zhiguoxu / flowx

A lightweight framework for building LLM applications, with similar interface as LangChain, but more concise internal implementation.

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FlowX

What's FlowX?

FlowX is a lightweight framework for building LLM applications. It offers an API interface similar to LangChain's LCEL, but with a more straightforward and simple internal implementation. Users familiar with LangChain can quickly get started with FlowX and extend or modify it as needed.

For example, FlowX implements the core functionality of LangChain's AgentExecutor within 400 lines of code. This is particularly beneficial for users who want to understand the underlying implementation of agents and make further optimizations.

FlowX is also very easy to use, as demonstrated by the following example of an Agent:

from core.tool import tool
from core.llm.openai.openai_llm import OpenAILLM
from core.agents.agent import Agent

llm = OpenAILLM(model="gpt-4o")


@tool
def multiply(left: int, right: int) -> int:
    """multiply"""
    return left * right


agent = Agent(llm=llm, tools=[multiply])
agent.invoke("what is 1024*2024?")

Why do we need FlowX?

Although LangChain provides a powerful framework for building LLM applications, its complex design also brings several issues with deeper use.

LangChain's extensive use of abstraction results in highly complex code, making it difficult to understand and maintain. While it initially simplifies the development process, as the complexity of requirements increases, these abstractions gradually become obstacles to productivity. Additionally, these abstractions increase the learning and debugging burden, forcing development teams to spend significant time dealing with internal framework code rather than focusing on application functionality.

Especially in today's rapidly evolving AI and LLM landscape, where new concepts and methods emerge weekly, a framework that is easy to understand and iterate on quickly is crucial!

To address these issues, FlowX adopts a more concise design with more refined code implementation, balancing abstraction and simplicity by the use of necessary abstractions without being overly complex. Ultimately, FlowX provides the same functionality and similar interfaces as LangChain but with significantly reduced code and fewer abstract concepts. This makes it easy to understand and modify FlowX, allowing for quick experimentation or customized development.

The project is still under development, with more features to be added. Your valuable feedback is welcome!