SShortSingh.
Back to feed

Developer Builds Open-Source AI Proxy Gateway With Sub-15ms Failover for LLM Outages

0
·1 views

A developer has built Selixes, an open-source edge proxy gateway designed to prevent AI agent crashes caused by LLM provider outages, rate limits, and latency spikes. The tool sits between an application and providers like OpenAI or Anthropic, automatically switching to a backup model in under 15 milliseconds if the primary connection fails mid-stream. To tackle failover latency, the system preemptively opens a background TCP connection to a fallback provider before failure occurs, rather than reacting after the fact. Selixes also uses atomic Redis operations to enforce session spending caps, acting as a circuit breaker against runaway API costs from retry loops. The gateway exposes an OpenAI-compatible endpoint, allowing teams to adopt it by simply changing a base URL without rewriting existing agent logic.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer Builds Concurrency-Safe Movie Seat Reservation System Using FastAPI and Redis

A developer built a movie reservation backend to explore how production systems prevent double-bookings when multiple users attempt to reserve the same seat simultaneously. The project uses FastAPI, PostgreSQL, Redis, and SQLAlchemy, organized in a layered architecture separating controllers, business logic, and database operations. Redis temporary locks prevent simultaneous seat selection, while Lua scripts ensure that multi-seat reservations are acquired atomically — either all seats are locked or none are. Lock ownership verification adds another safeguard, ensuring expired locks cannot be exploited by stale reservation requests. PostgreSQL unique constraints serve as a final failsafe, making duplicate seat bookings impossible even if all application-level protections fail.

0
ProgrammingDEV Community ·

Cognitive Defrag: Browser-Based Tool Scores Clarity of Task Descriptions Locally

A developer has released Cognitive Defrag, a free, browser-based tool designed to evaluate the structural clarity of written tasks, job descriptions, and project requirements before they are acted upon or fed into AI systems. The tool runs entirely locally, sending no user data to external servers, and produces a "chaos density index" by scanning text against a three-dimensional logic framework covering intent, resources, and available tools. It is aimed at freelancers, managers, and engineers who want an objective check on whether a brief or instruction is clearly formulated. No installation is required, and a live demo is available on GitHub Pages. The project is intentionally built without an AI backend, as the author argues that restoring logical structure in text requires human judgment rather than automated processing.

0
ProgrammingDEV Community ·

Developer Guide: How to Integrate Open-Weight LLM APIs Into Your Stack

Open-weight large language models (LLMs) are gaining traction as alternatives to proprietary AI systems, offering developers access to model weights, architectures, and training methodologies. Unlike closed-source models, open-weight LLMs enable transparency, domain-specific fine-tuning, and reduced costs, while eliminating dependence on a single vendor. Developers can run these models locally using tools like Ollama or vLLM, but hosted API providers offer a faster route to production without heavy GPU or DevOps requirements. A standard API integration workflow involves authentication via Bearer tokens, endpoint selection, payload construction with parameters like temperature and max_tokens, and structured JSON response handling. The guide demonstrates this process using the NovaStack API as a practical example, emphasizing secure credential management through environment variables rather than hardcoded keys.

0
ProgrammingDEV Community ·

Physical AI Hits Inflection Point as NVIDIA Adds Reasoning and Robots Drop to $25K

NVIDIA this week unveiled GR00T N1.6, a robot AI architecture that plans a full sequence of movements before acting, replacing the older reactive sensor-to-action model. Alongside it, NVIDIA released open-source Isaac GR00T models and the RoboLab benchmark, positioning itself as foundational infrastructure for robot manufacturers rather than a robot maker itself. Unitree has cut its humanoid robot price from $85,000 in 2023 to $25,000 in 2026, with a production target of 20,000 units this year, opening the market to mid-size buyers who could not justify earlier price points. US-based 1X Technologies also began serial production of its NEO humanoid in Hayward, California, marking the first domestic shift from R&D to volume manufacturing for a humanoid platform. Industry data from Capgemini shows 79 percent of organizations are now actively engaging with physical AI, while venture capital funding in the sector reached a record $37 billion through May 2026.