Comio

AI-powered platform to create, edit, deploy, and monitor applications.

Comio covers the full application lifecycle through a conversational AI interface:

• Create — Describe a project in plain English and Comio builds it from scratch
• Edit — Chat with an AI assistant that can read, edit, and refactor your code in a sandboxed environment
• Deploy — One-click deploy to production with automatic container builds
• Monitor — Detects anomalies via ML, diagnoses root causes with LLMs
• Fix — Proposes code fixes as PRs with human-in-the-loop approval

Architecture

Frontend (Next.js) → Backend (FastAPI) → AI Engine (LLM Adapters)
                                       → Docker Sandboxes (per-project)
                                       → Observability (Prometheus + Loki)
                                       → GCP (GKE + Terraform)

Tech Stack

Layer	Technology
Frontend	Next.js 16, TypeScript, Tailwind CSS, shadcn/ui
Backend	Python 3.12, FastAPI, SQLAlchemy, Alembic
Database	PostgreSQL 16 (pgvector), Redis 7
AI Engine	OpenAI, Anthropic, Ollama (provider-agnostic adapter)
Sandboxes	Docker containers with AI chat agent (tool-use)
Anomaly Detection	scikit-learn, statsmodels, Prophet
Observability	OpenTelemetry, Prometheus, Loki, Grafana
Infrastructure	GCP (GKE), Terraform, Kubernetes
CI/CD	GitHub Actions

Project Structure

comio/
├── apps/
│   ├── api/              # FastAPI backend
│   ├── web/              # Next.js frontend
│   └── demo-app/         # Demo microservice for testing
├── packages/
│   ├── ai-engine/        # LLM adapters, RCA, fix generation, chat agent
│   ├── anomaly-detector/ # ML-based anomaly detection
│   ├── observability/    # OTel configs, dashboards
│   └── shared/           # Shared types and utilities
├── infra/
│   ├── terraform/        # GCP infrastructure as code
│   ├── k8s/              # Kubernetes manifests
│   └── docker/           # Dockerfiles
├── docker-compose.yml    # Local dev services (Postgres, Redis)
└── .github/workflows/    # CI/CD pipelines

Quick Start

Prerequisites

• Python 3.12+
• Node.js 20+
• Docker Desktop (for Postgres, Redis, and sandboxes)
• Git

1. Clone and configure

git clone https://github.com/your-username/comio.git
cd comio
cp .env.example .env
# Edit .env and add your API keys (OpenAI/Anthropic, GitHub)

2. Start infrastructure services

docker compose up -d

This starts PostgreSQL (port 5432) and Redis (port 6379).

3. Set up the backend

lsof -ti tcp:8000 | xargs kill -9 2>/dev/null || true; cd /Users/abhinavkumar/Projects/Comio && source apps/api/.venv/bin/activate && uvicorn apps.api.main:app --reload --host 0.0.0.0 --port 8000

API will be available at http://localhost:8000 Interactive docs at http://localhost:8000/docs

4. Set up the frontend

cd apps/web
npm install
npm run dev

Frontend will be available at http://localhost:3000

5. Using the project sandbox and chat

• Visit /projects in the frontend to see your projects.
• Use Import Repo to call POST /projects/import and provision a sandbox for an existing GitHub repository.
• Use Create Project to call POST /projects/create and provision a blank sandbox for a new AI-created project.
• From a project row or detail page, click Open Sandbox to go to /projects/{id}/sandbox, where you can:
  • Start the per-project Docker sandbox.
  • Browse files via the left-hand file tree (backed by /projects/{id}/sandbox/files).
  • Chat with the AI assistant; messages are sent via /projects/{id}/sandbox/chat/sessions/{session_id}/messages and rendered from the returned event stream.

Development

Running linters

# Python
ruff check apps/api packages/
ruff format apps/api packages/

# Frontend
cd apps/web && npm run lint

Running tests

# Python
pytest apps/api packages/

# Frontend
cd apps/web && npm test

License

MIT