Search Results for "router data usage"
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61 projects for "router data usage" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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MCP Router
A Unified MCP Server Management App (MCP Manager)
MCP Router is an open-source management platform designed to simplify the deployment and coordination of Model Context Protocol (MCP) servers used by AI agents. MCP is an emerging standard that allows language models and AI assistants to connect to external tools, data sources, and services through a structured interface. The MCP Router project acts as a centralized manager that helps developers run, configure, and coordinate multiple MCP servers within a single environment. ... -
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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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ClaudeBar
A macOS menu bar application that monitors AI coding assistant usage
...It includes options to enable or disable monitoring for individual providers, supports multiple visual themes (including dark mode and a festive theme), and refreshes data at configurable intervals so users always have up-to-date information. -
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Chatbot
A full-featured, hackable Next.js AI chatbot built by Vercel
The Vercel Chatbot repository provides a full-featured, production-ready template for building modern AI chat applications using Next.js and the Vercel AI SDK. It is designed to give developers a fast starting point for deploying conversational interfaces with streaming responses and scalable infrastructure. The project integrates server components, authentication, and persistent storage to support real-world usage scenarios. It supports multiple AI providers through a unified gateway,... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Bionic GPT
Bionic is an on-premise replacement for ChatGPT
Bionic is an on-premise generative AI platform positioned as a private replacement for ChatGPT, with a strong emphasis on data confidentiality, team collaboration, and enterprise deployment. It can run locally on a laptop for small pilots, but it is also designed to scale into data center and Kubernetes environments for much larger usage. The interface is intentionally familiar, offering a ChatGPT-like experience with customizable branding, fast Rust-based performance, and conversation history management. ... -
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Latent Box
A collection of awesome-lists for AI, creativity and art. AI
Latent Box is an open-source platform focused on managing, deploying, and interacting with local or self-hosted AI models through a unified interface that simplifies experimentation and usage. It is designed to act as a control layer for running generative models, particularly those related to text and multimodal outputs, while maintaining full ownership of data and infrastructure. The platform emphasizes usability by providing a clean user interface that allows users to load models, configure parameters, and interact with them without needing deep technical knowledge of underlying frameworks. ... -
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
...Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context. The tool is designed to simplify development by automating repetitive work and providing instant clarifications on code behavior. User feedback and usage data are collected responsibly, with strict privacy safeguards and limited retention, ensuring no feedback is used to train generative models. Claude Code is open and actively maintained with community-driven bug reporting and feature requests. Its natural language interface makes advanced coding workflows accessible without leaving your coding environment. -
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Claude Cognitive
Persistent context and multi-instance coordination
Claude Cognitive is an advanced memory and context-management extension designed to address the stateless limitations of Claude Code by giving the model a form of persistent “working memory” and multi-instance coordination. It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. ... -
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Puck
Open source visual editor for building React drag-and-drop pages
Puck is an open source visual editor designed for React applications that enables developers to build customizable drag-and-drop page editing experiences. It allows teams to create their own page builders by defining React components that can be arranged and configured through a visual interface. Puck is component-based and configuration-driven, meaning developers specify how components render and which editable fields control their properties. Puck integrates directly into existing React... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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TONL
TONL (Token-Optimized Notation Language)
...TONL isn’t just a format — it includes a rich API for querying, indexing, modifying, and streaming data, along with tools for schema validation and TypeScript code generation. The platform comes with a complete command-line interface that supports interactive dashboards and cross-platform usage in browsers and server environments, and its high test coverage gives developers confidence in stability. -
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LEANN
Local RAG engine for private multimodal knowledge search on devices
...By recomputing embeddings during queries and using compact graph-based indexing structures, LEANN can maintain high search accuracy while minimizing disk usage. It aims to act as a unified personal knowledge layer that connects different types of data such as documents, code, images, and other local files into a searchable context for language models. -
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Claude Statusline
Minimal Claude Code statusline setup I personally use
Claude Statusline is a minimal status-line configuration for Claude Code that surfaces useful session and workspace information directly in the terminal. It is designed to show usage limits together with the current directory and Git branch information. Installation is handled through an npm command that copies the status-line script into the user’s Claude configuration directory. The installer automatically backs up an existing status line before replacing it. The setup relies on jq for JSON parsing, curl for retrieving rate-limit data, and Git for repository information. ... -
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Groq Python
The official Python Library for the Groq API
...Through this library, you can call Groq’s models from Python code — for example to request chat completions, code generation, transcription, or any supported endpoint — using idiomatic Python syntax. The SDK handles authentication (via environment variable or parameter), defines proper type-safe request/response data types, and supports both synchronous and asynchronous usage patterns depending on your application needs. This makes it easy to integrate Groq-powered AI capabilities into backend services, data pipelines, research notebooks, or applications written in Python. For those building AI-based tooling, automation scripts, or ML-backed backends, groq-python abstracts away HTTP request plumbing and exposes a clean API, accelerating development and reducing boilerplate. -
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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. ... -
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DeepSeek Prover V2
Advancing Formal Mathematical Reasoning via Reinforcement Learning
...The repository describes how they use recursive proof decomposition by prompting DeepSeek-V3 to break complex theorems into subgoals, synthesize proof sketches, and then combine them to bootstrap training data. They then fine-tune via reinforcement learning with binary correct/incorrect feedback to integrate informal reasoning with formal proof behavior. The repo releases two model sizes (7B and 671B) and provides evaluation performance (e.g. pass rates on MiniF2F, results on ProverBench) as well as prompt / usage examples for proof generation in Lean 4. ... -
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GPU Hot
Real-time NVIDIA GPU dashboard
...The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics including temperature, memory usage, power consumption, clock speeds, fan speed, and active processes. It can scale from monitoring a single GPU workstation to large distributed environments with dozens or even hundreds of GPUs by running lightweight containers on each node and aggregating the data centrally. -
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Sail
A drop-in Apache Spark replacement written in Rust
...It also emphasizes cost efficiency, with benchmarks showing significant performance improvements and reduced infrastructure usage compared to traditional systems. -
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EFAK-AI
A AI-Driven, Distributed and high-performance monitoring system
EFAK (Eagle For Apache Kafka) is an open-source monitoring and management platform designed to provide comprehensive visibility and operational control over Apache Kafka clusters through a unified web interface. The project focuses on simplifying Kafka administration by offering real-time insights into cluster health, performance metrics, and consumer activity, allowing engineers to quickly diagnose issues and optimize system behavior. It integrates advanced features such as intelligent... -
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Fli
Google Flights MCP and Python Library
Fli is a powerful Python library and command-line tool that provides direct programmatic access to Google Flights data through reverse-engineered API interactions rather than traditional web scraping. This approach enables faster, more reliable, and more stable access to flight information, avoiding the fragility associated with HTML parsing and UI changes. The library supports a wide range of flight search capabilities, including filtering by airline, departure time, number of stops, cabin... -
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Deep Learning Is Nothing
Deep learning concepts in an approachable style
Deep-Learning-Is-Nothing presents deep learning concepts in an approachable, from-scratch style that demystifies the stack behind modern models. It typically begins with linear algebra, calculus, and optimization refreshers before moving to perceptrons, multilayer networks, and gradient-based training. Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. Once the fundamentals are... -
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Agents 2.0
An Open-source Framework for Data-centric Language Agents
...During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. A prompt-based loss function is then applied to evaluate the quality of the outcome, generating language-based gradients that guide improvements to the agent pipeline. -
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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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LLM Datasets
Curated list of datasets and tools for post-training
...Quality is a recurring theme: examples and utilities help filter low-value samples, enforce length limits, and split train/validation consistently so results are comparable. Licensing and provenance are surfaced to encourage compliant usage and to guide dataset selection in commercial settings. For practitioners, the repo is a practical “starting pantry” that accelerates experimentation and helps keep data wrangling from dominating the project timeline. -
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Lagent
A lightweight framework for building LLM-based agents
Lagent is a lightweight open-source framework designed to help developers build autonomous agents powered by large language models. The framework provides tools and abstractions that allow language models to interact with external tools, execute tasks, and perform multi-step reasoning processes. Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with... -
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Ultralytics
Ultralytics YOLO
Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. The framework...
