Showing 13 open source projects for "event processing"

View related business solutions
  • $300 Free Credits for Your Google Cloud Projects Icon
    $300 Free Credits for Your Google Cloud Projects

    Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.

    Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
    Start Free Trial
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • 1
    Bytewax

    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.
    Downloads: 7 This Week
    Last Update:
    See Project
  • 2
    Edgee

    Edgee

    AI gateway with token compression for Claude Code, Codex, and more

    Edgee is an edge-native execution platform designed to run AI-driven logic and data processing directly at the network edge, reducing latency and improving responsiveness for modern applications. 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. ...
    Downloads: 3 This Week
    Last Update:
    See Project
  • 3
    Frigate NVR

    Frigate NVR

    NVR with realtime local object detection for IP cameras

    Frigate is a local network video recorder designed for real-time object detection on IP camera streams using machine learning. It runs entirely on local hardware and integrates closely with Home Assistant to provide smart surveillance without relying on cloud processing. The system uses OpenCV and TensorFlow to analyze video feeds and detect objects such as people, vehicles, and animals in real time. 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. ...
    Downloads: 6 This Week
    Last Update:
    See Project
  • 4
    clawhip

    clawhip

    claw + whip: Event-to-channel notification router

    Clawhip is an open-source daemon-first notification router designed to deliver structured events from development workflows directly to platforms like Discord and Slack. It acts as a central event-processing system that listens to sources such as Git, GitHub, tmux sessions, and custom CLI events, then routes them through a typed pipeline. Built with a clean separation between routing, rendering, and delivery, Clawhip ensures reliable and organized notifications without polluting AI agent contexts. It integrates seamlessly with tools like OpenClaw, OMX (oh-my-codex), and OMC (oh-my-claudecode) to monitor coding sessions and automate updates. ...
    Downloads: 3 This Week
    Last Update:
    See Project
  • 99.99% Uptime for MySQL and PostgreSQL Databases Icon
    99.99% Uptime for MySQL and PostgreSQL Databases

    Sub-second maintenance. 2x read/write performance. Built-in vector search for AI apps.

    Cloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
    Try Free
  • 5
    AdalFlow

    AdalFlow

    The library to build & auto-optimize LLM applications

    AdalFlow is a framework for building AI-powered automation workflows, enabling users to design and execute intelligent automation pipelines with minimal coding.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 6
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    ...The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. 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. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 7
    Memobase

    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. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • 8
    SpikingJelly

    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.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 9
    Live API Web Console

    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Host LLMs in Production With On-Demand GPUs Icon
    Host LLMs in Production With On-Demand GPUs

    NVIDIA L4 GPUs. 5-second cold starts. Scale to zero when idle.

    Deploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
    Try Free
  • 10
    Kimi-Audio

    Kimi-Audio

    Audio foundation model excelling in audio understanding

    Kimi-Audio is an ambitious open-source audio foundation model designed to unify a wide array of audio processing tasks — from speech recognition and audio understanding to generative conversation and sound event classification — within a single cohesive architecture. Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 11
    AI Deadlines

    AI Deadlines

    AI conference deadline countdowns

    ...The repository powers a website that displays countdown timers and structured information for top research conferences across subfields such as computer vision, natural language processing, machine learning, and robotics. The project maintains a curated dataset of conferences that includes metadata such as submission deadlines, abstract deadlines, event dates, conference locations, and related information. Researchers and students use the platform to plan their paper submissions and manage academic schedules without manually tracking multiple conference announcements. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 12
    ...This project has been migrated to github at http://jaerproject.net (or https://github.com/SensorsINI/jaer for the Java code). Commits have been disabled for the subversion sourceforge repository and new development is being done on the github repository. Java tools for Address-Event Representation (AER) neuromorphic processing. Uses USB hardware. See wiki at https://sourceforge.net/p/jaer/wiki/
    Downloads: 0 This Week
    Last Update:
    See Project
  • 13
    This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo