rust-mlops-template VS haystack

Compare rust-mlops-template vs haystack and see what are their differences.

haystack

:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots. (by deepset-ai)
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rust-mlops-template haystack
2 55
273 13,711
2.2% 3.1%
5.6 9.9
8 months ago 7 days ago
Rust Python
Creative Commons Zero v1.0 Universal Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

rust-mlops-template

Posts with mentions or reviews of rust-mlops-template. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-11.

haystack

Posts with mentions or reviews of haystack. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-28.

What are some alternatives?

When comparing rust-mlops-template and haystack you can also consider the following projects:

burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

langchain - 🦜🔗 Build context-aware reasoning applications

security_camera - Person detecting security camera monitor.

langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]

burn - Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. [Moved to: https://github.com/Tracel-AI/burn]

gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

kord - A music theory binary and library for Rust / JS.

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!

azi - Show Azure information

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

jina - ☁️ Build multimodal AI applications with cloud-native stack

BERT-pytorch - Google AI 2018 BERT pytorch implementation