Search Results for "event"
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Showing 79 open source projects for "event"
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. -
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Solace Agent Mesh
An event-driven framework designed to build multi-agent AI systems
Solace Agent Mesh is an event-driven framework designed to build, orchestrate, and scale multi-agent AI systems where specialized agents collaborate to solve complex tasks across distributed environments. It addresses one of the main challenges in modern AI systems, which is connecting isolated agents, data sources, and enterprise systems into a cohesive and interoperable ecosystem. -
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clawhip
claw + whip: Event-to-channel notification router
...The system emphasizes normalized event contracts (like session.* and agent.*) for consistent automation and routing logic. Overall, Clawhip serves as an operational backbone for developer workflows, enabling real-time visibility and control over distributed AI-driven tasks. -
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008
Open-source event-driven AI powered Softphone
008 is an open-source event-driven AI powered WebRTC Softphone compatible with macOS, Windows, and Linux. It is also accessible on the web (though official support for browser-related issues is not provided). The name '008' or 'agent 008' reflects our ambition: beyond crafting the premier Open Source Softphone, we aim to introduce a programmable, event-driven AI agent. -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Kiro
Kiro is an agentic IDE that works alongside you from prototype
...It introduces the concept of “specs,” which act as executable documentation that defines system behavior, constraints, and acceptance criteria, allowing developers to guide AI agents more precisely. Kiro also incorporates event-driven automation through “hooks,” enabling AI agents to perform tasks such as generating tests, updating documentation, or optimizing code whenever specific development events occur. -
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EventCatalog
Open source tool for documenting and exploring event-driven systems
...By bringing structure and governance to distributed systems, EventCatalog reduces confusion and helps teams make informed decisions faster. It is widely used by organizations to simplify event-driven systems and improve communication across teams. -
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LTX-2
Python inference and LoRA trainer package for the LTX-2 audio–video
...Beyond basic rendering scaffolding, LTX-2 includes optimized math libraries, resource loaders, utilities for texture and buffer handling, and integration points for native event loops and input systems. The framework targets both interactive graphical applications and media-rich experiences, making it a solid foundation for games, creative tools, or visualization systems that demand both performance and flexibility. While being low-level, it also provides sensible defaults and helper abstractions that reduce boilerplate and help teams maintain clear, maintainable code. -
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Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
Build Your Own OpenClaw is a step-by-step educational framework that teaches developers how to construct a fully functional AI agent system from scratch, gradually evolving from a simple chat loop into a multi-agent, production-ready architecture. The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. As the tutorial progresses, it introduces architectural improvements including event-driven systems, WebSocket communication, and configuration hot-reloading to support scalability and real-time interaction. -
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trench
Open-Source Analytics Infrastructure
...The system is built on top of high-performance data technologies including Apache Kafka and ClickHouse, which allows it to ingest and process very large volumes of events while maintaining fast query performance. It was originally developed to solve scaling challenges in product analytics systems where traditional relational databases become inefficient as event tables grow. The platform enables developers to collect events such as page views, user actions, and behavioral metrics while storing them in a column-oriented analytics database optimized for time-series workloads. By combining streaming ingestion with fast analytical queries, the system supports use cases such as product analytics dashboards, observability pipelines, and machine learning data preparation. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Elkeid
Open source solution that can meet the requirements of workloads
...For container or cloud-native workloads, it also supports gathering audit logs from Kubernetes and correlating events across processes, network, and file activity to detect security threats. The platform packages data collection, event-streaming, and a rule/event engine (called “HUB”) — letting users define detection rules, alerts, baseline checks, and policy enforcement. -
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Frigate NVR
NVR with realtime local object detection for IP cameras
...Frigate is optimized for efficiency and supports hardware acceleration across a wide range of devices, including GPUs and specialized inference hardware. It also provides event recording, snapshot management, and searchable video history to improve home or small-business security workflows. Overall, Frigate functions as a privacy-focused, AI-powered NVR platform for intelligent video monitoring. -
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Cloudflare Agents
Build and deploy AI Agents on Cloudflare
Cloudflare Agents is an open-source framework designed to help developers build, deploy, and manage AI agents that run at the network edge. It provides infrastructure for creating stateful, event-driven agents capable of real-time interaction while maintaining low latency through Cloudflare’s distributed platform. The project includes SDKs, templates, and deployment tooling that simplify the process of connecting agents to external APIs, storage systems, and workflows. Its architecture emphasizes persistent memory, enabling agents to maintain context across sessions and interactions. ... -
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Bytewax
Python Stream Processing
Bytewax is a Python framework that simplifies event and stream processing. Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. -
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SenseVoice
Multilingual speech recognition and audio understanding model
SenseVoice is a speech foundation model designed to perform multiple voice understanding tasks from audio input. It provides capabilities such as automatic speech recognition, spoken language identification, speech emotion recognition, and audio event detection within a single system. SenseVoice is trained on more than 400,000 hours of speech data and supports over 50 languages for multilingual recognition tasks. It is built to achieve high transcription accuracy while maintaining efficient inference performance. It includes different model variants optimized for either speed or accuracy, allowing developers to choose a configuration suitable for their use case. ... -
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VibeKit
Run Claude Code, Gemini, Codex in a clean, isolated sandbox
...The toolkit also supports testing and local iteration, with utilities that simulate event streams and mock model responses to make development predictable. -
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Team9
Team9 is a collaborative workspace for AI agents
...The system emphasizes a “local-first” architecture, allowing agents to run on user-controlled infrastructure while maintaining persistent memory and data privacy. It includes orchestration mechanisms that allow agents to operate continuously through scheduled tasks, event-driven triggers, and long-running processes. The platform also integrates messaging gateways and communication channels, enabling agents to interact with users and systems in real time. Its design reflects a shift toward treating AI agents as operational units within organizations rather than isolated tools. -
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SpikingJelly
SpikingJelly is an open-source deep learning framework
...The project provides the components needed to build, train, and evaluate neural models that communicate through discrete spikes rather than the continuous activations used in conventional artificial neural networks. This makes it especially relevant for researchers interested in biologically inspired computing, event-driven processing, and energy-efficient AI systems. The framework includes neuron models, surrogate gradient training methods, encoding strategies, network components, and utilities for simulation and experimentation, allowing users to develop a wide variety of spiking architectures. It also supports integration with familiar PyTorch workflows, which lowers the barrier for machine learning practitioners who want to explore spiking approaches without abandoning mainstream tooling. -
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Scene Framework
Android Single Activity Framework compatible with Fragment
...As such, Scene could serve as a backbone for media apps, games, or modular user interface projects, offering abstractions for scene management, resource loading, event dispatching, and lifecycle handling. Because of its open-source status, developers may adapt it to their own use-cases — customizing rendering, UI transitions, or content management — though the maturity and documentation may vary. -
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Live API Web Console
A react-based starter app for using the Live API over websockets
...Under the hood there’s an event-emitting WebSocket client, an audio in/out processing layer, and a minimal scaffolded view so you can focus on your app logic rather than wiring. -
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
...It also includes utilities for visualizing audio features and analyzing patterns within sound recordings, which can be useful in applications such as speech recognition, music classification, and acoustic event detection. Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework. -
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Memobase
Fast backend for long-term AI user memory via structured profiles
Memobase is an open source backend system that enables long-term user memory functionality for AI applications by capturing and structuring information about users across interactions. Its design centers on creating user profiles and recording event timelines, allowing AI systems to remember, understand, and evolve in their behaviour toward individual users over time. Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. 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. ... -
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Agently 4
Build GenAI application quick and easy
Agently is a Python framework for building generative-AI (“GenAI”) applications; it focuses on enabling developers to orchestrate AI agents, workflows, and event-driven logic in a robust, reusable way. With Agently, one can define agents that call different models, chain tasks, trigger workflows based on events, and switch models with minimal code changes. It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. ... -
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Edgee
AI gateway with token compression for Claude Code, Codex, and more
...It enables developers to deploy functions and workflows closer to users, allowing real-time processing without relying heavily on centralized cloud infrastructure. The platform is built to support event-driven architectures, where actions are triggered by incoming requests, user behavior, or external signals. It integrates AI capabilities into edge environments, making it possible to perform inference, personalization, and decision-making at the point of interaction. Edgee is optimized for performance and scalability, leveraging distributed execution to handle high volumes of requests efficiently. ... -
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Pydantic Logfire
Python observability platform for tracing apps, metrics, and logs
...Pydantic Logfire provides deep visibility into application performance by capturing traces, metrics, and logs through an OpenTelemetry-based architecture. It is particularly strong in Python environments, offering detailed insights into Python objects, event loops, database queries, and validation flows. Logfire also integrates closely with Pydantic models, enabling developers to inspect and analyze how data moves through validation layers. In addition to traditional observability, it supports modern AI and LLM-based applications by tracing full request lifecycles, including model calls and external dependencies. -
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BotKube
An app that helps you monitor your Kubernetes cluster
...BotKube can be integrated with multiple messaging platforms like - Slack, Mattermost, Microsoft Teams to help you monitor your Kubernetes cluster(s), debug critical deployments and gives recommendations for standard practices by running checks on the Kubernetes resources. BotKube watches Kubernetes resources and sends a notification to the channel if any event occurs for example a ImagePullBackOff error. You can customize the objects and level of events you want to get from the Kubernetes cluster. You can turn on/off notifications simply by sending a message to @BotKube. BotKube can execute kubectl commands on Kubernetes cluster without giving access to Kubeconfig or underlying infrastructure. ...
