← heapsort-ai

Open Source

313 items

ARTICLEDEV.to AI·4/23/2026

I built an open-source AI agent that turns a trade idea into a full backtest — here's why

The author built an open-source AI agent to streamline the process of transforming investment ideas into tested strategies, addressing the fragmentation of existing quantitative finance tools. This agent integrates data pulling from SEC filings with backtesting, offering reproducible results and combining AI-driven thesis generation with analytical rigor.

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ARTICLEDEV.to AI·3d ago

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This article critiques vendor lock-in in the AI API landscape, advocating for open-source-friendly alternatives. It highlights the significant cost savings and flexibility offered by Global API, which consolidates 184 AI models with a single API key.

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ARTICLEDEV.to AI·2d ago

I Built Yumii — An Open-Source AI Companion

Yumii is an open-source, locally-run AI companion featuring a Live2D avatar, real-time voice, and six personalities, now capable of long-term memory across sessions. It prioritizes accessibility with easy installation, comprehensive documentation, and a streamlined onboarding process, developed for the GitHub Finish-Up-A-Thon Challenge.

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ARTICLEDEV.to AI·3d ago

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This article compares open-source AI APIs with self-hosting models for small data science practices, focusing on cost and practicality. It offers a data scientist's perspective on choosing the optimal approach.

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DOCML Mastery·5d ago

Using Scikit-LLM with Open-Source LLMs

This article provides a tutorial on integrating locally hosted open-source large language models such as Mistral, Gemma, and Llama 3 for language tasks like text classification. It demonstrates how to achieve this for free using Ollama and the Scikit-LLM Python library.

Using Scikit-LLM with Open-Source LLMs
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DOCDEV.to AI·4/24/2026

How To Contribute to Open Source Embodied AI

This content explores the rise of open-source embodied AI, which democratizes the development of intelligent robots interacting with the physical world. It provides key takeaways for contributing, including engaging with platforms like ROS and Gazebo, developing programming and AI/ML skills, and actively participating in projects.

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