This roadmap outlines the implementation trajectory for the expansion plan, grouped into four major quarters of development.
Focus: Establishing the visual identity, developer experience, and structural foundations.
- Goals:
- Implement the Cyberpunk Design System (Tailwind, Next.js, Framer Motion).
- Build out the Distribution Hub (PyPI, Docker, Devcontainers, Conda configurations).
- Establish the MDX Documentation Portal (Search, Pagination, Versioning).
- Create the interactive "Terminal Loader" UX that masks complex latency.
- Expected Outcome: A highly polished, static-rendered frontend that looks professional, serves documentation flawlessly, and establishes the project's visual brand.
Focus: Building the core intelligence and routing systems for environment resolution.
- Goals:
- Initialize the robust FastAPI backend with PostgreSQL and strict Pydantic models.
- Construct the Compatibility Resolver (parsing CUDA, ROCm, and Python JSON matrices).
- Implement secure Jinja2 asynchronous script generation with negative-lookahead regex safety.
- Connect AI Providers (OpenRouter, OpenAI, Anthropic, Ollama) with SSE real-time streaming UI.
- Expected Outcome: The core "brain" of EnvForge is operational. The system can ingest hardware telemetry, calculate the delta against known working matrices, output safe bash scripts, and stream AI troubleshooting context.
Focus: Empowering the local developer environment and hardening the perimeter.
- Goals:
- Build the Python CLI Agent (Detectors for OS, CPU, NVIDIA, AMD, Python envs).
- Enable CLI Offline Capabilities (SQLite local cache, JSON export, self-updates).
- Implement the Webhook & Plugin Architecture (Event dispatching, HMAC signatures, dynamic loaders).
- Hardening Security (Redis rate limiters, JWT generation, PII sanitization).
- Expected Outcome: Developers can extract deterministic hardware data reliably, even on offline or air-gapped machines. Enterprise users can subscribe to system events via webhooks, and APIs are protected from abuse.
Focus: Preparing EnvForge for large-scale production deployments and team environments.
- Goals:
- Implement Deep Observability (Prometheus metrics, structlog JSON, Datadog/ELK hooks, Sentry).
- Automate the CI/CD Pipeline (GitHub Actions for TS/Pytest/Playwright, Dependabot, Release Drafter).
- Containerize and Orchestrate (Multi-stage Dockerfiles, Helm Charts, K8s manifests, HPA).
- Expected Outcome: A production-grade, highly available service that scales under load, catches regressions instantly via automated pipelines, and provides deep insights into application health.