Search Results for "custom control"
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Showing 48 open source projects for "custom control"
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AUTOMATIC1111 Stable Diffusion web UI
Stable Diffusion web UI
...Supporting both text-to-image (txt2img) and image-to-image (img2img) generation, this open-source UI offers a rich feature set including inpainting, outpainting, attention control, and multiple advanced upscaling options. With a flexible installation process across Windows, Linux, and Apple Silicon, plus support for GPUs and CPUs, it caters to a wide range of users—from hobbyists to professionals. The interface also supports prompt editing, batch processing, custom scripts, and many community extensions, making it a highly customizable and continually evolving platform for creative AI art generation. -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
...Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. Think building blocks for deep learning. -
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MHR-CFW
A Domain-Fronting Relay that routes traffic though GAS
MHR-CFW is a custom firmware project designed to modify and extend the functionality of specific gaming or embedded systems. It provides tools and patches that allow users to unlock additional features, bypass restrictions, or enhance performance. The project focuses on enabling deeper control over system behavior through firmware-level changes. It is particularly relevant for enthusiasts and developers interested in system modification and customization. -
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Open Notebook
An Open Source implementation of Notebook LM with more flexibility
Open Notebook is an open-source, privacy-focused alternative to Google’s Notebook LM that gives users full control over their research and AI workflows. Designed to be self-hosted, it ensures complete data sovereignty by keeping your content local or within your own infrastructure. The platform supports 16+ AI providers—including OpenAI, Anthropic, Ollama, Google, and LM Studio—allowing flexible model choice and cost optimization. Open Notebook enables users to organize and analyze... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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YandexStation
Management of Yandex Station and other smart home devices
YandexStation is a Home Assistant custom component that integrates Yandex-branded smart speakers and other devices with Alice into a unified smart home automation environment. It supports both local and cloud control, depending on the device type, with Yandex speakers often supporting both modes and third-party speakers typically limited to cloud control. The integration exposes playback and volume controls, as well as text-to-speech capabilities that send spoken messages in Alice’s voice directly to the speakers. ... -
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CoPaw
Your Personal AI Assistant; easy to install, deploy on local or coud
...It includes a browser-based Console for chatting, configuring models, managing memory, and extending capabilities with custom skills. With built-in cron scheduling, heartbeat check-ins, and extensible skill loading, CoPaw grows with your workflow over time. Easy installation options—including pip, one-line scripts, Docker, and cloud deployment—make it accessible for both developers and non-technical users. -
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Bear Stone Smart Home
Custom Home Assistant configuration with automations and scripts setup
Bear Stone Smart Home contains a personalized configuration setup for Home Assistant, an open source home automation platform. It defines how various smart home devices, services, and integrations are organized and controlled within a single environment. It includes configuration files that manage entities such as lights, sensors, switches, and media devices, enabling centralized automation and monitoring. It demonstrates how to structure Home Assistant YAML files for scalability and... -
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TreeQuest
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
TreeQuest, developed by SakanaAI, is a versatile Python library implementing adaptive tree search algorithms—such as AB‑MCTS—for enhancing inference-time performance of large language models (LLMs). It allows developers to define custom state-generation and scoring functions (e.g., via LLMs), and then efficiently explores possible answer trees during runtime. With support for multi-LLM collaboration, checkpointing, and mixed policies, TreeQuest enables smarter, trial‑and‑error question... -
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Video-subtitle-remover (VSR)
AI tool that removes hardcoded subtitles and text from videos locally
Video Subtitle Remover is an AI-based application designed to remove hardcoded subtitles from videos and generate new files without the embedded text. Video Subtitle Remover analyzes video frames and detects subtitle regions, then replaces the removed areas using an AI algorithm that fills the space with reconstructed visual content. This process aims to maintain the original resolution and visual continuity of the video after subtitle removal. It allows users to define a specific subtitle... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick access. ... -
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LitServe
Minimal Python framework for scalable AI inference servers fast
LitServe is a minimal Python framework designed for building custom AI inference servers with full control over how models are executed and served. It allows developers to define their own inference logic, making it suitable for complex systems such as multi-model pipelines, agents, and retrieval-augmented generation workflows. Unlike traditional serving tools that enforce rigid abstractions, LitServe focuses on flexibility by letting users control request handling, batching strategies, and output processing directly in Python. ... -
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LTX-2.3
Official Python inference and LoRA trainer package
LTX-2.3 is an open-source multimodal artificial intelligence foundation model developed by Lightricks for generating synchronized video and audio from prompts or other inputs. Unlike most earlier video generation systems that only produced silent clips, LTX-2 combines video and audio generation in a unified architecture capable of producing coherent audiovisual scenes. The model uses a diffusion-transformer-based architecture designed to generate high-fidelity visual frames while... -
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Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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ComfyUI-WanVideoWrapper
ComfyUI wrapper nodes for WanVideo and related models
...The project supports complex node-based pipelines where users can control sampling, conditioning, and frame continuity across generated sequences. It also enables extended video generation by linking outputs between iterations, allowing for longer and more coherent animations. Additionally, the wrapper often includes optimizations for performance, such as low VRAM configurations and multi-stage sampling strategies. -
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Tiktoken
tiktoken is a fast BPE tokeniser for use with OpenAI's models
tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization). The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding... -
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PyTorch Ignite
Library to help with training and evaluating neural networks
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Less code than pure PyTorch while ensuring maximum control and simplicity. Library approach and no program's control inversion. Use ignite where and when you need. Extensible API for metrics, experiment managers, and other components. The cool thing with handlers is that they offer unparalleled flexibility (compared to, for example, callbacks). Handlers can be any function: e.g.... -
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LoLLMs WEBUI
Local AI WebUI for running and managing large language models offlineA
lollms-webui is a locally hosted web interface designed to run and manage large language models without relying on external services. It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users... -
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Atomic Agents
Building AI agents, atomically
The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability. The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are... -
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FAY
Framework for building AI-powered interactive digital humans and agent
...Its architecture allows developers to combine different AI components such as speech recognition, text-to-speech, and large language models to create conversational digital agents. Fay provides multiple interfaces for text, voice, and digital human control, enabling developers to build interactive assistants, virtual presenters, or automated service agents. It also supports custom knowledge bases and configurable behaviors so developers can tailor the personality and responses of the digital human. -
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E2B Desktop Sandbox
E2B Desktop Sandbox for LLMs. E2B Sandbox
...The platform provides isolated virtual machines where applications can be executed safely without affecting the host system. Each sandbox runs independently and can be configured with custom dependencies or tools required by an AI agent or automation workflow. The system allows developers to programmatically create and control these virtual desktops through SDKs available in languages such as Python and JavaScript. Within a sandbox, developers can launch applications like browsers, editors, or other software that an AI agent may need to interact with. ... -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss... -
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vim-ai
AI-powered code assistant for Vim. OpenAI and ChatGPT plugin for Vim
...Its command set covers text completion, editing, chat continuation, image generation, and debugging utilities, making it more versatile than a narrow autocomplete add-on. The repository also highlights support for custom roles, vision features such as image-to-text, and an emerging provider-plugin model for extending compatibility further. A notable design point is that it only sends content the user explicitly selects or includes in prompts, which helps users control what is shared with the external model. -
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Cheshire Cat AI
AI agent microservice
...The framework includes built-in support for retrieval-augmented generation using vector databases such as Qdrant, enabling agents to incorporate external knowledge and documents into their responses. It is highly extensible through a plugin system that supports custom tools, event hooks, and workflows, giving developers fine-grained control over agent behavior and interactions. Cheshire Cat also supports multi-user environments with granular permissions and identity provider integration, making it suitable for enterprise use cases. -
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mcp-use
A solution to build and deploy MCP agents and applications
mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate server for each task using configurable pipelines or a built-in server manager. ...