ChatDev: Can LLM Agents really replace a software company?
52Behold ChatDev, the latest agents in a process to generate software code. It claims to be able to simulate a software company. However, can it really?
I like the way the structure is created in a clear and consistent way for the program to be developed from idea generation to execution. However, ChatDev suffers from 3 fundamental flaws in my opinion:
- Agents are only zero-shot prompted via description. They do not have different tools nor memory to learn across episodes
- Context length is still a constraint, especially given that all modular code needs to be in the prompt for effective generation
- Software created needs to be very similar to existing ones, otherwise it will be hard to generate. Moreover, to my knowledge, testing is not done on the real environment itself but just through visual inspection, leading to potential execution errors.
I will be covering this paper and the interesting ideas it contains, as well as some of my insights to improve it.
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ChatDev:
Slides: https://github.com/tanchongmin/TensorFlow-Implementations/blob/main/Paper_Reviews/ChatDev.pdf
Paper: https://arxiv.org/pdf/2307.07924.pdf
Code: https://github.com/OpenBMB/ChatDev
CAMEL: Communicative Agents for "Mind" Exploration of Large Scale Language Model Society
Paper: https://arxiv.org/pdf/2303.17760.pdf
MetaGPT: https://arxiv.org/pdf/2308.00352.pdf
Reflexion (Reflection to make output better): https://arxiv.org/pdf/2303.11366.pdf
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0:00 Introduction and Demo
11:33 CAMEL: Society of AI Minds
20:49 ChatDev Procedure
42:48 ChatDev Results
53:29 Pros and Cons
1:12:08 My own implementations to improve ChatDev
1:20:13 Discussion
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AI and ML enthusiast. Likes to think about the essences behind breakthroughs of AI and explain it in a simple and relatable way. Also, I am an avid game creator.
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