Search Results for "routing"
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66 projects for "routing" with 2 filters applied:
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Switchyard
Switchyard lets LLM applications route traffic across models
Switchyard is a Rust proxy and library for routing traffic between LLM clients and model backends. It translates among OpenAI Chat, OpenAI Responses, and Anthropic Messages formats so agents can keep using their native APIs. Requests can be distributed across vLLM, NVIDIA NIM, Ollama, OpenRouter, and other compatible endpoints. Routing strategies include random splits, LLM classification, signal-driven stage routing, escalation, and custom algorithms. -
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Claude Code Router
Use Claude Code as the foundation for coding infrastructure
Claude Code Router is a tool for routing Claude Code requests to different model providers and customizing how those requests are handled. It acts as a configurable layer between Claude Code and multiple LLM backends, allowing users to control routing, provider selection, transformations, and workflow behavior. The project is useful for developers who want to keep the Claude Code interface while experimenting with different models, cost profiles, and specialized request handling. ... -
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Envoy AI Gateway
Manages Unified Access to Generative AI Services
...The project extends Envoy Gateway to support AI-specific workloads, enabling organizations to route, secure, and scale requests to large language models and other generative AI services. In a typical deployment, the architecture uses a two-tier gateway model where an outer gateway handles authentication, routing, and global rate limiting while a second gateway manages traffic to self-hosted model serving clusters. This design allows organizations to centralize control over AI service access while maintaining flexibility in how backend model infrastructure is deployed. The gateway provides policy enforcement, observability, and routing capabilities that are specifically designed for AI inference workloads, including intelligent endpoint selection and request optimization. -
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ClawRouter
Smart LLM router
ClawRouter is a flexible networking and routing framework designed to support AI-oriented distributed systems and agent ecosystems by managing how messages, requests, and responses are routed between components. It provides a programmable router abstraction that can handle complex traffic patterns, enabling dynamic message forwarding, load balancing, and custom routing logic based on content, context, or policy rules. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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Sprix SAGE Router
State-aware SELF/COLLABORATE/HANDOFF routing for A2A agent networks
Sprix SAGE Router is an open-source routing layer for coordinating agents in Agent2Agent networks. It decides whether an active agent should continue alone, recruit collaborators, or hand a task to another specialist. Routing decisions account for current progress, capability coverage, context-transfer costs, permissions, budgets, and deadlines. The system assigns remaining requirements to agents through task dependency graphs and estimates execution schedules. -
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litelm
litellm without the bloat
litelm is a lightweight Python library that preserves the core routing and message-translation behavior of LiteLLM without its larger proxy and infrastructure layers. It supports provider/model routing, streaming, embeddings, text completions, tool calling, and the OpenAI Responses API. The package mirrors LiteLLM function names and response shapes so existing code can often switch with only an import change. -
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MSA: Memory Sparse Attention
Trainable latent-memory framework for 100M-token contexts
MSA, or Memory Sparse Attention, is a research framework for scaling language-model memory to extremely long contexts. It replaces full attention over all tokens with sparse selection of compressed latent memory states. Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. Its Memory Parallel engine distributes scoring and transfers only selected memory back to the accelerator. Memory Interleave alternates retrieval, context expansion, and generation to improve multi-hop reasoning across distant segments. ... -
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Weave Router
Model router for agentic systems
...It supports streaming, tool use, vision, and multiple API formats. Provider credentials remain local in self-hosted deployments and can be encrypted at rest. Built-in observability exposes routing decisions, costs, and OTLP traces through a dashboard or external monitoring tools. It integrates with Claude Code, Codex, OpenCode, Pi, Cursor, and custom applications. -
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Plano
Delivery infrastructure for agentic apps
Plano is an AI-native proxy and data plane designed to simplify the infrastructure required to deploy and operate agentic applications in production environments. It removes repetitive plumbing work from application code by centralizing capabilities such as agent routing, orchestration, guardrails, observability, and model selection. Built on modern proxy technology and compatible with any language or AI framework, Plano enables developers to focus on core agent logic instead of infrastructure complexity. The system provides intelligent LLM routing APIs that support model agility, along with filter chains for safety, moderation, and memory hooks. ... -
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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OpenMythos
A theoretical reconstruction of the Claude Mythos architecture
...It divides computation into three main stages, including a pre-processing phase, a looped recurrent reasoning block, and a final output refinement stage, creating a structured pipeline for inference. The architecture incorporates advanced techniques such as mixture-of-experts routing, adaptive computation time, and multiple attention mechanisms to dynamically allocate compute where needed. It is highly configurable through a centralized configuration system, allowing experimentation with different architectural parameters such as loop depth, attention type. -
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gemini-web2api
Convert Google Gemini web into OpenAI-compatible API
...The project can run as a simple local server and uses a mostly single-file design with an optional dependency for streaming. It supports model aliases for Flash, Thinking, Pro-style routing, Auto, and Lite variants. The tool also includes optional API keys, function calling, SSE streaming, web search access, Docker deployment, and client examples for OpenAI SDK-style usage. It is useful for developers who want local experimentation with OpenAI-compatible tooling while routing requests through Gemini web behavior. -
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kgateway
The Cloud-Native API Gateway and AI Gateway
...It implements the Kubernetes Gateway API and can operate as both a lightweight in-cluster microgateway and a centralized gateway capable of handling billions of API calls with high performance and low latency. By integrating with Envoy and advanced data planes, it handles modern ingress concerns such as traffic routing, authentication, authorization, rate limiting, and observability for traditional HTTP/gRPC services and AI workloads alike. Beyond standard API traffic, kgateway also supports gateway patterns tailored for large language model (LLM) consumption, inference routing, and Model Context Protocol (MCP) orchestration, enabling secure access to models, tools, and agent interactions. -
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Mastra
The TypeScript AI agent framework
...It integrates cleanly with React, Next.js, and Node-based backends, but can also run as a standalone server, giving teams flexibility in how they deploy their AI logic. At its core, Mastra provides abstractions for agents, workflows, tools, memory, retrieval, and model routing, so developers can focus on specifying behavior rather than wiring infrastructure from scratch. Model routing lets you connect to dozens of providers (OpenAI, Anthropic, Gemini, and others) through a single standardized interface, while agents orchestrate LLM calls and tools to solve open-ended tasks with internal reasoning loops. ... -
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Flash-MoE
Running a big model on a small laptop
Flash-MoE is a high-performance implementation of mixture-of-experts (MoE) architectures designed to optimize the efficiency and scalability of large AI models. It focuses on accelerating routing and computation by leveraging optimized kernels and memory management techniques, allowing models to dynamically select specialized sub-networks during inference. The project aims to reduce the computational cost typically associated with MoE systems while maintaining or improving performance. It likely includes support for GPU acceleration and parallel processing, enabling it to handle large-scale workloads effectively. ... -
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AxonHub
Use any SDK to call 100+ LLMs
...The system also provides infrastructure features such as request routing, failover mechanisms, load balancing, and cost management for AI applications. This architecture makes it easier to experiment with multiple models and manage production deployments that rely on several providers simultaneously. -
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AG KIT
Antigravity-first agent engineering kit with rules, skills
AG Kit is an open-source engineering toolkit designed primarily for Google Antigravity agent workspaces. It installs a structured .agents environment containing rules, skills, workflows, specialist agents, and persistent memory. The toolkit provides intelligent routing across 20 role definitions and includes repeatable commands for planning, debugging, testing, deploying, and orchestration. MCP configuration guidance helps agents connect to external tools while preserving reviewable workspace settings. A native pre-tool safety gate blocks high-confidence destructive commands without interfering with normal project cleanup. ... -
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One API
The LLM API management & distribution system
...It includes features such as authentication, rate limiting, and usage tracking, making it suitable for production environments. One API also provides a web-based dashboard for managing keys, monitoring usage, and configuring routing rules. Its architecture is designed for scalability, allowing teams to deploy it as a centralized layer in their AI infrastructure. By abstracting the complexity of working with multiple APIs, it simplifies development and reduces vendor lock-in. -
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TinyClaw
The original Tiny Claw as your personal autonomous AI companion
...Its philosophy centers on creating a persistent AI companion that behaves more like a helpful digital partner than a purely configurable assistant. TinyClaw incorporates self-improving memory and smart routing mechanisms intended to reduce large language model costs by tiering queries intelligently. The framework is designed to be self-configuring and easy to set up compared to more complex agent stacks, with a Bun-native runtime and built-in web interface. Overall, TinyClaw aims to democratize autonomous AI agents by delivering a lightweight, extensible, and personality-driven companion platform that evolves with the user over time. -
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Laya-MLX
Native MLX runtime for Laya typed decision models
...Its implementation moves the encoder, decision transformer, scoring head, and action head into MLX. The project reports short-decision latency in the single-digit to low-teens millisecond range on an M3 Max, depending on the checkpoint. It also includes routing utilities, demos, validation tests, benchmarks, and a Python API. -
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ZGI
Open-source platform for building AI applications
ZGI is a source-available platform for building, publishing, and operating AI agents and executable workflows. It combines agent configuration, visual orchestration, retrieval, structured data, model routing, and reusable skills in one workspace. Workflows can include branches, loops, approvals, HTTP requests, database operations, code execution, and scheduled tasks. Agents can connect to approved knowledge, files, databases, and tools. Finished applications can be exposed through a WebApp, internal app center, API, or internal calls. ... -
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MCP Router
A Unified MCP Server Management App (MCP Manager)
...This enables AI applications to access multiple tools and knowledge sources through a unified interface rather than connecting to each service individually. The project provides infrastructure for routing requests between clients and MCP servers, enabling scalable multi-tool agent systems. Developers building AI agents can use the platform to manage tool endpoints, control service availability, and simplify agent integration workflows. -
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Unla
Gateway service that instantly transforms existing MCP Servers
...Its goal is to let teams “wire up” tools they already run—internal REST endpoints, third-party APIs, or local MCP servers—and present a single, reliable MCP interface to clients like Claude Desktop, Cursor, and IDEs. The gateway focuses on operational concerns you’d expect in production: multi-instance availability, health checking, and declarative routing that maps upstreams to MCP tools and resources. A quick-start and CLI make it easy to stand up an API server, while the package structure exposes helpers for people who want to embed or extend the gateway. Because it is itself MCP-speaking, Unla can sit in front of mixed fleets and normalize transports and schemas for clients. Documentation and pkg.go.dev pages reinforce the positioning as a stable, Go-native building block for MCP deployments. -
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VibeSDK
Open source full-stack AI vibe coding platform & web app generator
...VibeSDK gives you the exact methodology, tools, and confidence to turn your ideas into revenue-generating products, faster than you thought possible. Live preview of generated apps in isolated sandbox containers. Support for React + TypeScript + Tailwind generation, backend routing, and modern web stack scaffolding. -
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LazyCodex
The one and only agent harness for complex codebases
LazyCodex is an agent harness for using Codex on complex software projects. It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced. LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. ... -
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MoBA
MoBA: Mixture of Block Attention for Long-Context LLMs
...Instead of forcing each token to attend to every other token in the sequence, MoBA divides the context into blocks and dynamically routes queries to only the most relevant segments of information. This routing strategy reduces the computational cost associated with traditional attention while preserving performance on reasoning and long-context tasks. The approach allows language models to scale to significantly longer input contexts without the quadratic computational cost normally associated with transformer attention mechanisms.
