Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 14
Sort By:
Showing 2743 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
View related business solutions-
Our xDM platform turns business users into data champions.It empowers organizations of any size to build trusted data applications quickly, with fast time to value using a single software platform for governance, master data, reference data, data quality, enrichment, and workflows.
-
Pylon is an All-in-one B2B Support Platform for modern B2B businesses.We bring together everything a post-sales teams team needs including a ticketing system, B2B omnichannel integrations (Slack Connect, Microsoft Teams), modern chat widget, knowledge base, AI support bot, account management, customer marketing, and more.
-
1
OpenVINO Model Server
A scalable inference server for models optimized with OpenVINO
...It supports model deployment in diverse environments including Docker, bare-metal machines, and Kubernetes clusters, and is especially useful in microservices architectures where AI services need to scale independently. The system supports a wide range of model sources, letting you host models from local storage, remote object storage, or even pull from model hubs. -
2
AgentHub
GitHub is for humans. AgentHub is for agents
...Rather than focusing solely on human collaboration, the system is designed around an “agent-first” paradigm where AI agents can contribute code, discuss changes, and coordinate problem solving. The platform treats code repositories not just as storage for files but as active environments where agents can propose modifications, review changes, and exchange structured messages. This approach reflects emerging research in multi-agent software development where groups of AI systems collaborate on complex engineering problems. -
3
FileScope MCP
Analyzes your codebase identifying important files based on dependency
FileScopeMCP is a TypeScript-based tool that analyzes codebases to identify important files based on dependency relationships. It generates diagrams and importance scores per file, aiding in understanding code structure and assisting AI assistants in navigating complex projects. -
4
Anomaly Detection Learning Resources
Anomaly detection related books, papers, videos, and toolboxes
...It includes materials covering a wide range of anomaly detection domains, including time series data, graph data, tabular datasets, and real-time monitoring systems. By compiling resources from multiple programming ecosystems such as Python, R, and other machine learning platforms, the repository allows users to discover both research papers and practical implementations. -
MaintainX is the world-leading mobile-first workflow management platform for industrial and frontline workers.Your day-to-day maintenance tasks, simplified. MaintainX eliminates the paperwork, so you can spend less time on your clipboard and more time getting things done.
-
5
edge-tts
Use Microsoft Edge's online text-to-speech service from Python
...It wraps the same cloud voices used by Edge, exposing them through a simple CLI (edge-tts, edge-playback) and a Python API, so you can script high-quality speech generation in your own applications. The tool lets you list available voices, specify locale and voice name, and generate audio files in common formats like MP3 or WAV. It also supports generating subtitle files (such as SRT or VTT) alongside the speech, which is handy for video narration, e-learning, or accessibility workflows. From the CLI you can adjust parameters such as speaking rate, volume, and pitch, giving you some control over prosody without diving into SSML. ... -
6
Computer Vision Annotation Tool (CVAT)
Interactive video and image annotation tool for computer vision
...It offers many powerful features, including automatic annotation using deep learning models, interpolation of bounding boxes between key frames, LDAP and more. It is being used by its own professional data annotation team to annotate millions of objects with different properties. The UX and UI were also specially developed by the team for computer vision tasks. CVAT supports several annotation formats. Format selection can be done after clicking on the Upload annotation and Dump annotation buttons. -
7
Aidea
Flutter-based cross-platform app integrating major AI models
AIdea is a comprehensive Flutter-based cross-platform app integrating major AI models—OpenAI GPT, Chinese models Tongyi Qianwen and Wenxin Yiyan, plus image models like Stable Diffusion for text-to-image, image-to-image, SDXL 1.0, super-resolution, and colorization. It includes a client app, server backend, and Docker deployment scripts for hosted setups. -
8
RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
RWKV (pronounced as RwaKuv) is an RNN with GPT-level LLM performance, which can also be directly trained like a GPT transformer (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility... -
9
ReMe
Memory Management Kit for Agents
...It is designed to support long-running agent workflows where context matters and working memory alone isn’t enough, helping agents remember user preferences, task histories, and relevant past observations. The toolkit provides APIs to offload large, ephemeral outputs to external storage and reload them on demand, which reduces memory bloat and keeps active context concise. By combining embeddings, vector search, and summarization workflows, ReMe lets developers build agent systems that can recall and apply past knowledge in future reasoning tasks. The project fits into the broader agent-oriented programming ecosystem by supplying a standardized memory layer that integrates with agent frameworks. -
Managed File Transfer SoftwareFor too many businesses, complex file transfer needs make it difficult to create, manage and support data flows to and from internal and external systems. Progress® MOVEit® empowers enterprises to take control of their file transfer workflows with solutions that help secure, simplify and centralize data exchanges throughout the organization.
-
10
JimuReport
Open source drag-and-drop reporting and dashboard builder platform
...JimuReport supports traditional report generation, print templates, and modern dashboard visualizations for business intelligence scenarios. JimuReport also includes components for building interactive charts, data tables, and analytical displays that can be used in enterprise applications. It can connect to multiple data sources and retrieve data through SQL queries, APIs, or other structured formats. It can be embedded into Java applications using Spring Boot integration modules. -
11
GLM-5
From Vibe Coding to Agentic Engineering
GLM-5 is a next-generation open-source large language model (LLM) developed by the Z .ai team under the zai-org organization that pushes the boundaries of reasoning, coding, and long-horizon agentic intelligence. Building on earlier GLM series models, GLM-5 dramatically scales the parameter count (to roughly 744 billion) and expands pre-training data to significantly improve performance on complex tasks such as multi-step reasoning, software engineering workflows, and agent orchestration compared to its predecessors like GLM-4.5. It incorporates innovations like DeepSeek Sparse Attention (DSA) to preserve massive context windows while reducing deployment costs and supporting long context processing, which is crucial for detailed plans and agent tasks. -
12
Deep Research
Use any LLMs (Large Language Models) for Deep Research
...It combines “thinking” and “task” model roles with live internet access to plan, search, read, and synthesize findings into structured outputs. The project emphasizes privacy: processing and storage happen locally, avoiding server-side retention of your queries and notes. A simple web UI lets you enter topics and configure models, while the backend streams progress as sources are fetched and arguments are weighed. It offers MCP server support and SSE APIs, so IDEs and agent clients can drive the same workflow programmatically. ... -
13
PrivateGPT
Interact with your documents using the power of GPT
PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem). -
14
PySyft
Data science on data without acquiring a copy
...Wherever your data wants to live in your ownership, the Syft ecosystem exists to help keep it there while allowing it to be used privately. -
15
Claw Hunter
MDM-ready scripts for detecting and monitoring OpenClaw
...The tool performs risk assessment by auditing agent permissions, capabilities, and access levels, allowing security teams to evaluate potential attack surfaces. It also helps ensure that these agents do not unintentionally expose sensitive data or create unauthorized access paths across systems. -
16
OpenFold
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction
...OpenFold is trainable in full precision, half precision, or bfloat16 with or without DeepSpeed, and we've trained it from scratch, matching the performance of the original. We've publicly released model weights and our training data — some 400,000 MSAs and PDB70 template hit files — under a permissive license. Model weights are available via scripts in this repository while the MSAs are hosted by the Registry of Open Data on AWS (RODA). -
17
bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous compute infrastructure. The project’s focus on extreme quantization dramatically reduces memory footprint and energy consumption compared with traditional 16-bit or 32-bit LLMs, making it practical to deploy advanced language understanding and generation models on everyday machines. ... -
18
FiftyOne
The open-source tool for building high-quality datasets
...FiftyOne provides the building blocks for optimizing your dataset analysis pipeline. Use it to get hands-on with your data, including visualizing complex labels, evaluating your models, exploring scenarios of interest, identifying failure modes, finding annotation mistakes, and much more! Surveys show that machine learning engineers spend over half of their time wrangling data, but it doesn't have to be that way. -
19
X-AnyLabeling
Effortless data labeling with AI support from Segment Anything
X-AnyLabeling is an open-source data annotation platform designed to streamline the process of labeling datasets for computer vision and multimodal AI applications. The software integrates an AI-powered labeling engine that allows users to generate annotations automatically with the assistance of modern vision models such as Segment Anything and various object detection frameworks. -
20
Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
21
Extractous
Fast and efficient unstructured data extraction
Extractous is a Rust-based unstructured data extraction library focused on fast local parsing of documents and other content-heavy files. Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. ... -
22
Enchanted
Enchanted is iOS and macOS app for chatting with language models
Enchanted is an open-source, cross-platform application built to let users chat with privately hosted large language models from Apple devices, including macOS, iOS, and visionOS. Designed to work seamlessly with servers like Ollama, it provides a privacy-focused alternative to traditional cloud AI UIs by connecting directly to your own LLM endpoints such as Llama, Mistral, Vicuna, and more. The interface resembles familiar commercial chat apps but emphasizes local control, offline... -
23
Apache Hamilton
Helps data scientists define testable self-documenting dataflows
...This approach encourages modular, testable, and maintainable data pipelines because each transformation is isolated and easily unit tested. The framework also automatically tracks lineage and metadata about how data is produced, which improves debugging, reproducibility, and transparency in data workflows. -
24
mcpo
A simple, secure MCP-to-OpenAPI proxy server
mcpo is a minimal bridge that exposes any MCP tool as an OpenAPI-compatible HTTP server. Instead of writing glue code, you point mcpo at an MCP server command and it generates REST endpoints and an OpenAPI spec that other systems (or LLM agent frameworks) can call immediately. This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI... -
25
Superduper
Superduper: Integrate AI models and machine learning workflows
...This allows developers to completely avoid implementing MLOps, ETL pipelines, model deployment, data migration, and synchronization. Using Superduper is simply "CAPE": Connect to your data, apply arbitrary AI to that data, package and reuse the application on arbitrary data, and execute AI-database queries and predictions on the resulting AI outputs and data.
