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llm_council/.cursor/rules.md
Irina Levit 3546c04348
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feat: Major UI/UX improvements and production readiness 
## Features Added

### Document Reference System
- Implemented numbered document references (@1, @2, etc.) with autocomplete dropdown
- Added fuzzy filename matching for @filename references
- Document filtering now prioritizes numeric refs > filename refs > all documents
- Autocomplete dropdown appears when typing @ with keyboard navigation (Up/Down, Enter/Tab, Escape)
- Document numbers displayed in UI for easy reference

### Conversation Management
- Added conversation rename functionality with inline editing
- Implemented conversation search (by title and content)
- Search box always visible, even when no conversations exist
- Export reports now replace @N references with actual filenames

### UI/UX Improvements
- Removed debug toggle button
- Improved text contrast in dark mode (better visibility)
- Made input textarea expand to full available width
- Fixed file text color for better readability
- Enhanced document display with numbered badges

### Configuration & Timeouts
- Made HTTP client timeouts configurable (connect, write, pool)
- Added .env.example with all configuration options
- Updated timeout documentation

### Developer Experience
- Added `make test-setup` target for automated test conversation creation
- Test setup script supports TEST_MESSAGE and TEST_DOCS env vars
- Improved Makefile with dev and test-setup targets

### Documentation
- Updated ARCHITECTURE.md with all new features
- Created comprehensive deployment documentation
- Added GPU VM setup guides
- Removed unnecessary markdown files (CLAUDE.md, CONTRIBUTING.md, header.jpg)
- Organized documentation in docs/ directory

### GPU VM / Ollama (Stability + GPU Offload)
- Updated GPU VM docs to reflect the working systemd environment for remote Ollama
- Standardized remote Ollama port to 11434 (and added /v1/models verification)
- Documented required env for GPU offload on this VM:
  - `OLLAMA_MODELS=/mnt/data/ollama`, `HOME=/mnt/data/ollama/home`
  - `OLLAMA_LLM_LIBRARY=cuda_v12` (not `cuda`)
  - `LD_LIBRARY_PATH=/usr/local/lib/ollama:/usr/local/lib/ollama/cuda_v12`

## Technical Changes

### Backend
- Enhanced `docs_context.py` with reference parsing (numeric and filename)
- Added `update_conversation_title` to storage.py
- New endpoints: PATCH /api/conversations/{id}/title, GET /api/conversations/search
- Improved report generation with filename substitution

### Frontend
- Removed debugMode state and related code
- Added autocomplete dropdown component
- Implemented search functionality in Sidebar
- Enhanced ChatInterface with autocomplete and improved textarea sizing
- Updated CSS for better contrast and responsive design

## Files Changed
- Backend: config.py, council.py, docs_context.py, main.py, storage.py
- Frontend: App.jsx, ChatInterface.jsx, Sidebar.jsx, and related CSS files
- Documentation: README.md, ARCHITECTURE.md, new docs/ directory
- Configuration: .env.example, Makefile
- Scripts: scripts/test_setup.py

## Breaking Changes
None - all changes are backward compatible

## Testing
- All existing tests pass
- New test-setup script validates conversation creation workflow
- Manual testing of autocomplete, search, and rename features
2025-12-28 18:15:02 -05:00

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Cursor Rules (Project Standards)

Non-negotiables

  • Never commit secrets. Never paste credentials into code, docs, or logs.
  • Prefer env vars over hardcoding (see .env.example).
  • Add/extend tests for any behavior change.

Backend standards

  • Use the provider abstraction (backend/llm_client.py) for all model calls.
  • Keep request/response payloads explicit and logged safely (no secrets).
  • Treat uploaded documents as untrusted input:
    • enforce .md extension
    • enforce size limits
    • never execute content

Frontend standards

  • Keep API calls in frontend/src/api.js.
  • Keep app state + orchestration in frontend/src/App.jsx.
  • Components should be readable and small.

Testing

  • Backend: make test-backend
  • Frontend: make test-frontend

Architecture

  • The app runs locally; the GPU VM runs an OpenAI-compatible inference server.
  • The app calls the VM over HTTP (or via SSH tunnel) and does not "use the GPU" directly.