Search Results for "multi-system" - Page 26
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Showing 1143 open source projects for "multi-system"
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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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InternGPT
Open source demo platform where you can easily showcase your AI models
...The framework connects multiple specialized AI models that perform tasks such as object detection, segmentation, captioning, and visual editing while coordinating them through a central conversational interface. This architecture enables the system to plan actions, execute visual operations, and return results in a coherent dialogue with the user. -
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Memobase
Fast backend for long-term AI user memory via structured profiles
...The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks. -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ... -
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Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
...The repository allows others to reproduce their results, experiment with different LLM backends (e.g. the user may supply keys for supported models), and observe how their adaptive meta-system handles the logic and abstraction challenges. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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IMS Toucan
Controllable and fast Text-to-Speech for over 7000 languages
IMS-Toucan is a toolkit for training, using, and teaching state-of-the-art text-to-speech systems, built at the Institute for Natural Language Processing (IMS), University of Stuttgart. It is the official home of ToucanTTS, a massively multilingual TTS system designed to support over 7,000 languages with a single unified framework. The toolkit focuses on being fast and controllable while not requiring huge amounts of compute, making it practical for research labs and smaller teams. It includes complete pipelines for preprocessing datasets, training models, and running inference, plus a storage configuration system to manage where models and caches are stored. ... -
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pg-aiguide
MCP server and Claude plugin for Postgres skills and documentation
pg-aiguide is a tool designed to enhance AI-assisted development with PostgreSQL by providing structured knowledge and skills directly to coding agents. It acts as a bridge between database documentation and AI tools, enabling more accurate generation of SQL queries and database interactions. The system integrates with Claude Code through an MCP server, allowing agents to access curated PostgreSQL knowledge in real time. It focuses on improving developer productivity by reducing errors and providing context-aware suggestions. The project also includes documentation and examples that help users understand best practices in database design and querying. ... -
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Kiln
Open source platform for managing, testing, and deploying AI apps
...Its workflow-oriented approach helps teams move from experimentation to production by organizing assets and results in a consistent format. It is particularly useful for teams working with large language models who need visibility into how changes impact outputs and overall system quality. -
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PySINDy
A package for the sparse identification of nonlinear dynamical systems
...The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. This approach is particularly valuable in scientific fields such as physics, engineering, and biology where researchers seek both predictive accuracy and theoretical insight. The library provides tools for constructing libraries of candidate functions, performing sparse regression, and validating discovered models against observed data. ... -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
...The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph representing the pipeline, allowing the system to execute transformations in the correct order. This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. The framework also automatically tracks lineage and metadata about how data is produced, which improves debugging, reproducibility, and transparency in data workflows. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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SageAttention
NeurIPS2025 Spotlight] Quantized Attention
...Since attention operations are often the most computationally expensive component of modern AI models, SageAttention introduces quantization techniques that significantly reduce computational overhead while preserving model accuracy. The system achieves this by using low-precision numerical formats such as INT4, FP8, or INT8 to represent key matrices within the attention computation. These optimizations allow models to perform matrix operations faster and consume less memory during inference. SageAttention is designed to function as a plug-and-play replacement for standard attention implementations, enabling developers to accelerate existing models without modifying their architecture. -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
DeepWiki Open is an open-source, AI-powered wiki generator that automatically creates fully navigable, richly structured wiki documentation for GitHub, GitLab, or Bitbucket repositories by combining code analysis, vector embeddings, retrieval-augmented generation (RAG), and visualization tools. Users can enter a repository URL and the system will clone the project, build semantic embeddings of its codebase, extract architecture and relationships, generate human-readable documentation, and produce visual diagrams to help explain complex code structure. DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. ... -
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video2robot
End-to-end pipeline converting generative videos
...The pipeline supports both prompt-to-video generation using models like Veo/Sora and video upload processing, followed by human pose extraction through a 3D pose model and retargeting of that motion to robot joints using a general motion retargeting system. This workflow allows users to generate robot motion files that specify joint angles, root positions, and orientations that can be deployed on supported robot platforms (e.g., Unitree models). Video2robot includes scripts for each stage of the pipeline (generation, extraction, conversion, visualization) and can run as a CLI or through a basic web UI. -
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nanocode
Minimal Claude Code alternative. Single Python file, zero dependencies
...It implements a full agentic loop where the model can reason, decide when to use tools, execute those tools, and iterate until producing a final answer, making it useful for simple AI-assisted coding workflows. It includes a set of integrated tools such as read, write, edit, glob, grep, and bash that let the agent interact with the file system and shell commands directly from the terminal, and it keeps a conversation history with colored terminal output for readability. The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants. -
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PPTAgent
PPTAgent: Generating and Evaluating Presentations
PPTAgent is a research system for generating and evaluating slide decks that goes beyond simple text-to-slides. It follows a two-stage, edit-based workflow: first it analyzes reference presentations to infer slide roles and structure, then it drafts an outline and iteratively performs editing actions to produce new slides. The project includes both the generation agent and an evaluation framework, PPTEval, to score content quality, design, and coherence. -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
...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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fastai
Deep learning library
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying... -
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Superlinked
Superlinked is a Python framework for AI Engineers
Superlinked is a Python framework designed for AI engineers to build high-performance search and recommendation applications that combine structured and unstructured data. -
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TensorLy
Tensor Learning in Python
TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU. -
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GalTransl
Automated translation solution for visual novels
GalTransl is an automated translation system specifically designed for visual novels, particularly those in the “galgame” genre, leveraging large language models to streamline and enhance the translation process. It integrates support for multiple advanced LLM providers such as GPT-4, Claude, DeepSeek, and other models, enabling high-quality, context-aware translations that go beyond traditional machine translation approaches. -
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MineContext
MineContext is your proactive context-aware AI partner
MineContext is an open-source, proactive AI assistant designed to capture, understand, and leverage a user’s digital context in order to provide meaningful insights, summaries, and productivity support. The system continuously collects contextual data from sources such as screenshots and user activity, then processes and organizes this information into structured knowledge that can be reused later. Unlike traditional chat-based assistants, MineContext operates in the background and delivers proactive outputs such as daily summaries, task suggestions, and contextual reminders without requiring explicit prompts. ... -
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Paperless-AI
AI-powered document analysis and tagging for Paperless-ngx
Paperless-AI is an AI-powered extension designed to enhance document management within Paperless-ngx by automating analysis, classification, and organization tasks. It continuously monitors incoming documents and processes them using various AI backends, enabling automatic assignment of titles, tags, document types, and correspondents. It integrates with multiple OpenAI-compatible services as well as local models, giving users flexibility in how document intelligence is handled. A key... -
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Guardrails
Framework for validating and controlling LLM outputs in AI apps
Guardrails is an open source Python framework designed to help developers build more reliable and controlled applications powered by large language models. It provides mechanisms for validating and constraining both the inputs sent to a model and the outputs generated by it, helping reduce risks such as harmful content, prompt injection, or inaccurate responses. Guardrails works by applying configurable guards that intercept and evaluate interactions with the model before results are... -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on... -
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hls4ml
Machine learning on FPGAs using HLS
hls4ml is an open-source framework that enables machine learning models to be implemented directly on hardware such as FPGAs and ASICs using high-level synthesis techniques. The system converts trained neural network models from common machine learning frameworks into hardware description code suitable for ultra-low-latency inference. This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. ... -
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LibrePhotos
A self-hosted open source photo management service
LibrePhotos is an open-source self-hosted photo management platform designed to organize, browse, and analyze personal media libraries while preserving user privacy. The system allows individuals to store and manage their photos and videos locally rather than relying on commercial cloud services. It provides features similar to services like Google Photos but runs on a private server controlled by the user. The application includes AI-powered tools that automatically analyze images to detect faces, objects, and locations, allowing photos to be grouped and searched more efficiently. ...
