embedchain
Verba
| embedchain | Verba | |
|---|---|---|
| 6 | 4 | |
| 8,541 | 2,364 | |
| 2.3% | 14.5% | |
| 9.8 | 8.9 | |
| 6 days ago | 1 day ago | |
| Python | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
embedchain
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
You can use embedchain[1] to connect various data sources and then get a RAG application running on your local and production very easily. Embedchain is an open source RAG framework and It follows a conventional but configurable approach.
The conventional approach is suitable for software engineer where they may not be less familiar with AI. The configurable approach is suitable for ML engineer where they have sophisticated uses and would want to configure chunking, indexing and retrieval strategies.
[1]: https://github.com/embedchain/embedchain
- Embedchain
- Framework to easily create LLM powered bots over any dataset
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[D] Hardest thing about building with LLMs?
Langchain is a big wrapper in itself and people can't be bothered to even use that to write 10 lines of code. Look at the traction this project is getting https://github.com/embedchain/embedchain, at it's heart it's just using few modules from langchain. The whole thing, chunking+embedding+retrieval+promoting can be done in 100 lines without langchain and embedchain.
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AI — weekly megathread!
Embedchain: a framework to easily create LLM powered bots over any dataset [Link].
- EmbedChain: Framework to easily create LLM powered bots over any dataset.
Verba
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
So far the recommendations are mostly hosted, so here's one local: https://github.com/weaviate/Verba
I'm very happy with its results, even though the system is still young and a little bit janky. You can use it with either GPT API, or your local models through LiteLlm. (I'm running ollama + dolphin-mixtral)
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Canopy is an open-source Retrieval Augmented Generation (RAG) framework
Weaviate did something similar recently with Verba[1], which feels like it still needs some time in the oven. Will definitely check this out.
https://github.com/weaviate/Verba
- Verba: The Golden RAGtriever
- Show HN: Verba – An open-source RAG application
What are some alternatives?
trulens - Evaluation and Tracking for LLM Experiments
langroid - Harness LLMs with Multi-Agent Programming
HeimdaLLM - Constrain LLM output
WebGLM - WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)
openchat - OpenChat: Advancing Open-source Language Models with Imperfect Data
gpt-migrate - Easily migrate your codebase from one framework or language to another.
searchGPT - Grounded search engine (i.e. with source reference) based on LLM / ChatGPT / OpenAI API. It supports web search, file content search etc.
llmo - Your friendly terminal-based AI pair programmer
aide - LLM shell and document interogator
bark - 🔊 Text-Prompted Generative Audio Model
gpt-author
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore