Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 21
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1049 projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" with 2 filters applied:
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PeerGFS PEER Software - File Sharing and CollaborationPeerGFS is a software-only solution developed to solve file management/file replication challenges in multi-site, multi-platform, and hybrid multi-cloud environments.
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Quality and compliance software for growing life science companiesAutomate gap analysis across FDA, ISO 13485, MDR, and 28+ regulatory standards. Cross-map evidence once, reuse across submissions. Get real-time risk alerts and board-ready dashboards, so you can expand into new markets with confidence
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MolmoWeb
Open multimodal web agent built by Ai2
MolmoWeb is an open-source multimodal web agent designed to autonomously navigate and interact with web browsers using vision-language models, representing a significant step toward fully agentic AI systems that can operate in real-world digital environments. The system takes natural language instructions and translates them into sequences of browser actions such as clicking, typing, scrolling, and navigating, effectively performing tasks on behalf of the user. Unlike traditional automation... -
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ToolUniverse
Democratizing AI scientists with ToolUniverse
...Instead of requiring custom pipelines or fine-tuning, ToolUniverse wraps around existing models and enables them to reason, experiment, and iterate on complex workflows such as drug discovery, data analysis, and hypothesis testing. The platform abstracts tool usage behind a consistent interface, allowing AI agents to compose multi-step workflows, refine tool definitions automatically, and even generate new tools from natural language descriptions. -
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DeepReasoning
High-performance API combining reasoning and creative AI models
...Built with Rust, the backend focuses on performance, low latency, and efficient resource usage for demanding workloads. It follows a bring-your-own-key approach, giving users full control over their API credentials and data privacy. Additionally, it supports self-hosting and extensive configuration, making it suitable for developers who want flexibility and control. -
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Talk to Figma MCP
AI bridge enabling Cursor agents to read and modify Figma designs
cursor-talk-to-figma-mcp is an open source integration that connects AI coding agents with Figma through the Model Context Protocol (MCP). It allows AI tools such as Cursor or other compatible agents to directly communicate with Figma documents and interact with design elements programmatically. Through this integration, an AI assistant can read the structure of a design, retrieve information about nodes or selections, and perform modifications to the layout or content.... -
Run your private office with the ONLYOFFICEA Comprehensive Alternative to Office 365 for Business
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GitMCP
Turn any GitHub repository into an MCP documentation server for AI
...It enables developer-focused AI tools to access up-to-date project documentation and source code so that responses are grounded in real repository content rather than outdated training data. By exposing repository documentation and code through standardized MCP tools, GitMCP helps reduce incorrect or fabricated answers when AI systems assist with coding tasks. It can operate in repository-specific mode, where an AI assistant connects to a particular project, or in a generic mode that allows switching between multiple repositories dynamically. ... -
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hls4ml
Machine learning on FPGAs using HLS
...This approach allows machine learning algorithms to run directly on specialized hardware, making them suitable for applications that require extremely fast response times and minimal power consumption. The framework was originally developed for high-energy physics experiments where real-time decision systems must process large volumes of data with strict latency constraints. Over time, it has expanded to support a variety of scientific and industrial applications including signal processing, embedded systems, and biomedical monitoring. -
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Advanced NLP with spaCy
Advanced NLP with spaCy: A free online course
...The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and training custom NLP models. It also demonstrates how spaCy pipelines work and how developers can extend them with custom components and training data. The course is structured as a hands-on learning environment where students can run code examples, experiment with NLP techniques, and build practical language processing applications. Because spaCy is widely used in production environments, the course emphasizes industrial-strength NLP workflows and best practices. -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and... -
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crème de la crème of AI courses
This repository is a curated collection of links to various courses
crème de la crème of AI courses is an open-source repository that serves as a curated directory of high-quality educational resources related to artificial intelligence, machine learning, and modern data science. The project aggregates links to online courses, tutorials, lecture series, and learning materials from universities, research labs, and independent educators. The repository organizes courses by topic, difficulty level, format, and release year, allowing learners to quickly identify relevant material depending on their experience and interests. ... -
The AI coach for teams, built on validated assessments.Give managers and teams proactive, contextual coaching to lead effectively, communicate clearly, and navigate real work situations as they happen.
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Machine Learning for Software Engineers
A complete daily plan for studying to become a machine learning engine
...The repository presents a top-down learning path that emphasizes hands-on experience rather than heavy theoretical prerequisites, making it particularly approachable for developers who already have programming experience but limited formal training in machine learning. The project organizes a multi-month study schedule that covers topics such as machine learning fundamentals, algorithm understanding, data preparation, and practical experimentation. It aggregates a wide range of resources including books, online courses, Kaggle competitions, podcasts, conferences, and community learning opportunities. The repository is structured to help learners gradually build the skills required for machine learning engineering positions while maintaining a focus on real-world application development. -
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MiroFlow
Agent framework that enables tool-use agent tasks
MiroFlow is a high-performance open-source framework designed for building intelligent AI agents capable of solving complex reasoning and research tasks. The system introduces a hierarchical architecture that organizes components into control, agent, and foundation layers, allowing developers to manage agent orchestration and tool interactions in a structured manner. One of the core innovations of MiroFlow is its use of agent graphs, which enable flexible orchestration of multiple sub-agents... -
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Prompt Poet
Streamlines and simplifies prompt design for both developers
...By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. The framework supports dynamic prompts that adapt to runtime data, allowing developers to inject variables, context, and examples directly into templates. This approach is particularly useful in production environments where prompt consistency, maintainability, and versioning are important. -
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AgentEvolver
Towards Efficient Self-Evolving Agent System
...These mechanisms enable agents to continuously improve their capabilities while interacting with complex environments and tools. AgentEvolver also integrates environment sandboxes, experience management systems, and modular data pipelines to support large-scale experimentation. -
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DriveLM
Driving with Graph Visual Question Answering
...Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models answer structured questions about the environment to guide decision making. The system includes DriveLM-Data, a dataset built on driving environments such as nuScenes and CARLA, where human-written reasoning steps connect different layers of driving tasks. This design allows models to learn relationships between objects, behaviors, and navigation decisions through graph-structured logic. -
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BuildingAI
Build your own AI application system for free
...The platform aims to bridge the gap between natural language interfaces and building design tools by allowing AI systems to interpret user instructions and convert them into structured architectural operations. By combining generative AI capabilities with building data models, the system can assist with tasks such as design generation, spatial reasoning, and building component creation. The project is intended for architects, engineers, and developers exploring how AI can automate or augment design workflows in the architecture, engineering, and construction industries. It supports interactions where users describe building features, layouts, or modifications in natural language and the AI translates those instructions into actionable design operations. -
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PKU Beaver
Constrained Value Alignment via Safe Reinforcement Learning
PKU Beaver is an open-source research project focused on improving the safety alignment of large language models through reinforcement learning from human feedback under explicit safety constraints. The framework introduces techniques that separate helpfulness and harmlessness signals during training, allowing models to optimize for useful responses while minimizing harmful behavior. To support this process, the project provides datasets containing human-labeled examples that encode both... -
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WebGLM
An Efficient Web-enhanced Question Answering System
...The system is based on the General Language Model architecture and was designed to enable language models to interact directly with web information during the question-answering process. Instead of relying solely on knowledge stored in the model’s training data, the system retrieves relevant web content and integrates it into the reasoning process. WebGLM introduces several components that coordinate this process, including a retrieval module that selects relevant web documents, a generator that produces answers, and a scoring system that evaluates the quality of generated responses. The architecture aims to improve the reliability and usefulness of AI systems that answer questions about current or external knowledge sources. -
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code-act
Official Repo for ICML 2024 paper
...This approach helps unify reasoning and action planning within large language model agents by using code as the primary interface between the model and the external world. The framework also includes training data, models, and evaluation tools designed to study how language models can become more capable autonomous agents. -
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ChatWiki
ChatWiki WeChat official account's AI knowledge base workflow agent
ChatWiki is an open-source AI knowledge base and workflow automation platform designed to help organizations build intelligent question-answering systems using large language models and retrieval-augmented generation techniques. The system enables companies to transform internal documents and data into searchable knowledge bases that can power AI assistants capable of answering domain-specific questions. It provides a complete pipeline for ingesting documents, preprocessing and segmenting content, generating vector embeddings, and retrieving relevant information during conversations. The platform supports multiple large language models and allows developers to easily connect cloud-based or local models to power the chatbot. ... -
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LongWriter
Unleashing 10,000+ Word Generation from Long Context LLMs
LongWriter is an open-source framework and set of large language models designed to enable ultra-long text generation that can exceed 10,000 words while maintaining coherence and structure. Traditional large language models can process large inputs but often struggle to generate long outputs due to limitations in training data and alignment strategies. LongWriter addresses this challenge by introducing a specialized dataset and training approach that encourages models to produce longer responses. The system uses an agent-based pipeline called AgentWrite that decomposes large writing tasks into smaller subtasks, allowing the model to produce long documents section by section. ... -
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LlamaGen
Autoregressive Model Beats Diffusion
LlamaGen is an open-source research project that introduces a new approach to image generation by applying the autoregressive next-token prediction paradigm used in large language models to visual generation tasks. Instead of relying on diffusion models, the framework treats images as sequences of tokens that can be generated progressively using transformer architectures similar to those used for text generation. The project explores how scaling autoregressive models and improving image... -
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Magicoder
Empowering Code Generation with OSS-Instruct
...This technique uses open-source code repositories as a foundation for generating more realistic and diverse instruction datasets for training language models. By grounding training data in real open-source examples, Magicoder aims to reduce bias and improve the reliability of code generation results compared to models trained solely on synthetic instructions. The project includes model implementations, training resources, and evaluation benchmarks that demonstrate how the approach improves instruction-following and code synthesis capabilities. ... -
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vLLM Semantic Router
System Level Intelligent Router for Mixture-of-Models at Cloud
...This approach allows developers to combine multiple models with different strengths, such as lightweight models for simple queries and more advanced reasoning models for complex tasks. The router operates as an intelligent layer between users and model infrastructure, capturing signals from prompts, responses, and contextual data to improve decision-making. It can also integrate safety and monitoring mechanisms that detect issues such as jailbreak attempts, hallucinations, or sensitive information exposure. -
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ai-cookbook
Examples and tutorials to help developers build AI systems
...The repository contains examples that demonstrate how to build AI workflows using modern tools such as large language models, autonomous agents, and external APIs. Developers can learn how to construct applications like intelligent assistants, automation pipelines, and AI-powered data analysis tools through step-by-step tutorials and ready-to-run scripts. The code examples are designed to emphasize practical architecture patterns that are commonly used in production environments, helping developers understand how to integrate AI services into software products. -
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RunAnywhere
Production ready toolkit to run AI locally
...The toolkit allows developers to integrate language models, speech recognition, and voice synthesis capabilities into mobile or desktop applications while keeping all computation local. By running models entirely on device, the platform eliminates network latency and protects user data because information does not leave the device. The SDK supports popular open-source models such as Llama, Mistral, and Qwen, enabling developers to build AI-powered features such as chat interfaces and voice assistants with minimal external dependencies. It also includes integrated pipelines that combine speech-to-text, large language models, and text-to-speech into a complete conversational system.
