118 skills found · Page 2 of 4
superlinear-ai / Graphchain⚡️ An efficient cache for the execution of dask graphs.
larchanka / Manbot🧬 ManBot — Multi-process AI platform with type-safe IPC and capability graph execution
sbhooley / AinativelangAINL helps turn AI from "a smart conversation" into "a structured worker." It is designed for teams building AI workflows that need multiple steps, state and memory, tool use, repeatable execution, validation and control, and lower dependence on long prompt loops. AINL is a compact, graph-canonical, AI-native programming system for (READ: README)
sean-mcclure / Machine FlowMachine Flow enables visual execution and tracking of machine learning workflows. Users dynamically create dependency graphs, with each node responsible for executing a task and displaying results.
tenstorrent / Ttnn VisualizerA comprehensive tool for visualizing and analyzing model execution, offering interactive graphs, memory plots, tensor details, buffer overviews, operation flow graphs, and multi-instance support with file or SSH-based report loading.
gabyx / ExecutionGraphFast Generic Execution Graph/Network
AMDResearch / DAGEEDirected Acyclic Graph Execution Engine (DAGEE) is a C++ library that enables programmers to express computation and data movement, as task graphs that are scheduled concurrently and asynchronously on both CPUs and GPUs.
perone / FesteFeste is a free and open-source framework allowing scalable composition of NLP tasks using a graph execution model that is optimized and executed by specialized schedulers.
MetanoKid / Msbuild Flame GraphTurns MSBuild executions into flame graphs
CaSkade-Automation / CaSkade MESSkillMEx is a novel manufacturing execution system (MES) based on semantically modelled skills of machines. SkillMEx uses a knowledge graph to manage skills and execute them. BPMN is used to model and execute complex production processes.
rhosocial / Go DagA Go-based framework has been developed to oversee the execution of workflows delineated by directed acyclic graphs (DAGs).
ngriere / High Frequency Data Order Book AnalyserIf you are professionals, retailers or even organisms trading on a financial market, you know that data given on online platforms is not precise enough. Banks and huge financial institutions use powerful computers to transact a large number of orders at very fast speed. Thus, thousands of buying and selling orders are launched within a fraction of a second. So why can’t you see it? High Frequency Data analyser, is an innovative program helping you to analyze high frequency data in order to increase your understanding of the market. High Frequency Data takes trading to the next level, transforming your order book into a interactive visual map. You can now observe visual trading patterns and create new trading strategies. You can chose the parameters you are interested in. ( Volume/askBid). You can observe executed orders and analyse the impact of these executions on the market. You can pause and save the graph whenever you want in order to study more deeply a situation. It plays real time information and offers you many indicators to get an accurate vision of the market.(market indicator) You can visualize the available shares for each value with a very deep order book. (avancer dans le order book). You can also export your data into Excel and draw your most significant graphs. For a deeper and precise order book analysis, download High Frequency Data analyser now!
busyster996 / RustDagcuterDagcuter is a Rust library for executing Directed Acyclic Graphs (DAGs) of tasks. It manages task dependencies, detects circular dependencies, and supports customizable task lifecycles (PreExecution, Execute, and PostExecution). It also enables concurrent execution of independent tasks for improved performance.
BismuthCloud / AsimovA Python framework for building AI agent systems with robust task management in the form of a graph execution engine, inference capabilities, and caching. We support advanced features like State Snapshotting, Middleware, LLM Directed Graph Execution, Open Telemetry Integrations and more.
AndrewChau / Learn Gremlin Jupyter NotebookAs a believer of learning through examples, I have decided to put my own examples of Gremlin queries inside Jupyter Notebooks for people to actually try out. The course is roughly based on this book (http://kelvinlawrence.net/book/Gremlin-Graph-Guide.pdf) by krlawrence but adapted into Python for execution inside a Jupyter Notebook.
calltrace / TraverseCall graph-based analysis tools for Solidity smart contracts. Visualize contract interactions, generate Foundry tests, analyze storage patterns, and trace execution paths.
avivcarmis / Java RedEffective Concurrency Modules for Java
anhvvcs / CoranaCorana is a Dynamic Symbolic Execution Engine for ARM Cortex-M aiming to incrementally reconstruct the precise Control Flow Graph (CFG) of IoT malware under the presence of obfuscation techniques e.g., indirect jumps and opaque predicates
cgoinglove / Ts EdgeA lightweight, type-safe workflow engine for TypeScript that helps you create flexible, graph-based execution flows
11divyansh / OxyJenOxyJen is an open-source Java framework for orchestrating LLM workloads with graph-style execution, context-aware memory, and deterministic retry/fallback. It treats LLMs as native nodes (not helper utilities), allowing developers to build multi-step AI pipelines that integrate cleanly with existing Java code.
