mirror of https://github.com/InternLM/InternLM
74 lines
2.4 KiB
Markdown
74 lines
2.4 KiB
Markdown
# Lagnet
|
|
|
|
English | [简体中文](lagent_zh-CN.md)
|
|
|
|
## 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](https://github.com/InternLM/lagent/tree/main/examples) for more details.
|
|
|
|
## Installation
|
|
|
|
Install with pip (Recommended).
|
|
|
|
```bash
|
|
pip install lagent
|
|
```
|
|
|
|
Optionally, you could also build Lagent from source in case you want to modify the code:
|
|
|
|
```bash
|
|
git clone https://github.com/InternLM/lagent.git
|
|
cd lagent
|
|
pip install -e .
|
|
```
|
|
|
|
## Run ReAct Web Demo
|
|
|
|
```bash
|
|
# 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.
|
|
|
|
```python
|
|
# 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.
|
|
>>> $-\\frac{1}{3}+\\frac{{\\sqrt{3}}}{3}i$
|
|
```
|