Cx330xu Prompt System
Centralized 50+ prompt templates with team collaboration and versioning — serves as prompt infrastructure for Agent / RAG projects
Situation
Prompts in LLM applications were scattered across multiple repositories with no versioning or reuse mechanism. Each new project required manual copy-paste of old prompts, and team collaboration was friction-heavy. We needed a centralized, deployable prompt management solution.
Task
Design and build a lightweight prompt management infrastructure with:
- CRUD operations and version tracking for prompt templates
- Tag/project-based categorization and search
- RESTful API for integration with Agent / RAG systems
- Local (Linux) and Docker deployment support
Action
- Backend: FastAPI (Python) with Pydantic validation, SQLite for lightweight storage
- Frontend: Next.js + TypeScript with App Router for the management UI
- Deploy: Dockerfile + docker-compose.yml with setup docs (
DEPLOY.md) - Key decisions:
- Decoupled API/UI → API can be consumed independently by other services
- Docker-first → zero Python/Node setup for team members
- Template variables →
{{context}}placeholders with template inheritance
Result
- ✅ 50+ prompt templates under centralized management with version history and one-click rollback
- ✅ API response <50ms (local), Docker container startup <10s
- ✅ Serving as prompt infrastructure for 3 Agent projects
- 🔜 Roadmap: LLM evaluation framework integration for prompt A/B testing
Technical Documentation
Technical Challenges Why this project? What unique problem does it solve?
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Solution Comparison & Decisions Trade-offs and rationale behind key technical choices
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Architecture Design System architecture, data flow, and core design patterns
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This structured documentation directly addresses technical interviewer evaluation dimensions.
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