Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 5
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Showing 2236 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Respond 100x faster, more accurately, and improve your documentationSlash response times for questionnaires, audits, and RFPs by up to 90%. OptiValue.ai automates the heavy lifting, freeing your team to focus on strategic priorities with intuitive tools for seamless review and validation.
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Your go-to FinOps platformUnlike reporting-only FinOps tools, FinOpsly unifies cloud (AWS, Azure, GCP), data (Snowflake, Databricks, BigQuery), and AI costs into a single system of action — enabling teams to plan spend before it happens, automate optimization safely, and prove value in weeks, not quarters.
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Chronos Forecasting
Pretrained (Language) Models for Probabilistic Time Series Forecasting
...Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes. -
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Paperclip
Open-source orchestration for zero-human companies
Paperclip is an open-source tool designed to help AI systems and developer tools access academic research papers through a standardized interface. The project implements a server based on the Model Context Protocol (MCP), a framework that allows large language models and AI agents to connect to external data sources and tools in a consistent way. By acting as a middleware layer, Paperclip aggregates multiple academic databases and exposes them through a single interface, allowing AI applications to search and retrieve scholarly papers without needing to integrate with each provider individually. The system supports repositories such as arXiv, OpenAlex, and the Open Science Framework, giving AI agents access to a large body of research literature. ... -
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IMS Toucan
Controllable and fast Text-to-Speech for over 7000 languages
...The toolkit focuses on being fast and controllable while not requiring huge amounts of compute, making it practical for research labs and smaller teams. It includes complete pipelines for preprocessing datasets, training models, and running inference, plus a storage configuration system to manage where models and caches are stored. IMS-Toucan ships with several ready-to-run scripts, including GUIs for interactive demos, prosody override tools, zero-shot language embedding injection, and text-to-audio file generation. Pretrained models are automatically downloaded when needed, and there is an online demo instance hosted on GPU that anyone can try. -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling ecosystems. Agent-Lightning introduces a lightweight training pipeline that observes agents’ execution traces, converts them into structured data, and feeds them into training algorithms, enabling users to improve agent behaviors systematically. ... -
Stigg | SaaS Monetization and Entitlements APIA monetization platform is a standalone middleware that sits between your application and your business applications, as part of the modern enterprise billing stack. Stigg unifies all the APIs and abstractions billing and platform engineers had to build and maintain in-house otherwise. Acting as your centralized source of truth, with a highly scalable and flexible entitlements management, rolling out any pricing and packaging change is now a self-service, risk-free, exercise.
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
AgenticSeek is a fully local autonomous AI assistant designed as a privacy-focused alternative to cloud-based agent platforms. It runs entirely on the user’s hardware and can autonomously browse the web, write code, and plan multi-step tasks without sending data to external services. The system is optimized for local reasoning models and emphasizes zero cloud dependency to maintain full user control. AgenticSeek includes intelligent agent selection, allowing it to determine the best internal agent to handle a given request. It also supports hands-free workflows such as automated web form interaction and information extraction. ... -
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Firebase MCP
Model Context Protocol (MCP) server to interact with Firebase service
A Model Context Protocol (MCP) server that enables Large Language Model (LLM) clients to interact seamlessly with Firebase services, facilitating operations across Authentication, Firestore, and Storage. -
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Octelium
A next-gen FOSS self-hosted unified zero trust secure access platform
Octelium is an open source, self-hosted unified secure-access platform built for modern infrastructure and hybrid environments. It positions itself as more than a typical VPN; it supports zero-trust network access (ZTNA), “BeyondCorp”-style access, API/AI gateway functionality, and even serves as a PaaS-like deployment surface. One of its key strengths is identity-based, application-layer (L7) aware control, meaning access decisions are made per request, with context and policy rather than simple network-level allow/block rules. ... -
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KubeAI
Private Open AI on Kubernetes
Get inferencing running on Kubernetes: LLMs, Embeddings, Speech-to-Text. KubeAI serves an OpenAI compatible HTTP API. Admins can configure ML models by using the Model Kubernetes Custom Resources. KubeAI can be thought of as a Model Operator (See Operator Pattern) that manages vLLM and Ollama servers. -
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JAI Workflow
Build programmatically custom agentic workflows, AI Agents, RAG system
JAI-Workflow is a framework for building and managing machine learning workflows, streamlining the process from data ingestion to model deployment. -
Self-hosted password managerOn-premise solution with double encryption and certified development processes for maximum protection of corporate data. Zero‑knowledge architecture ensures your passwords never leave your infrastructure.
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Aix-DB
Based on the LangChain/LangGraph framework
...The platform supports multiple types of data sources and provides an end-to-end pipeline that includes intent recognition, SQL generation, database execution, and visual presentation of results. Its architecture includes multiple layers such as a web interface, API gateway, AI service layer, and data storage layer that support relational databases, vector stores, graph databases, and file systems. -
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dataline
AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake
dataline is an open-source AI data analysis and visualization platform that allows users to interact with datasets using natural language. The system enables both technical and non-technical users to explore data by asking questions conversationally, which the platform translates into database queries and analytical operations. It supports connections to multiple structured data sources such as PostgreSQL, MySQL, Snowflake, SQLite, Excel files, CSV datasets, and other database systems. ... -
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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Kalavai
Turn everyday devices into your own AI cluster
...Do you have an old desktop or a gaming laptop gathering dust? Aggregate resources from multiple machines and say goodbye to CUDA out-of-memory errors. Deploy your favorite open-source LLM, fine-tune it with your own data, or simply run your distributed work, zero-DevOps. Simple. Private. Yours. -
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OpenVoice
Instant voice cloning by MIT and MyShell. Audio foundation model
...It is designed not only to match the timbre of the reference voice, but also to give granular control over style parameters such as emotion, accent, rhythm, pauses, and intonation. The model supports cross-lingual and even zero-shot cross-lingual voice cloning, so a speaker recorded in one language can be made to speak naturally in others. Architecturally, OpenVoice separates “tone color” cloning from style control, which makes it easier to keep a consistent identity while flexibly changing prosody or language. The project provides open-weight models, inference code, and examples, making it suitable both for research and for building production voice experiences. ... -
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txtai
Build AI-powered semantic search applications
...Innovation is happening at a rapid pace, models can understand concepts in documents, audio, images and more. Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai. -
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Habit Tracker
Habit Tracker for the AI Coding Workshop
Habit Tracker is a personal habit-tracking web application designed to help users build and maintain daily habits through intuitive UI and analytics that visualize progress over time. It runs locally with a FastAPI backend (Python) and a React frontend, storing all data in a lightweight SQLite database so there’s no need for user accounts or cloud storage, which keeps habit data fully private and self-contained. The app provides streak tracking and completion rates for each habit, giving users feedback on consistency and motivation by showing how often habits are completed and where they may be lagging. ... -
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Vearch
A distributed system for embedding-based vector retrieval
...This GIF provides a clear demonstration of the project vearch usage and its internal structure. The use of vearch is mainly divided into three steps. Firstly, create DB and Space, then import your data, and finally, you can search on your own dataset. -
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Milvus
Vector database for scalable similarity search and AI applications
Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. Average latency measured in milliseconds on trillion vector datasets. ... -
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Sopro TTS
A lightweight text-to-speech model with zero-shot voice cloning
Sopro TTS is an open-source text-to-speech (TTS) project that implements a lightweight model capable of producing speech from text with zero-shot voice cloning, meaning it can mimic a speaker’s voice from only a few seconds of reference audio. Built with a 169 million-parameter architecture that uses dilated convolutions and cross-attention layers instead of large Transformer stacks, it achieves relatively fast real-time performance even on CPUs (about a 0.25 real-time factor measured on an M3 base). ... -
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Framelink MCP for Figma
MCP server enabling AI coding tools to access Figma design data
Figma-Context-MCP is an open source server that connects Figma design data with AI-powered coding tools through the Model Context Protocol (MCP). It allows coding assistants to retrieve structured information from Figma files so they can better translate visual designs into working code. Instead of relying on screenshots or manual descriptions, Figma-Context-MCP accesses layout, styling, and component metadata directly from the Figma API and presents it in a simplified format optimized for AI models. ... -
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segment-geospatial
A Python package for segmenting geospatial data with the SAM
The segment-geospatial package draws its inspiration from segment-anything-eo repository authored by Aliaksandr Hancharenka. To facilitate the use of the Segment Anything Model (SAM) for geospatial data, I have developed the segment-anything-py and segment-geospatial Python packages, which are now available on PyPI and conda-forge. My primary objective is to simplify the process of leveraging SAM for geospatial data analysis by enabling users to achieve this with minimal coding effort. I have adapted the source code of segment-geospatial from the segment-anything-eo repository, and credit for its original version goes to Aliaksandr Hancharenka. -
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Machine Learning and Data Science Apps
A curated list of applied machine learning and data science notebooks
...Most examples are written in Python and frequently use Jupyter notebooks to present practical implementations and experiments. The project encourages contributions from data scientists and domain experts who want to share applied analytics projects and techniques that address real business challenges. -
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Agent Development Kit (ADK)
Open-source, code-first Python toolkit for building, evaluating, etc.
ADK (Android Device Key) Python is a reference implementation by Google for working with Android attestation keys in Python. It facilitates the integration of Android attestation features into backends or systems that require verification of device identity and integrity. This is especially important in high-security applications where verifying that a device is genuine and uncompromised is critical. -
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JADX-AI-MCP
Plugin for JADX to integrate MCP server
JADX-AI-MCP is an open-source plugin that integrates large language models into the JADX Android decompiler to assist with reverse engineering and code analysis tasks. The project connects JADX with AI assistants through the Model Context Protocol, enabling language models to interact directly with decompiled Android application code. Through this integration, AI systems can inspect classes, analyze methods, retrieve application manifests, and examine other elements of Android packages in real time. ... -
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HY-Motion 1.0
HY-Motion model for 3D character animation generation
...Built on advanced deep learning architectures that combine Diffusion Transformer (DiT) and flow matching techniques, HY-Motion scales these approaches to the billion-parameter level, resulting in strong instruction-following capabilities and richer motion outputs compared to existing open-source models. The training strategy for the HY-Motion series includes extensive pre-training on thousands of hours of varied motion data, fine-tuning on curated high-quality datasets, and reinforcement learning with human feedback, which improves both the plausibility and adaptability of generated motion sequences.
