open-webui
llmsherpa
| open-webui | llmsherpa | |
|---|---|---|
| 9 | 6 | |
| 20,138 | 970 | |
| 44.1% | 16.2% | |
| 10.0 | 6.6 | |
| 3 days ago | 9 days ago | |
| Svelte | Jupyter Notebook | |
| MIT License | MIT 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.
open-webui
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Run Large and Small Language Models locally with ollama
Luckily, there are some open-source projects like Open WebUI, which provide a web-based experience similar to ChatGPT, that you can also run locally and point to any model. To start the Open WebUI Docker container locally, run the command below in your Terminal (make sure, that ollama serve is still running).
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open-webui VS LibreChat - a user suggested alternative
2 projects | 29 Feb 2024
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Show HN: I made an app to use local AI as daily driver
I like the project.
What does this have that is better than https://github.com/open-webui/open-webui ?
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LlamaCloud and LlamaParse
Be careful with unstructured:
https://github.com/Unstructured-IO/unstructured/blob/d11c70c...
from: https://github.com/open-webui/open-webui/issues/687
- Open WebUI: ChatGPT-Style WebUI for Ollama
- Announcing the New Era of 'open-webui'
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Ollama is now available on Windows in preview
For anyone else who missed the announcement a few hours ago, open-webui is the rebranding of the project formerly known as ollama-webui [0].
I can vouch for it as a solid frontend for Ollama. It works really well and has had an astounding pace of development. Every few weeks I pull the latest docker images and am always surprised by how much has improved.
[0] https://github.com/open-webui/open-webui/discussions/764
llmsherpa
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LlamaCloud and LlamaParse
To get good RAG performance you will need a good chunking strategy. Simply getting all the text is not good enough and knowing the boundaries of table, list, paragraph, section etc. is helpful.
Great work by llamaindex team. Also feel free to try https://github.com/nlmatics/llmsherpa which takes into account some of the things I mentioned.
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Show HN: Open-source Rule-based PDF parser for RAG
I wrote about split points and the need for including section hierarchy in this post: https://ambikasukla.substack.com/p/efficient-rag-with-docume...
All this is automated in the llmsherpa parser https://github.com/nlmatics/llmsherpa which you can use as an API over this library.
What are some alternatives?
ollama-webui - ChatGPT-Style WebUI for LLMs (Formerly Ollama WebUI) [Moved to: https://github.com/open-webui/open-webui]
unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
Awesome-RAG
llama_parse - Parse files for optimal RAG
chainlit - Build Conversational AI in minutes ⚡️
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data
Ollamac - A macOS app for interacting with the Ollama models
marker - Convert PDF to markdown quickly with high accuracy
NeoGPT - Chat effortlessly, execute commands, and interpret code with Llama3, Phi3, and more - your local AI assistant. Enjoy seamless interaction while ensuring ultimate privacy
paperetl - 📄 ⚙️ ETL processes for medical and scientific papers