Lagent#
What’s Lagent?#
Lagent is a lightweight open-source framework that allows users to efficiently build large language model(LLM)-based agents. It also provides some typical tools to augment LLM. The overview of the framework is shown below:
This document primarily highlights the basic usage of Lagent. For a comprehensive understanding of the toolkit, please refer to examples for more details.
Installation#
Install with pip (Recommended).
pip install lagent
Optionally, you could also build Lagent from source in case you want to modify the code:
git clone https://github.com/InternLM/lagent.git
cd lagent
pip install -e .
Run ReAct Web Demo#
# You need to install streamlit first
# pip install streamlit
streamlit run examples/react_web_demo.py
Then you can chat through the UI shown as below
Run a ReAct agent with InternLM2.5-Chat#
NOTE: If you want to run a HuggingFace model, please run pip install -e .[all] first.
# Import necessary modules and classes from the "lagent" library.
from lagent.agents import ReAct
from lagent.actions import ActionExecutor, GoogleSearch, PythonInterpreter
from lagent.llms import HFTransformer
# Initialize the HFTransformer-based Language Model (llm) and provide the model name.
llm = HFTransformer('internlm/internlm2_5-7b-chat')
# Initialize the Google Search tool and provide your API key.
search_tool = GoogleSearch(api_key='Your SERPER_API_KEY')
# Initialize the Python Interpreter tool.
python_interpreter = PythonInterpreter()
# Create a chatbot by configuring the ReAct agent.
chatbot = ReAct(
llm=llm, # Provide the Language Model instance.
action_executor=ActionExecutor(
actions=[search_tool, python_interpreter] # Specify the actions the chatbot can perform.
),
)
# Ask the chatbot a mathematical question in LaTeX format.
response = chatbot.chat('若$z=-1+\sqrt{3}i$,则$\frac{z}{{z\overline{z}-1}}=\left(\ \ \right)$')
# Print the chatbot's response.
print(response.response) # Output the response generated by the chatbot.
>>> $-\frac{1}{3}+\frac{\sqrt{3}}{3}i$