haystack
EdgeChains
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| haystack | EdgeChains | |
|---|---|---|
| 54 | 12 | |
| 13,633 | 284 | |
| 5.8% | 7.7% | |
| 9.9 | 9.3 | |
| 2 days ago | 5 days ago | |
| Python | JavaScript | |
| Apache License 2.0 | 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.
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
EdgeChains
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HonoJS: Small, simple, and ultrafast web framework for the Edges
We build a WASM compiler to compile our prompts and chains into webassembly. Honojs was a critical part of it.
https://github.com/arakoodev/EdgeChains/
- looking for someone to codereview an opensource Typescript+webassembly framework for Generative AI apps
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Overview: AI Assembly Architectures
EdgeChains: github.com/arakoodev/EdgeChains
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Stanford DSPy: The framework for programming with foundation models
would love your thoughts on this as well - https://github.com/arakoodev/edgechains
got frustrated in the same way with "Black Box Prompting - every library hides prompts/chains in layers of libraries...while it should have been declarative.
EdgeChains - allows u to specify ur prompt and chain in jsonnet. This why i think Generative AI needs declarative orchestration and not previous generations. https://github.com/arakoodev/edgechains#why-do-you-need-decl...
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Show HN: Chat with your data using LangChain, Pinecone, and Airbyte
when will you have pgvector as a destination ? we (https://github.com/arakoodev/edgechains) work with a lot of enterprises and they would not move away from using redis or pgvector even as their vector store. Is there a way where we can leverage that ?
Second, for a LOT of enterprises, they want to use non-openai embedding models (minilm, GTE, BGE), will you support that. For e.g. in Edgechains we natively support BGE and minilm. Would you be able to support that ?
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Chunking 2M+ files a day for Code Search using Syntax Trees
oh really ? Thats awfully kind. I'll take that in for EdgeChains as well.
https://github.com/arakoodev/EdgeChains/issues/172
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Langchain Is Pointless
Promptfile is written in markdown, which is unsuited for templates and config management.
I have an attempt in the same domain, would love feedback
We didnt invent a new markup - we used jsonnet which is used in large scale kubernetes and has a grammar that has been well tested for config mgmt.
https://github.com/arakoodev/EdgeChains/blob/main/Examples/r...
Prompts live outside the code.
- Calling ChatGPT API from Spring Boot
What are some alternatives?
langchain - 🦜🔗 Build context-aware reasoning applications
autogen - A programming framework for agentic AI. Discord: https://aka.ms/autogen-dc. Roadmap: https://aka.ms/autogen-roadmap
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
AgentVerse - 🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation
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!
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
awesome-ai-agents - A list of AI autonomous agents
jina - ☁️ Build multimodal AI applications with cloud-native stack