gerev
haystack
| gerev | haystack | |
|---|---|---|
| 28 | 55 | |
| 2,610 | 13,711 | |
| 0.3% | 3.1% | |
| 8.5 | 9.9 | |
| 4 months ago | 4 days ago | |
| Python | Python | |
| MIT License | 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.
gerev
- A FOSS chat bot trained on docs/ansible?
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Show HN: GPT-4-powered web searches for developers on Phind.com
https://github.com/gerevai/gerev to see for yourself.
Or you could try our sweet little demo: https://demo.gerev.ai
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Show HN: I “leaked” W23 YC internal pages and made them searchable
Some legit funny stuff is hiding here.
You can use gerev to host your own workplace search engine: <https://github.com/gerevai/gerev>
Disclaimer: no I didn't leak YC's internal intranet! all output by partners was generated by ChatGPT. don't sue me!
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What do you self host that has replaced paid services?
gerev - self hosted search engine
- FLaNK Stack Weekly 27 March 2023
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Show HN: Google-like search for workplace knowledge
Or easily bring up important docs in real-time during meetings.
I believe private data should remain private. All too often, AI products send private data to cloud-based LLMs. I believe that AI should assist users without breaching their privacy.
Feel free to check it out <https://github.com/gerevai/gerev>
- ChatGPT-like workplace search engine
- Show HN: Google-Like Search for Workplaces
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A new tool - webdev workplace search engine
https://github.com/gerevai/gerev - growing super fast.
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?
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
langchain - 🦜🔗 Build context-aware reasoning applications
gerevai
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
pgvector - Open-source vector similarity search for Postgres
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
spring-boot-startup-report - Spring Boot Startup Report library generates an interactive Spring Boot application startup report that lets you understand what contributes to the application startup time and perhaps helps to optimize it.
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!
dotfiles - The best and strongest dotfiles. Editor: Neovim; Shell: zsh(zinit, powerlevel10k); Terminal: wezterm; Desktop: hyprland/sway, ulauncher, dunst; OS: ArchLinux (Ubuntu/Fedora/CentOS)
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
specification - Serverless Workflow Specification
jina - ☁️ Build multimodal AI applications with cloud-native stack