embedchain
anything-llm
embedchain | anything-llm | |
---|---|---|
6 | 21 | |
8,541 | 12,782 | |
2.3% | 24.4% | |
9.8 | 9.8 | |
6 days ago | 2 days ago | |
Python | JavaScript | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
anything-llm
- AnythingLLM: Chat with your documents using any LLM
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Ask HN: How do I train a custom LLM/ChatGPT on my own documents in Dec 2023?
anything-llm looks pretty interesting and easy to use https://github.com/Mintplex-Labs/anything-llm
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local/private llm based chatbot using free/open source tools.
You can just fork AnythingLLM for a very advanced starting point or just straight rip the code ive already written to build yours 🚀
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Some solutions that work on older intel macs
AnythingLLM also works on an Intel Mac (i develop it on an intel mac) and can use any GGUF model to do local inferencing. Includes document embedding + local vector database so i can do chatting with documents and even coding inside of it. Pretty much a ChatGPT equilivent i can run locally via the repo or docker.
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What tools or programs have you made or are working on?
If you want a UI you can leverage https://github.com/Mintplex-Labs/anything-llm and do all your coding in localhost with a locally running model.
- Web interface for Azure Open Ai
- DIY custom AI chatbot trained on your company data
What are some alternatives?
trulens - Evaluation and Tracking for LLM Experiments
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
HeimdaLLM - Constrain LLM output
privateGPT - Interact with your documents using the power of GPT, 100% privately, no data leaks [Moved to: https://github.com/zylon-ai/private-gpt]
WebGLM - WebGLM: An Efficient Web-enhanced Question Answering System (KDD 2023)
LLMStack - No-code platform to build LLM Agents, workflows and applications with your data
openchat - OpenChat: Advancing Open-source Language Models with Imperfect Data
gpt4all - gpt4all: run open-source LLMs anywhere
gpt-migrate - Easily migrate your codebase from one framework or language to another.
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
searchGPT - Grounded search engine (i.e. with source reference) based on LLM / ChatGPT / OpenAI API. It supports web search, file content search etc.
CSharp-ChatBot-GPT - This repository contains a simple C# chatbot powered by OpenAI’s ChatGPT. The chatbot utilizes the RestSharp and Newtonsoft.Json libraries to interact with the ChatGPT API and process user input.