dvclive
quivr
| dvclive | quivr | |
|---|---|---|
| 5 | 23 | |
| 158 | 33,605 | |
| 3.8% | 3.6% | |
| 8.8 | 9.9 | |
| 3 days ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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.
dvclive
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First 15 Open Source Advent projects
10. DVC by Iterative | Github | tutorial
- Log and track ML metrics, parameters, models with Git and DVC
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[P] Extension for VS Code to track ML experiments
There is no designated way to dump metrics. In the case of data for plots, we have a simple logger that might help: https://github.com/iterative/dvclive
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Show HN: DVC Studio – Git-Based ML Experiments Management
DVC has metrics logger similar to other experiment management tool: https://github.com/iterative/dvclive/
Also, metrics & params section of the docs explains this (but yes, it is not perfect yet): https://dvc.org/doc/start/metrics-parameters-plots
quivr
- Ask HN: I have many PDFs – what is the best local way to leverage AI for search?
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privateGPT VS quivr - a user suggested alternative
2 projects | 12 Jan 2024
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First 15 Open Source Advent projects
3. Quivr | GitHub | tutorial
- What's the catch with codecanyon?
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Went down the rabbit hole of 100% local RAG, it works but are there better options?
I used Ollama (with Mistral 7B) and Quivr to get a local RAG up and running and it works fine, but was surprised to find there are no easy user-friendly ways to do it. Most other local LLM UIs don't implement this use case (I looked here), even though it is one of the most useful local LLM use-cases I can think of: search and summarize information from sensitive / confidential documents.
- FLaNK Stack Weekly for 21 August 2023
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Discord Is Not Documentation
In my opinion LLM based document search tools such as OSS Quivr may be better suited for documentation search for startups.
A highly customed Quivr with one of the 'Open Source LLMs' may provides great 'semantic search' for product documentation.
https://github.com/StanGirard/quivr
- Quivr
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I built an open source website that lets you upload large files such as academic PDFs or books and ask ChatGPT questions based on your custom knowledge base. So far, I've tried it with long ebooks like Plato's Republic, old letters, and random academic PDFs, and it works shockingly well.
Hey thanks for creating this, will try later if i have time. Meanwhile, do you try some of other second brain app such as this, and how was the comparison? The one i mentioned was trending on github so i think its decent (been playing with it since last week or so, also). But i already starred your repo so i can come back later.
- Quivr – Your Second Brain, Empowered by Generative AI
What are some alternatives?
phoenix - AI Observability & Evaluation
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
pytest-visual - A visual testing framework for ML with automated change detection
Flowise - Drag & drop UI to build your customized LLM flow
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
chart-gpt - AI tool to build charts based on text input
dvc - 🦉 ML Experiments and Data Management with Git
databerry - The no-code platform for building custom LLM Agents
OpenLLM - Run any open-source LLMs, such as Llama 2, Mistral, as OpenAI compatible API endpoint in the cloud.
xTuring - Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.
khoj - Your AI second brain. Get answers to your questions, whether they be online or in your own notes. Use online AI models (e.g gpt4) or private, local LLMs (e.g llama3). Self-host locally or use our cloud instance. Access from Obsidian, Emacs, Desktop app, Web or Whatsapp.