quivr
haystack
quivr | haystack | |
---|---|---|
22 | 55 | |
32,917 | 13,711 | |
7.7% | 3.1% | |
9.9 | 9.9 | |
about 24 hours ago | 6 days ago | |
TypeScript | 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.
quivr
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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
- Quivr: Chatting with your own docs
haystack
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Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
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Release Radar • March 2024 Edition
View on GitHub
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First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
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Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
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Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
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Which LLM framework(s) do you use in production and why?
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!??
- Overview: AI Assembly Architectures
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Llama2 and Haystack on Colab
I recently conducted some experiments with Llama2 and Haystack (https://github.com/deepset-ai/haystack), the NLP/LLM framework.
The notebook can be helpful for those trying to load Llama2 on Colab.
1) Installed Transformers from the main branch (and other libraries)
- Build with LLMs for production with Haystack – has 10k stars on GitHub
- Show HN: Haystack – Production-Ready LLM Framework
What are some alternatives?
localGPT - Chat with your documents on your local device using GPT models. No data leaves your device and 100% private.
langchain - 🦜🔗 Build context-aware reasoning applications
chart-gpt - AI tool to build charts based on text input
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
Flowise - Drag & drop UI to build your customized LLM flow
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
databerry - The no-code platform for building custom LLM Agents
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
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
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
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.
jina - ☁️ Build multimodal AI applications with cloud-native stack