parabol
haystack
Our great sponsors
| parabol | haystack | |
|---|---|---|
| 33 | 54 | |
| 1,847 | 13,633 | |
| 1.9% | 5.8% | |
| 9.8 | 9.9 | |
| 4 days ago | 2 days ago | |
| TypeScript | Python | |
| GNU General Public License v3.0 or later | 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.
parabol
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How to Run a Sprint Retrospective
Parabol: Does much of the heavy lifting of facilitating for you. Applies a pre-defined structure to your retro agenda.
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Retrospective Tools
similar to teamretro: https://www.parabol.co/
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Any recommendations for improving remote only retrospective sessions?
Not sure it helps with the issues you mention, but I found https://www.parabol.co/ to stimulate discussion. Everyone writes their thoughts on their own first, then they get shown to the group, you group them, vote, and discuss in order of most votes.
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PSA don't use Datadog agent in a GraphQL project
We faced something similar. To improve GraphQL performance, we use graphql-jit. We turned off all other tracing that datadog turns on by default. Then, we then wrote a custom tracer to connect graphql-jit to dd-trace. Hopefully this same pattern works for you!
- When you use Parabol to run a meeting, you don't have to be a well-seasoned facilitator—but with features that nudge and guide you along the way, you'll feel like a pro in no time! Don’t let pricing stop you: Parabol is free for up to 2 teams. Yup, 100% free.
- You don’t have to be an agile team to benefit from regularly iterating and improving on projects. Anyone can run great retrospectives and create continuous improvement in their work. - even if you lose track, we won't. Don’t let pricing stop you: Parabol is free for up to 2 teams. Yup, 100% free.
- TIL 92% of users agreed that Parabol improves the efficiency of their meetings. By keeping meetings democratic and fair with anonymous voting, they learn what development teams want to talk about giving everyone a voice. Don’t let pricing stop you: Parabol is free for up to 2 teams. Yup, 100% free.
- Discover patterns, prioritize what matters as a team, and implement them with multiplayer grouping. Parabol’s AI automates naming groups so scrum masters don’t have to, leaving only the change up to you and your team. Don’t let pricing stop you: Parabol is free for up to 2 teams. Yup, 100% free.
haystack
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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
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Langchain Is Pointless
there is an alternative that is production-grade - deepset haystack https://haystack.deepset.ai/
p.s. i am contributor so there could be bias
What are some alternatives?
Baserow - Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins
langchain - 🦜🔗 Build context-aware reasoning applications
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
orchest - Build data pipelines, the easy way 🛠️
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
sgr - sgr (command line client for Splitgraph) and the splitgraph Python library
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!
sucrase - Super-fast alternative to Babel for when you can target modern JS runtimes
k6 - A modern load testing tool, using Go and JavaScript - https://k6.io
jina - ☁️ Build multimodal AI applications with cloud-native stack