Search Results for "script%20executor%20synapse"
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Showing 69 open source projects for "script%20executor%20synapse"
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The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
...Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies. -
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Claude Skills
Public repository for Agent Skills
Claude Skills is a public repository that showcases and serves as a collection of skills — modular, reusable packages of instructions, scripts, and resources that Claude and other compatible agents can dynamically discover and load to extend their capabilities on specialized tasks. Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document... -
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Stable Diffusion web UI for AMDGPUs
Stable Diffusion WebUI optimized for AMD GPUs with editing tools
...It includes tools such as inpainting and outpainting for editing specific areas of an image, along with features like prompt matrix generation and attention controls to fine-tune outputs. Users can emphasize or de-emphasize elements in prompts to influence results more precisely. A one-click setup script simplifies installation, although Python and Git are still required. Stable Diffusion WebUI AMDGPU focuses on improving accessibility for AMD GPU users, offering an alternative to CUDA-based implementations while maintaining compatibility with many existing Stable Diffusion capabilities and extensions. -
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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kokoro-onnx
TTS with kokoro and onnx runtime
...It focuses on running efficiently on commodity hardware, including macOS with Apple Silicon, while still delivering near real-time performance for many use cases. The project ships prebuilt model files and a simple example script, so you can go from installation to producing an audio.wav file in just a few steps. It supports multiple languages and voices, with a curated voice list and configuration via a VOICES file hosted alongside the models. The package is distributed on PyPI, meaning you can integrate it directly into applications or scripts using standard Python tooling. ... -
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MoneyPrinterTurbo
Generate short videos with one click using AI LLM
MoneyPrinterTurbo is an AI-driven tool that enables users to generate high-definition short videos with minimal input. By providing a topic or keyword, the system automatically creates video scripts, sources relevant media assets, adds subtitles, and incorporates background music, resulting in a polished video ready for distribution. -
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nanoGPT
The simplest, fastest repository for training/finetuning models
...It distills the GPT architecture into a few hundred lines of Python code, making it far easier to understand than large, production-scale implementations. The repo is organized with a training pipeline (dataset preprocessing, model definition, optimizer, training loop) and inference script so you can train a small GPT on text datasets like Shakespeare or custom corpora. It emphasizes readability and clarity: the training loop is cleanly written, and the code avoids heavy abstractions, letting students follow the architecture step by step. While simple, it can still train non-trivial models on modern GPUs and generate coherent text. ... -
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SAM 3D Objects
Models for object and human mesh reconstruction
...It supports both single-object and multi-object generation, allowing you to reconstruct entire scenes rather than just isolated items. The repository provides code to run inference, a quickstart demo.py script, and environment setup instructions that connect to hosted checkpoints and configuration files. Outputs are aimed at downstream usability: the reconstructed assets are textured meshes suitable for further editing, rendering, or integration into 3D pipelines and engines. -
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ShortGPT
AI framework for automated short video creation and editing tools
ShortGPT is an experimental AI-powered framework designed to automate the creation of short-form and long-form video content. It provides a structured system that handles multiple stages of the content creation workflow, including script generation, asset sourcing, voiceover synthesis, and video editing. ShortGPT uses large language models to generate scripts and prompts that guide the automated editing and production process. ShortGPT includes specialized content engines that manage different workflows, such as generating short videos, producing longer videos, and translating existing videos into other languages. ... -
Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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OpenMontage
World's first open-source, agentic video production system
OpenMontage is an open-source, agent-driven video production system that transforms AI coding assistants into fully automated multimedia creation pipelines. Instead of focusing on a single capability such as text-to-video generation, it treats video production as a structured, multi-stage workflow that mirrors how a real production team operates, including research, scripting, asset generation, editing, and final rendering. The system orchestrates a large collection of tools and models... -
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Chatterbox
SoTA open-source TTS
Chatterbox is Resemble AI's first production-grade open source TTS model. Licensed under MIT, Chatterbox has been benchmarked against leading closed-source systems like ElevenLabs and is consistently preferred in side-by-side evaluations. Whether you're working on memes, videos, games, or AI agents, Chatterbox brings your content to life. It's also the first open source TTS model to support emotion exaggeration control, a powerful feature that makes your voices stand out. Try it now on our... -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
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BudouX
Standalone, small, language-neutral
...It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training script. -
14
edge-tts
Use Microsoft Edge's online text-to-speech service from Python
edge-tts is a Python module and command-line tool that gives you direct access to Microsoft Edge’s online text-to-speech service without needing the Edge browser, Windows, or any API key. It wraps the same cloud voices used by Edge, exposing them through a simple CLI (edge-tts, edge-playback) and a Python API, so you can script high-quality speech generation in your own applications. The tool lets you list available voices, specify locale and voice name, and generate audio files in common formats like MP3 or WAV. It also supports generating subtitle files (such as SRT or VTT) alongside the speech, which is handy for video narration, e-learning, or accessibility workflows. ... -
15
ticket
Fast, powerful, git-native ticket tracking in a single bash script
ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. ... -
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nanochat
The best ChatGPT that $100 can buy
...The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and speed: you can boot a fresh GPU box and drive the whole pipeline via a single script, producing a usable chat model in hours and a clear markdown report of what happened. The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection. -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
...Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code, hyperparameters, launch commands, input data, and resulting model weights. Set wandb.config once at the beginning of your script to save your hyperparameters, input settings (like dataset name or model type), and any other independent variables for your experiments. This is useful for analyzing your experiments and reproducing your work in the future. Setting configs also allows you to visualize the relationships between features of your model architecture or data pipeline and model performance. -
18
Style-Bert-VITS2
Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles
...The project targets both power users and beginners: Windows users without Git or Python can install and run it using bundled .bat scripts, while advanced users can work with virtual environments, uv, and Python tooling. It includes a full GUI editor to script dialogue, set different styles per line, edit dictionaries, and save/load projects, plus a separate web UI and Colab notebooks for training and experimentation. For those who only need synthesis, the project is published as a Python library (pip install style-bert-vits2) and can run on CPU without an NVIDIA GPU, though training still requires GPU hardware. -
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ChatTTS_colab
One-click deployment (including offline integration package)
...It has first-class support for long-form audio generation, making it suitable for audiobooks, podcasts, or long narration tasks. The project also implements multi-speaker or role-based reading, letting users assign different voices to different characters in a script and even use a large language model to generate that script in one step. -
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firerpa LAMDA
The most powerful Android RPA agent framework
lamda is an Android RPA agent framework that provides visual remote desktop control and automation at scale, geared toward testing, automation validation, and device management. It exposes a clean UI to monitor and interact with connected devices and includes tooling to script actions reliably across apps and OS versions. The project emphasizes low-friction setup and powerful control primitives so teams can move from interactive validation to repeatable automation. A public wiki, releases, and issue tracker show active development across areas like connectivity, instrumentation compatibility, and robustness under detection. ... -
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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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autoresearch for AMD
AI agents running research on single-GPU nanochat training
autoresearch for AMD is a framework for autonomous scientific experimentation in machine learning, enabling AI agents to iteratively improve models through a continuous loop of hypothesis generation, experimentation, and evaluation. The system is built around a minimal structure that includes a data preparation module, a training script that can be modified, and a program specification that guides the agent’s decision-making process. During each iteration, the agent edits the training code, runs an experiment within a fixed time budget, evaluates performance metrics, and decides whether to retain or discard the changes. This loop allows the system to explore a wide range of architectural and hyperparameter configurations without human intervention. ... -
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MCP for Unity
AI bridge enabling assistants to control and automate Unity Editor
Unity MCP is an open source integration that connects AI assistants with the Unity Editor through the Model Context Protocol (MCP). It acts as a bridge that allows language models and AI coding tools to interact directly with a Unity development environment using structured commands and tools. By linking an AI assistant to a running Unity project, the system enables automated operations such as managing project assets, modifying scenes, editing scripts, and performing other development tasks... -
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SAM 3D Body
Code for running inference with the SAM 3D Body Model 3DB
SAM 3D Body is a promptable model for single-image full-body 3D human mesh recovery, designed to estimate detailed human pose and shape from just one RGB image. It reconstructs the full body, including feet and hands, using the Momentum Human Rig (MHR), a parametric mesh representation that decouples skeletal structure from surface shape for more accurate and interpretable results. The model is trained to be robust in diverse, in-the-wild conditions, so it handles varied clothing,... -
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autoresearch-mlx
Apple Silicon (MLX) port of Karpathy's autoresearch
autoresearch-mlx is an Apple Silicon–optimized implementation of the autoresearch framework that enables autonomous AI research loops to run natively on MLX without requiring PyTorch or CUDA dependencies. It maintains the core autoresearch structure, where an AI agent iteratively edits a training script, executes experiments under a fixed time budget, and evaluates results based on a defined metric such as validation bits per byte. The system is tailored for Apple hardware, leveraging unified memory and MLX capabilities to achieve efficient training on Mac devices. It includes a minimal and focused project structure consisting of data preparation utilities, a modifiable training file, and a program specification that governs the agent’s behavior. ...
