Search Results for "live-graph"
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Showing 641 open source projects for "live-graph"
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Deep-Live-Cam
Real time face swap and one-click video deepfake
Real time face swap and one-click video deepfake with only a single image. Choose a face (image with the desired face) and the target image/video (image/video in which you want to replace the face) and click on Start. Open File Explorer and navigate to the directory you select your output to be in. You will find a directory named <video_title> where you can see the frames being swapped in real time. Once the processing is done, it will create the output file. -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. -
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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
...The system likely leverages AI techniques for entity extraction, relationship mapping, and graph construction, enabling automated knowledge organization. It can be used to power recommendation systems, research tools, or intelligent assistants that require contextual understanding of technical topics. The project emphasizes scalability and adaptability, allowing it to handle large datasets and evolving knowledge bases. By structuring information into graph form, it enables more meaningful navigation and discovery compared to traditional document-based systems. -
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Code-Graph-RAG
The ultimate RAG for your monorepo
Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. -
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code-review-graph
Local-first code intelligence graph for MCP and CLI
Code Review Graph is a local-first code intelligence tool that builds a persistent structural map of a software repository. It parses source files with Tree-sitter and stores functions, classes, imports, calls, inheritance, and test relationships in a SQLite graph. When code changes, blast-radius analysis identifies the callers, dependents, and tests most likely to be affected. -
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Live Agent Studio
Open source AI Agents hosted on the oTTomator Live Agent Studio
Live Agent Studio is a curated repository of open-source AI agents associated with the oTTomator Live Agent Studio platform, showcasing a variety of agent implementations that illustrate how autonomous and semi-autonomous tools can be constructed using modern AI frameworks. Each agent in the collection is designed for a specific use case — such as content summarization, task automation, travel planning, or RAG workflows — and is provided with the code or configuration needed to explore and extend it on your own, making the repository both a learning resource and a practical starting point for real projects. ... -
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CogDB
Micro Graph Database for Python Applications
Cog is a lightweight, embedded graph database for Go that provides a simple interface for storing and querying graph-based data structures, making it useful for knowledge representation and graph analytics. -
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Google DeepMind GraphCast and GenCast
Global weather forecasting model using graph neural networks and JAX
GraphCast, developed by Google DeepMind, is a research-grade weather forecasting framework that employs graph neural networks (GNNs) to generate medium-range global weather predictions. The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with diffusion-based ensemble forecasting for probabilistic weather prediction. ... -
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AI Powered Knowledge Graph Generator
AI Powered Knowledge Graph Generator
AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. -
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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AIQuant
AI-powered platform for quantitative trading
...It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation. -
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nano-graphrag
A simple, easy-to-hack GraphRAG implementation
...The system extracts entities and relationships from documents using language models and organizes them into graph structures that can be queried during generation. Developers can integrate different storage backends and embedding engines, including vector databases and graph databases such as Neo4j, allowing flexible experimentation with hybrid retrieval methods. -
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DGL
Python package built to ease deep learning on graph
...We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. -
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EdgeDB
A next-generation graph-relational database
...Powered by the Postgres query engine under the hood, EdgeDB thinks about schema the same way you do: as objects with properties connected by links. It's like a relational database with an object-oriented data model, or a graph database with strict schema. We call it a graph-relational database. The core unit of schema in the graph-relational model is the object type, analogous to a table in SQL. Object types contain properties and can be linked to other object types to form a schema graph. -
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Flowsint
Graph-based OSINT investigation platform w visual relationship mapping
Flowsint is an open source OSINT investigation platform designed to help analysts explore and understand relationships between digital entities through a visual graph interface. The platform focuses on reconnaissance and open source intelligence workflows, enabling investigators to map connections between domains, IP addresses, organizations, individuals, and other data points. By presenting these relationships in an interactive graph, Flowsint allows users to quickly identify patterns, associations, and investigative leads that might be difficult to detect through traditional data analysis methods. ... -
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GenAI Processors
GenAI Processors is a lightweight Python library
...Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which makes sophisticated agent behaviors easy to express with simple operators. The library offers built-in processors for classic turn-based Gemini calls as well as Live API streaming, so you can mix “batch” and real-time interactions in the same graph. It leans on Python’s asyncio to coordinate concurrency, handle network I/O, and juggle background compute threads without blocking. -
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Semantica
Graph-Native Infrastructure for Context and Accountable AI Systems
Semantica is an open-source graph-native infrastructure layer for building explainable and auditable AI systems. It ingests fragmented data, extracts meaningful entities and relationships, and transforms them into context and knowledge graphs. Deterministic reasoning, ontology management, provenance tracking, and decision records help explain how conclusions were reached. -
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ComfyUI
The most powerful and modular diffusion model GUI, api and backend
The most powerful and modular diffusion model is GUI and backend. This UI will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart-based interface. We are a team dedicated to iterating and improving ComfyUI, supporting the ComfyUI ecosystem with tools like node manager, node registry, cli, automated testing, and public documentation. Open source AI models will win in the long run against closed models and we are only at the beginning. Our core mission is to advance and democratize AI tooling. ... -
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Youtu-GraphRAG
Vertically Unified Agents for Graph Retrieval-Augmented Reasoning
Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. -
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StreamCap
Multi-Platform Live Stream Automatic Recording Tool
StreamCap is a multi-platform live stream recording client that enables automated capture and management of live broadcasts from over 40 streaming platforms worldwide. Built on FFmpeg and StreamGet, it provides a robust system for monitoring live stream availability and automatically starting recordings when streams go online. The software supports batch recording and scheduled monitoring, allowing users to manage multiple streams simultaneously without manual intervention. ... -
21
amrlib
A python library that makes AMR parsing, generation and visualization
A python library that makes AMR parsing, generation and visualization simple. amrlib is a python module designed to make processing for Abstract Meaning Representation (AMR) simple by providing the following functions. Sentence to Graph (StoG) parsing to create AMR graphs from English sentences. Graph to Sentence (GtoS) generation for turning AMR graphs into English sentences. A QT-based GUI to facilitate the conversion of sentences to graphs and back to sentences. Methods to plot AMR graphs in both the GUI and as library functions. Training and test code for both the StoG and GtoS models. ... -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
...The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, Graphify serves as a bridge between raw data and visual insight. -
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SAG
SQL-Driven RAG Engine
...The architecture also includes a three-stage retrieval pipeline consisting of recall, expansion, and reranking steps to improve search accuracy. The engine integrates semantic vector similarity with traditional full-text search to improve both recall and precision. Because the knowledge graph is generated dynamically, the system can adapt to new information without requiring manual graph maintenance. -
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Vedana
Open source multi-agent RAG over a knowledge graph
Vedana is an open-source multi-agent RAG system built around a typed knowledge graph. It is designed for questions that require structure, completeness, and traceability instead of simple text similarity. The system lets agents navigate data step by step through Cypher queries, vector search, document lookup, and source verification. Its architecture combines a knowledge graph, pgvector-based embeddings, incremental ETL, and a backoffice interface for chat, metrics, prompt tuning, and data loading. ... -
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PyMongo
PyMongo - the Official MongoDB Python driver
The PyMongo distribution contains tools for interacting with MongoDB database from Python. The bson package is an implementation of the BSON format for Python. The pymongo package is a native Python driver for MongoDB. The gridfs package is a gridfs implementation on top of pymongo.
