The article discusses the OVON agentic framework for mitigating hallucinations in Large Language Models (LLMs). It explains the structured, collaborative pipeline involving front-end and reviewer agents, the use of 'Conversation Envelopes' and 'Whispers' for efficient data exchange, and novel KPIs for measuring success. The article also addresses future directions and the importance of trust in AI systems.
Minimalist LLM Framework in 100 Lines. Enable LLMs to Program Themselves.
Encore is an open-source backend framework and cloud platform for building distributed systems. It automates infrastructure, offers end-to-end type-safety, and provides built-in observability.
Automated Infrastructure: Local & Cloud (AWS/GCP) provisioning Infrastructure semantics within application code No separate config tools needed
Type-Safe Microservices: Define & call APIs like normal functions Full type-safety & IDE auto-complete Automatic protocol communication boilerplate
Faster Development: Hot reload & automatic local infrastructure setup Simplified, speedier development process
Observability: API explorer, distributed tracing, architecture diagrams Service catalog with automatic API documentation
Cloud Platform: Seamless workflow with CI/CD, testing, & infrastructure provisioning Preview environments for every PR
Security & Scalability: Battle-tested AWS/GCP services Best practices for security & scalability Metrics & logging for critical aspects
The article discusses the limitations of Large Language Models (LLMs) in planning and self-verification tasks, and proposes an LLM-Modulo framework to leverage their strengths in a more effective manner. The framework combines LLMs with external model-based verifiers to generate, evaluate, and improve plans, ensuring their correctness and efficiency.
"Simply put, we take the stance that LLMs are amazing giant external non-veridical memories that can serve as powerful cognitive orthotics for human or machine agents, if rightly used."
Mesop is a Python-based UI framework that allows you to rapidly build web apps like demos and internal apps. Easy to get started, fast iteration, and flexible & composable.
open-source LLM tools offer transparency, flexibility, cost-effectiveness, and heightened data security.
