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Top 23 Reasoning Open-Source Projects
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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Awesome-LLM-Reasoning
Reasoning in LLMs: Papers and Resources, including Chain-of-Thought, OpenAI o1, and DeepSeek-R1 🍓
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Project mention: Hugging Face is looking for reasoning datasets beyond math, science and coding | dev.to | 2025-04-16
OpenThoughts-114k generation code
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Project mention: Being on The Semantic Web is easy, and, frankly, well worth the bother | news.ycombinator.com | 2024-08-21
The semantic web standards are sorely lacking (for decades now) a killer application. Not in a theoretical universe of decentralized philosopher-computer-scientists but in the dumbed down, swipe-the-next-30sec-video, adtech oligopolized digital landscape of walled gardens. Providing better search metadata is hardly that killer app. Not in 2024.
The lack of adoption has, imho, two components.
1. bad luck: the Web got worse, a lot worse. There hasn't been a Wikipedia-like event for many decades. This was not pre-ordained. Bad stuff happens to societies when they don't pay attention. In a parallel universe where the good Web won, the semantic path would have been much more traveled and developed.
2. incompleteness of vision: if you dig to their nuclear core, semantic apps offer things like SPARQL queries and reasoners. Great, these functionalities are both unique and have definite utility but there is a reason (pun) that the excellent Protege project [1] is not the new spreadsheet. The calculus of cognitive cost versus tangible benefit to the average user is not favorable. One thing that is missing are abstractions that will help bridge that divide.
Still, if we aspire to a better Web, the semantic web direction (if not current state) is our friend. The original visionaries of the semantic web where not out of their mind, they just did not account for the complex socio-economics of digital technology adoption.
[1] https://protege.stanford.edu/
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ThoughtSource
A central, open resource for data and tools related to chain-of-thought reasoning in large language models. Developed @ Samwald research group: https://samwald.info/
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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Project mention: Understanding R1-Zero-Like Training: A Critical Perspective | news.ycombinator.com | 2025-03-22
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self-refine
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
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Neurosymbolic AI represents a convergence of symbolic reasoning (exemplified by Prolog's logic programming) and neural networks' pattern recognition capabilities. This hybrid approach addresses the limitations of each paradigm while leveraging their complementary strengths. For a deeper dive in the concepts and history of symbolic AI, see excellent article here on dev.to by developers from Nucleoid, and reference to various readings on the bottom of this article.
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lumos
Code and data for "Lumos: Learning Agents with Unified Data, Modular Design, and Open-Source LLMs" (by allenai)
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multi1
multi1: create o1-like reasoning chains with multiple AI providers (and locally). Supports LiteLLM as backend too for 100+ providers at once.
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awesome-rust-formalized-reasoning
An exhaustive list of all Rust resources regarding automated or semi-automated formalization efforts in any area, constructive mathematics, formal algorithms, and program verification.
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neurallambda
Reasoning Computers. Lambda Calculus, Fully Differentiable. Also Neural Stacks, Queues, Arrays, Lists, Trees, and Latches.
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Project mention: Self-hosting LLMs for Production Systems: Solving the Model Quality Challenge | dev.to | 2025-04-07
For more information on setting up self-hosted models, check out our documentation on model configuration.
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meta-prompting
Official implementation of paper "Meta Prompting for AI Systems" (https://arxiv.org/abs/2311.11482)
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multimodal
A collection of multimodal datasets, and visual features for VQA and captionning in pytorch. Just run "pip install multimodal" (by cdancette)
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nyt-connections
Benchmark that evaluates LLMs using 651 NYT Connections puzzles extended with extra trick words
On the extended version of NYT Connections - https://github.com/lechmazur/nyt-connections/:
Claude Opus 4 Thinking 16K: 52.7.
Claude Opus 4 No Reasoning: 34.8.
Claude Sonnet 4 Thinking 64K: 39.6.
Claude Sonnet 4 Thinking 16K: 41.4 (Sonnet 3.7 Thinking 16K was 33.6).
Claude Sonnet 4 No Reasoning: 25.7 (Sonnet 3.7 No Reasoning was 19.2).
Claude Sonnet 4 Thinking 64K refused to provide one puzzle answer, citing "Output blocked by content filtering policy." Other models did not refuse.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Reasoning discussion
Reasoning related posts
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Strengths and limitations of diffusion language models – sean goedecke
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Gemini Diffusion
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GRPO experiment: I trained a Language Model to schedule events
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Prolog-MCP Server: Neurosymbolic AI for Modern Workflows
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Hugging Face is looking for reasoning datasets beyond math, science and coding
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Understanding R1-Zero-Like Training: A Critical Perspective
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Open Thoughts: open data curation for reasoning models
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A note from our sponsor - InfluxDB
www.influxdata.com | 19 Jun 2025
Index
What are some of the best open-source Reasoning projects? This list will help you:
# | Project | Stars |
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1 | typedb | 3,997 |
2 | Awesome-LLM-Reasoning | 3,152 |
3 | ReAct | 2,614 |
4 | open-thoughts | 1,920 |
5 | math | 1,136 |
6 | Protégé | 1,094 |
7 | ThoughtSource | 976 |
8 | understand-r1-zero | 983 |
9 | self-refine | 702 |
10 | Nucleoid | 621 |
11 | pal | 486 |
12 | lumos | 465 |
13 | opennars | 395 |
14 | multi1 | 347 |
15 | awesome-rust-formalized-reasoning | 342 |
16 | neurallambda | 261 |
17 | rci-agent | 234 |
18 | orra | 210 |
19 | meta-prompting | 176 |
20 | awesome-reasoning | 136 |
21 | OpenNARS-for-Applications | 98 |
22 | multimodal | 82 |
23 | nyt-connections | 101 |