Universal memory service with semantic search, autonomous consolidation, and multi-client support for AI applications.
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Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications.
CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms.
An open-source cross-platform performance library for deep learning applications.
Turns websites into lightweight desktop apps, useful for packaging web tools as simple cross-platform applications.
Fast and simple framework for building and running distributed applications.
An LLM-based autonomous agent controlling real-world applications via RESTful APIs.
Testing infrastructure for LLM and agentic applications with collaborative evaluation.
Provides containers to encapsulate and deploy EdgeML pipelines and applications.
Bleeding-Edge Multi-Agent Orchestration Framework for Enterprise Applications.
A neuro-symbolic framework for building applications with LLMs at the core.
Provides an open-source base to create both specialized and general purpose chatbots for various applications.
The easiest, and fastest way to run AI-generated Python code safely.
Open-source Python toolkit that tracks whether ChatGPT, Claude, and Perplexity cite your site. MIT license, runs locally on your credentials.
Open-source Python library enabling ML model inspection and interpretation.
An open source Python library focused on outlier, adversarial and drift detection.
A simple, but essential Bayesian optimization package, written in Python.
Bayesian Inference Tools in Python.
) - A desktop client written in python. Currently Linux only
A lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
The community bot for the Python Discord community
Lightweight, extensible data validation library for Python.
A simple pip-installable Python tool to generate your HTML citation world map from your Google Scholar ID.
Python library for data-centric AI and machine learning with messy, real-world data and labels.