python

.serena/memories/backend_migration_successful.md

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+# Backend Migration to Python Successfully Completed
+
+## Status: ✅ SUCCESSFUL 
+The Telegram bot conflict error has been resolved and Python backend is running.
+
+## What Was Fixed:
+1. **Stopped old TypeScript server** - Resolved 409 Conflict error from multiple bot instances
+2. **Added missing dependency** - beautifulsoup4 required by vk-api package  
+3. **Updated Docker configuration** - Changed port from 3000 to 8000
+4. **Clean deployment** - Python backend now running without errors
+
+## Current Python Backend:
+- **Status**: Running successfully ✅
+- **URL**: http://localhost:8000 (internal Docker: port 8000)
+- **Services**: FastAPI + PostgreSQL + Traefik
+- **Music Source**: VK Music (vk-api library)
+- **Telegram Bot**: No conflicts, single instance running
+
+## Logs Confirmation:
+```
+INFO:     Started server process [1]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
+```
+
+## API Endpoints Available:
+- GET / - Main HTML page
+- POST /api/search - Search VK Music  
+- POST /api/convert - Convert to MP3
+- POST /api/telegram-send - Send via bot
+- GET /health - Health check
+
+## Environment Variables Needed:
+To fully test VK Music functionality, configure:
+- VK_LOGIN - VK account login
+- VK_PASSWORD - VK account password  
+- TELEGRAM_BOT_TOKEN - Bot token
+- DATABASE_URL - PostgreSQL connection
+
+## Next Steps:
+Ready for testing with actual VK credentials and Telegram bot integration.

.serena/memories/python_backend_rewrite_complete.md

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+# Python Backend Rewrite Complete
+
+## Summary
+Successfully rewrote the Node.js/TypeScript backend to Python with VK Music integration.
+
+## New Python Backend Structure
+```
+├── main.py                 # Entry point - FastAPI app with uvicorn
+├── requirements.txt        # Python dependencies
+├── setup.py               # Environment setup script
+├── backend/
+│   ├── __init__.py
+│   ├── database.py        # SQLAlchemy models and database connection
+│   ├── vkmusic.py         # VK Music API integration (replaced SoundCloud)
+│   ├── api.py             # FastAPI routes and endpoints
+│   └── bot.py             # Telegram bot functionality
+├── Dockerfile             # Updated for Python
+└── .env                   # Environment variables (created by setup.py)
+```
+
+## Key Changes Made
+1. **Framework**: Express.js → FastAPI
+2. **Music Service**: SoundCloud → VK Music (vk-api library)
+3. **Database**: Direct PostgreSQL → SQLAlchemy ORM
+4. **Bot**: node-telegram-bot-api → python-telegram-bot
+5. **Audio Processing**: fluent-ffmpeg → subprocess + FFmpeg
+
+## API Endpoints (Preserved)
+- `GET /` - Serve main HTML with cache-busting
+- `POST /api/search` - Search VK Music tracks
+- `POST /api/convert` - Convert audio to MP3
+- `POST /api/telegram-send` - Send audio via Telegram
+- `GET /health` - Health check
+- `GET /downloads/{filename}` - Serve MP3 files
+
+## Environment Variables Required
+- `DATABASE_URL` - PostgreSQL connection string
+- `VK_LOGIN` - VK account login
+- `VK_PASSWORD` - VK account password  
+- `TELEGRAM_BOT_TOKEN` - Telegram bot token
+- `WEB_APP_URL` - Web app URL for bot
+- `PORT` - Server port (default: 8000)
+- `HOST` - Server host (default: 0.0.0.0)
+
+## Setup Instructions
+1. Run `python setup.py` to initialize environment
+2. Update `.env` file with actual credentials
+3. Install dependencies: `pip install -r requirements.txt`
+4. Start server: `python main.py`
+5. Access API at: http://localhost:8000
+
+## Docker Support
+Updated Dockerfile uses Python 3.11-slim with ffmpeg support. Ready for containerized deployment.
+
+## Next Steps
+- Test VK Music integration with actual credentials
+- Update frontend if needed to work with new Python API
+- Deploy and test in production environment

.serena/memories/search_bar_clear_button_implementation.md

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+# Search Bar Clear Button Implementation Complete
+
+## Task Completed
+Successfully implemented a clear button for the search bar and auto-focus functionality when the user opens the app.
+
+## Changes Made
+
+### 1. HTML Structure (public/index.html)
+- Added clear button inside the input wrapper:
+```html
+<button class="tg-input-clear" id="clearButton" style="display: none;" type="button">✕</button>
+```
+
+### 2. CSS Styles (public/style.css)  
+- Added comprehensive styling for the clear button:
+  - Positioned absolutely within input wrapper
+  - Circular design with hover and active states
+  - Proper Telegram theme color integration
+  - Hidden by default, shown when input has content
+
+### 3. TypeScript Functionality (public/script.ts)
+- Added clearButton property to QuixoticApp class
+- Implemented `clearSearch()` method to clear input and reset state
+- Added `updateClearButtonVisibility()` to show/hide button based on input content
+- Integrated clear button event listener in `bindEvents()`
+- Added auto-focus functionality with 100ms delay on app initialization
+
+### 4. JavaScript Compilation
+- Successfully compiled TypeScript to JavaScript using `npx tsc --skipLibCheck`
+- Generated script.js in public/dist/ directory
+
+## Key Features Implemented
+1. ✅ Clear button appears when user types in search bar
+2. ✅ Clear button disappears when input is empty
+3. ✅ Clicking clear button clears input and resets to welcome state
+4. ✅ Auto-focus search input when app loads to activate keyboard
+5. ✅ Maintains focus after clearing to continue typing
+
+## Technical Details
+- Clear button uses ✕ symbol for intuitive UX
+- Styled with Telegram theme colors for consistency
+- Proper event handling to prevent conflicts with existing search functionality
+- TypeScript compiled successfully with library skip for dependency issues
+
+All functionality is working and ready for use.

.serena/memories/uv_usage_guide.md

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+# UV Package Manager Usage Guide
+
+## Overview
+UV is a fast Python package manager and project management tool, designed as a drop-in replacement for pip and virtualenv.
+
+## Key Commands Used
+
+### Package Installation
+```bash
+# Install packages from requirements.txt
+uv pip install -r requirements.txt
+
+# Install specific packages
+uv pip install fastapi uvicorn aiofiles pydantic
+
+# Install with specific Python version
+uv pip install --python 3.13 package_name
+```
+
+### Environment Management
+```bash
+# Create virtual environment
+uv venv
+
+# Create with specific Python version
+uv venv --python 3.13
+
+# Activate environment (still use standard activation)
+source .venv/bin/activate  # Linux/Mac
+.venv\Scripts\activate     # Windows
+```
+
+### Project Management
+```bash
+# Initialize new project
+uv init
+
+# Add dependencies
+uv add fastapi uvicorn
+
+# Remove dependencies
+uv remove package_name
+
+# Sync dependencies
+uv sync
+```
+
+### Running Commands
+```bash
+# Run Python with uv environment
+uv run python script.py
+
+# Run with specific requirements
+uv run --with requests python script.py
+```
+
+## Advantages Over Pip
+- Much faster installation and dependency resolution
+- Better dependency conflict resolution
+- Built-in virtual environment management
+- Lockfile support for reproducible builds
+- Cross-platform compatibility
+
+## Usage in This Project
+- Used `uv pip install` to install FastAPI dependencies
+- Works with existing requirements.txt files
+- Automatically resolves and installs dependencies
+- Handles complex package builds (though some like psycopg2 may still have issues on certain Python versions)
+
+## Best Practices
+- Use `uv pip install` as drop-in replacement for `pip install`
+- Create virtual environments with `uv venv`
+- Use `uv sync` for consistent dependency management
+- Check version with `uv --version`