TextGen
GitHub:oobabooga/text-generation-webui A gradio web UI for running Large Language Models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA.
This example goes over how to use LangChain to interact with LLM models via the text-generation-webui API integration.
Please ensure that you have text-generation-webui configured and an LLM installed. Recommended installation via the one-click installer appropriate for your OS.
Once text-generation-webui is installed and confirmed working via the web interface, please enable the api option either through the web model configuration tab, or by adding the run-time arg --api to your start command.
Set model_url and run the example
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)
API Reference:
Streaming Version
You should install websocket-client to use this feature.
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)