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awesome-golang-ai

Golang AI applications have incredible potential. With unique features like inexplicable speed, easy debugging, concurrency, and excellent libraries for ML, deep learning, and reinforcement learning.
https://github.com/promacanthus/awesome-golang-ai

Last synced: 5 days ago
JSON representation

  • General Machine Learning libraries

    • Pipeline and Data Version

      • goml - line Machine Learning in Go (and so much more).
      • golearn
      • gonum
      • gorgonia
      • goro - level Machine Learning Library for Go.
      • goga
      • hep - hep.org/x/hep packages and tools.
      • hector
      • sklearn
      • spago - contained Machine Learning and Natural Language Processing library in Go.

  • Neural Networks

  • Linear Algebra

  • Probability Distributions

    • Pipeline and Data Version

  • Regression

  • Bayesian Classifiers

  • Recommendation Engines

  • Evolutionary Algorithms

  • Graph

    • Pipeline and Data Version

  • Cluster

    • Pipeline and Data Version

      • kmeans - means clustering algorithm implementation written in Go.
      • gokmeans - means algorithm implemented in Go (golang).

  • Anomaly Detection

  • DataFrames

  • Explaining Model

  • Large Language Model

    • DevTools

      • go-attention
      • langchaingo - based programs in Go.
      • gpt4all-bindings - language interfaces to easily integrate and interact with GPT4All's local LLMs, simplifying model loading and inference for developers.
      • go-openai - 3, GPT-4, DALL·E, Whisper API wrapper for Go.
      • llama.go
      • eino
      • fabric - source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.
      • genkit - powered apps with familiar code-centric patterns. Genkit makes it easy to develop, integrate, and test AI features with observability and evaluations. Genkit works with various models and platforms.
      • ollama - R1, Phi-4, Gemma 2, and other large language models.

    • SDKs

    • ChatGPT Apps

    • Pipeline and Data Version

      • pachyderm - Centric Pipelines and Data Versioning.

    • Vector Database

      • milvus - performance, cloud-native vector database built for scalable vector ANN search.
      • weaviate - 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​.
      • tidb - the open-source, cloud-native, distributed SQL database designed for modern applications.

  • Reinforcement Learning

  • Benchmark

    • English

      • MTEB
      • ARC-AGI
      • GPQA - Level Google-Proof Q&A Benchmark.
      • ARC-Challenge
      • BBH - Bench Tasks and Whether Chain-of-Thought Can Solve Them.
      • HelloSwag
      • IFEval - following capabilities of large language models by incorporating 25 verifiable instruction types (e.g., format constraints, keyword inclusion) and applying dual strict-loose metrics for automated, objective assessment of model compliance.
      • MMLU-CF - free Multi-task Language Understanding Benchmark.
      • MMLU-Pro - Task Language Understanding Benchmark.
      • PIQA
      • WinoGrande
      • BIG-bench
      • MMLU
      • LiveBench - Free LLM Benchmark.

    • Math

      • Omni-MATH - MATH is a comprehensive and challenging benchmark specifically designed to assess LLMs' mathematical reasoning at the Olympiad level.
      • grade-school-math - step reasoning capabilities in language models, revealing that even large transformers struggle with these conceptually simple yet procedurally complex tasks.
      • MATH - solving capabilities, offering dataset loaders, evaluation code, and pre-training data.
      • MathVista
      • TAU-bench - source benchmark suite designed to evaluate the performance of large language models (LLMs) on complex reasoning tasks across multiple domains.
      • AIME

    • Chinese

    • Code

      • BigCodeBench
      • Code4Bench
      • CRUXEval
      • HumanEval
      • MBPP - sourced Python programming problems, designed to be solvable by entry level programmers, covering programming fundamentals, standard library functionality, and so on.
      • MultiPL-E - programming language benchmark for LLMs.
      • SWE-bench - bench is a benchmark suite designed to evaluate the capabilities of large language models (LLMs) in solving real-world software engineering tasks, focusing on actual software bug-fixing challenges extracted from open-source projects.
      • AIDER - related tasks, such as code writing and editing.
      • LiveCodeBench
      • BFCL - calling capability of different LLMs.

    • Tool Use

      • BFCL
      • T-Eval - Eval: Evaluating Tool Utilization Capability of Large Language Models Step by Step.
      • WildBench

    • Open ended

      • Arena-Hard - Hard-Auto: An automatic LLM benchmark.

    • False refusal

    • Multi-modal

      • geneval - focused framework for evaluating text-to-image alignment.
      • LongVideoBench
      • MLVU - task Long Video Understanding Benchmark.
      • perception_test
      • TempCompass
      • Video-MME - MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.
      • VBench - source project aiming to build a comprehensive evaluation benchmark for video generation models.
      • DPG-Bench

      • ADeLe
      • SWELancer - Lancer-Benchmark** is designed to evaluate the capabilities of frontier LLMs in solving real-world freelance software engineering tasks, exploring their potential to generate economic value through complex software development scenarios.

  • [Model Context Protocol](https://modelcontextprotocol.io/introduction)

  • Decision Trees

Programming Languages
Go 58 Python 30 Jupyter Notebook 5 HTML 2 JavaScript 2 TypeScript 1
Categories
Benchmark 48 Large Language Model 18 General Machine Learning libraries 10 Neural Networks 9 DataFrames 3 Explaining Model 3 Anomaly Detection 3 Recommendation Engines 3 Regression 2 Reinforcement Learning 2 Bayesian Classifiers 2 Linear Algebra 2 Cluster 2 Evolutionary Algorithms 2 [Model Context Protocol](https://modelcontextprotocol.io/introduction) 2 Probability Distributions 1 Decision Trees 1 Graph 1
Sub Categories
Pipeline and Data Version 47 English 14 Code 10 Multi-modal 10 DevTools 9 Math 6 Vector Database 3 SDKs 3 Tool Use 3 Chinese 3 ChatGPT Apps 2 Open ended 1 False refusal 1
Keywords
go 21 golang 17 machine-learning 13 llm 6 neural-network 6 artificial-intelligence 5 ai 5 chatgpt 4 gpt-3 4 openai 4 deep-learning 4 benchmark 4 data-science 4 gpt-4 3 vector-database 3 statistics 3 scientific-computing 3 language-model 2 recommender-system 2 large-language-models 2 evaluation 2 dataframe 2 llama 2 multimodal-large-language-models 2 rag 2 chatgpt-api 2 langchain 2 semantic-search 2 neural-search 2 information-retrieval 2 serverless 2 optimization 2 neural-networks 2 natural-language-processing 2 regression 2 deeplearning 2 computation-graph 2 automatic-differentiation 2 matrix 2 data-analysis 2 image-search 2 nearest-neighbor-search 2 hnsw 2 vector-search 2 cloud-native 2 matrix-multiplication 1 sparse-linear-systems 1 sparse-matrices 1 sparse-matrix 1 sparse-representations 1