Open Source AI Development Apps

Discover the best open source AI Development tools to build intelligent applications. From ML frameworks to data labeling, and unlock the power of AI.

98 apps available

Apps in AI Development

Python
67%
AGPL 3.0

MiroFish

AI Agents · AI Development

81,570

A universal swarm intelligence engine that spawns thousands of autonomous AI agents to simulate and predict how real-world events unfold across social, financial, and political domains.

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65
Repo Health
65
Technical
79
Dependency
Built with
Python 67%
Vue 33%
Updated 1 weeks ago
TypeScript
100%
MIT

deer-workflow

AI Agents · AI Development

552

An open-source TypeScript runtime that treats coding agents as replaceable workers inside code-defined, observable Workflow graphs.

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64
Repo Health
81
Technical
0
Dependency
Built with
TypeScript 100%
Updated 2 months ago
Python
66%
Other

Morphik

AI Development · Databases · Search

3,717

Morphik is an AI-native ingestion and retrieval engine that lets developers store, search, and reason over visually rich documents — scanned PDFs, manuals, slides, and video — without duct-taping together OCR, an embedding model, and a vector database.

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64
Repo Health
71
Technical
67
Dependency
Built with
Python 66%
TypeScript 23%
Updated 3 days ago
Python
99%
Apache 2.0

Rasa Open Source

AI Assistants · AI Development · Voice AI

21,353

Rasa Open Source is a Python machine learning framework for building contextual, multi-turn chatbots and voice assistants that understand natural language and maintain conversation state.

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62
Repo Health
78
Technical
63
Dependency
Built with
Python 99%
Updated 3 months ago
Python
83%
MIT

Gemma Multimodal Fine-Tuner

AI Development

1,516

An Apple-Silicon-native LoRA fine-tuning tool for Gemma on text, image, and audio data — with a wizard CLI, live browser-based training visualizer, and streaming from GCS/BigQuery for datasets too large for local disk.

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60
Repo Health
68
Technical
72
Dependency
Built with
Python 83%
Updated 2 weeks ago
TypeScript
96%
Apache 2.0

Pezzo

AI Development · Monitoring

3,278

Open-source LLMOps platform for prompt management, AI observability, intelligent caching, and real-time cost tracking across LLM providers.

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59
Repo Health
75
Technical
66
Dependency
Built with
TypeScript 96%
Updated 2 months ago
Elixir
97%
Apache 2.0

symphony

AI Agents · AI Development

27,805

Symphony turns your issue tracker into an autonomous implementation engine—spawning isolated coding agents per ticket so your team manages work, not agents.

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59
Repo Health
83
Technical
0
Dependency
Built with
Elixir 97%
Updated 1 months ago
C++
52%
MIT

GPT4All

AI Assistants · AI Development

77,354

Run large language models privately on your laptop — no GPU, no cloud, no data leaving your device.

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53
Repo Health
80
Technical
74
Dependency
Built with
C++ 52%
QML 30%
Updated 1 years ago
Rust
79%
Apache 2.0

TensorZero

Ab Testing Experimentation · AI Development · Monitoring

11,708

TensorZero unifies the LLM gateway, observability, evaluation, optimization, and experimentation stack behind a single OpenAI-compatible API, built in Rust for sub-millisecond p99 latency.

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53
Repo Health
87
Technical
68
Dependency
Built with
Rust 79%
TypeScript 15%
Updated 4 months ago
TypeScript
84%
Apache 2.0

ktx

AI Development · Analytics · Data Engineering

1,623

ktx builds a self-improving context layer over your data warehouse so AI agents like Claude Code and Codex query it with approved metric definitions instead of reinventing SQL logic from scratch.

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52
Repo Health
85
Technical
71
Dependency
Built with
TypeScript 84%
Updated 2 days ago
Rust
63%
MIT

PostgresML

AI Development · Databases

6,823

Run ML training and LLM inference natively inside PostgreSQL with GPU acceleration — no data movement required.

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51
Repo Health
76
Technical
64
Dependency
Built with
Rust 63%
JavaScript 11%
Updated 1 years ago
TypeScript
95%
MIT

Open Lovable

AI Development

28,793

An open-source AI app builder that scrapes a live website and recreates it as a modern React app through chat — built by Firecrawl as a self-hostable example of the Lovable.dev workflow.

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50
Repo Health
66
Technical
69
Dependency
Built with
TypeScript 95%
Updated 2 weeks ago
Python
100%
MIT

Unlimited OCR

AI Development

28,300

Baidu's open-source OCR model for "one-shot, long-horizon parsing" — published with an arXiv paper, a Hugging Face model release, and vLLM inference support, aimed at document understanding beyond typical page-by-page OCR limits.

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50
Repo Health
69
Technical
0
Dependency
Built with
Python 100%
Updated yesterday
Python
97%
MIT

local-deep-researcher

AI Assistants · AI Development

9,387

A fully local web research assistant that iteratively searches, summarizes, and refines markdown reports using any Ollama or LMStudio model—no cloud or API keys required.

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49
Repo Health
74
Technical
76
Dependency
Built with
Python 97%
Updated 1 weeks ago
TypeScript
98%
MIT

Tersa

AI Agents · AI Development

1,043

An open-source visual canvas for building AI workflows by connecting nodes across 35+ model providers with drag-and-drop simplicity.

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46
Repo Health
77
Technical
71
Dependency
Built with
TypeScript 98%
Updated 5 months ago

About AI Development

Build the Future with AI Development Tools

The AI Development category is focused on enabling developers to create applications with intelligent capabilities. This goes beyond simply using pre-built AI APIs; it’s about the entire lifecycle of machine learning (ML) – from data preparation and model training to deployment, monitoring, and continuous improvement. Whether you’re a seasoned data scientist or just starting to explore the world of AI, these tools provide the building blocks for innovative solutions. Core concepts include deep learning, natural language processing (NLP), computer vision, and predictive analytics.

This category includes a diverse range of app types. You’ll find MLOps platforms for tracking experiments and managing model versions, data labeling tools to prepare training datasets, model serving frameworks for deploying models at scale, and AI-powered code assistants that streamline development workflows. Furthermore, specialized libraries for specific AI tasks (e.g., PyTorch for deep learning, spaCy for NLP) are often found here.

The value of AI Development lies in its ability to solve complex problems across many industries. Predictive maintenance in manufacturing, fraud detection in finance, personalized recommendations in e-commerce, and image recognition for autonomous vehicles are just a few examples. By automating tasks, gaining insights from data, and creating more intuitive user experiences, AI Development tools empower businesses to gain a competitive edge. Investing in this category means embracing the future of software and unlocking unprecedented possibilities.

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