Search Results for "feedback"
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Showing 157 open source projects for "feedback"
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ty
An extremely fast Python type checker and language server
...It is positioned as a next-generation alternative to tools such as mypy and Pyright, offering significantly faster performance through incremental analysis and optimized execution. The tool is designed from the ground up to power editor integrations, enabling real-time feedback as developers write code with minimal latency. ty includes advanced type system capabilities such as intersection types, improved type inference, and detailed diagnostics that help identify issues even in partially typed codebases. It supports integration with multiple development environments through its language server implementation, providing features like code navigation, auto-completion, and inline hints. -
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ImageReward
[NeurIPS 2023] ImageReward: Learning and Evaluating Human Preferences
...It is provided as a Python package (image-reward) that enables quick scoring of generated images against textual prompts, with APIs for ranking, scoring, and filtering outputs. Beyond evaluation, ImageReward supports Reward Feedback Learning (ReFL), a method for directly fine-tuning diffusion models such as Stable Diffusion using human-preference feedback, leading to demonstrable improvements in image quality. -
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Reef
Continual learning infra for self-improving agents
Reef is open-source infrastructure for building AI agents that continually improve from interaction and feedback. It connects live inference, feedback collection, learning, evaluation, and versioned deployment in one lifecycle. The system can improve either underlying model weights or the surrounding agent harness, including prompts, skills, and rules. Its core loop follows four stages: serve requests, observe feedback, grow candidate improvements, and commit accepted updates. ... -
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EvoAgentX
Self-evolving AI agent framework for automated workflows
EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows, evaluation, and evolution, enabling flexible experimentation and scaling. EvoAgentX integrates optimisation algorithms to refine prompts, tool usage, and workflow structures over time. ... -
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TruLens
Evaluation and Tracking for LLM Experiments
TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation. Fine-grained, stack-agnostic instrumentation and comprehensive evaluations help identify failure modes and systematically iterate to improve applications. ... -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
...It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. By iterating through these stages, the framework continuously refines models and strategies using feedback from previous results. RD-Agent focuses heavily on automating complex tasks such as feature engineering, model design, and experimentation, which are traditionally time-consuming in machine learning and quantitative research workflows. RD-Agent can analyze data, generate experimental code, run evaluations, and learn from outcomes to improve future iterations. -
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OpenBiliClaw
Local-first open-source cross-platform AI content discovery agent
OpenBiliClaw is a free, open-source, local-first AI agent designed for personalized content discovery across social media and online platforms. It learns user interests from browsing activity, conversations, and explicit feedback to generate relevant recommendations. The application discovers content from Bilibili, YouTube, Reddit, TikTok, X, Xiaohongshu, Zhihu, GitHub, and other services. Its evolving preference model adjusts recommendations when users like, dismiss, or discuss suggested content. Personal data is stored locally in SQLite rather than requiring centralized profile storage. ... -
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MetaClaw
Just talk to your agent
MetaClaw is an AI or agent-oriented system that appears to focus on advanced control, coordination, or training of autonomous agents, potentially within reinforcement learning or tool-using environments. The project likely emphasizes meta-level reasoning, where agents are not only executing tasks but also adapting their strategies based on feedback and performance signals. It may incorporate mechanisms for learning from interactions, improving decision-making over time, and generalizing across different domains. The architecture suggests scalability, allowing the system to handle multiple agents or complex workflows simultaneously. It is likely designed for experimentation with next-generation agent systems that combine planning, learning, and execution. ... -
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DeepTutor
AI-Powered Personalized Learning Assistant
DeepTutor is an AI-powered tutoring and learning assistant framework designed to automatically teach, explain, and reinforce academic or technical concepts in depth according to a learner’s specific needs. It goes beyond simple Q&A by constructing multi-stage educational narratives, breaking down complex topics into sequenced “lesson steps,” and offering prompts, examples, and exercises that build on each other in a logical curriculum. The core architecture combines LLM-based reasoning with... -
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yt-dlp-gui
A cross-platform GUI wrapper for yt-dlp written in PySide6
yt-dlp-gui is a cross-platform graphical interface for the popular command-line video downloader yt-dlp, created to make video and audio downloads from sites like YouTube, Vimeo, Twitch, and others easier for everyday users without needing to work directly with command-line arguments. Written in PySide6 (Python with Qt bindings), it wraps the powerful yt-dlp engine in a visual application that lets users paste video URLs, choose formats, apply presets, and start downloads with a click, while... -
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KaTrain
Improve your Baduk skills by training with KataGo
KaTrain is an advanced training and analysis tool for the board game Go that leverages the powerful KataGo AI engine to provide real-time feedback and in-depth game review capabilities. It is designed to help players of all skill levels improve by identifying mistakes, analyzing move efficiency, and offering alternative strategies based on AI evaluation. The application allows users to play against AI opponents with adjustable difficulty, including intentionally weakened versions of the engine that simulate human-like play styles. ... -
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Implicit
Fast Python collaborative filtering for implicit feedback datasets
This project provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets. All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding up making recommendations. -
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Open Interface
Control Any Computer Using LLMs
...By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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AIBuildAI
An AI agent that automatically builds AI models
...The framework is designed to support experimentation with self-improving AI pipelines, allowing developers to test concepts like automated architecture search or adaptive system evolution. It integrates multiple components including prompt management, execution control, and feedback loops to ensure that generated outputs can be evaluated and improved over time. -
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Blik360
Self hosted & open source anonymous 360 review software
Blik is an open source, self-hosted platform for anonymous 360-degree feedback and performance review cycles, built with a strong focus on privacy, transparency, and developer-friendly deployment. It allows organizations to run review cycles where employees get anonymous feedback from peers, managers, and direct reports, without vendor lock-in or per-user licensing costs. The system is built using the Django framework, with a PostgreSQL backend, and is packaged for easy deployment via Docker Compose, making it accessible for small teams or startups to spin up on their own infrastructure. ... -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. In addition to code analysis, the tool can produce daily development summaries and notifications that help teams track progress and review activity across projects. -
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PaLM + RLHF - Pytorch
Implementation of RLHF (Reinforcement Learning with Human Feedback)
PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT. -
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MathCode
A Frontier Mathematical Coding Agent
...It is designed to transform plain-language mathematical reasoning into verified Lean 4 code and formal proofs. The project combines AI agents with Lean Language Server Protocol integration, allowing it to inspect compiler feedback, search for lemmas, and iteratively repair failed proof attempts. It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. ... -
19
Pyxel
A retro game engine for Python
...Thanks to its simple specifications inspired by retro gaming consoles, such as only 16 colors can be displayed and only 4 sounds can be played back at the same time, you can feel free to enjoy making pixel art style games. The motivation for the development of Pyxel is the feedback from users. Please give Pyxel a star on GitHub! Pyxel's specifications and APIs are inspired by PICO-8 and TIC-80. Pyxel is open source and free to use. Let's start making a retro game with Pyxel! Runs on Windows, Mac, Linux, and Web. Using the Pyxel Web Launcher or custom elements for HTML, you can run Pyxel in a web browser without any installation work. ... -
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Oppia
A free, online learning platform to make quality education accessible
Oppia is an online learning tool that enables anyone to easily create and share interactive activities (called 'explorations'). These activities simulate a one-on-one conversation with a tutor, making it possible for students to learn by doing while getting feedback. Oppia identifies common wrong answers and provides tailored feedback, so that students get a personalized experience. Our lessons keep students engaged through playful characters and use different strategies to solidify their knowledge. Check out our math lessons with proven results! In addition to developing the Oppia platform, the team is also developing and piloting a set of free and effective lessons on basic mathematics. ... -
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HY-Motion 1.0
HY-Motion model for 3D character animation generation
...The training strategy for the HY-Motion series includes extensive pre-training on thousands of hours of varied motion data, fine-tuning on curated high-quality datasets, and reinforcement learning with human feedback, which improves both the plausibility and adaptability of generated motion sequences. -
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colleague-skill
Transform a cold separation into a warm Skill
...The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. It emphasizes communication and coordination, ensuring that agents can contribute meaningfully to shared objectives. This makes it particularly useful for complex projects where multiple perspectives or iterative refinement are needed. -
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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code optimization, and scientific workflows. It includes built-in tasks, a command-line runner, and a visual dashboard for following generations as they evolve. ... -
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AI Researcher
An autonomous AI researcher
...The system emphasizes modularity, so teams can swap in new reasoning modules, data retrieval strategies, or domain knowledge bases depending on the research topic. Through self-supervised feedback loops, agents adjust their strategies based on prior outcomes, improving both the quality and relevance of results over time. -
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H2O Wave
Realtime Web Apps and Dashboards for Python and R
...Instant control over every connected web browser using a simple and intuitive programming model. Preview your app live as you code. Dramatically reduce the time and effort to build web apps. Easily share your apps with end-users, get feedback, improve and iterate. ~10MB static executables for Linux, Windows, OSX, BSD, Solaris on AMD64, 386, ARM, PPC. Run it on a RPi Zero for great good!
