Ireneusz Bachanowicz
c5202ca4c5
- Updated .cursorrules with clearer project organization - Removed setup-project.sh script and consolidated project documentation - Simplified and restructured project rules, overview, and resources - Added comprehensive task list with detailed development roadmap - Cleaned up and standardized markdown files in .cursor/rules directory
30 lines
1.6 KiB
Markdown
30 lines
1.6 KiB
Markdown
---
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description: Details the technology stack chosen for the CV Optimization Platform.
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globs:
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---
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# Technology Stack
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## Frontend
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- **Framework:** React.js (using Next.js for server-side rendering and routing)
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- **Styling:** Tailwind CSS
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- **State Management:** (Initially simple React state, consider Context API or Zustand if complexity grows)
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- **UI Library:** (Consider a component library like Material UI or Ant Design if needed for more complex UI elements later)
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## Backend
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- **Language:** Node.js (with Express.js framework) or Python (with Flask/FastAPI - *Decision needed based on your preference and libraries for LLM interaction*)
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- **API Framework:** Express.js (Node.js) or Flask/FastAPI (Python)
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- **Document Processing Libraries:**
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- Python: `PyPDF2`, `python-docx` (if using Python backend)
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- Node.js: `pdf-parse`, `docx-parser` (if using Node.js backend)
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## Database
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- **Initial Stage:** File-based storage (for simplicity in MVP) - *Consider moving to MongoDB or PostgreSQL for user accounts and scalable data storage later.*
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- **Future Scalable Database:** MongoDB (NoSQL) or PostgreSQL (Relational) - *To be decided based on data structure and scalability needs.*
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## LLM Integration
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- **Primary LLM Provider:** OpenAI API (GPT models) - for initial development and ease of use.
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- **Potential Alternative:** Hugging Face Transformers - for exploring open-source models and potential cost optimization in the future.
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## Deployment
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- **Frontend Hosting:** Vercel (for Next.js applications)
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- **Backend Hosting:** Render or Heroku (or AWS/Google Cloud/Azure for more control and scalability) |