reor VS llm-classifier

Compare reor vs llm-classifier and see what are their differences.

reor

Self-organizing AI note-taking app that runs models locally. (by reorproject)

llm-classifier

Classify data instantly using an LLM (by lamini-ai)
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reor llm-classifier
7 4
4,235 181
7.9% 10.5%
9.9 7.8
7 days ago about 1 month ago
TypeScript Python
GNU Affero General Public License v3.0 GNU General Public License v3.0 or later
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.

reor

Posts with mentions or reviews of reor. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-03.

llm-classifier

Posts with mentions or reviews of llm-classifier. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-13.

What are some alternatives?

When comparing reor and llm-classifier you can also consider the following projects:

pong-wars

ml-ferret

obsidian-releases - Community plugins list, theme list, and releases of Obsidian.

llm-routing-agent - Agent that routes to different tools - LLM classifier SDK

Deep_Object_Pose - Deep Object Pose Estimation (DOPE) – ROS inference (CoRL 2018)

langroid - Harness LLMs with Multi-Agent Programming

get-the-news-rss-atom-feed-summary - Get a summary of the most recent news from an RSS or Atom feed using Amazon Bedrock.

heynote - A dedicated scratchpad for developers

java-snapshot-testing - Facebook style snapshot testing for JAVA Tests

Weaviate - Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.