @@ def predict_tgui_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
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def run_coorotine(mutable):
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async def get_result(mutable):
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async for response in run(prompt):
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# Print intermediate steps
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print(response[len(mutable[0]):])
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mutable[0] = response
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asyncio.run(get_result(mutable))
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thread_listen = threading.Thread(target=run_coorotine, args=(mutable,))
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