Search Results for "live-graph" - Page 4
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Showing 641 open source projects for "live-graph"
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GraphRAG
A modular graph-based Retrieval-Augmented Generation (RAG) system
The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs. -
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X4G
Fast and modern gateway for VLESS tunneling on WebSocket and XHTTP
X4G is a self-hosted gateway for operating VLESS tunnels over WebSocket and two XHTTP transport modes. It also includes an internal HTTP proxy for clients that need a conventional proxy endpoint. A web dashboard displays service statistics, hourly traffic charts, live connections, activity records, and error logs. Administrators can create unlimited connection links with individual traffic quotas, bandwidth limits, expiration dates, ports, and simultaneous IP restrictions. Subscription groups combine multiple configurations into shareable public pages that can be protected with passwords and exported as QR codes. ... -
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GRR
GRR Rapid Response, remote live forensics for incident response
GRR Rapid Response is an incident response framework focused on remote live forensics. It consists of a python client (agent) that is installed on target systems, and python server infrastructure that can manage and talk to clients. The goal of GRR is to support forensics and investigations in a fast, scalable manner to allow analysts to quickly triage attacks and perform analysis remotely. GRR client is deployed on systems that one might want to investigate. -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. 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. ... -
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Graphene-Django
Integrate GraphQL into your Django project
...Our primary focus in this tutorial is to give a good understanding of how to connect models from Django ORM to Graphene object types. GraphQL presents your objects to the world as a graph structure rather than a more hierarchical structure to which you may be accustomed. In order to create this representation, Graphene needs to know about each type of object which will appear in the graph. -
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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LLM Vision
Visual intelligence for your home.
LLM Vision is an open-source integration for Home Assistant that adds multimodal large language model capabilities to smart home environments. The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process events from surveillance platforms such as Frigate and convert them into meaningful summaries, notifications, or structured data for automation workflows. ... -
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VOID-TOOLS
OSINT, Discord, web & network utilities
VOID-TOOLS is a Python terminal multitool suite for OSINT, Discord, web, network, social, Roblox, and utility workflows. It is built around a Rich-powered terminal dashboard with keyboard navigation, a cinematic boot flow, category panels, and a live sidebar. The tool organizes many modules into categories and marks premium tools separately from free ones. It includes bilingual setup, theme selection, fuzzy search, category filters, custom plugin loading, and remote manifest updates. The project describes itself as educational and authorized-use-only, especially because some modules relate to security, network checks, webhooks, and platform administration. ... -
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MiniCPM-o
A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming
...Capable of running on end-side devices such as smartphones and tablets, it provides powerful features like real-time speech conversation, video understanding, and multimodal live streaming. With 8 billion parameters, MiniCPM-o 2.6 surpasses its predecessors in versatility and efficiency, making it one of the most robust models available. It supports both text and audio inputs to generate outputs in various forms, including voice cloning, emotion control, and interactive role-playing. -
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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Remarkable for Linux
The Markdown Editor for Linux
With Live Preview you can see your changes as you make them. There is no need to export first to check your syntax. This is accompanied by synchronized scrolling. Remarkable has Github Flavoured Markdown. This has a simple, easy-to-learn syntax with features like checklists, highlighting, links, images and more. Remarkable allows you to export your files to PDF and HTML from within the app. -
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Argilla
The open-source data curation platform for LLMs
Argilla is a production-ready framework for building and improving datasets for NLP projects. Deploy your own Argilla Server on Spaces with a few clicks. Use embeddings to find the most similar records with the UI. This feature uses vector search combined with traditional search (keyword and filter based). Argilla is free, open-source, and 100% compatible with major NLP libraries (Hugging Face transformers, spaCy, Stanford Stanza, Flair, etc.). In fact, you can use and combine your preferred... -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. ... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. ... -
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OpenSRE
Build your own AI SRE agents. The open source toolkit for the AI era
...Its multi-agent architecture allows parallel reasoning across systems, mimicking how experienced SRE teams debug complex issues. The platform also incorporates memory and knowledge graph capabilities to learn from past incidents and improve future investigations. It is designed to run locally within an organization’s infrastructure, ensuring data privacy and compliance. -
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OpenSage
An agent framework that enables AI to create their own agent
...The framework is built around the concept of an Agent Development Kit (ADK), providing structured components for memory, reasoning, and task decomposition while allowing agents to iteratively improve their own design. A key innovation is its hierarchical and graph-based memory system, which enables agents to store, retrieve, and organize information across complex workflows with improved efficiency and contextual awareness. -
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
...It enables developers to give otherwise stateless models a structured memory layer that can store, retrieve, and manage contextual information over time. OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. It supports multiple embedding strategies, including synthetic and semantic embeddings, allowing developers to balance speed and accuracy depending on their use case. OpenMemory integrates with various AI tools and environments, offering SDKs and APIs that simplify adding memory capabilities to applications. ... -
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OmAgent
Build multimodal language agents for fast prototype and production
...Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. Its architecture uses a graph-based workflow engine where tasks are represented as nodes in a directed workflow, enabling modular composition of complex reasoning pipelines. The framework also includes support for various reasoning strategies commonly used in language agents, such as chain-of-thought prompting, self-consistency reasoning, and ReAct-style decision loops. -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost weights, feature extractors, or initialization networks end-to-end. The implementation supports batched optimization on GPU, robust losses, damping strategies, and custom factors, making it practical for real-time systems. ... -
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Jupynium
Selenium-automated Jupyter Notebook that is synchronised with NeoVim
It's just like a markdown live preview, but it's Jupyter Notebook live preview. Jupynium uses Selenium to automate Jupyter Notebook, synchronizing everything you type on Neovim. Never leave Neovim. Switch tabs on the browser as you switch files on Neovim. Note that it doesn't sync from Notebook to Neovim so only modify from Neovim. -
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Omnigent
A meta-harness for all your AI agents
...Sessions can move across terminal, browser, desktop, and mobile interfaces while keeping messages, files, terminals, and subagents in sync. The platform supports collaboration, shared live sessions, co-driving, conversation forking, and remote access from deployed servers. It also includes policy controls for approvals, tool access, spending limits, sandboxing, and server-wide governance. Omnigent is useful for teams and power users who want multi-agent supervision, safer execution, and flexible access from different devices. -
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Weibo Crawler
Python crawler for collecting and downloading Sina Weibo user data
...It also captures detailed data about each post, including the content, publishing time, topics, mentions, likes, reposts, and comments. In addition to textual data, the project can download original media from posts, such as images, videos, and Live Photo content. Collected data can be exported to structured formats such as CSV or JSON or stored in databases for further analysis and research. It supports incremental crawling so users can periodically collect only newly published posts, making it useful for ongoing monitoring or dataset updates. -
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PersonaLive
Expressive Portrait Image Animation for Live Streaming
PersonaLive is an open-source diffusion-based portrait animation framework focused on generating expressive, long-duration animated sequences in real time, primarily for live streaming or interactive applications. It leverages deep generative models that condition on a static reference image and a driving input (such as motion or expression cues) to produce a seamless animated portrait sequence that can run indefinitely without segmentation artifacts. The framework prioritizes low-latency and streamable output, making it suitable for real-time creative workflows, broadcast overlays, or interactive avatars on consumer-grade GPUs. ... -
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iptv-api
IPTV live stream source automatic update tool
IPTV API is an automated platform for collecting, validating, testing, filtering, and publishing IPTV stream sources. It aggregates local files and subscriptions, then generates playable results as M3U, TXT, or API output. Users can customize channel templates, aliases, logos, EPG data, protocol preferences, geographic filters, providers, resolution, and speed requirements. The system measures latency, throughput, resolution, and frame rate while removing invalid, unavailable, or repetitive... -
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Koila
Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code
...The library introduces a lazy evaluation mechanism that delays computation until it is actually required, allowing the framework to better estimate the memory requirements of a model before execution. By building a computational graph first and executing operations only when necessary, koila reduces the risk of running out of GPU memory during the forward pass of neural network training. This approach enables developers to experiment with larger batch sizes and more complex architectures while maintaining stable training behavior. The system acts as a thin wrapper around PyTorch tensors and operations, meaning that it integrates easily into existing PyTorch code without requiring major changes to model implementations. ... -
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openbench
Provider-agnostic, open-source evaluation infrastructure
openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way.
