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Lagent is an open source LLM agent framework, which enables people to efficiently turn a large language model to agent. It also provides some typical tools to enlighten the ablility of LLM. The overview of our framework is shown below:
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Support multiple agent frameworks out of box. We implement ReAct, AutoGPT and ReWOO, which enables the agents to drive LLMs for multiple trails of reasoning and tool utilization.
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Extremely simple and easy to extend. The framework is quite simple with clear project structure. With only 20 lines of code, you are able to construct your own agent. It also supports three typical tools: Python interpreter, API call, and google search.
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Support various large language models. We support different LLMs, including API-based (GPT3.5/4) and HuggingFace-based (LLaMa2, InternLM) models.
Please see Overview for the general introduction of Lagent. Meanwhile, we provide extremely simple code for quick start. You may refer to examples for more details.
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 .
from lagent.agents import ReWOO
from lagent.actions import ActionExecutor, GoogleSearch, LLMQA
from lagent.llms import GPTAPI
llm = GPTAPI(model_type='gpt-3.5-turbo', key=['OPENAI_API_KEY'])
search_tool = GoogleSearch(api_key='SERPER_API_KEY')
llmqa_tool = LLMQA(llm)
chatbot = ReWOO(
llm=llm,
action_executor=ActionExecutor(
actions=[search_tool, llmqa_tool]),
)
response = chatbot.chat('What profession does Nicholas Ray and Elia Kazan have in common')
print(response.response)
>>> Film director.
NOTE: If you want to run a HuggingFace model, please run pip install -e .[all]
first.
from lagent.agents import ReAct
from lagent.actions import ActionExecutor, GoogleSearch, PythonInterpreter
from lagent.llms import HFTransformer
llm = HFTransformer('internlm/internlm-7b-chat-v1.1')
search_tool = GoogleSearch()
python_interpreter = PythonInterpreter()
chatbot = ReAct(
llm=llm,
action_executor=ActionExecutor(
actions=[search_tool, python_interpreter]),
)
response = chatbot.chat('若$z=-1+\sqrt{3}i$,则$\frac{z}{{z\overline{z}-1}}=\left(\ \ \right)$ (A) $-1+\sqrt{3}i$ (B) $-1-\sqrt{3}i$ (C) $-\frac{1}{3}+\frac{{\sqrt{3}}}{3}i$ (D) $-\frac{1}{3}-\frac{{\sqrt{3}}}{3}i$')
print(response.response)
>>> 根据已有的信息,可以求得$z=-1+\\sqrt{3}i$,然后代入计算,得到结果为$-\\frac{1}{3}+\\frac{{\\sqrt{3}}}{3}i$。因此,答案是(C)。
This project is released under the Apache 2.0 license.