๐ LazyLLM looks like a super simple low-code open-source framework for building multi-agent applications
๐กLazyLLM supports a variety of applications that leverage multi-agent systems and LLMs like RAG, fine-tuning, content-generation etc.
and defines workflows such as pipeline, parallel, diverter, if, switch, and loop etc.
โณ These are the features that struck to me most:
- ๐ LazyLLM allows developers to assemble AI applications easily using pre-built modules and data flows, even if they are not familiar with large models.
- ๐ The framework offers a one-click deployment feature which can be particularly useful during the Proof of Concept phase, as it manages the sequential start-up and configuration of various services like LLMs and embeddings.
- ๐ It supports deployment across different infrastructure platforms such as bare-metal servers, Slurm clusters, and public clouds.
- ๐ It has a built-in support for grid search and allows automatic exploration of different model configurations, retrieval strategies, and fine-tuning parameters to optimize application performance
The features arenโt flashy or anything new, but LazyLLM is built in a straightforward way.
The repository is pretty new and actively being developed, but itโs nice to see so many low-code approaches being built. It helps developers from diverse backgrounds quickly build a prototype
Github ๐ https://github.com/LazyAGI/LazyLLM
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