Search Results for "processing" - Page 13
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Showing 1085 open source projects for "processing"
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
...Rivet supports multiple large language model providers and integrates with services such as embeddings and transcription systems, allowing developers to create richer AI-powered features. Its architecture emphasizes composability, where different components like prompts, APIs, and data processing steps can be combined into reusable pipelines. -
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ComfyUI-3D-Pack
An extensive node suite that enables ComfyUI to process 3D inputs
ComfyUI-3D-Pack is an extension package for the ComfyUI visual AI workflow environment that enables users to generate and manipulate 3D assets using advanced machine learning techniques. ComfyUI itself is a node-based interface for designing and executing generative AI pipelines, and this extension expands its capabilities by introducing nodes specifically designed for working with three-dimensional data. The package allows the platform to process inputs such as meshes and UV textures and... -
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LangChain for Java
LangChain4j is an open-source Java library
...The library provides a unified API that allows developers to connect Java applications to multiple AI providers and embedding databases without having to implement separate integrations for each service. Its architecture includes abstractions for prompts, chat interactions, document processing, embeddings, and vector storage, enabling developers to build complex AI workflows with minimal boilerplate code. LangChain4j also implements common design patterns used in generative AI systems, such as retrieval-augmented generation pipelines, tool calling, and intelligent agent frameworks. These abstractions allow developers to orchestrate interactions between language models, external tools, and knowledge bases in a structured and scalable way. -
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h2oGPT
Private chat with local GPT with document, images, video, etc.
h2oGPT is an open-source platform that allows users to interact with local GPT models in a completely private environment. It supports a variety of document types, including PDFs, Word files, images, video frames, and even audio, enabling users to query and analyze their documents or engage in a private chat with AI. The platform is designed to be secure and offline, ensuring that all data remains private and under the user's control. h2oGPT supports several AI models, including oLLaMa and... -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Orpheus TTS
Towards Human-Sounding Speech
...It is designed to produce human-like speech with natural intonation, emotion, and rhythm, targeting quality comparable to or better than many closed-source systems. The project ships both pretrained and finetuned English models, as well as a family of multilingual models released as a research preview, and includes data-processing scripts so users can train or finetune their own variants. Inference is provided through a Python package that uses vLLM under the hood for high-throughput, low-latency generation, including streaming examples that show how to generate audio chunks in real time. The maintainers provide Colab notebooks, a standardized prompting format, and one-click deployment via Baseten for production-grade, FP8/FP16 optimized inference with ~200 ms streaming latency. -
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OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
...It often includes modular components that can be adapted to different machine learning pipelines, enabling flexibility across use cases such as recommendation systems, natural language processing, or multimodal tasks. OpenHarness is designed to integrate with modern ML ecosystems, supporting distributed training and efficient resource utilization. It also emphasizes collaboration, enabling teams to share configurations and results in a standardized format. -
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Open Multi-Agent
One runTeam() call from goal to result
...The architecture is designed to be extensible, enabling integration with external tools and APIs to expand agent capabilities. It is particularly useful for research, automation, and development workflows that require multiple perspectives or stages of processing. Overall, open-multi-agent provides a foundation for building scalable and cooperative AI systems. -
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Scriberr
Self-hosted AI audio transcription
Scriberr is a self-hosted AI-powered transcription platform designed to convert audio and video into highly accurate text while prioritizing privacy and local processing. Unlike cloud-based transcription services, Scriberr runs entirely on the user’s machine, ensuring that sensitive recordings are never sent to third-party servers and remain fully under user control. It leverages modern speech recognition models such as Whisper and other advanced architectures to deliver precise transcripts with word-level timing and speaker identification. ... -
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TADA
Open Source Speech Language Model
TADA is an open-source speech-language modeling framework designed to unify spoken audio and text representations within a single generative architecture. The system focuses on aligning speech and text streams using a dual-alignment mechanism that synchronizes the acoustic signal with its textual representation. By modeling both modalities together, the framework allows developers to build systems capable of generating, understanding, and transforming speech and language simultaneously. This... -
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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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Happy-LLM
Large Language Model Principles and Practice Tutorial from Scratch
Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer architecture, pre-training paradigms, and model scaling strategies while also providing hands-on coding examples so readers can implement and experiment with their own models. The tutorial emphasizes practical understanding by walking users through building and training small language models, including tokenizer construction, pre-training workflows, and fine-tuning methods. -
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nesa
Run AI models end-to-end encrypted
nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality,... -
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Matter AI
Matter AI is open-source AI Code Reviewer Agent
Matter AI is an AI-powered platform designed to enhance productivity through automated content generation, data analysis, and decision support. It leverages machine learning models to process text, analyze patterns, and generate insights, making it suitable for businesses looking to optimize data-driven decision-making. Matter AI integrates with various data sources and provides customizable AI workflows tailored to different industries. -
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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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Arch
Arch is an intelligent prompt gateway. Engineered with (fast) LLMs
Arch is an intelligent Layer 7 gateway designed to protect, observe, and personalize LLM applications (agents, assistants, co-pilots) with your APIs. Engineered with purpose-built LLMs, Arch handles the critical but undifferentiated tasks related to the handling and processing of prompts, including detecting and rejecting jailbreak attempts, intelligently calling "backend" APIs to fulfill the user's request represented in a prompt, routing to and offering disaster recovery between upstream LLMs, and managing the observability of prompts and LLM interactions in a centralized way. -
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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. ... -
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BeeAI Framework
Build production-ready AI agents in both Python and Typescript
...BeeAI also provides orchestration tools for designing dynamic workflows, enabling multiple agents to coordinate tasks through structured execution flows, retries, and parallel processing. -
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FISSURE
The RF and reverse engineering framework for everyone
...The platform supports workflows related to signal discovery, demodulation, packet inspection, fuzzing, and attack simulation, making it useful for both defensive research and controlled lab testing. Its architecture is oriented toward extensibility, so users can integrate additional hardware, signal-processing components, and protocol-specific modules depending on their needs. -
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HivisionIDPhoto
HivisionIDPhotos: a lightweight and efficient AI ID photos tools
...It also allows the generation of layout sheets such as six-inch photo arrangements for printing multiple ID photos on a single page. The project focuses on building a practical pipeline for automated ID photo production using AI-based segmentation and image processing techniques. -
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MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web... -
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Stripe AI
One-stop shop for building AI-powered products and businesses
...It enables developers to connect large language models and AI agents with Stripe APIs so that automated systems can perform actions such as handling transactions, managing subscriptions, or processing financial events. The platform is particularly relevant for companies building AI-driven products that require monetization, usage-based billing, or programmable financial interactions. By offering ready-to-use integrations and development tools, Stripe AI reduces the complexity of connecting AI systems with payment services. -
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ModernBERT
Bringing BERT into modernity via both architecture changes and scaling
ModernBERT is an open-source research project that modernizes the classic BERT encoder architecture by incorporating recent advances in transformer design, training techniques, and efficiency improvements. The goal of the project is to bring BERT-style models up to date with the capabilities of modern large language models while preserving the strengths of bidirectional encoder architectures used for tasks such as classification, retrieval, and semantic search. ModernBERT introduces... -
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AI Powered Knowledge Graph Generator
AI Powered Knowledge Graph Generator
...Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project enables systems to automatically extract relationships and insights from large volumes of data. These capabilities make knowledge graph platforms particularly useful for applications such as recommendation engines, enterprise knowledge management, and research data exploration. The system emphasizes structured data modeling and graph-based queries that allow users to explore relationships that would be difficult to identify using traditional relational databases. -
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xLSTM
Neural Network architecture based on ideas of the original LSTM
xLSTM is an open-source machine learning architecture that reimagines the classic Long Short-Term Memory (LSTM) network for modern large-scale language modeling and sequence processing tasks. The project introduces a new recurrent neural network design that incorporates exponential gating mechanisms and enhanced memory structures to overcome limitations of traditional LSTM models. By introducing innovations such as matrix-based memory and improved normalization techniques, xLSTM improves the ability of recurrent networks to capture long-range dependencies in sequential data. ... -
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Helicone
Open source LLM-Observability Platform for Developers
Open source LLM-Observability Platform for Developers. One-line integration for monitoring, metrics, evals, agent tracing, prompt management, playground, etc. Supports OpenAI SDK, Vercel AI SDK, Anthropic SDK, LiteLLM, LLamaIndex, LangChain, and more.
