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@ -13,23 +13,15 @@ Documentation: https://zachary62.github.io/miniLLMFlow/
## Why Mini LLM Flow?
Mini LLM Flow is designed to **be the framework used by LLM assistants**. In the future, LLM app development will be heavily **LLM-assisted**: Users specify requirements, and LLM assistants design, build, and maintain themselves. Current LLM assistants:
Mini LLM Flow is designed to be **the framework used by LLMs**. In the future, LLM projects will self-programmed by LLMs themselves: Users specify requirements, and LLMs will design, build, and maintain. Current LLMs:
1. **👍 Shine at Low-level Implementation:** LLMs can handle APIs, tools, chunking, prompting, etc. These don't belong in a general-purpose framework; they're too specialized to maintain and optimize.
1. **👍 Shine at Low-level Implementation**
LLMs excel at APIs, tools, chunking, prompting, etc. These don't belong in a general-purpose framework; they're too specialized to maintain and optimize.
2. **👎 Struggle with High-level Paradigms:** Paradigms like MapReduce, task decomposition, and agents are powerful. However, designing these elegantly remains challenging for LLMs.
The ideal framework for LLMs should (1) remove specialized low-level implementations, and (2) keep high-level paradigms to program against. Hence, I built this minimal (100-line) framework so LLMs can focus on what matters.
2. **👎 Struggle with High-level Paradigms**
Paradigms like MapReduce, task decomposition, and agents are powerful. However, designing these elegantly remains challenging for LLMs.
The ideal framework for LLM assistants should:
(1) Remove specialized low-level implementations.
(2) Keep high-level paradigms to program against.
Hence, I built this minimal (100-line) framework so LLMs can focus on what matters.
Mini LLM Flow is also a great learning resource, as many frameworks abstract too much away.
Mini LLM Flow is also a great learning resource, as current frameworks abstract too much away.
<div align="center">
<img src="/assets/minillmflow.jpg" width="400"/>