PACE: Multi-Agent AI Microservice (Actor-Critic)

PACE (Pipelined Actor-Critic Ensemble) is a production-grade AI microservice engineered from the ground up to solve two massive problems in generative AI: expensive cloud hardware costs and unreliable model hallucinations.

By pairing specialized "Actor" (generator) models with "Critic" (validator) models, PACE creates a self-correcting inference loop. It filters out bad code, fake facts, and broken citations before the user ever sees them.
 

Core Masteries Included

• Coding Mastery: Generates code, runs it in an isolated Docker sandbox, and evaluates syntax/logic before returning the final snippet.
• Literacy Mastery: Summarizes local texts with built-in Natural Language Inference (NLI) to prevent factual hallucination.
• Research Mastery: Synthesizes live web/academic sources into literature reviews while validating citation existence and accuracy against the source abstract.

Key Technical Features

• State Machine: Pre-trained model orchestrator dynamically loads and unloads 8B and 4B parameter models into GPU memory, ensuring you never hit a CUDA Out of Memory (OOM) error and can be change according to specific requirments
• Dual Execution Tiers: Features a latency-optimized "Fast Mode" (single-pass) and an accuracy-optimized "Pro Mode" (Actor-Critic loop up to 5 iterations).
• Ironclad Security: Includes JWT authentication, API rate limiting, and mandatory Docker sandboxing with seccomp profiles for arbitrary code execution.
• Premium Frontend UI: Comes with a fully responsive React + Vite web client featuring a sleek, cyberpunk-inspired dark mode aesthetic and real-time generation trackers.

Tech Stack

• Backend: Python 3.11+, FastAPI, PyTorch (CUDA-Optimized).
• Frontend: React 18, Vite.
• Infrastructure: Docker, Cloudflare Tunnels (Hybrid Local-Cloud setup ready).
• Bonus Blueprint: A cross-platform Flutter app is currently in active development, meaning this ecosystem is actively growing.

What You Get

• Complete backend API and frontend UI source code.
• Pre-configured Dockerfiles and environment scripts.
• Comprehensive README, system architecture diagrams, and hardware budget analysis.
• Step-by-step deployment instructions for local networks, Render, and Hugging Face Spaces.