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TextGen

GitHub:oobabooga/text-generation-webui 一个用于运行大型语言模型（如LLaMA、llama.cpp、GPT-J、Pythia、OPT和GALACTICA）的gradio网页界面。

本示例介绍了如何通过text-generation-webui API集成使用LangChain与LLM模型进行交互。

请确保您已配置好text-generation-webui并安装了LLM。建议通过适用于您操作系统的一键安装程序进行安装。

一旦通过网页界面安装并确认text-generation-webui正常工作，请通过网页模型配置选项卡或通过向启动命令添加运行时参数--api来启用api选项。

设置 model_url 并运行示例​

model_url = "http://localhost:5000"
from langchain.chains import LLMChain
from langchain.globals import set_debug
from langchain_community.llms import TextGen
from langchain_core.prompts import PromptTemplate

set_debug(True)

template = """Question: {question}

Answer: Let's think step by step."""


prompt = PromptTemplate.from_template(template)
llm = TextGen(model_url=model_url)
llm_chain = LLMChain(prompt=prompt, llm=llm)
question = "What NFL team won the Super Bowl in the year Justin Bieber was born?"

llm_chain.run(question)

流式版本​

您应该安装websocket-client以使用此功能。 pip install websocket-client

model_url = "ws://localhost:5005"
from langchain.chains import LLMChain
from langchain.globals import set_debug
from langchain_community.llms import TextGen
from langchain_core.callbacks import StreamingStdOutCallbackHandler
from langchain_core.prompts import PromptTemplate

set_debug(True)

template = """Question: {question}

Answer: Let's think step by step."""


prompt = PromptTemplate.from_template(template)
llm = TextGen(
    model_url=model_url, streaming=True, callbacks=[StreamingStdOutCallbackHandler()]
)
llm_chain = LLMChain(prompt=prompt, llm=llm)
question = "What NFL team won the Super Bowl in the year Justin Bieber was born?"

llm_chain.run(question)
llm = TextGen(model_url=model_url, streaming=True)
for chunk in llm.stream("Ask 'Hi, how are you?' like a pirate:'", stop=["'", "\n"]):
    print(chunk, end="", flush=True)

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