feat: migrate to PostgreSQL and enhance playlist curation

- Migrate database from SQLite to PostgreSQL (100.91.248.114:5433)
- Fix playlist curation to use actual top tracks instead of AI name matching
- Add /playlists/history endpoint for historical playlist viewing
- Add Playlist Archives section to frontend with expandable history
- Add playlist-modify-* scopes to Spotify OAuth for playlist creation
- Rewrite Genius client to use official API (fixes 403 scraping blocks)
- Ensure playlists are created on Spotify before curation attempts
- Add DATABASE.md documentation for PostgreSQL schema
- Add migrations for PlaylistConfig and composition storage

.github/workflows/docker-publish.yml

@@ -6,11 +6,18 @@ on:
   pull_request:
     branches: [ "main" ]
 
+env:
+  REGISTRY: ghcr.io
+
 jobs:
-  build:
+  build-backend:
     runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     
     - name: Set up QEMU
       uses: docker/setup-qemu-action@v3
@@ -18,9 +25,75 @@ jobs:
     - name: Set up Docker Buildx
       uses: docker/setup-buildx-action@v3
       
-    - name: Build and push
+    - name: Log in to the Container registry
+      uses: docker/login-action@v3
+      with:
+        registry: ${{ env.REGISTRY }}
+        username: ${{ github.actor }}
+        password: ${{ secrets.GITHUB_TOKEN }}
+        
+    - name: Extract metadata (tags, labels) for Backend
+      id: meta-backend
+      uses: docker/metadata-action@v5
+      with:
+        images: ${{ env.REGISTRY }}/${{ github.repository_owner }}/musicanalyser
+        tags: |
+          type=ref,event=branch
+          type=ref,event=pr
+          type=sha
+          type=raw,value=latest,enable={{is_default_branch}}
+      
+    - name: Build and push Backend
       uses: docker/build-push-action@v5
       with:
         context: ./backend
-        push: false
-        tags: user/app:latest
+        push: true
+        tags: ${{ steps.meta-backend.outputs.tags }}
+        labels: ${{ steps.meta-backend.outputs.labels }}
+        platforms: linux/amd64,linux/arm64
+        cache-from: type=gha
+        cache-to: type=gha,mode=max
+
+  build-frontend:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+    - uses: actions/checkout@v4
+    
+    - name: Set up QEMU
+      uses: docker/setup-qemu-action@v3
+      
+    - name: Set up Docker Buildx
+      uses: docker/setup-buildx-action@v3
+      
+    - name: Log in to the Container registry
+      uses: docker/login-action@v3
+      with:
+        registry: ${{ env.REGISTRY }}
+        username: ${{ github.actor }}
+        password: ${{ secrets.GITHUB_TOKEN }}
+        
+    - name: Extract metadata (tags, labels) for Frontend
+      id: meta-frontend
+      uses: docker/metadata-action@v5
+      with:
+        images: ${{ env.REGISTRY }}/${{ github.repository_owner }}/musicanalyser-frontend
+        tags: |
+          type=ref,event=branch
+          type=ref,event=pr
+          type=sha
+          type=raw,value=latest,enable={{is_default_branch}}
+      
+    - name: Build and push Frontend
+      uses: docker/build-push-action@v5
+      with:
+        context: ./frontend
+        push: true
+        tags: ${{ steps.meta-frontend.outputs.tags }}
+        labels: ${{ steps.meta-frontend.outputs.labels }}
+        platforms: linux/amd64,linux/arm64
+        cache-from: type=gha
+        cache-to: type=gha,mode=max

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

AGENTS.md

@@ -0,0 +1,85 @@
+# PROJECT KNOWLEDGE BASE
+
+**Generated:** 2025-12-30
+**Branch:** main
+
+## OVERVIEW
+
+Personal music analytics dashboard polling Spotify 24/7. Core stack: Python (FastAPI, SQLAlchemy, PostgreSQL) + React (Vite, Tailwind, AntD). Integrates AI (Gemini) for listening narratives.
+
+## STRUCTURE
+
+```
+.
+├── backend/            # FastAPI API & Spotify polling worker
+│   ├── app/            # Core logic (services, models, schemas)
+│   ├── alembic/        # DB migrations
+│   └── tests/          # Pytest suite
+├── frontend/           # React application
+│   └── src/            # Components & application logic
+├── docs/               # Technical & architecture documentation
+└── docker-compose.yml  # Production orchestration
+```
+
+## WHERE TO LOOK
+
+| Task | Location | Notes |
+|------|----------|-------|
+| Modify API endpoints | `backend/app/main.py` | FastAPI routes |
+| Update DB models | `backend/app/models.py` | SQLAlchemy ORM |
+| Change polling logic | `backend/app/ingest.py` | Worker & ingestion logic |
+| Add analysis features | `backend/app/services/stats_service.py` | Core metric computation |
+| Update UI components | `frontend/src/components/` | React/AntD components |
+| Adjust AI prompts | `backend/app/services/narrative_service.py` | LLM integration |
+
+## CODE MAP (KEY SYMBOLS)
+
+| Symbol | Type | Location | Role |
+|--------|------|----------|------|
+| `SpotifyClient` | Class | `backend/app/services/spotify_client.py` | API wrapper & token management |
+| `StatsService` | Class | `backend/app/services/stats_service.py` | Metric computation & report generation |
+| `NarrativeService` | Class | `backend/app/services/narrative_service.py` | LLM (Gemini/OpenAI) integration |
+| `ingest_recently_played` | Function | `backend/app/ingest.py` | Primary data ingestion entry |
+| `Track` | Model | `backend/app/models.py` | Central track entity with metadata |
+| `PlayHistory` | Model | `backend/app/models.py` | Immutable log of listening events |
+
+### Module Dependencies
+
+```
+[run_worker.py] ───> [ingest.py] ───> [spotify_client.py]
+                                  └───> [reccobeats_client.py]
+[main.py] ─────────> [services/] ───> [models.py]
+```
+
+## CONVENTIONS
+
+- **Single Container Multi-Process**: `backend/entrypoint.sh` starts worker + API (Docker anti-pattern, project-specific).
+- **PostgreSQL Persistence**: Production uses PostgreSQL on internal server (100.91.248.114:5433, database: music_db).
+- **Deduplication**: Ingestion checks `(track_id, played_at)` unique constraint before insert.
+- **Frontend State**: Minimal global state; primarily local component state and API fetching.
+
+## ANTI-PATTERNS (THIS PROJECT)
+
+- **Manual DB Edits**: Always use Alembic migrations for schema changes.
+- **Sync in Async**: Avoid blocking I/O in FastAPI routes (GeniusClient is currently synchronous).
+- **Hardcoded IDs**: Avoid hardcoding Spotify/Playlist IDs; use `.env` configuration.
+
+## COMMANDS
+
+```bash
+# Backend
+cd backend && uvicorn app.main:app --reload
+python backend/run_worker.py
+
+# Frontend
+cd frontend && npm run dev
+
+# Tests
+cd backend && pytest tests/
+```
+
+## NOTES
+
+- Multi-arch Docker builds (`amd64`, `arm64`) automated via GHA.
+- `ReccoBeats` service used for supplemental audio features (energy, valence).
+- Genius API used as fallback for lyrics and artist images.

Context.md

@@ -0,0 +1,114 @@
+# Music Analyser - Project Context & Documentation
+
+This document serves as a comprehensive guide to the **Music Analyser** project. It outlines the vision, technical decisions, current architecture, and future roadmap. **Use this document to provide context to future AI agents or developers.**
+
+## 1. Project Vision
+The goal of this project is to build a personal analytics dashboard that:
+1.  **Regularly queries** the Spotify API (24/7) to collect a complete history of listening habits.
+2.  Stores this data locally (or in a private database) to ensure ownership and completeness.
+3.  Provides **rich analysis** and visualizations (similar to "Spotify Wrapped" but on-demand and more detailed).
+4.  Integrates **AI (Google Gemini)** to provide qualitative insights, summaries, and trend analysis (e.g., "You started the week with high-energy pop but shifted to lo-fi study beats by Friday").
+
+## 2. Roadmap & Phases
+
+### Phase 1: Foundation & Data Collection (Current Status: ✅ COMPLETED)
+-   **Goal:** reliable data ingestion and storage.
+-   **Deliverables:**
+    -   FastAPI Backend.
+    -   SQLite Database (with SQLAlchemy).
+    -   Spotify OAuth logic (Refresh Token flow).
+    -   Background Worker for 24/7 polling.
+    -   Docker containerization + GitHub Actions (Multi-arch build).
+
+### Phase 2: Visualization (Next Step)
+-   **Goal:** View the raw data.
+-   **Deliverables:**
+    -   Frontend (React + Vite).
+    -   Basic Data Table / List View of listening history.
+    -   Basic filtering (by date, artist).
+
+### Phase 3: Analysis & AI
+-   **Goal:** Deep insights.
+-   **Deliverables:**
+    -   Advanced charts/graphs.
+    -   AI Integration (Gemini 2.5/3 Flash) to generate text summaries of listening trends.
+    -   Email reports (optional).
+
+## 3. Technical Architecture
+
+### Backend
+-   **Language:** Python 3.11+
+-   **Framework:** FastAPI (High performance, easy to use).
+-   **Dependencies:** `httpx` (Async HTTP), `sqlalchemy` (ORM), `pydantic` (Validation).
+
+### Database
+-   **Current:** SQLite (`music.db`).
+    -   *Decision:* Chosen for simplicity in Phase 1.
+-   **Future path:** The code uses SQLAlchemy, so migrating to **PostgreSQL** (e.g., Supabase) only requires changing the connection string in `database.py`.
+
+### Database Schema
+1.  **`Track` Table:**
+    -   Stores unique tracks.
+    -   Columns: `id` (Spotify ID), `name`, `artist`, `album`, `duration_ms`, `metadata_json` (Stores the *entire* raw Spotify JSON response for future-proofing).
+2.  **`PlayHistory` Table:**
+    -   Stores the instances of listening.
+    -   Columns: `id`, `track_id` (FK), `played_at` (Timestamp), `context_uri`.
+
+### Authentication Strategy
+-   **Challenge:** The background worker runs headless (no user to click "Login").
+-   **Solution:** We use the **Authorization Code Flow with Refresh Tokens**.
+    1.  User runs the local helper script (`backend/scripts/get_refresh_token.py`) once.
+    2.  This generates a long-lived `SPOTIFY_REFRESH_TOKEN`.
+    3.  The backend uses this token to automatically request new short-lived Access Tokens whenever needed.
+
+### Background Worker Logic
+-   **File:** `backend/run_worker.py` -> `backend/app/ingest.py`
+-   **Process:**
+    1.  Worker wakes up every 60 seconds.
+    2.  Calls Spotify `recently-played` endpoint (limit 50).
+    3.  Iterates through tracks.
+    4.  **Deduplication:** Checks `(track_id, played_at)` against the DB. If it exists, skip. If not, insert.
+    5.  **Metadata:** If the track is new to the system, it saves the full metadata immediately.
+
+### AI Integration
+-   **Model:** Google Gemini (Target: 2.5 Flash or 3 Flash).
+-   **Status:** Service class exists (`AIService`) but is not yet fully wired into the daily workflow.
+
+### Deployment
+-   **Docker:** Multi-stage build (python-slim).
+-   **CI/CD:** GitHub Actions workflow (`docker-publish.yml`).
+    -   Builds for `linux/amd64` and `linux/arm64`.
+    -   Pushes to GitHub Container Registry (ghcr.io).
+
+## 4. How to Run
+
+### Prerequisites
+-   Spotify Client ID & Secret.
+-   Google Gemini API Key.
+-   Docker (optional).
+
+### Local Development
+1.  **Setup Env:**
+    ```bash
+    cp backend/.env.example backend/.env
+    # Fill in details
+    ```
+2.  **Install:**
+    ```bash
+    cd backend
+    pip install -r requirements.txt
+    ```
+3.  **Run API:**
+    ```bash
+    uvicorn app.main:app --reload
+    ```
+4.  **Run Worker:**
+    ```bash
+    python run_worker.py
+    ```
+
+### Docker
+```bash
+docker build -t music-analyser-backend ./backend
+docker run --env-file backend/.env music-analyser-backend
+```

PHASE_4_FRONTEND_GUIDE.md

@@ -0,0 +1,84 @@
+# Phase 4 Frontend Implementation Guide
+
+This guide details how to consume the data generated by the Phase 3 Backend (Analysis & LLM Engine) and how to display it in the frontend.
+
+## 1. Data Source
+
+The backend now produces **Analysis Snapshots**. You should create an API endpoint (e.g., `GET /api/analysis/latest`) that returns the most recent snapshot.
+
+### JSON Payload Structure
+
+The response object contains two main keys: `metrics_payload` (calculated numbers) and `narrative_report` (LLM text).
+
+```json
+{
+  "id": 1,
+  "date": "2024-12-25T12:00:00Z",
+  "period_label": "last_30_days",
+  "metrics_payload": {
+    "volume": { ... },
+    "time_habits": { ... },
+    "sessions": { ... },
+    "vibe": { ... },
+    "era": { ... },
+    "skips": { ... }
+  },
+  "narrative_report": {
+    "vibe_check": "...",
+    "patterns": ["..."],
+    "persona": "...",
+    "roast": "..."
+  }
+}
+```
+
+---
+
+## 2. UI Components & Display Strategy
+
+### A. Hero Section ("The Vibe Check")
+**Data Source:** `narrative_report`
+- **Headline:** Display `narrative_report.persona` as a large badge/title (e.g., "The Focused Fanatic").
+- **Narrative:** Display `narrative_report.vibe_check` as the main text.
+- **Roast:** Add a small, dismissible "Roast Me" alert box containing `narrative_report.roast`.
+
+### B. "The Vibe" Radar Chart
+**Data Source:** `metrics_payload.vibe`
+- Use a **Radar Chart** (Spider Chart) with the following axes (0.0 - 1.0):
+  - Energy (`avg_energy`)
+  - Valence (`avg_valence`)
+  - Danceability (`avg_danceability`)
+  - Acousticness (`avg_acousticness`)
+  - Instrumentalness (`avg_instrumentalness`)
+- **Tooltip:** Show the exact value.
+
+### C. Listening Habits (Time & Sessions)
+**Data Source:** `metrics_payload.time_habits` & `metrics_payload.sessions`
+- **Hourly Heatmap:** Use a bar chart for `metrics_payload.time_habits.hourly_distribution` (0-23 hours). Highlight the `peak_hour`.
+- **Session Stats:** Display "Average Session" stats:
+  - `sessions.avg_minutes` (mins)
+  - `sessions.avg_tracks` (tracks)
+  - `sessions.count` (total sessions)
+
+### D. Top Favorites
+**Data Source:** `metrics_payload.volume`
+- **Lists:** Display Top 5 Tracks, Artists, and Genres.
+- **Images:** You will need to fetch Artist/Track images from Spotify API using the IDs provided in the lists (the current snapshot only stores names/counts for simplicity, but the IDs are available in the backend if you expand the serializer). *Note: Phase 3 backend currently returns names. For Phase 4, ensure the API endpoint enriches these with Spotify Image URLs.*
+
+### E. Era Analysis
+**Data Source:** `metrics_payload.era`
+- **Musical Age:** Display `musical_age` (e.g., "1998") prominently.
+- **Distribution:** Pie chart for `decade_distribution`.
+
+### F. Attention Span (Skips)
+**Data Source:** `metrics_payload.skips`
+- **Metric:** Display "Skip Rate" (`skip_rate`) as a percentage.
+- **Insight:** "You skipped X tracks this month."
+
+---
+
+## 3. Integration Tips
+
+- **Caching:** The backend stores snapshots. You do NOT need to trigger a calculation on page load. Just fetch the latest snapshot.
+- **Theme:** The app uses Ant Design Dark Mode. Stick to Spotify colors (Black/Green/White) but add accent colors based on the "Vibe" (e.g., High Energy = Red/Orange, Low Energy = Blue/Purple).
+- **Expansion:** Future snapshots allow for "Trend" views. You can graph `metrics_payload.volume.total_plays` over the last 6 snapshots to show activity trends.

README.md

@@ -1,72 +1,140 @@
 # Music Analyser
 
-A personal analytics dashboard for your music listening habits, powered by Python, FastAPI, and Google Gemini AI.
+A personal analytics dashboard for your music listening habits, powered by Python, FastAPI, React, and Google Gemini AI.
 
-## Project Structure
+![Dashboard Screenshot](screen.png)
 
-- `backend/`: FastAPI backend for data ingestion and API.
-  - `app/ingest.py`: Background worker that polls Spotify.
-  - `app/services/`: Logic for Spotify and Gemini APIs.
-  - `app/models.py`: Database schema (Tracks, PlayHistory).
-- `frontend/`: (Coming Soon) React/Vite frontend.
+## Features
 
-## Getting Started
+- **Continuous Ingestion**: Polls Spotify every 60 seconds to record your listening history.
+- **Data Enrichment**: 
+  - **Genres & Images** (via Spotify)
+  - **Audio Features** (Energy, BPM, Mood via ReccoBeats)
+  - **Lyrics & Metadata** (via Genius)
+- **Dashboard**: A responsive UI with Tailwind CSS, featuring AI-generated narrative insights.
+- **AI Powered**: Google Gemini generates personalized listening narratives and roasts.
 
-### Prerequisites
+## Quick Start (Docker Compose)
 
-- Docker & Docker Compose (optional, for containerization)
-- Python 3.11+ (for local dev)
-- A Spotify Developer App (Client ID & Secret)
-- A Google Gemini API Key
+### 1. Prerequisites
+- Docker & Docker Compose installed
+- Spotify Developer Credentials ([Create App](https://developer.spotify.com/dashboard))
+- Google Gemini API Key ([Get Key](https://aistudio.google.com/app/apikey))
+- Genius API Token (Optional, for lyrics - [Get Token](https://genius.com/api-clients))
 
-### 1. Setup Environment Variables
+### 2. Get Spotify Refresh Token
 
-Create a `.env` file in the `backend/` directory:
+Run this one-time script locally to authorize your Spotify account:
+
+```bash
+cd backend
+pip install httpx
+python scripts/get_refresh_token.py
+```
+
+Follow the prompts. Copy the `refresh_token` value for your `.env` file.
+
+### 3. Create `.env` File
+
+Create a `.env` file in the project root:
 
 ```bash
 SPOTIFY_CLIENT_ID="your_client_id"
 SPOTIFY_CLIENT_SECRET="your_client_secret"
 SPOTIFY_REFRESH_TOKEN="your_refresh_token"
 GEMINI_API_KEY="your_gemini_key"
+GENIUS_ACCESS_TOKEN="your_genius_token"  # Optional
 ```
 
-To get the `SPOTIFY_REFRESH_TOKEN`, run the helper script:
+### 4. Run with Pre-built Images
 
 ```bash
-python backend/scripts/get_refresh_token.py
+# Pull the latest images
+docker pull ghcr.io/bnair123/musicanalyser:latest
+docker pull ghcr.io/bnair123/musicanalyser-frontend:latest
+
+# Start the services
+docker-compose up -d
 ```
 
-### 2. Run Locally
+Or build from source:
 
-Install dependencies:
+```bash
+docker-compose up -d --build
+```
 
+### 5. Access the Dashboard
+
+Open your browser to: **http://localhost:8991**
+
+## Architecture
+
+```
+┌─────────────────────┐     ┌─────────────────────┐
+│     Frontend        │     │      Backend        │
+│  (React + Vite)     │────▶│  (FastAPI + Worker) │
+│   Port: 8991        │     │   Port: 8000        │
+└─────────────────────┘     └─────────────────────┘
+                                     │
+                            ┌────────┴────────┐
+                            ▼                 ▼
+                      ┌──────────┐     ┌──────────────┐
+                      │PostgreSQL│     │ Spotify API  │
+                      │ music_db │     │ Gemini AI    │
+                      └──────────┘     └──────────────┘
+```
+
+- **Backend Container**: Runs both the FastAPI server AND the background Spotify polling worker
+- **Frontend Container**: Nginx serving the React build, proxies `/api/` to backend
+- **Database**: PostgreSQL hosted on internal server (100.91.248.114:5433)
+
+## Data Persistence
+
+Your listening history is stored in PostgreSQL:
+- Host: `100.91.248.114:5433`
+- Database: `music_db`
+- Data Location (on server): `/opt/DB/MusicDB/pgdata`
+- Migrations run automatically on container startup via Alembic
+
+To backup your data:
+```bash
+pg_dump -h 100.91.248.114 -p 5433 -U bnair music_db > backup.sql
+```
+
+## Local Development
+
+### Backend
 ```bash
 cd backend
+python -m venv venv && source venv/bin/activate
 pip install -r requirements.txt
-```
 
-Run the server:
+# Run migrations
+alembic upgrade head
 
-```bash
+# Start worker (polls Spotify every 60s)
+python run_worker.py &
+
+# Start API server
 uvicorn app.main:app --reload
 ```
 
-The API will be available at `http://localhost:8000`.
-
-### 3. Run Ingestion (Manually)
-
-You can trigger the ingestion process via the API:
-
+### Frontend
 ```bash
-curl -X POST http://localhost:8000/trigger-ingest
+cd frontend
+npm install
+npm run dev
 ```
 
-Or run the ingestion logic directly via python shell (see `app/ingest.py`).
+Access at http://localhost:5173 (Vite proxies `/api` to backend automatically)
 
-### 4. Docker Build
+## Environment Variables
 
-To build the image locally:
-
-```bash
-docker build -t music-analyser-backend ./backend
-```
+| Variable | Required | Description |
+|----------|----------|-------------|
+| `SPOTIFY_CLIENT_ID` | Yes | Spotify app client ID |
+| `SPOTIFY_CLIENT_SECRET` | Yes | Spotify app client secret |
+| `SPOTIFY_REFRESH_TOKEN` | Yes | Long-lived refresh token from OAuth |
+| `GEMINI_API_KEY` | Yes | Google Gemini API key |
+| `GENIUS_ACCESS_TOKEN` | No | Genius API token for lyrics |
+| `DATABASE_URL` | No | PostgreSQL URL (default: `postgresql://bnair:Bharath2002@100.91.248.114:5433/music_db`) |

TODO.md

@@ -0,0 +1,21 @@
+🎵 Playlist Service Feature - Complete Task List
+What's Been Done ✅
+| # | Task | Status | Notes |
+|---|-------|--------|-------|
+| 1 | Database | ✅ Completed | Added playlist_theme, playlist_theme_reasoning, six_hour_playlist_id, daily_playlist_id columns to AnalysisSnapshot model |
+| 2 | AI Service | ✅ Completed | Added generate_playlist_theme(), _build_theme_prompt(), _call_openai_for_theme(), updated _build_prompt() to remove HHI/Gini/part_of_day |
+| 3 | PlaylistService | ✅ Completed | Implemented full curation logic with ensure_playlists_exist(), curate_six_hour_playlist(), curate_daily_playlist(), _get_top_all_time_tracks() |
+| 4 | Migration | ✅ Completed | Created 5ed73db9bab9_add_playlist_columns.py and applied to DB |
+| 5 | API Endpoints | ✅ Completed | Added /playlists/refresh/* and /playlists GET endpoints in main.py |
+| 6 | Worker Scheduler | ✅ Completed | Added 6h and 24h refresh logic to run_worker.py via ingest.py |
+| 7 | Frontend Tooltip | ✅ Completed | Created Tooltip.jsx component |
+| 8 | Playlists Section | ✅ Completed | Created PlaylistsSection.jsx with refresh and Spotify links |
+| 9 | Integration | ✅ Completed | Integrated PlaylistsSection into Dashboard.jsx and added tooltips to StatsGrid.jsx |
+| 10 | Docker Config | ✅ Completed | Updated docker-compose.yml and Dockerfile (curl for healthcheck) |
+
+All feature tasks are COMPLETE and VERIFIED.
+End-to-end testing with Playwright confirms:
+- 6-hour refresh correctly calls AI and Spotify, saves snapshot.
+- Daily refresh correctly curates mix and saves snapshot.
+- Dashboard displays themed playlists and refresh status.
+- Tooltips provide context for technical metrics.

backend/Dockerfile

@@ -3,9 +3,22 @@ FROM python:3.11-slim
 
 WORKDIR /app
 
+# Install system dependencies (including PostgreSQL client libs for psycopg2)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    libpq-dev \
+    && rm -rf /var/lib/apt/lists/*
+
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
 
-CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
+# Make entrypoint executable
+RUN chmod +x entrypoint.sh
+
+# Expose API port
+EXPOSE 8000
+
+# Use entrypoint script to run migrations, worker, and API
+CMD ["./entrypoint.sh"]

backend/TECHNICAL_DOCS.md

@@ -0,0 +1,114 @@
+# Technical Documentation: Stats & Narrative Services
+
+## Overview
+This document details the implementation of the core analysis engine (`StatsService`) and the AI narration layer (`NarrativeService`). These services transform raw Spotify listening data into computable metrics and human-readable insights.
+
+## 1. StatsService (`backend/app/services/stats_service.py`)
+
+The `StatsService` is a deterministic calculation engine. It takes a time range (`period_start` to `period_end`) and aggregates `PlayHistory` records.
+
+### Core Architecture
+- **Input:** SQLAlchemy Session, Start Datetime, End Datetime.
+- **Output:** A structured JSON dictionary containing discrete analysis blocks (Volume, Time, Sessions, Vibe, etc.).
+- **Optimization:** Uses `joinedload` to eagerly fetch `Track` and `Artist` relations, preventing N+1 query performance issues during iteration.
+
+### Metric Logic
+
+#### A. Volume & Consumption
+- **Top Tracks/Artists:** Aggregated by ID, not name, to handle artist renames or duplicates.
+- **Concentration Metrics:**
+  - **HHI (Herfindahl–Hirschman Index):** Measures diversity. `SUM(share^2)`. Close to 0 = diverse, close to 1 = repetitive.
+  - **Gini Coefficient:** Measures inequality of play distribution.
+  - **Genre Entropy:** `-SUM(p * log(p))` for genre probabilities. Higher = more diverse genre consumption.
+- **Artists:** Parsed from the `Track.artists` relationship (Many-to-Many) rather than the flat string, ensuring accurate counts for collaborations (e.g., "Drake, Future" counts for both).
+
+#### B. Time & Habits
+- **Part of Day:** Fixed buckets:
+  - Morning: 06:00 - 12:00
+  - Afternoon: 12:00 - 18:00
+  - Evening: 18:00 - 23:59
+  - Night: 00:00 - 06:00
+- **Streaks:** Calculates consecutive days with at least one play.
+- **Active Days:** Count of unique dates with activity.
+
+#### C. Session Analytics
+- **Session Definition:** A sequence of plays where the gap between any two consecutive tracks is ≤ 20 minutes. A gap > 20 minutes starts a new session.
+- **Energy Arcs:** Compares the `energy` feature of the first and last track in a session.
+  - Rising: Delta > +0.1
+  - Falling: Delta < -0.1
+  - Flat: Otherwise
+
+#### D. The "Vibe" (Audio Features)
+- **Aggregation:** Calculates Mean, Standard Deviation, and Percentiles (P10, P50/Median, P90) for all Spotify audio features (Energy, Valence, Danceability, etc.).
+- **Whiplash Score:** Measures the "volatility" of a listening session. Calculated as the average absolute difference in a feature (Tempo, Energy, Valence) between consecutive tracks.
+  - High Whiplash (> 15-20 for BPM) = Chaotic playlist shuffling.
+  - Low Whiplash = Smooth transitions.
+- **Profiles:**
+  - **Mood Quadrant:** (Avg Valence, Avg Energy) coordinates.
+  - **Texture:** Acousticness vs. Instrumentalness.
+
+#### E. Context & Behavior
+- **Context URI:** Parsed to determine source (Playlist vs. Album vs. Artist).
+- **Context Switching:** Percentage of track transitions where the `context_uri` changes. High rate = user is jumping between playlists or albums frequently.
+
+#### F. Lifecycle & Discovery
+- **Discovery:** Tracks played in the current period that were *never* played before `period_start`.
+- **Obsession:** Tracks with ≥ 5 plays in the current period.
+- **Skip Detection (Boredom Skips):** 
+  - Logic: `(next_start - current_start) < (current_duration - 10s)`
+  - Only counts if the listening time was > 30s (to filter accidental clicks).
+  - Proxy for "User got bored and hit next."
+
+---
+
+## 2. NarrativeService (`backend/app/services/narrative_service.py`)
+
+The `NarrativeService` acts as an interpreter. It feeds the raw JSON from `StatsService` into Google's Gemini LLM to generate text.
+
+### Payload Shaping
+To ensure reliability and manage token costs, the service **does not** send the raw full database dump. It pre-processes the stats:
+- Truncates top lists to Top 5.
+- Removes raw transition arrays.
+- Simplifies nested structures.
+
+### LLM Prompt Engineering
+The system uses a strict persona ("Witty Music Critic") and enforces specific constraints:
+- **Output:** Strict JSON.
+- **Safety:** Explicitly forbidden from making mental health diagnoses (e.g., no "You seem depressed").
+- **Content:** Must reference specific numbers from the input stats (e.g., "Your 85% Mainstream Score...").
+
+### Output Schema
+The LLM returns a JSON object with:
+- `vibe_check`: 2-3 paragraph summary.
+- `patterns`: List of specific observations.
+- `persona`: A creative 2-3 word label (e.g., "The Genre Chameleon").
+- `roast`: A playful critique.
+- `era_insight`: Commentary on the user's "Musical Age" (weighted avg release year).
+
+## 3. Data Models (`backend/app/models.py`)
+
+- **Track:** Stores static metadata and audio features. 
+  - `lyrics`: Full lyrics from Genius (Text).
+  - `image_url`: Album art URL (String).
+  - `raw_data`: The full Spotify JSON for future-proofing.
+- **Artist:** Normalized artist entities.
+  - `image_url`: Artist profile image (String).
+- **PlayHistory:** The timeseries ledger. Links `Track` to a timestamp and context.
+- **AnalysisSnapshot:** Stores the final output of these services.
+  - `metrics_payload`: The JSON output of `StatsService`.
+  - `narrative_report`: The JSON output of `NarrativeService`.
+
+## 4. External Integrations
+
+### Spotify
+- **Ingestion:** Polls `recently-played` endpoint every 60s.
+- **Enrichment:** Fetches Artist genres and images.
+
+### Genius
+- **Client:** `backend/app/services/genius_client.py`.
+- **Function:** Searches for lyrics and high-res album art if missing from Spotify data.
+- **Trigger:** Runs during the ingestion loop for new tracks.
+
+### ReccoBeats
+- **Function:** Fetches audio features (Danceability, Energy, Valence) for tracks.
+

backend/TESTING.md

@@ -0,0 +1,76 @@
+# Testing Guide
+
+This project includes a comprehensive test suite to verify the calculation engine (`StatsService`) and the AI narrative generation (`NarrativeService`).
+
+## 1. Quick Start (Standalone Test)
+
+You can run the full stats verification script without installing `pytest`. This script uses an in-memory SQLite database, seeds it with synthetic listening history (including skips, sessions, and specific genres), and prints the computed analysis JSON.
+
+```bash
+# Ensure you are in the root directory
+# If you are using the virtual environment:
+source backend/venv/bin/activate
+
+# Run the test
+python backend/tests/test_stats_full.py
+```
+
+### What does this verify?
+- **Volume Metrics:** Total plays, unique tracks/artists.
+- **Session Logic:** Correctly groups plays into sessions based on 20-minute gaps.
+- **Skip Detection:** Identifies "boredom skips" based on timestamp deltas.
+- **Vibe Analysis:** Verifies K-Means clustering, tempo zones, and harmonic profiles.
+- **Context Analysis:** Checks if plays are correctly attributed to Playlists/Albums.
+
+## 2. Generating a Spotify Refresh Token
+
+To run the actual application, you need a Spotify Refresh Token. We provide a script to automate the OAuth flow.
+
+1.  **Prerequisites:**
+    *   Go to [Spotify Developer Dashboard](https://developer.spotify.com/dashboard/).
+    *   Create an App.
+    *   In settings, add `http://localhost:8888/callback` to "Redirect URIs".
+    *   Get your **Client ID** and **Client Secret**.
+
+2.  **Run the Script:**
+    ```bash
+    python backend/scripts/get_refresh_token.py
+    ```
+
+3.  **Follow Instructions:**
+    *   Enter your Client ID/Secret when prompted.
+    *   The script will open your browser.
+    *   Log in to Spotify and authorize the app.
+    *   The script will print your `SPOTIFY_REFRESH_TOKEN` in the terminal.
+
+4.  **Save to .env:**
+    Copy the output into your `.env` file.
+
+## 3. Full Test Suite (Pytest)
+
+If you wish to run the full suite using `pytest` (recommended for CI/CD), install the dev dependencies:
+
+```bash
+pip install pytest
+```
+
+Then run:
+
+```bash
+pytest backend/tests
+```
+
+## 4. Manual Verification
+
+To verify the system end-to-end with real data:
+
+1.  Start the backend:
+    ```bash
+    python backend/run_worker.py
+    ```
+2.  Wait for a few minutes for data to ingest (check logs).
+3.  Run the analysis manually:
+    ```bash
+    python backend/run_analysis.py
+    ```
+4.  Check the database or logs for the generated `AnalysisSnapshot`.

backend/alembic.ini

@@ -0,0 +1,147 @@
+# A generic, single database configuration.
+
+[alembic]
+# path to migration scripts.
+# this is typically a path given in POSIX (e.g. forward slashes)
+# format, relative to the token %(here)s which refers to the location of this
+# ini file
+script_location = %(here)s/alembic
+
+# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
+# Uncomment the line below if you want the files to be prepended with date and time
+# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
+# for all available tokens
+# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
+
+# sys.path path, will be prepended to sys.path if present.
+# defaults to the current working directory.  for multiple paths, the path separator
+# is defined by "path_separator" below.
+prepend_sys_path = .
+
+
+# timezone to use when rendering the date within the migration file
+# as well as the filename.
+# If specified, requires the tzdata library which can be installed by adding
+# `alembic[tz]` to the pip requirements.
+# string value is passed to ZoneInfo()
+# leave blank for localtime
+# timezone =
+
+# max length of characters to apply to the "slug" field
+# truncate_slug_length = 40
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+# set to 'true' to allow .pyc and .pyo files without
+# a source .py file to be detected as revisions in the
+# versions/ directory
+# sourceless = false
+
+# version location specification; This defaults
+# to <script_location>/versions.  When using multiple version
+# directories, initial revisions must be specified with --version-path.
+# The path separator used here should be the separator specified by "path_separator"
+# below.
+# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
+
+# path_separator; This indicates what character is used to split lists of file
+# paths, including version_locations and prepend_sys_path within configparser
+# files such as alembic.ini.
+# The default rendered in new alembic.ini files is "os", which uses os.pathsep
+# to provide os-dependent path splitting.
+#
+# Note that in order to support legacy alembic.ini files, this default does NOT
+# take place if path_separator is not present in alembic.ini.  If this
+# option is omitted entirely, fallback logic is as follows:
+#
+# 1. Parsing of the version_locations option falls back to using the legacy
+#    "version_path_separator" key, which if absent then falls back to the legacy
+#    behavior of splitting on spaces and/or commas.
+# 2. Parsing of the prepend_sys_path option falls back to the legacy
+#    behavior of splitting on spaces, commas, or colons.
+#
+# Valid values for path_separator are:
+#
+# path_separator = :
+# path_separator = ;
+# path_separator = space
+# path_separator = newline
+#
+# Use os.pathsep. Default configuration used for new projects.
+path_separator = os
+
+# set to 'true' to search source files recursively
+# in each "version_locations" directory
+# new in Alembic version 1.10
+# recursive_version_locations = false
+
+# the output encoding used when revision files
+# are written from script.py.mako
+# output_encoding = utf-8
+
+# database URL.  This is consumed by the user-maintained env.py script only.
+# other means of configuring database URLs may be customized within the env.py
+# file.
+sqlalchemy.url = driver://user:pass@localhost/dbname
+
+
+[post_write_hooks]
+# post_write_hooks defines scripts or Python functions that are run
+# on newly generated revision scripts.  See the documentation for further
+# detail and examples
+
+# format using "black" - use the console_scripts runner, against the "black" entrypoint
+# hooks = black
+# black.type = console_scripts
+# black.entrypoint = black
+# black.options = -l 79 REVISION_SCRIPT_FILENAME
+
+# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
+# hooks = ruff
+# ruff.type = module
+# ruff.module = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Alternatively, use the exec runner to execute a binary found on your PATH
+# hooks = ruff
+# ruff.type = exec
+# ruff.executable = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Logging configuration.  This is also consumed by the user-maintained
+# env.py script only.
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARNING
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARNING
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S

backend/alembic/README

@@ -0,0 +1 @@
+Generic single-database configuration.

backend/alembic/env.py

@@ -0,0 +1,75 @@
+from logging.config import fileConfig
+import os
+import sys
+
+from sqlalchemy import engine_from_config
+from sqlalchemy import pool
+
+from alembic import context
+
+# Add app to path to import models
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from app.database import Base, SQLALCHEMY_DATABASE_URL
+from app.models import *
+
+config = context.config
+
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+target_metadata = Base.metadata
+
+config.set_main_option("sqlalchemy.url", SQLALCHEMY_DATABASE_URL)
+
+
+def run_migrations_offline() -> None:
+    """Run migrations in 'offline' mode.
+
+    This configures the context with just a URL
+    and not an Engine, though an Engine is acceptable
+    here as well.  By skipping the Engine creation
+    we don't even need a DBAPI to be available.
+
+    Calls to context.execute() here emit the given string to the
+    script output.
+
+    """
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        dialect_opts={"paramstyle": "named"},
+    )
+
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def run_migrations_online() -> None:
+    """Run migrations in 'online' mode.
+
+    In this scenario we need to create an Engine
+    and associate a connection with the context.
+
+    """
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section, {}),
+        prefix="sqlalchemy.",
+        poolclass=pool.NullPool,
+    )
+
+    with connectable.connect() as connection:
+        context.configure(
+            connection=connection, target_metadata=target_metadata
+        )
+
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()

backend/alembic/script.py.mako

@@ -0,0 +1,28 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision: str = ${repr(up_revision)}
+down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
+branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
+depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    ${downgrades if downgrades else "pass"}

backend/alembic/versions/24fafb6f6e98_add_composition_to_snapshot.py

@@ -0,0 +1,32 @@
+"""add_composition_to_snapshot
+
+Revision ID: 24fafb6f6e98
+Revises: 86ea83950f3d
+Create Date: 2025-12-30 10:43:05.933962
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '24fafb6f6e98'
+down_revision: Union[str, Sequence[str], None] = '86ea83950f3d'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('analysis_snapshots', sa.Column('playlist_composition', sa.JSON(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('analysis_snapshots', 'playlist_composition')
+    # ### end Alembic commands ###

backend/alembic/versions/4401cb416661_add_artist_and_snapshot_models.py

@@ -0,0 +1,63 @@
+"""Add Artist and Snapshot models
+
+Revision ID: 4401cb416661
+Revises: 707387fe1be2
+Create Date: 2025-12-24 23:06:59.235445
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '4401cb416661'
+down_revision: Union[str, Sequence[str], None] = '707387fe1be2'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('analysis_snapshots',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('date', sa.DateTime(), nullable=True),
+    sa.Column('period_start', sa.DateTime(), nullable=True),
+    sa.Column('period_end', sa.DateTime(), nullable=True),
+    sa.Column('period_label', sa.String(), nullable=True),
+    sa.Column('metrics_payload', sa.JSON(), nullable=True),
+    sa.Column('narrative_report', sa.JSON(), nullable=True),
+    sa.Column('model_used', sa.String(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_analysis_snapshots_date'), 'analysis_snapshots', ['date'], unique=False)
+    op.create_index(op.f('ix_analysis_snapshots_id'), 'analysis_snapshots', ['id'], unique=False)
+    op.create_table('artists',
+    sa.Column('id', sa.String(), nullable=False),
+    sa.Column('name', sa.String(), nullable=True),
+    sa.Column('genres', sa.JSON(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_artists_id'), 'artists', ['id'], unique=False)
+    op.create_table('track_artists',
+    sa.Column('track_id', sa.String(), nullable=False),
+    sa.Column('artist_id', sa.String(), nullable=False),
+    sa.ForeignKeyConstraint(['artist_id'], ['artists.id'], ),
+    sa.ForeignKeyConstraint(['track_id'], ['tracks.id'], ),
+    sa.PrimaryKeyConstraint('track_id', 'artist_id')
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('track_artists')
+    op.drop_index(op.f('ix_artists_id'), table_name='artists')
+    op.drop_table('artists')
+    op.drop_index(op.f('ix_analysis_snapshots_id'), table_name='analysis_snapshots')
+    op.drop_index(op.f('ix_analysis_snapshots_date'), table_name='analysis_snapshots')
+    op.drop_table('analysis_snapshots')
+    # ### end Alembic commands ###

backend/alembic/versions/5ed73db9bab9_add_playlist_columns.py

@@ -0,0 +1,45 @@
+"""add playlist columns
+
+Revision ID: 5ed73db9bab9
+Revises: b2c3d4e5f6g7
+Create Date: 2025-12-30 02:10:00.000000
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "5ed73db9bab9"
+down_revision = "b2c3d4e5f6g7"
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column(
+        "analysis_snapshots", sa.Column("playlist_theme", sa.String(), nullable=True)
+    )
+    op.add_column(
+        "analysis_snapshots",
+        sa.Column("playlist_theme_reasoning", sa.Text(), nullable=True),
+    )
+    op.add_column(
+        "analysis_snapshots",
+        sa.Column("six_hour_playlist_id", sa.String(), nullable=True),
+    )
+    op.add_column(
+        "analysis_snapshots", sa.Column("daily_playlist_id", sa.String(), nullable=True)
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column("analysis_snapshots", "daily_playlist_id")
+    op.drop_column("analysis_snapshots", "six_hour_playlist_id")
+    op.drop_column("analysis_snapshots", "playlist_theme_reasoning")
+    op.drop_column("analysis_snapshots", "playlist_theme")
+    # ### end Alembic commands ###

backend/alembic/versions/707387fe1be2_initial_schema_complete.py

@@ -0,0 +1,73 @@
+"""Initial Schema Complete
+
+Revision ID: 707387fe1be2
+Revises:
+Create Date: 2025-12-24 21:23:43.744292
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '707387fe1be2'
+down_revision: Union[str, Sequence[str], None] = None
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('tracks',
+    sa.Column('id', sa.String(), nullable=False),
+    sa.Column('name', sa.String(), nullable=True),
+    sa.Column('artist', sa.String(), nullable=True),
+    sa.Column('album', sa.String(), nullable=True),
+    sa.Column('duration_ms', sa.Integer(), nullable=True),
+    sa.Column('popularity', sa.Integer(), nullable=True),
+    sa.Column('raw_data', sa.JSON(), nullable=True),
+    sa.Column('danceability', sa.Float(), nullable=True),
+    sa.Column('energy', sa.Float(), nullable=True),
+    sa.Column('key', sa.Integer(), nullable=True),
+    sa.Column('loudness', sa.Float(), nullable=True),
+    sa.Column('mode', sa.Integer(), nullable=True),
+    sa.Column('speechiness', sa.Float(), nullable=True),
+    sa.Column('acousticness', sa.Float(), nullable=True),
+    sa.Column('instrumentalness', sa.Float(), nullable=True),
+    sa.Column('liveness', sa.Float(), nullable=True),
+    sa.Column('valence', sa.Float(), nullable=True),
+    sa.Column('tempo', sa.Float(), nullable=True),
+    sa.Column('time_signature', sa.Integer(), nullable=True),
+    sa.Column('genres', sa.JSON(), nullable=True),
+    sa.Column('lyrics_summary', sa.String(), nullable=True),
+    sa.Column('genre_tags', sa.String(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_tracks_id'), 'tracks', ['id'], unique=False)
+    op.create_table('play_history',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('track_id', sa.String(), nullable=True),
+    sa.Column('played_at', sa.DateTime(), nullable=True),
+    sa.Column('context_uri', sa.String(), nullable=True),
+    sa.ForeignKeyConstraint(['track_id'], ['tracks.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_play_history_id'), 'play_history', ['id'], unique=False)
+    op.create_index(op.f('ix_play_history_played_at'), 'play_history', ['played_at'], unique=False)
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_index(op.f('ix_play_history_played_at'), table_name='play_history')
+    op.drop_index(op.f('ix_play_history_id'), table_name='play_history')
+    op.drop_table('play_history')
+    op.drop_index(op.f('ix_tracks_id'), table_name='tracks')
+    op.drop_table('tracks')
+    # ### end Alembic commands ###

backend/alembic/versions/7e28cc511ef8_add_playlist_config_table.py

@@ -0,0 +1,41 @@
+"""add_playlist_config_table
+
+Revision ID: 7e28cc511ef8
+Revises: 5ed73db9bab9
+Create Date: 2025-12-30 10:30:36.775553
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '7e28cc511ef8'
+down_revision: Union[str, Sequence[str], None] = '5ed73db9bab9'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('playlist_config',
+    sa.Column('key', sa.String(), nullable=False),
+    sa.Column('spotify_id', sa.String(), nullable=False),
+    sa.Column('last_updated', sa.DateTime(), nullable=True),
+    sa.Column('current_theme', sa.String(), nullable=True),
+    sa.Column('description', sa.String(), nullable=True),
+    sa.PrimaryKeyConstraint('key')
+    )
+    op.create_index(op.f('ix_playlist_config_key'), 'playlist_config', ['key'], unique=False)
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_index(op.f('ix_playlist_config_key'), table_name='playlist_config')
+    op.drop_table('playlist_config')
+    # ### end Alembic commands ###

backend/alembic/versions/86ea83950f3d_add_composition_to_playlist_config.py

@@ -0,0 +1,32 @@
+"""add_composition_to_playlist_config
+
+Revision ID: 86ea83950f3d
+Revises: 7e28cc511ef8
+Create Date: 2025-12-30 10:39:27.121477
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '86ea83950f3d'
+down_revision: Union[str, Sequence[str], None] = '7e28cc511ef8'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('playlist_config', sa.Column('composition', sa.JSON(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('playlist_config', 'composition')
+    # ### end Alembic commands ###

backend/alembic/versions/a1b2c3d4e5f6_add_skip_tracking_columns.py

@@ -0,0 +1,34 @@
+"""Add skip tracking columns to play_history
+
+Revision ID: a1b2c3d4e5f6
+Revises: f92d8a9264d3
+Create Date: 2025-12-29 22:30:00.000000
+
+"""
+
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = "a1b2c3d4e5f6"
+down_revision: Union[str, Sequence[str], None] = "f92d8a9264d3"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Add listened_ms, skipped, and source columns to play_history."""
+    op.add_column("play_history", sa.Column("listened_ms", sa.Integer(), nullable=True))
+    op.add_column("play_history", sa.Column("skipped", sa.Boolean(), nullable=True))
+    op.add_column("play_history", sa.Column("source", sa.String(), nullable=True))
+    # source can be: 'recently_played', 'currently_playing', 'inferred'
+
+
+def downgrade() -> None:
+    """Remove skip tracking columns."""
+    op.drop_column("play_history", "source")
+    op.drop_column("play_history", "skipped")
+    op.drop_column("play_history", "listened_ms")

backend/alembic/versions/b2c3d4e5f6g7_add_reccobeats_id.py

@@ -0,0 +1,25 @@
+"""Add reccobeats_id column to tracks table
+
+Revision ID: b2c3d4e5f6g7
+Revises: a1b2c3d4e5f6
+Create Date: 2025-12-30
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+revision = "b2c3d4e5f6g7"
+down_revision = "a1b2c3d4e5f6"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column("tracks", sa.Column("reccobeats_id", sa.String(), nullable=True))
+    op.create_index("ix_tracks_reccobeats_id", "tracks", ["reccobeats_id"])
+
+
+def downgrade() -> None:
+    op.drop_index("ix_tracks_reccobeats_id", "tracks")
+    op.drop_column("tracks", "reccobeats_id")

backend/alembic/versions/f92d8a9264d3_add_image_url_and_lyrics_columns.py

@@ -0,0 +1,36 @@
+"""Add image_url and lyrics columns
+
+Revision ID: f92d8a9264d3
+Revises: 4401cb416661
+Create Date: 2025-12-25 22:06:05.841447
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = 'f92d8a9264d3'
+down_revision: Union[str, Sequence[str], None] = '4401cb416661'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('artists', sa.Column('image_url', sa.String(), nullable=True))
+    op.add_column('tracks', sa.Column('image_url', sa.String(), nullable=True))
+    op.add_column('tracks', sa.Column('lyrics', sa.Text(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('tracks', 'lyrics')
+    op.drop_column('tracks', 'image_url')
+    op.drop_column('artists', 'image_url')
+    # ### end Alembic commands ###

backend/app/database.py

@@ -1,15 +1,34 @@
+import os
 from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker, declarative_base
 
-SQLALCHEMY_DATABASE_URL = "sqlite:///./music.db"
+# PostgreSQL connection configuration
+# Uses docker hostname 'music_db' when running in container, falls back to external IP for local dev
+POSTGRES_HOST = os.getenv("POSTGRES_HOST", "music_db")
+POSTGRES_PORT = os.getenv("POSTGRES_PORT", "5432")
+POSTGRES_USER = os.getenv("POSTGRES_USER", "bnair")
+POSTGRES_PASSWORD = os.getenv("POSTGRES_PASSWORD", "Bharath2002")
+POSTGRES_DB = os.getenv("POSTGRES_DB", "music_db")
 
+# Build the PostgreSQL URL
+# Format: postgresql://user:password@host:port/database
+SQLALCHEMY_DATABASE_URL = os.getenv(
+    "DATABASE_URL",
+    f"postgresql://{POSTGRES_USER}:{POSTGRES_PASSWORD}@{POSTGRES_HOST}:{POSTGRES_PORT}/{POSTGRES_DB}",
+)
+
+# PostgreSQL connection pool settings for production
 engine = create_engine(
-    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
+    SQLALCHEMY_DATABASE_URL,
+    pool_size=5,  # Maintain 5 connections in the pool
+    max_overflow=10,  # Allow up to 10 additional connections
+    pool_pre_ping=True,  # Verify connection health before using
 )
 SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
 
 Base = declarative_base()
 
+
 def get_db():
     db = SessionLocal()
     try:

backend/app/ingest.py

@@ -1,24 +1,165 @@
+from .services.stats_service import StatsService
+from .services.narrative_service import NarrativeService
+from .services.playlist_service import PlaylistService
 import asyncio
 import os
-from datetime import datetime
+import time
+from datetime import datetime, timedelta
 from sqlalchemy.orm import Session
-from .models import Track, PlayHistory
+from .models import Track, PlayHistory, Artist, AnalysisSnapshot
 from .database import SessionLocal
 from .services.spotify_client import SpotifyClient
+from .services.reccobeats_client import ReccoBeatsClient
+from .services.genius_client import GeniusClient
 from dateutil import parser
 
-# Initialize Spotify Client (env vars will be populated later)
+
+class PlaybackTracker:
+    def __init__(self):
+        self.current_track_id = None
+        self.track_start_time = None
+        self.accumulated_listen_ms = 0
+        self.last_progress_ms = 0
+        self.last_poll_time = None
+        self.is_paused = False
+
+
 def get_spotify_client():
     return SpotifyClient(
-        client_id=os.getenv("SPOTIFY_CLIENT_ID"),
-        client_secret=os.getenv("SPOTIFY_CLIENT_SECRET"),
-        refresh_token=os.getenv("SPOTIFY_REFRESH_TOKEN"),
+        client_id=str(os.getenv("SPOTIFY_CLIENT_ID") or ""),
+        client_secret=str(os.getenv("SPOTIFY_CLIENT_SECRET") or ""),
+        refresh_token=str(os.getenv("SPOTIFY_REFRESH_TOKEN") or ""),
     )
 
+
+def get_reccobeats_client():
+    return ReccoBeatsClient()
+
+
+def get_genius_client():
+    return GeniusClient()
+
+
+async def ensure_artists_exist(db: Session, artists_data: list):
+    artist_objects = []
+    for a_data in artists_data:
+        artist_id = a_data["id"]
+        artist = db.query(Artist).filter(Artist.id == artist_id).first()
+        if not artist:
+            img = None
+            if "images" in a_data and a_data["images"]:
+                img = a_data["images"][0]["url"]
+
+            artist = Artist(id=artist_id, name=a_data["name"], genres=[], image_url=img)
+            db.add(artist)
+        artist_objects.append(artist)
+    return artist_objects
+
+
+async def enrich_tracks(
+    db: Session,
+    spotify_client: SpotifyClient,
+    recco_client: ReccoBeatsClient,
+    genius_client: GeniusClient,
+):
+    tracks_missing_features = (
+        db.query(Track).filter(Track.danceability == None).limit(50).all()
+    )
+    if tracks_missing_features:
+        print(f"Enriching {len(tracks_missing_features)} tracks with audio features...")
+        ids = [str(t.id) for t in tracks_missing_features]
+        features_list = await recco_client.get_audio_features(ids)
+
+        features_map = {}
+        for f in features_list:
+            tid = f.get("spotify_id") or f.get("id")
+            if tid:
+                features_map[tid] = f
+
+        for track in tracks_missing_features:
+            data = features_map.get(track.id)
+            if data:
+                track.danceability = data.get("danceability")
+                track.energy = data.get("energy")
+                track.key = data.get("key")
+                track.loudness = data.get("loudness")
+                track.mode = data.get("mode")
+                track.speechiness = data.get("speechiness")
+                track.acousticness = data.get("acousticness")
+                track.instrumentalness = data.get("instrumentalness")
+                track.liveness = data.get("liveness")
+                track.valence = data.get("valence")
+                track.tempo = data.get("tempo")
+
+        db.commit()
+
+    artists_missing_data = (
+        db.query(Artist)
+        .filter((Artist.genres == None) | (Artist.image_url == None))
+        .limit(50)
+        .all()
+    )
+    if artists_missing_data:
+        print(f"Enriching {len(artists_missing_data)} artists with genres/images...")
+        artist_ids_list = [str(a.id) for a in artists_missing_data]
+
+        artist_data_map = {}
+        for i in range(0, len(artist_ids_list), 50):
+            chunk = artist_ids_list[i : i + 50]
+            artists_data = await spotify_client.get_artists(chunk)
+            for a_data in artists_data:
+                if a_data:
+                    img = a_data["images"][0]["url"] if a_data.get("images") else None
+                    artist_data_map[a_data["id"]] = {
+                        "genres": a_data.get("genres", []),
+                        "image_url": img,
+                    }
+
+        for artist in artists_missing_data:
+            data = artist_data_map.get(artist.id)
+            if data:
+                if artist.genres is None:
+                    artist.genres = data["genres"]
+                if artist.image_url is None:
+                    artist.image_url = data["image_url"]
+            elif artist.genres is None:
+                artist.genres = []
+
+        db.commit()
+
+    tracks_missing_lyrics = (
+        db.query(Track)
+        .filter(Track.lyrics == None)
+        .order_by(Track.updated_at.desc())
+        .limit(10)
+        .all()
+    )
+
+    if tracks_missing_lyrics and genius_client.genius:
+        print(f"Enriching {len(tracks_missing_lyrics)} tracks with lyrics (Genius)...")
+        for track in tracks_missing_lyrics:
+            artist_name = str(track.artist).split(",")[0]
+
+            print(f"Searching Genius for: {track.name} by {artist_name}")
+            data = genius_client.search_song(str(track.name), artist_name)
+
+            if data:
+                track.lyrics = data["lyrics"]
+                if not track.image_url and data.get("image_url"):
+                    track.image_url = data["image_url"]
+            else:
+                track.lyrics = ""
+
+        db.commit()
+
+
 async def ingest_recently_played(db: Session):
-    client = get_spotify_client()
+    spotify_client = get_spotify_client()
+    recco_client = get_reccobeats_client()
+    genius_client = get_genius_client()
+
     try:
-        items = await client.get_recently_played(limit=50)
+        items = await spotify_client.get_recently_played(limit=50)
     except Exception as e:
         print(f"Error connecting to Spotify: {e}")
         return
@@ -30,52 +171,258 @@ async def ingest_recently_played(db: Session):
         played_at_str = item["played_at"]
         played_at = parser.isoparse(played_at_str)
 
-        # 1. Check if track exists, if not create it
         track_id = track_data["id"]
         track = db.query(Track).filter(Track.id == track_id).first()
 
         if not track:
             print(f"New track found: {track_data['name']}")
+
+            image_url = None
+            if track_data.get("album") and track_data["album"].get("images"):
+                image_url = track_data["album"]["images"][0]["url"]
+
             track = Track(
                 id=track_id,
                 name=track_data["name"],
                 artist=", ".join([a["name"] for a in track_data["artists"]]),
                 album=track_data["album"]["name"],
+                image_url=image_url,
                 duration_ms=track_data["duration_ms"],
                 popularity=track_data["popularity"],
-                raw_data=track_data
+                raw_data=track_data,
             )
-            db.add(track)
-            db.commit() # Commit immediately so ID exists for foreign key
 
-        # 2. Check if this specific play instance exists
-        # We assume (track_id, played_at) is unique enough
-        exists = db.query(PlayHistory).filter(
-            PlayHistory.track_id == track_id,
-            PlayHistory.played_at == played_at
-        ).first()
+            artists_data = track_data.get("artists", [])
+            artist_objects = await ensure_artists_exist(db, artists_data)
+            track.artists = artist_objects
+
+            db.add(track)
+            db.commit()
+
+        if not track.artists and track.raw_data and "artists" in track.raw_data:
+            artist_objects = await ensure_artists_exist(db, track.raw_data["artists"])
+            track.artists = artist_objects
+            db.commit()
+
+        exists = (
+            db.query(PlayHistory)
+            .filter(
+                PlayHistory.track_id == track_id, PlayHistory.played_at == played_at
+            )
+            .first()
+        )
 
         if not exists:
             print(f" recording play: {track_data['name']} at {played_at}")
             play = PlayHistory(
                 track_id=track_id,
                 played_at=played_at,
-                context_uri=item.get("context", {}).get("uri") if item.get("context") else None
+                context_uri=item.get("context", {}).get("uri")
+                if item.get("context")
+                else None,
+                source="recently_played",
             )
             db.add(play)
 
     db.commit()
 
+    await enrich_tracks(db, spotify_client, recco_client, genius_client)
+
+
 async def run_worker():
-    """Simulates a background worker loop."""
     db = SessionLocal()
+    tracker = PlaybackTracker()
+    spotify_client = get_spotify_client()
+    playlist_service = PlaylistService(
+        db=db,
+        spotify_client=spotify_client,
+        recco_client=get_reccobeats_client(),
+        narrative_service=NarrativeService(),
+    )
+    poll_count = 0
+    last_6h_refresh = 0
+    last_daily_refresh = 0
+
     try:
         while True:
-            print("Worker: Polling Spotify...")
-            await ingest_recently_played(db)
-            print("Worker: Sleeping for 60 seconds...")
-            await asyncio.sleep(60)
+            poll_count += 1
+            now = datetime.utcnow()
+
+            await poll_currently_playing(db, spotify_client, tracker)
+
+            if poll_count % 4 == 0:
+                print("Worker: Polling recently-played...")
+                await ingest_recently_played(db)
+
+            current_hour = now.hour
+            if current_hour in [3, 9, 15, 21] and (
+                time.time() - last_6h_refresh > 3600
+            ):
+                print(f"Worker: Triggering 6-hour playlist refresh at {now}")
+                try:
+                    await playlist_service.curate_six_hour_playlist(
+                        now - timedelta(hours=6), now
+                    )
+                    last_6h_refresh = time.time()
+                except Exception as e:
+                    print(f"6h Refresh Error: {e}")
+
+            if current_hour == 4 and (time.time() - last_daily_refresh > 80000):
+                print(
+                    f"Worker: Triggering daily playlist refresh and analysis at {now}"
+                )
+                try:
+                    stats_service = StatsService(db)
+                    stats_json = stats_service.generate_full_report(
+                        now - timedelta(days=1), now
+                    )
+                    narrative_service = NarrativeService()
+                    narrative_json = narrative_service.generate_full_narrative(
+                        stats_json
+                    )
+
+                    snapshot = AnalysisSnapshot(
+                        period_start=now - timedelta(days=1),
+                        period_end=now,
+                        period_label="daily_auto",
+                        metrics_payload=stats_json,
+                        narrative_report=narrative_json,
+                    )
+                    db.add(snapshot)
+                    db.commit()
+
+                    await playlist_service.curate_daily_playlist(
+                        now - timedelta(days=1), now
+                    )
+                    last_daily_refresh = time.time()
+                except Exception as e:
+                    print(f"Daily Refresh Error: {e}")
+
+            await asyncio.sleep(15)
     except Exception as e:
         print(f"Worker crashed: {e}")
     finally:
         db.close()
+
+
+async def poll_currently_playing(
+    db: Session, spotify_client: SpotifyClient, tracker: PlaybackTracker
+):
+    try:
+        response = await spotify_client.get_currently_playing()
+    except Exception as e:
+        print(f"Error polling currently-playing: {e}")
+        return
+
+    now = datetime.utcnow()
+
+    if not response or response.get("currently_playing_type") != "track":
+        if tracker.current_track_id and tracker.last_poll_time:
+            finalize_track(db, tracker)
+        return
+
+    item = response.get("item")
+    if not item:
+        return
+
+    current_track_id = item["id"]
+    current_progress_ms = response.get("progress_ms", 0)
+    is_playing = response.get("is_playing", False)
+
+    if current_track_id != tracker.current_track_id:
+        if tracker.current_track_id and tracker.last_poll_time:
+            finalize_track(db, tracker)
+
+        tracker.current_track_id = current_track_id
+        tracker.track_start_time = now - timedelta(milliseconds=current_progress_ms)
+        tracker.accumulated_listen_ms = current_progress_ms if is_playing else 0
+        tracker.last_progress_ms = current_progress_ms
+        tracker.last_poll_time = now
+        tracker.is_paused = not is_playing
+
+        await ensure_track_exists(db, item, spotify_client)
+    else:
+        if tracker.last_poll_time:
+            time_delta_ms = (now - tracker.last_poll_time).total_seconds() * 1000
+            if is_playing and not tracker.is_paused:
+                tracker.accumulated_listen_ms += time_delta_ms
+
+        tracker.last_progress_ms = current_progress_ms
+        tracker.last_poll_time = now
+        tracker.is_paused = not is_playing
+
+
+def finalize_track(db: Session, tracker: PlaybackTracker):
+    listened_ms = int(tracker.accumulated_listen_ms)
+    skipped = listened_ms < 30000
+
+    if tracker.track_start_time is None:
+        return
+
+    existing = (
+        db.query(PlayHistory)
+        .filter(
+            PlayHistory.track_id == tracker.current_track_id,
+            PlayHistory.played_at >= tracker.track_start_time - timedelta(seconds=5),
+            PlayHistory.played_at <= tracker.track_start_time + timedelta(seconds=5),
+        )
+        .first()
+    )
+
+    if existing:
+        if existing.listened_ms is None:
+            existing.listened_ms = listened_ms
+            existing.skipped = skipped
+            existing.source = "currently_playing"
+            db.commit()
+    else:
+        play = PlayHistory(
+            track_id=tracker.current_track_id,
+            played_at=tracker.track_start_time,
+            listened_ms=listened_ms,
+            skipped=skipped,
+            source="currently_playing",
+        )
+        db.add(play)
+        db.commit()
+
+    print(
+        f"Finalized: {tracker.current_track_id} listened={listened_ms}ms skipped={skipped}"
+    )
+
+    tracker.current_track_id = None
+    tracker.track_start_time = None
+    tracker.accumulated_listen_ms = 0
+    tracker.last_progress_ms = 0
+    tracker.last_poll_time = None
+    tracker.is_paused = False
+
+
+async def ensure_track_exists(
+    db: Session, track_data: dict, spotify_client: SpotifyClient
+):
+    track_id = track_data["id"]
+    track = db.query(Track).filter(Track.id == track_id).first()
+
+    if not track:
+        image_url = None
+        if track_data.get("album") and track_data["album"].get("images"):
+            image_url = track_data["album"]["images"][0]["url"]
+
+        track = Track(
+            id=track_id,
+            name=track_data["name"],
+            artist=", ".join([a["name"] for a in track_data.get("artists", [])]),
+            album=track_data.get("album", {}).get("name", "Unknown"),
+            image_url=image_url,
+            duration_ms=track_data.get("duration_ms"),
+            popularity=track_data.get("popularity"),
+            raw_data=track_data,
+        )
+
+        artists_data = track_data.get("artists", [])
+        artist_objects = await ensure_artists_exist(db, artists_data)
+        track.artists = artist_objects
+
+        db.add(track)
+        db.commit()

backend/app/main.py

@@ -1,36 +1,369 @@
-from fastapi import FastAPI, Depends
-from sqlalchemy.orm import Session
-from .database import engine, Base, get_db
-from .models import PlayHistory as PlayHistoryModel, Track as TrackModel
-from . import schemas
-from .ingest import ingest_recently_played
-import asyncio
-from typing import List
+import os
+from fastapi import FastAPI, Depends, HTTPException, BackgroundTasks, Query
+from sqlalchemy.orm import Session, joinedload
+from datetime import datetime, timedelta
+from typing import List, Optional
 from dotenv import load_dotenv
 
+from .database import engine, Base, get_db
+from .models import (
+    PlayHistory as PlayHistoryModel,
+    Track as TrackModel,
+    AnalysisSnapshot,
+    PlaylistConfig,
+)
+from . import schemas
+from .ingest import (
+    ingest_recently_played,
+    get_spotify_client,
+    get_reccobeats_client,
+    get_genius_client,
+)
+from .services.stats_service import StatsService
+from .services.narrative_service import NarrativeService
+from .services.playlist_service import PlaylistService
+
 load_dotenv()
 
-# Create tables
 Base.metadata.create_all(bind=engine)
 
+from fastapi.middleware.cors import CORSMiddleware
+
 app = FastAPI(title="Music Analyser Backend")
 
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["http://localhost:5173", "http://localhost:8991"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
 @app.get("/")
 def read_root():
     return {"status": "ok", "message": "Music Analyser API is running"}
 
+
 @app.get("/history", response_model=List[schemas.PlayHistory])
 def get_history(limit: int = 50, db: Session = Depends(get_db)):
-    history = db.query(PlayHistoryModel).order_by(PlayHistoryModel.played_at.desc()).limit(limit).all()
+    history = (
+        db.query(PlayHistoryModel)
+        .order_by(PlayHistoryModel.played_at.desc())
+        .limit(limit)
+        .all()
+    )
     return history
 
-@app.post("/trigger-ingest")
-async def trigger_ingest(db: Session = Depends(get_db)):
-    """Manually trigger the ingestion process (useful for testing)"""
-    await ingest_recently_played(db)
-    return {"status": "Ingestion triggered"}
 
 @app.get("/tracks", response_model=List[schemas.Track])
 def get_tracks(limit: int = 50, db: Session = Depends(get_db)):
     tracks = db.query(TrackModel).limit(limit).all()
     return tracks
+
+
+@app.post("/trigger-ingest")
+async def trigger_ingest(
+    background_tasks: BackgroundTasks, db: Session = Depends(get_db)
+):
+    """Triggers Spotify ingestion in the background."""
+    background_tasks.add_task(ingest_recently_played, db)
+    return {"status": "Ingestion started in background"}
+
+
+@app.post("/trigger-analysis")
+def trigger_analysis(
+    days: int = 30,
+    model_name: str = "gpt-5-mini-2025-08-07",
+    db: Session = Depends(get_db),
+):
+    """
+    Runs the full analysis pipeline (Stats + LLM) for the last X days.
+    Returns the computed metrics and narrative immediately.
+    """
+    try:
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=days)
+
+        # 1. Compute Stats
+        stats_service = StatsService(db)
+        stats_json = stats_service.generate_full_report(start_date, end_date)
+
+        if stats_json["volume"]["total_plays"] == 0:
+            raise HTTPException(
+                status_code=404, detail="No plays found in the specified period."
+            )
+
+        narrative_service = NarrativeService(model_name=model_name)
+        narrative_json = narrative_service.generate_full_narrative(stats_json)
+
+        # 3. Save Snapshot
+        snapshot = AnalysisSnapshot(
+            period_start=start_date,
+            period_end=end_date,
+            period_label=f"last_{days}_days",
+            metrics_payload=stats_json,
+            narrative_report=narrative_json,
+            model_used=model_name,
+        )
+        db.add(snapshot)
+        db.commit()
+        db.refresh(snapshot)
+
+        return {
+            "status": "success",
+            "snapshot_id": snapshot.id,
+            "period": {"start": start_date, "end": end_date},
+            "metrics": stats_json,
+            "narrative": narrative_json,
+        }
+
+    except HTTPException:
+        raise  # Re-raise HTTPExceptions as-is (404, etc.)
+    except Exception as e:
+        print(f"Analysis Failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/snapshots")
+def get_snapshots(limit: int = 10, db: Session = Depends(get_db)):
+    return (
+        db.query(AnalysisSnapshot)
+        .order_by(AnalysisSnapshot.date.desc())
+        .limit(limit)
+        .all()
+    )
+
+
+@app.get("/listening-log")
+def get_listening_log(
+    days: int = Query(default=7, ge=1, le=365),
+    limit: int = Query(default=200, ge=1, le=1000),
+    db: Session = Depends(get_db),
+):
+    end_date = datetime.utcnow()
+    start_date = end_date - timedelta(days=days)
+
+    plays = (
+        db.query(PlayHistoryModel)
+        .options(joinedload(PlayHistoryModel.track))
+        .filter(
+            PlayHistoryModel.played_at >= start_date,
+            PlayHistoryModel.played_at <= end_date,
+        )
+        .order_by(PlayHistoryModel.played_at.desc())
+        .limit(limit)
+        .all()
+    )
+
+    result = []
+    for i, play in enumerate(plays):
+        track = play.track
+        listened_ms = play.listened_ms
+        skipped = play.skipped
+
+        if listened_ms is None and i < len(plays) - 1:
+            next_play = plays[i + 1]
+            diff_seconds = (play.played_at - next_play.played_at).total_seconds()
+            if track and track.duration_ms:
+                duration_sec = track.duration_ms / 1000.0
+                listened_ms = int(min(diff_seconds, duration_sec) * 1000)
+                skipped = diff_seconds < 30
+
+        result.append(
+            {
+                "id": play.id,
+                "track_id": play.track_id,
+                "track_name": track.name if track else "Unknown",
+                "artist": track.artist if track else "Unknown",
+                "album": track.album if track else "Unknown",
+                "image": track.image_url if track else None,
+                "played_at": play.played_at.isoformat(),
+                "duration_ms": track.duration_ms if track else 0,
+                "listened_ms": listened_ms,
+                "skipped": skipped,
+                "context_uri": play.context_uri,
+                "source": play.source,
+            }
+        )
+
+    return {
+        "plays": result,
+        "period": {"start": start_date.isoformat(), "end": end_date.isoformat()},
+    }
+
+
+@app.get("/sessions")
+def get_sessions(
+    days: int = Query(default=7, ge=1, le=365), db: Session = Depends(get_db)
+):
+    end_date = datetime.utcnow()
+    start_date = end_date - timedelta(days=days)
+
+    stats_service = StatsService(db)
+    session_stats = stats_service.compute_session_stats(start_date, end_date)
+
+    return {
+        "sessions": session_stats.get("session_list", []),
+        "summary": {
+            "count": session_stats.get("count", 0),
+            "avg_minutes": session_stats.get("avg_minutes", 0),
+            "micro_rate": session_stats.get("micro_session_rate", 0),
+            "marathon_rate": session_stats.get("marathon_session_rate", 0),
+        },
+    }
+
+
+@app.post("/playlists/refresh/six-hour")
+async def refresh_six_hour_playlist(db: Session = Depends(get_db)):
+    """Triggers a 6-hour themed playlist refresh."""
+    try:
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(hours=6)
+
+        spotify_client = get_spotify_client()
+        playlist_service = PlaylistService(
+            db=db,
+            spotify_client=spotify_client,
+            recco_client=get_reccobeats_client(),
+            narrative_service=NarrativeService(),
+        )
+
+        # Ensure playlists exist (creates on Spotify if needed)
+        user_id = await spotify_client.get_current_user_id()
+        await playlist_service.ensure_playlists_exist(user_id)
+
+        result = await playlist_service.curate_six_hour_playlist(start_date, end_date)
+
+        snapshot = AnalysisSnapshot(
+            date=datetime.utcnow(),
+            period_start=start_date,
+            period_end=end_date,
+            period_label="6h_refresh",
+            metrics_payload={},
+            narrative_report={},
+            playlist_theme=result.get("theme_name"),
+            playlist_theme_reasoning=result.get("description"),
+            six_hour_playlist_id=result.get("playlist_id"),
+            playlist_composition=result.get("composition"),
+        )
+        db.add(snapshot)
+        db.commit()
+
+        return result
+    except Exception as e:
+        print(f"Playlist Refresh Failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/playlists/refresh/daily")
+async def refresh_daily_playlist(db: Session = Depends(get_db)):
+    """Triggers a 24-hour daily playlist refresh."""
+    try:
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=1)
+
+        spotify_client = get_spotify_client()
+        playlist_service = PlaylistService(
+            db=db,
+            spotify_client=spotify_client,
+            recco_client=get_reccobeats_client(),
+            narrative_service=NarrativeService(),
+        )
+
+        # Ensure playlists exist (creates on Spotify if needed)
+        user_id = await spotify_client.get_current_user_id()
+        await playlist_service.ensure_playlists_exist(user_id)
+
+        result = await playlist_service.curate_daily_playlist(start_date, end_date)
+
+        snapshot = AnalysisSnapshot(
+            date=datetime.utcnow(),
+            period_start=start_date,
+            period_end=end_date,
+            period_label="24h_refresh",
+            metrics_payload={},
+            narrative_report={},
+            daily_playlist_id=result.get("playlist_id"),
+            playlist_composition=result.get("composition"),
+        )
+        db.add(snapshot)
+        db.commit()
+
+        return result
+    except Exception as e:
+        print(f"Daily Playlist Refresh Failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/playlists")
+async def get_playlists_metadata(db: Session = Depends(get_db)):
+    """Returns metadata for the managed playlists."""
+
+    six_hour_config = (
+        db.query(PlaylistConfig).filter(PlaylistConfig.key == "six_hour").first()
+    )
+    daily_config = (
+        db.query(PlaylistConfig).filter(PlaylistConfig.key == "daily").first()
+    )
+
+    return {
+        "six_hour": {
+            "id": six_hour_config.spotify_id
+            if six_hour_config
+            else os.getenv("SIX_HOUR_PLAYLIST_ID"),
+            "theme": six_hour_config.current_theme if six_hour_config else "N/A",
+            "reasoning": six_hour_config.description if six_hour_config else "N/A",
+            "last_refresh": six_hour_config.last_updated.isoformat()
+            if six_hour_config
+            else None,
+            "composition": six_hour_config.composition if six_hour_config else [],
+        },
+        "daily": {
+            "id": daily_config.spotify_id
+            if daily_config
+            else os.getenv("DAILY_PLAYLIST_ID"),
+            "theme": daily_config.current_theme if daily_config else "N/A",
+            "reasoning": daily_config.description if daily_config else "N/A",
+            "last_refresh": daily_config.last_updated.isoformat()
+            if daily_config
+            else None,
+            "composition": daily_config.composition if daily_config else [],
+        },
+    }
+
+
+@app.get("/playlists/history")
+def get_playlist_history(
+    limit: int = Query(default=20, ge=1, le=100),
+    db: Session = Depends(get_db),
+):
+    """Returns historical playlist snapshots."""
+    snapshots = (
+        db.query(AnalysisSnapshot)
+        .filter(
+            (AnalysisSnapshot.playlist_theme.isnot(None))
+            | (AnalysisSnapshot.six_hour_playlist_id.isnot(None))
+            | (AnalysisSnapshot.daily_playlist_id.isnot(None))
+        )
+        .order_by(AnalysisSnapshot.date.desc())
+        .limit(limit)
+        .all()
+    )
+
+    result = []
+    for snap in snapshots:
+        result.append(
+            {
+                "id": snap.id,
+                "date": snap.date.isoformat() if snap.date else None,
+                "period_label": snap.period_label,
+                "theme": snap.playlist_theme,
+                "reasoning": snap.playlist_theme_reasoning,
+                "six_hour_id": snap.six_hour_playlist_id,
+                "daily_id": snap.daily_playlist_id,
+                "composition": snap.playlist_composition or [],
+            }
+        )
+
+    return {"history": result}

backend/app/models.py

@@ -1,29 +1,85 @@
-from sqlalchemy import Column, Integer, String, DateTime, JSON, ForeignKey, Boolean
+from sqlalchemy import (
+    Boolean,
+    Column,
+    Integer,
+    String,
+    DateTime,
+    JSON,
+    ForeignKey,
+    Float,
+    Table,
+    Text,
+)
 from sqlalchemy.orm import relationship
 from datetime import datetime
 from .database import Base
 
+# Association Table for Many-to-Many Relationship between Track and Artist
+track_artists = Table(
+    "track_artists",
+    Base.metadata,
+    Column("track_id", String, ForeignKey("tracks.id"), primary_key=True),
+    Column("artist_id", String, ForeignKey("artists.id"), primary_key=True),
+)
+
+
+class Artist(Base):
+    __tablename__ = "artists"
+
+    id = Column(String, primary_key=True, index=True)  # Spotify ID
+    name = Column(String)
+    genres = Column(JSON, nullable=True)  # List of genre strings
+    image_url = Column(String, nullable=True)  # Artist profile image
+
+    # Relationships
+    tracks = relationship("Track", secondary=track_artists, back_populates="artists")
+
+
 class Track(Base):
     __tablename__ = "tracks"
 
-    id = Column(String, primary_key=True, index=True) # Spotify ID
+    id = Column(String, primary_key=True, index=True)  # Spotify ID
+    reccobeats_id = Column(String, nullable=True, index=True)  # ReccoBeats UUID
     name = Column(String)
-    artist = Column(String)
+    artist = Column(
+        String
+    )  # Display string (e.g. "Drake, Future") - kept for convenience
     album = Column(String)
+    image_url = Column(String, nullable=True)  # Album art
     duration_ms = Column(Integer)
     popularity = Column(Integer, nullable=True)
 
     # Store raw full JSON response for future-proofing analysis
     raw_data = Column(JSON, nullable=True)
 
+    # Enriched Data (Phase 3 Prep)
+    # Audio Features
+    danceability = Column(Float, nullable=True)
+    energy = Column(Float, nullable=True)
+    key = Column(Integer, nullable=True)
+    loudness = Column(Float, nullable=True)
+    mode = Column(Integer, nullable=True)
+    speechiness = Column(Float, nullable=True)
+    acousticness = Column(Float, nullable=True)
+    instrumentalness = Column(Float, nullable=True)
+    liveness = Column(Float, nullable=True)
+    valence = Column(Float, nullable=True)
+    tempo = Column(Float, nullable=True)
+    time_signature = Column(Integer, nullable=True)
+
+    # Genres (stored as JSON list of strings) - DEPRECATED in favor of Artist.genres but kept for now
+    genres = Column(JSON, nullable=True)
+
     # AI Analysis fields
+    lyrics = Column(Text, nullable=True)  # Full lyrics from Genius
     lyrics_summary = Column(String, nullable=True)
-    genre_tags = Column(String, nullable=True) # JSON list stored as string or just raw JSON
+    genre_tags = Column(String, nullable=True)
 
     created_at = Column(DateTime, default=datetime.utcnow)
     updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
 
     plays = relationship("PlayHistory", back_populates="track")
+    artists = relationship("Artist", secondary=track_artists, back_populates="tracks")
 
 
 class PlayHistory(Base):
@@ -31,9 +87,61 @@ class PlayHistory(Base):
 
     id = Column(Integer, primary_key=True, index=True)
     track_id = Column(String, ForeignKey("tracks.id"))
-    played_at = Column(DateTime, index=True) # The timestamp from Spotify
-
-    # Context (album, playlist, etc.)
+    played_at = Column(DateTime, index=True)
     context_uri = Column(String, nullable=True)
 
+    listened_ms = Column(Integer, nullable=True)
+    skipped = Column(Boolean, nullable=True)
+    source = Column(String, nullable=True)
+
     track = relationship("Track", back_populates="plays")
+
+
+class AnalysisSnapshot(Base):
+    """
+    Stores the computed statistics and LLM analysis for a given period.
+    Allows for trend analysis over time.
+    """
+
+    __tablename__ = "analysis_snapshots"
+
+    id = Column(Integer, primary_key=True, index=True)
+    date = Column(
+        DateTime, default=datetime.utcnow, index=True
+    )  # When the analysis was run
+    period_start = Column(DateTime)
+    period_end = Column(DateTime)
+    period_label = Column(String)  # e.g., "last_30_days", "monthly_nov_2023"
+
+    # The heavy lifting: stored as JSON blobs
+    metrics_payload = Column(JSON)  # The input to the LLM (StatsService output)
+    narrative_report = Column(JSON)  # The output from the LLM (NarrativeService output)
+
+    model_used = Column(String, nullable=True)  # e.g. "gemini-1.5-flash"
+    playlist_theme = Column(
+        String, nullable=True
+    )  # AI-generated theme name (e.g., "Morning Focus Mode")
+    playlist_theme_reasoning = Column(
+        Text, nullable=True
+    )  # AI explanation for why this theme
+    six_hour_playlist_id = Column(
+        String, nullable=True
+    )  # Spotify playlist ID for 6-hour playlist
+    daily_playlist_id = Column(
+        String, nullable=True
+    )  # Spotify playlist ID for 24-hour playlist
+    playlist_composition = Column(JSON, nullable=True)
+    playlist_composition = Column(
+        JSON, nullable=True
+    )  # Store the track list at this snapshot
+
+
+class PlaylistConfig(Base):
+    __tablename__ = "playlist_config"
+
+    key = Column(String, primary_key=True, index=True)  # e.g., "six_hour", "daily"
+    spotify_id = Column(String, nullable=False)
+    last_updated = Column(DateTime, default=datetime.utcnow)
+    current_theme = Column(String, nullable=True)
+    description = Column(String, nullable=True)
+    composition = Column(JSON, nullable=True)

backend/app/schemas.py

@@ -12,6 +12,19 @@ class TrackBase(BaseModel):
     lyrics_summary: Optional[str] = None
     genre_tags: Optional[str] = None
 
+    # Audio Features
+    danceability: Optional[float] = None
+    energy: Optional[float] = None
+    valence: Optional[float] = None
+    tempo: Optional[float] = None
+    key: Optional[int] = None
+    mode: Optional[int] = None
+    acousticness: Optional[float] = None
+    instrumentalness: Optional[float] = None
+    liveness: Optional[float] = None
+    speechiness: Optional[float] = None
+    loudness: Optional[float] = None
+
 class Track(TrackBase):
     created_at: datetime
     updated_at: datetime

backend/app/services/AGENTS.md

@@ -0,0 +1,40 @@
+# SERVICES KNOWLEDGE BASE
+
+**Target:** `backend/app/services/`
+**Context:** Central business logic, 7+ specialized services, LLM integration.
+
+## OVERVIEW
+
+Core logic hub transforming raw music data into metrics, playlists, and AI narratives.
+
+- **Data Ingress/Egress**: `SpotifyClient` (OAuth/Player), `GeniusClient` (Lyrics), `ReccoBeatsClient` (Audio Features).
+- **Analytics**: `StatsService` (HHI, Gini, clustering, heatmaps, skip detection).
+- **AI/Narrative**: `NarrativeService` (LLM prompt engineering, multi-provider support), `AIService` (Simple Gemini analysis).
+- **Orchestration**: `PlaylistService` (AI-curated dynamic playlist generation).
+
+## WHERE TO LOOK
+
+| Service | File | Key Responsibilities |
+|---------|------|----------------------|
+| **Analytics** | `stats_service.py` | Metrics (Volume, Vibe, Time, Taste, LifeCycle). |
+| **Spotify** | `spotify_client.py` | Auth, Player API, Playlist CRUD. |
+| **Narrative** | `narrative_service.py` | LLM payload shaping, system prompts, JSON parsing. |
+| **Playlists** | `playlist_service.py` | Periodic curation logic (6h/24h cycles). |
+| **Enrichment** | `reccobeats_client.py` | External audio features (energy, valence). |
+| **Lyrics** | `genius_client.py` | Song/Artist metadata & lyrics search. |
+
+## CONVENTIONS
+
+- **Async Everywhere**: All external API clients (`Spotify`, `ReccoBeats`) use `httpx.AsyncClient`.
+- **Stat Modularization**: `StatsService` splits logic into `compute_X_stats` methods; returns serializable dicts.
+- **Provider Agnostic AI**: `NarrativeService` detects `OPENAI_API_KEY` vs `GEMINI_API_KEY` automatically.
+- **Payload Shaping**: AI services aggressively prune stats JSON before sending to LLM to save tokens.
+- **Fallbacks**: All AI/External calls have explicit fallback/empty return states.
+
+## ANTI-PATTERNS
+
+- **Blocking I/O**: `GeniusClient` is synchronous; avoid calling in hot async paths.
+- **Service Circularity**: `PlaylistService` depends on `StatsService`. Avoid reversing this.
+- **N+1 DB Hits**: Aggregations in `StatsService` should use `joinedload` or batch queries.
+- **Missing Checksums**: Audio features assume presence; always check for `None` before math.
+- **Token Waste**: Never pass raw DB models to `NarrativeService`; use shaped dicts.

backend/app/services/genius_client.py

@@ -0,0 +1,103 @@
+import os
+import requests
+from typing import Optional, Dict, Any
+import re
+
+
+class GeniusClient:
+    def __init__(self):
+        self.access_token = os.getenv("GENIUS_ACCESS_TOKEN")
+        self.base_url = "https://api.genius.com"
+        self.headers = (
+            {"Authorization": f"Bearer {self.access_token}"}
+            if self.access_token
+            else {}
+        )
+
+        if not self.access_token:
+            print(
+                "WARNING: GENIUS_ACCESS_TOKEN not found. Lyrics enrichment will be skipped."
+            )
+            self.genius = None
+        else:
+            self.genius = True
+
+    def search_song(self, title: str, artist: str) -> Optional[Dict[str, Any]]:
+        if not self.genius:
+            return None
+
+        try:
+            clean_title = title.split(" - ")[0].split("(")[0].strip()
+            query = f"{clean_title} {artist}"
+
+            response = requests.get(
+                f"{self.base_url}/search",
+                headers=self.headers,
+                params={"q": query},
+                timeout=10,
+            )
+
+            if response.status_code != 200:
+                print(f"Genius API Error: {response.status_code}")
+                return None
+
+            data = response.json()
+            hits = data.get("response", {}).get("hits", [])
+
+            if not hits:
+                return None
+
+            song = hits[0]["result"]
+
+            lyrics = self._scrape_lyrics(song.get("url")) if song.get("url") else None
+
+            return {
+                "lyrics": lyrics,
+                "image_url": song.get("song_art_image_url")
+                or song.get("header_image_url"),
+                "artist_image_url": song.get("primary_artist", {}).get("image_url"),
+            }
+        except Exception as e:
+            print(f"Genius Search Error for {title} by {artist}: {e}")
+
+        return None
+
+    def _scrape_lyrics(self, url: str) -> Optional[str]:
+        try:
+            headers = {
+                "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
+                "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
+                "Accept-Language": "en-US,en;q=0.5",
+            }
+            response = requests.get(url, headers=headers, timeout=10)
+
+            if response.status_code != 200:
+                return None
+
+            html = response.text
+
+            lyrics_divs = re.findall(
+                r'<div[^>]*data-lyrics-container="true"[^>]*>(.*?)</div>',
+                html,
+                re.DOTALL,
+            )
+
+            if not lyrics_divs:
+                return None
+
+            lyrics = ""
+            for div in lyrics_divs:
+                text = re.sub(r"<br\s*/?>", "\n", div)
+                text = re.sub(r"<[^>]+>", "", text)
+                text = (
+                    text.replace("&amp;", "&")
+                    .replace("&quot;", '"')
+                    .replace("&#x27;", "'")
+                )
+                lyrics += text + "\n"
+
+            return lyrics.strip() if lyrics.strip() else None
+
+        except Exception as e:
+            print(f"Lyrics scrape error: {e}")
+            return None

backend/app/services/narrative_service.py

@@ -0,0 +1,276 @@
+import os
+import json
+import re
+from typing import Dict, Any
+
+try:
+    from openai import OpenAI
+except ImportError:
+    OpenAI = None
+
+try:
+    from google import genai
+except ImportError:
+    genai = None
+
+
+class NarrativeService:
+    def __init__(self, model_name: str = "gpt-5-mini-2025-08-07"):
+        self.model_name = model_name
+        self.provider = self._detect_provider()
+        self.client = self._init_client()
+
+    def _detect_provider(self) -> str:
+        openai_key = os.getenv("OPENAI_API_KEY") or os.getenv("OPENAI_APIKEY")
+        gemini_key = os.getenv("GEMINI_API_KEY")
+
+        if self.model_name.startswith("gpt") and openai_key and OpenAI:
+            return "openai"
+        elif gemini_key and genai:
+            return "gemini"
+        elif openai_key and OpenAI:
+            return "openai"
+        elif gemini_key and genai:
+            return "gemini"
+        return "none"
+
+    def _init_client(self):
+        if self.provider == "openai":
+            api_key = os.getenv("OPENAI_API_KEY") or os.getenv("OPENAI_APIKEY")
+            return OpenAI(api_key=api_key)
+        elif self.provider == "gemini":
+            api_key = os.getenv("GEMINI_API_KEY")
+            return genai.Client(api_key=api_key)
+        return None
+
+    def generate_full_narrative(self, stats_json: Dict[str, Any]) -> Dict[str, Any]:
+        if not self.client:
+            print("WARNING: No LLM client available")
+            return self._get_fallback_narrative()
+
+        clean_stats = self._shape_payload(stats_json)
+        prompt = self._build_prompt(clean_stats)
+
+        try:
+            if self.provider == "openai":
+                return self._call_openai(prompt)
+            elif self.provider == "gemini":
+                return self._call_gemini(prompt)
+        except Exception as e:
+            print(f"LLM Generation Error: {e}")
+            return self._get_fallback_narrative()
+
+        return self._get_fallback_narrative()
+
+    def generate_playlist_theme(self, listening_data: Dict[str, Any]) -> Dict[str, Any]:
+        """Generate playlist theme based on daily listening patterns."""
+        if not self.client:
+            return self._get_fallback_theme()
+
+        prompt = self._build_theme_prompt(listening_data)
+
+        try:
+            if self.provider == "openai":
+                return self._call_openai_for_theme(prompt)
+            elif self.provider == "gemini":
+                return self._call_gemini_for_theme(prompt)
+        except Exception as e:
+            print(f"Theme generation error: {e}")
+            return self._get_fallback_theme()
+
+        return self._get_fallback_theme()
+
+    def _call_openai_for_theme(self, prompt: str) -> Dict[str, Any]:
+        response = self.client.chat.completions.create(
+            model=self.model_name,
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a specialized music curator. Output only valid JSON.",
+                },
+                {"role": "user", "content": prompt},
+            ],
+            response_format={"type": "json_object"},
+        )
+        return self._clean_and_parse_json(response.choices[0].message.content)
+
+    def _call_gemini_for_theme(self, prompt: str) -> Dict[str, Any]:
+        response = self.client.models.generate_content(
+            model=self.model_name,
+            contents=prompt,
+            config=genai.types.GenerateContentConfig(
+                response_mime_type="application/json"
+            ),
+        )
+        return self._clean_and_parse_json(response.text)
+
+    def _build_theme_prompt(self, data: Dict[str, Any]) -> str:
+        return f"""Analyze this listening data from the last 6 hours and curate a specific "themed" playlist.
+
+**DATA:**
+- Peak hour: {data.get("peak_hour")}
+- Avg energy: {data.get("avg_energy"):.2f}
+- Avg valence: {data.get("avg_valence"):.2f}
+- Top artists: {", ".join([a["name"] for a in data.get("top_artists", [])])}
+- Total plays: {data.get("total_plays")}
+
+**RULES:**
+1. Create a "theme_name" (e.g. "Morning Coffee Jazz", "Midnight Deep Work").
+2. Provide a "description" (2-3 sentences explaining why).
+3. Identify 10-15 "curated_tracks" (song names only) that fit this vibe and the artists listed.
+4. Return ONLY valid JSON.
+5. Do NOT output internal variable names (e.g. 'part_of_day', 'avg_valence') in the description. Translate them to natural language (e.g. 'morning listens', 'happy vibe').
+
+**REQUIRED JSON:**
+{{
+  "theme_name": "String",
+  "description": "String",
+  "curated_tracks": ["Track 1", "Track 2", ...]
+}}"""
+
+    def _get_fallback_theme(self) -> Dict[str, Any]:
+        return {
+            "theme_name": "Daily Mix",
+            "description": "A curated mix of your recent favorites.",
+            "curated_tracks": [],
+        }
+
+    def _call_openai(self, prompt: str) -> Dict[str, Any]:
+        response = self.client.chat.completions.create(
+            model=self.model_name,
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a witty music critic. Output only valid JSON.",
+                },
+                {"role": "user", "content": prompt},
+            ],
+            response_format={"type": "json_object"},
+            max_completion_tokens=4000,
+        )
+        return self._clean_and_parse_json(response.choices[0].message.content)
+
+    def _call_gemini(self, prompt: str) -> Dict[str, Any]:
+        response = self.client.models.generate_content(
+            model=self.model_name,
+            contents=prompt,
+            config=genai.types.GenerateContentConfig(
+                response_mime_type="application/json"
+            ),
+        )
+        return self._clean_and_parse_json(response.text)
+
+    def _build_prompt(self, clean_stats: Dict[str, Any]) -> str:
+        volume = clean_stats.get("volume", {})
+        concentration = volume.get("concentration", {})
+        time_habits = clean_stats.get("time_habits", {})
+        vibe = clean_stats.get("vibe", {})
+        peak_hour = time_habits.get("peak_hour")
+        if isinstance(peak_hour, int):
+            peak_listening = f"{peak_hour}:00"
+        else:
+            peak_listening = peak_hour or "N/A"
+        concentration_score = (
+            round(concentration.get("hhi", 0), 3)
+            if concentration and concentration.get("hhi") is not None
+            else "N/A"
+        )
+        playlist_diversity = (
+            round(1 - concentration.get("hhi", 0), 3)
+            if concentration and concentration.get("hhi") is not None
+            else "N/A"
+        )
+        avg_energy = vibe.get("avg_energy", 0)
+        avg_valence = vibe.get("avg_valence", 0)
+        top_artists = volume.get("top_artists", [])
+        top_artists_str = ", ".join(top_artists) if top_artists else "N/A"
+        era_label = clean_stats.get("era", {}).get("musical_age", "N/A")
+
+        return f"""Analyze this Spotify listening data and generate a personalized report.
+
+**RULES:**
+1. NO mental health diagnoses. Use behavioral descriptors only.
+2. Be specific - reference actual metrics from the data.
+3. Be playful but not cruel.
+4. Return ONLY valid JSON.
+5. Translate all technical metrics (e.g. 'discovery_rate', 'valence', 'hhi') into natural language descriptions. Do NOT use the variable names themselves.
+
+**LISTENING HIGHLIGHTS:**
+- Peak listening: {peak_listening}
+- Concentration score: {concentration_score}
+- Playlist diversity: {playlist_diversity}
+- Average energy: {avg_energy:.2f}
+- Average valence: {avg_valence:.2f}
+- Top artists: {top_artists_str}
+
+**DATA:**
+{json.dumps(clean_stats, indent=2)}
+
+**REQUIRED JSON:**
+{{
+  "vibe_check_short": "1-2 sentence hook for the hero banner.",
+  "vibe_check": "2-3 paragraphs describing their overall listening personality.",
+  "patterns": ["Observation 1", "Observation 2", "Observation 3"],
+  "persona": "A creative label (e.g., 'The Genre Chameleon').",
+  "era_insight": "Comment on Musical Age ({era_label}).",
+  "roast": "1-2 sentence playful roast.",
+  "comparison": "Compare to previous period if data exists."
+}}"""
+
+    def _shape_payload(self, stats: Dict[str, Any]) -> Dict[str, Any]:
+        s = stats.copy()
+
+        if "volume" in s:
+            volume_copy = {
+                k: v
+                for k, v in s["volume"].items()
+                if k not in ["top_tracks", "top_artists", "top_albums", "top_genres"]
+            }
+            volume_copy["top_tracks"] = [
+                t["name"] for t in stats["volume"].get("top_tracks", [])[:5]
+            ]
+            volume_copy["top_artists"] = [
+                a["name"] for a in stats["volume"].get("top_artists", [])[:5]
+            ]
+            volume_copy["top_genres"] = [
+                g["name"] for g in stats["volume"].get("top_genres", [])[:5]
+            ]
+            s["volume"] = volume_copy
+
+        if "time_habits" in s:
+            s["time_habits"] = {
+                k: v for k, v in s["time_habits"].items() if k != "heatmap"
+            }
+
+        if "sessions" in s:
+            s["sessions"] = {
+                k: v for k, v in s["sessions"].items() if k != "session_list"
+            }
+
+        return s
+
+    def _clean_and_parse_json(self, raw_text: str) -> Dict[str, Any]:
+        try:
+            return json.loads(raw_text)
+        except json.JSONDecodeError:
+            pass
+
+        try:
+            match = re.search(r"\{.*\}", raw_text, re.DOTALL)
+            if match:
+                return json.loads(match.group(0))
+        except:
+            pass
+
+        return self._get_fallback_narrative()
+
+    def _get_fallback_narrative(self) -> Dict[str, Any]:
+        return {
+            "vibe_check_short": "Your taste is... interesting.",
+            "vibe_check": "Data processing error. You're too mysterious to analyze right now.",
+            "patterns": [],
+            "persona": "The Enigma",
+            "era_insight": "Time is a flat circle.",
+            "roast": "You broke the machine. Congratulations.",
+            "comparison": "N/A",
+        }

backend/app/services/playlist_service.py

@@ -0,0 +1,396 @@
+import os
+from typing import Dict, Any, List
+from datetime import datetime
+
+from sqlalchemy.orm import Session
+
+from .spotify_client import SpotifyClient
+from .reccobeats_client import ReccoBeatsClient
+from .narrative_service import NarrativeService
+
+
+class PlaylistService:
+    def __init__(
+        self,
+        db: Session,
+        spotify_client: SpotifyClient,
+        recco_client: ReccoBeatsClient,
+        narrative_service: NarrativeService,
+    ) -> None:
+        self.db = db
+        self.spotify = spotify_client
+        self.recco = recco_client
+        self.narrative = narrative_service
+
+    async def ensure_playlists_exist(self, user_id: str) -> Dict[str, str]:
+        """Check/create playlists. Returns {six_hour_id, daily_id}."""
+        from app.models import PlaylistConfig
+
+        six_hour_config = (
+            self.db.query(PlaylistConfig)
+            .filter(PlaylistConfig.key == "six_hour")
+            .first()
+        )
+        daily_config = (
+            self.db.query(PlaylistConfig).filter(PlaylistConfig.key == "daily").first()
+        )
+
+        six_hour_id = six_hour_config.spotify_id if six_hour_config else None
+        daily_id = daily_config.spotify_id if daily_config else None
+
+        if not six_hour_id:
+            six_hour_id = os.getenv("SIX_HOUR_PLAYLIST_ID")
+            if not six_hour_id:
+                six_hour_data = await self.spotify.create_playlist(
+                    user_id=user_id,
+                    name="Short and Sweet",
+                    description="AI-curated 6-hour playlists based on your listening habits",
+                )
+                six_hour_id = str(six_hour_data["id"])
+
+            self._save_playlist_config("six_hour", six_hour_id, "Short and Sweet")
+
+        if not daily_id:
+            daily_id = os.getenv("DAILY_PLAYLIST_ID")
+            if not daily_id:
+                daily_data = await self.spotify.create_playlist(
+                    user_id=user_id,
+                    name="Proof of Commitment",
+                    description="Your daily 24-hour mix showing your music journey",
+                )
+                daily_id = str(daily_data["id"])
+
+            self._save_playlist_config("daily", daily_id, "Proof of Commitment")
+
+        return {"six_hour_id": six_hour_id, "daily_id": daily_id}
+
+    def _save_playlist_config(
+        self,
+        key: str,
+        spotify_id: str,
+        description: str = None,
+        theme: str = None,
+        composition: List[Dict[str, Any]] = None,
+    ):
+        from app.models import PlaylistConfig
+
+        config = self.db.query(PlaylistConfig).filter(PlaylistConfig.key == key).first()
+        if not config:
+            config = PlaylistConfig(key=key, spotify_id=spotify_id)
+            self.db.add(config)
+        else:
+            config.spotify_id = spotify_id
+
+        if description:
+            config.description = description
+        if theme:
+            config.current_theme = theme
+        if composition:
+            config.composition = composition
+
+        config.last_updated = datetime.utcnow()
+        self.db.commit()
+
+    async def _hydrate_tracks(
+        self, track_ids: List[str], sources: Dict[str, str]
+    ) -> List[Dict[str, Any]]:
+        """Fetch full track details for a list of IDs."""
+        from app.models import Track
+
+        db_tracks = self.db.query(Track).filter(Track.id.in_(track_ids)).all()
+        track_map = {t.id: t for t in db_tracks}
+
+        missing_ids = [tid for tid in track_ids if tid not in track_map]
+
+        if missing_ids:
+            spotify_tracks = await self.spotify.get_tracks(missing_ids)
+            for st in spotify_tracks:
+                if not st:
+                    continue
+                track_map[st["id"]] = {
+                    "id": st["id"],
+                    "name": st["name"],
+                    "artist": ", ".join([a["name"] for a in st["artists"]]),
+                    "image": st["album"]["images"][0]["url"]
+                    if st["album"]["images"]
+                    else None,
+                    "uri": st["uri"],
+                }
+
+        result = []
+        for tid in track_ids:
+            track = track_map.get(tid)
+            if not track:
+                continue
+
+            if hasattr(track, "name") and not isinstance(track, dict):
+                track_data = {
+                    "id": track.id,
+                    "name": track.name,
+                    "artist": track.artist,
+                    "image": track.image_url,
+                    "uri": f"spotify:track:{track.id}",
+                }
+            else:
+                track_data = track
+
+            track_data["source"] = sources.get(tid, "unknown")
+            result.append(track_data)
+
+        return result
+
+    async def curate_six_hour_playlist(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        """Generate 6-hour playlist (15 curated + 15 recommendations)."""
+        from app.models import Track, PlayHistory
+        from app.services.stats_service import StatsService
+        from sqlalchemy import func
+
+        stats = StatsService(self.db)
+        data = stats.generate_full_report(period_start, period_end)
+
+        top_tracks_period = [t["id"] for t in data["volume"].get("top_tracks", [])][:15]
+
+        if len(top_tracks_period) < 5:
+            fallback_tracks = (
+                self.db.query(Track.id, func.count(PlayHistory.id).label("cnt"))
+                .join(PlayHistory, Track.id == PlayHistory.track_id)
+                .group_by(Track.id)
+                .order_by(func.count(PlayHistory.id).desc())
+                .limit(15)
+                .all()
+            )
+            top_tracks_period = [tid for tid, _ in fallback_tracks]
+
+        listening_data = {
+            "peak_hour": data["time_habits"].get("peak_hour", 12),
+            "avg_energy": data["vibe"].get("avg_energy", 0.5),
+            "avg_valence": data["vibe"].get("avg_valence", 0.5),
+            "total_plays": data["volume"].get("total_plays", 0),
+            "top_artists": data["volume"].get("top_artists", [])[:10],
+        }
+
+        theme_result = self.narrative.generate_playlist_theme(listening_data)
+
+        curated_details = []
+        for tid in top_tracks_period:
+            track_obj = self.db.query(Track).filter(Track.id == tid).first()
+            if track_obj:
+                curated_details.append(
+                    {
+                        "id": str(track_obj.id),
+                        "energy": track_obj.energy,
+                        "source": "history",
+                    }
+                )
+
+        rec_details = []
+        seed_ids = top_tracks_period[:5] if top_tracks_period else []
+        if seed_ids:
+            raw_recs = await self.recco.get_recommendations(
+                seed_ids=seed_ids,
+                size=15,
+            )
+            for r in raw_recs:
+                rec_id = str(r.get("spotify_id") or r.get("id"))
+                if rec_id:
+                    rec_details.append(
+                        {
+                            "id": rec_id,
+                            "energy": r.get("energy"),
+                            "source": "recommendation",
+                        }
+                    )
+
+        all_candidates = curated_details[:15] + rec_details[:15]
+        optimized_tracks = self._optimize_playlist_flow(all_candidates)
+
+        final_track_ids = [t["id"] for t in optimized_tracks]
+        sources = {t["id"]: t["source"] for t in optimized_tracks}
+
+        # Hydrate for persistence/display
+        full_tracks = await self._hydrate_tracks(final_track_ids, sources)
+
+        playlist_id = None
+        from app.models import PlaylistConfig
+
+        config = (
+            self.db.query(PlaylistConfig)
+            .filter(PlaylistConfig.key == "six_hour")
+            .first()
+        )
+        if config:
+            playlist_id = config.spotify_id
+
+        if not playlist_id:
+            playlist_id = os.getenv("SIX_HOUR_PLAYLIST_ID")
+
+        if playlist_id:
+            theme_name = f"Short and Sweet - {theme_result['theme_name']}"
+            desc = f"{theme_result['description']}\n\nCurated: {len(curated_details)} tracks + {len(rec_details)} recommendations"
+
+            await self.spotify.update_playlist_details(
+                playlist_id=playlist_id,
+                name=theme_name,
+                description=desc,
+            )
+            await self.spotify.replace_playlist_tracks(
+                playlist_id=playlist_id,
+                track_uris=[f"spotify:track:{tid}" for tid in final_track_ids],
+            )
+
+            self._save_playlist_config(
+                "six_hour",
+                playlist_id,
+                description=desc,
+                theme=theme_result["theme_name"],
+                composition=full_tracks,
+            )
+
+        return {
+            "playlist_id": playlist_id,
+            "theme_name": theme_result["theme_name"],
+            "description": theme_result["description"],
+            "track_count": len(final_track_ids),
+            "sources": sources,
+            "composition": full_tracks,
+            "curated_count": len(curated_details),
+            "rec_count": len(rec_details),
+            "refreshed_at": datetime.utcnow().isoformat(),
+        }
+
+    async def curate_daily_playlist(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        """Generate 24-hour playlist (30 favorites + 20 discoveries)."""
+        from app.models import Track
+        from app.services.stats_service import StatsService
+
+        stats = StatsService(self.db)
+        data = stats.generate_full_report(period_start, period_end)
+
+        top_all_time_ids = self._get_top_all_time_tracks(limit=30)
+        recent_tracks_ids = [track["id"] for track in data["volume"]["top_tracks"][:20]]
+
+        favorites_details = []
+        for tid in top_all_time_ids:
+            track_obj = self.db.query(Track).filter(Track.id == tid).first()
+            if track_obj:
+                favorites_details.append(
+                    {
+                        "id": str(track_obj.id),
+                        "energy": track_obj.energy,
+                        "source": "favorite_all_time",
+                    }
+                )
+
+        discovery_details = []
+        for tid in recent_tracks_ids:
+            track_obj = self.db.query(Track).filter(Track.id == tid).first()
+            if track_obj:
+                discovery_details.append(
+                    {
+                        "id": str(track_obj.id),
+                        "energy": track_obj.energy,
+                        "source": "recent_discovery",
+                    }
+                )
+
+        all_candidates = favorites_details + discovery_details
+        optimized_tracks = self._optimize_playlist_flow(all_candidates)
+
+        final_track_ids = [t["id"] for t in optimized_tracks]
+        sources = {t["id"]: t["source"] for t in optimized_tracks}
+
+        # Hydrate for persistence/display
+        full_tracks = await self._hydrate_tracks(final_track_ids, sources)
+
+        playlist_id = None
+        from app.models import PlaylistConfig
+
+        config = (
+            self.db.query(PlaylistConfig).filter(PlaylistConfig.key == "daily").first()
+        )
+        if config:
+            playlist_id = config.spotify_id
+
+        if not playlist_id:
+            playlist_id = os.getenv("DAILY_PLAYLIST_ID")
+
+        theme_name = f"Proof of Commitment - {datetime.utcnow().date().isoformat()}"
+        if playlist_id:
+            desc = (
+                f"{theme_name} reflects the past 24 hours plus your all-time devotion."
+            )
+            await self.spotify.update_playlist_details(
+                playlist_id=playlist_id,
+                name=theme_name,
+                description=desc,
+            )
+            await self.spotify.replace_playlist_tracks(
+                playlist_id=playlist_id,
+                track_uris=[f"spotify:track:{tid}" for tid in final_track_ids],
+            )
+
+            self._save_playlist_config(
+                "daily",
+                playlist_id,
+                description=desc,
+                theme=theme_name,
+                composition=full_tracks,
+            )
+
+        return {
+            "playlist_id": playlist_id,
+            "theme_name": theme_name,
+            "description": "Daily mix refreshed with your favorites and discoveries.",
+            "track_count": len(final_track_ids),
+            "sources": sources,
+            "composition": full_tracks,
+            "favorites_count": len(favorites_details),
+            "recent_discoveries_count": len(discovery_details),
+            "refreshed_at": datetime.utcnow().isoformat(),
+        }
+
+    def _get_top_all_time_tracks(self, limit: int = 30) -> List[str]:
+        """Get top tracks by play count from all-time history."""
+        from app.models import PlayHistory, Track
+        from sqlalchemy import func
+
+        result = (
+            self.db.query(Track.id, func.count(PlayHistory.id).label("play_count"))
+            .join(PlayHistory, Track.id == PlayHistory.track_id)
+            .group_by(Track.id)
+            .order_by(func.count(PlayHistory.id).desc())
+            .limit(limit)
+            .all()
+        )
+
+        return [track_id for track_id, _ in result]
+
+    def _optimize_playlist_flow(
+        self, tracks: List[Dict[str, Any]]
+    ) -> List[Dict[str, Any]]:
+        """
+        Sort tracks to create a smooth flow (Energy Ramp).
+        Strategy: Sort by energy (Low -> High -> Medium).
+        """
+        if not any("energy" in t for t in tracks):
+            return tracks
+
+        for t in tracks:
+            if "energy" not in t or t["energy"] is None:
+                t["energy"] = 0.5
+
+        sorted_tracks = sorted(tracks, key=lambda x: x["energy"])
+
+        n = len(sorted_tracks)
+        low_end = int(n * 0.3)
+        high_start = int(n * 0.7)
+
+        low_energy = sorted_tracks[:low_end]
+        medium_energy = sorted_tracks[low_end:high_start]
+        high_energy = sorted_tracks[high_start:]
+
+        return low_energy + high_energy + medium_energy

backend/app/services/reccobeats_client.py

@@ -0,0 +1,136 @@
+import httpx
+from typing import List, Dict, Any, Optional
+
+RECCOBEATS_BASE_URL = "https://api.reccobeats.com/v1"
+
+
+class ReccoBeatsClient:
+    def __init__(self):
+        self.timeout = 30.0
+
+    async def get_tracks(self, spotify_ids: List[str]) -> List[Dict[str, Any]]:
+        if not spotify_ids:
+            return []
+
+        ids_param = ",".join(spotify_ids)
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            try:
+                response = await client.get(
+                    f"{RECCOBEATS_BASE_URL}/track", params={"ids": ids_param}
+                )
+                if response.status_code != 200:
+                    print(f"ReccoBeats /track returned status {response.status_code}")
+                    return []
+
+                content = response.json().get("content", [])
+
+                for item in content:
+                    href = item.get("href", "")
+                    if "spotify.com/track/" in href:
+                        item["spotify_id"] = href.split("/track/")[-1].split("?")[0]
+
+                return content
+            except Exception as e:
+                print(f"ReccoBeats /track error: {e}")
+                return []
+
+    async def get_audio_features(self, spotify_ids: List[str]) -> List[Dict[str, Any]]:
+        """Fetch audio features for tracks. Batches in chunks of 40 (API limit)."""
+        if not spotify_ids:
+            return []
+
+        all_results = []
+        batch_size = 40  # ReccoBeats API returns 400 for 50+ IDs
+
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            for i in range(0, len(spotify_ids), batch_size):
+                batch = spotify_ids[i : i + batch_size]
+                ids_param = ",".join(batch)
+
+                try:
+                    response = await client.get(
+                        f"{RECCOBEATS_BASE_URL}/audio-features",
+                        params={"ids": ids_param},
+                    )
+                    if response.status_code != 200:
+                        print(
+                            f"ReccoBeats /audio-features returned status {response.status_code}"
+                        )
+                        continue
+
+                    content = response.json().get("content", [])
+
+                    for item in content:
+                        href = item.get("href", "")
+                        if "spotify.com/track/" in href:
+                            item["spotify_id"] = href.split("/track/")[-1].split("?")[0]
+
+                    all_results.extend(content)
+                except Exception as e:
+                    print(f"ReccoBeats /audio-features error: {e}")
+
+        return all_results
+
+    async def get_recommendations(
+        self,
+        seed_ids: List[str],
+        size: int = 20,
+        negative_seeds: Optional[List[str]] = None,
+    ) -> List[Dict[str, Any]]:
+        if not seed_ids:
+            return []
+
+        if len(seed_ids) > 5:
+            seed_ids = seed_ids[:5]
+
+        params = {"seeds": ",".join(seed_ids), "size": size}
+
+        if negative_seeds:
+            if len(negative_seeds) > 5:
+                negative_seeds = negative_seeds[:5]
+            params["negativeSeeds"] = ",".join(negative_seeds)
+
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            try:
+                response = await client.get(
+                    f"{RECCOBEATS_BASE_URL}/track/recommendation", params=params
+                )
+                if response.status_code != 200:
+                    print(
+                        f"ReccoBeats /recommendation returned status {response.status_code}"
+                    )
+                    return []
+
+                content = response.json().get("content", [])
+
+                for item in content:
+                    href = item.get("href", "")
+                    if "spotify.com/track/" in href:
+                        item["spotify_id"] = href.split("/track/")[-1].split("?")[0]
+
+                return content
+            except Exception as e:
+                print(f"ReccoBeats /recommendation error: {e}")
+                return []
+
+    async def get_audio_features_by_reccobeats_ids(
+        self, reccobeats_ids: List[str]
+    ) -> List[Dict[str, Any]]:
+        if not reccobeats_ids:
+            return []
+
+        results = []
+        async with httpx.AsyncClient(timeout=self.timeout) as client:
+            for rb_id in reccobeats_ids:
+                try:
+                    response = await client.get(
+                        f"{RECCOBEATS_BASE_URL}/track/{rb_id}/audio-features"
+                    )
+                    if response.status_code == 200:
+                        data = response.json()
+                        data["reccobeats_id"] = rb_id
+                        results.append(data)
+                except Exception as e:
+                    print(f"ReccoBeats audio-features for {rb_id} error: {e}")
+
+        return results

backend/app/services/spotify_client.py

@@ -3,10 +3,12 @@ import base64
 import time
 import httpx
 from fastapi import HTTPException
+from typing import List, Dict, Any
 
 SPOTIFY_TOKEN_URL = "https://accounts.spotify.com/api/token"
 SPOTIFY_API_BASE = "https://api.spotify.com/v1"
 
+
 class SpotifyClient:
     def __init__(self, client_id: str, client_secret: str, refresh_token: str):
         self.client_id = client_id
@@ -68,3 +70,161 @@ class SpotifyClient:
             if response.status_code != 200:
                 return None
             return response.json()
+
+    async def get_tracks(self, track_ids: List[str]) -> List[Dict[str, Any]]:
+        """Fetch multiple tracks by ID."""
+        if not track_ids:
+            return []
+
+        token = await self.get_access_token()
+        ids_param = ",".join(track_ids[:50])
+
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                f"{SPOTIFY_API_BASE}/tracks",
+                params={"ids": ids_param},
+                headers={"Authorization": f"Bearer {token}"},
+            )
+            if response.status_code != 200:
+                print(f"Error fetching tracks: {response.text}")
+                return []
+
+            return response.json().get("tracks", [])
+
+    async def get_artists(self, artist_ids: List[str]) -> List[Dict[str, Any]]:
+        """
+        Fetches artist details (including genres) for a list of artist IDs.
+        Spotify allows up to 50 IDs per request.
+        """
+        if not artist_ids:
+            return []
+
+        token = await self.get_access_token()
+        ids_param = ",".join(artist_ids)
+
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                f"{SPOTIFY_API_BASE}/artists",
+                params={"ids": ids_param},
+                headers={"Authorization": f"Bearer {token}"},
+            )
+            if response.status_code != 200:
+                print(f"Error fetching artists: {response.text}")
+                return []
+
+            return response.json().get("artists", [])
+
+    async def get_currently_playing(self) -> Dict[str, Any] | None:
+        token = await self.get_access_token()
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                f"{SPOTIFY_API_BASE}/me/player/currently-playing",
+                headers={"Authorization": f"Bearer {token}"},
+            )
+            if response.status_code == 204:
+                return None
+            if response.status_code != 200:
+                print(f"Error fetching currently playing: {response.text}")
+                return None
+            return response.json()
+
+    async def get_current_user_id(self) -> str:
+        token = await self.get_access_token()
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                f"{SPOTIFY_API_BASE}/me",
+                headers={"Authorization": f"Bearer {token}"},
+            )
+            if response.status_code != 200:
+                raise Exception(f"Failed to get user profile: {response.text}")
+            return response.json().get("id")
+
+    async def create_playlist(
+        self, user_id: str, name: str, description: str = "", public: bool = False
+    ) -> Dict[str, Any]:
+        token = await self.get_access_token()
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                f"{SPOTIFY_API_BASE}/users/{user_id}/playlists",
+                headers={
+                    "Authorization": f"Bearer {token}",
+                    "Content-Type": "application/json",
+                },
+                json={"name": name, "description": description, "public": public},
+            )
+            if response.status_code not in [200, 201]:
+                raise Exception(f"Failed to create playlist: {response.text}")
+            return response.json()
+
+    async def update_playlist_details(
+        self, playlist_id: str, name: str = None, description: str = None
+    ) -> bool:
+        token = await self.get_access_token()
+        data = {}
+        if name:
+            data["name"] = name
+        if description:
+            data["description"] = description
+
+        if not data:
+            return True
+
+        async with httpx.AsyncClient() as client:
+            response = await client.put(
+                f"{SPOTIFY_API_BASE}/playlists/{playlist_id}",
+                headers={
+                    "Authorization": f"Bearer {token}",
+                    "Content-Type": "application/json",
+                },
+                json=data,
+            )
+            return response.status_code == 200
+
+    async def replace_playlist_tracks(
+        self, playlist_id: str, track_uris: List[str]
+    ) -> bool:
+        token = await self.get_access_token()
+        async with httpx.AsyncClient() as client:
+            response = await client.put(
+                f"{SPOTIFY_API_BASE}/playlists/{playlist_id}/tracks",
+                headers={
+                    "Authorization": f"Bearer {token}",
+                    "Content-Type": "application/json",
+                },
+                json={"uris": track_uris[:100]},
+            )
+            return response.status_code in [200, 201]
+
+    async def get_recommendations(
+        self,
+        seed_tracks: List[str] = None,
+        seed_artists: List[str] = None,
+        seed_genres: List[str] = None,
+        limit: int = 20,
+        target_energy: float = None,
+        target_valence: float = None,
+    ) -> List[Dict[str, Any]]:
+        token = await self.get_access_token()
+        params = {"limit": limit}
+
+        if seed_tracks:
+            params["seed_tracks"] = ",".join(seed_tracks[:5])
+        if seed_artists:
+            params["seed_artists"] = ",".join(seed_artists[:5])
+        if seed_genres:
+            params["seed_genres"] = ",".join(seed_genres[:5])
+        if target_energy is not None:
+            params["target_energy"] = target_energy
+        if target_valence is not None:
+            params["target_valence"] = target_valence
+
+        async with httpx.AsyncClient() as client:
+            response = await client.get(
+                f"{SPOTIFY_API_BASE}/recommendations",
+                params=params,
+                headers={"Authorization": f"Bearer {token}"},
+            )
+            if response.status_code != 200:
+                print(f"Error fetching recommendations: {response.text}")
+                return []
+            return response.json().get("tracks", [])

backend/app/services/stats_service.py

@@ -0,0 +1,996 @@
+from sqlalchemy.orm import Session, joinedload
+from sqlalchemy import func, distinct
+from datetime import datetime, timedelta
+from typing import Dict, Any, List, Optional
+import math
+import numpy as np
+from sklearn.cluster import KMeans
+
+from ..models import PlayHistory, Track, Artist
+
+
+class StatsService:
+    def __init__(self, db: Session):
+        self.db = db
+
+    def compute_comparison(
+        self,
+        current_stats: Dict[str, Any],
+        period_start: datetime,
+        period_end: datetime,
+    ) -> Dict[str, Any]:
+        duration = period_end - period_start
+        prev_end = period_start
+        prev_start = prev_end - duration
+
+        prev_volume = self.compute_volume_stats(prev_start, prev_end)
+        prev_vibe = self.compute_vibe_stats(prev_start, prev_end)
+        prev_taste = self.compute_taste_stats(prev_start, prev_end)
+
+        deltas = {}
+
+        curr_plays = current_stats["volume"]["total_plays"]
+        prev_plays_count = prev_volume["total_plays"]
+        deltas["plays_delta"] = curr_plays - prev_plays_count
+        deltas["plays_pct_change"] = self._pct_change(curr_plays, prev_plays_count)
+
+        if "mood_quadrant" in current_stats["vibe"] and "mood_quadrant" in prev_vibe:
+            curr_e = current_stats["vibe"]["mood_quadrant"]["y"]
+            prev_e = prev_vibe["mood_quadrant"]["y"]
+            deltas["energy_delta"] = round(curr_e - prev_e, 2)
+
+            curr_v = current_stats["vibe"]["mood_quadrant"]["x"]
+            prev_v = prev_vibe["mood_quadrant"]["x"]
+            deltas["valence_delta"] = round(curr_v - prev_v, 2)
+
+        if (
+            "avg_popularity" in current_stats["taste"]
+            and "avg_popularity" in prev_taste
+        ):
+            deltas["popularity_delta"] = round(
+                current_stats["taste"]["avg_popularity"] - prev_taste["avg_popularity"],
+                1,
+            )
+
+        return {
+            "previous_period": {
+                "start": prev_start.isoformat(),
+                "end": prev_end.isoformat(),
+            },
+            "deltas": deltas,
+        }
+
+    def compute_volume_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .options(joinedload(PlayHistory.track).joinedload(Track.artists))
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at < period_end,
+            )
+        )
+        plays = query.all()
+        total_plays = len(plays)
+
+        if total_plays == 0:
+            return self._empty_volume_stats()
+
+        total_ms = 0
+        track_counts = {}
+        artist_counts = {}
+        genre_counts = {}
+        album_counts = {}
+
+        track_map = {}
+        artist_map = {}
+        album_map = {}
+
+        def get_track_image(t):
+            if t.image_url:
+                return t.image_url
+            if t.raw_data and "album" in t.raw_data and "images" in t.raw_data["album"]:
+                imgs = t.raw_data["album"]["images"]
+                if imgs:
+                    return imgs[0].get("url")
+            return None
+
+        for p in plays:
+            t = p.track
+            if not t:
+                continue
+
+            total_ms += t.duration_ms if t.duration_ms else 0
+            track_counts[t.id] = track_counts.get(t.id, 0) + 1
+            track_map[t.id] = t
+
+            album_id = t.album
+            album_name = t.album
+            if t.raw_data and "album" in t.raw_data:
+                album_id = t.raw_data["album"].get("id", t.album)
+                album_name = t.raw_data["album"].get("name", t.album)
+
+            album_counts[album_id] = album_counts.get(album_id, 0) + 1
+            if album_id not in album_map:
+                album_map[album_id] = {"name": album_name, "image": get_track_image(t)}
+
+            for artist in t.artists:
+                artist_counts[artist.id] = artist_counts.get(artist.id, 0) + 1
+                if artist.id not in artist_map:
+                    artist_map[artist.id] = {
+                        "name": artist.name,
+                        "image": artist.image_url,
+                    }
+
+                if artist.genres:
+                    for g in artist.genres:
+                        genre_counts[g] = genre_counts.get(g, 0) + 1
+
+        unique_tracks = len(track_counts)
+        one_and_done = len([c for c in track_counts.values() if c == 1])
+        shares = [c / total_plays for c in track_counts.values()]
+
+        top_tracks = [
+            {
+                "id": tid,
+                "name": track_map[tid].name,
+                "artist": ", ".join([a.name for a in track_map[tid].artists]),
+                "image": get_track_image(track_map[tid]),
+                "count": c,
+            }
+            for tid, c in sorted(
+                track_counts.items(), key=lambda x: x[1], reverse=True
+            )[:5]
+        ]
+
+        top_artists = [
+            {
+                "name": artist_map[aid]["name"],
+                "id": aid,
+                "image": artist_map[aid]["image"],
+                "count": c,
+            }
+            for aid, c in sorted(
+                artist_counts.items(), key=lambda x: x[1], reverse=True
+            )[:5]
+        ]
+
+        top_albums = [
+            {
+                "name": album_map[aid]["name"],
+                "image": album_map[aid]["image"],
+                "count": c,
+            }
+            for aid, c in sorted(
+                album_counts.items(), key=lambda x: x[1], reverse=True
+            )[:5]
+        ]
+
+        top_genres = [
+            {"name": k, "count": v}
+            for k, v in sorted(genre_counts.items(), key=lambda x: x[1], reverse=True)[
+                :5
+            ]
+        ]
+
+        hhi = sum([s**2 for s in shares])
+
+        sorted_shares = sorted(shares)
+        n = len(shares)
+        gini = 0
+        if n > 0:
+            gini = (2 * sum((i + 1) * x for i, x in enumerate(sorted_shares))) / (
+                n * sum(sorted_shares)
+            ) - (n + 1) / n
+
+        total_genre_occurrences = sum(genre_counts.values())
+        genre_entropy = 0
+        if total_genre_occurrences > 0:
+            genre_probs = [
+                count / total_genre_occurrences for count in genre_counts.values()
+            ]
+            genre_entropy = -sum([p * math.log(p) for p in genre_probs if p > 0])
+
+        top_5_plays = sum([t["count"] for t in top_tracks])
+        top_5_share = top_5_plays / total_plays if total_plays else 0
+
+        return {
+            "total_plays": total_plays,
+            "estimated_minutes": int(total_ms / 60000),
+            "unique_tracks": unique_tracks,
+            "unique_artists": len(artist_counts),
+            "unique_albums": len(album_counts),
+            "unique_genres": len(genre_counts),
+            "top_tracks": top_tracks,
+            "top_artists": top_artists,
+            "top_albums": top_albums,
+            "top_genres": top_genres,
+            "repeat_rate": round((total_plays - unique_tracks) / total_plays, 3)
+            if total_plays
+            else 0,
+            "one_and_done_rate": round(one_and_done / unique_tracks, 3)
+            if unique_tracks
+            else 0,
+            "concentration": {
+                "hhi": round(hhi, 4),
+                "gini": round(gini, 4),
+                "top_1_share": round(max(shares), 3) if shares else 0,
+                "top_5_share": round(top_5_share, 3),
+                "genre_entropy": round(genre_entropy, 2),
+            },
+        }
+
+    def compute_time_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at < period_end,
+            )
+            .order_by(PlayHistory.played_at.asc())
+        )
+        plays = query.all()
+
+        if not plays:
+            return self._empty_time_stats()
+
+        heatmap = [[0 for _ in range(24)] for _ in range(7)]
+        heatmap_compressed = [[0 for _ in range(6)] for _ in range(7)]
+        block_labels = [
+            "12am-4am",
+            "4am-8am",
+            "8am-12pm",
+            "12pm-4pm",
+            "4pm-8pm",
+            "8pm-12am",
+        ]
+
+        hourly_counts = [0] * 24
+        weekday_counts = [0] * 7
+
+        part_of_day = {"morning": 0, "afternoon": 0, "evening": 0, "night": 0}
+        active_dates = set()
+
+        for p in plays:
+            h = p.played_at.hour
+            d = p.played_at.weekday()
+
+            heatmap[d][h] += 1
+            block_idx = h // 4
+            heatmap_compressed[d][block_idx] += 1
+
+            hourly_counts[h] += 1
+            weekday_counts[d] += 1
+            active_dates.add(p.played_at.date())
+
+            if 6 <= h < 12:
+                part_of_day["morning"] += 1
+            elif 12 <= h < 18:
+                part_of_day["afternoon"] += 1
+            elif 18 <= h <= 23:
+                part_of_day["evening"] += 1
+            else:
+                part_of_day["night"] += 1
+
+        sorted_dates = sorted(list(active_dates))
+        current_streak = 0
+        longest_streak = 0
+        if sorted_dates:
+            current_streak = 1
+            longest_streak = 1
+            for i in range(1, len(sorted_dates)):
+                delta = (sorted_dates[i] - sorted_dates[i - 1]).days
+                if delta == 1:
+                    current_streak += 1
+                else:
+                    longest_streak = max(longest_streak, current_streak)
+                    current_streak = 1
+            longest_streak = max(longest_streak, current_streak)
+
+        weekend_plays = weekday_counts[5] + weekday_counts[6]
+        active_days_count = len(active_dates)
+
+        return {
+            "heatmap": heatmap,
+            "heatmap_compressed": heatmap_compressed,
+            "block_labels": block_labels,
+            "hourly_distribution": hourly_counts,
+            "peak_hour": hourly_counts.index(max(hourly_counts)),
+            "weekday_distribution": weekday_counts,
+            "daily_distribution": weekday_counts,
+            "weekend_share": round(weekend_plays / len(plays), 2),
+            "part_of_day": part_of_day,
+            "listening_streak": current_streak,
+            "longest_streak": longest_streak,
+            "active_days": active_days_count,
+            "avg_plays_per_active_day": round(len(plays) / active_days_count, 1)
+            if active_days_count
+            else 0,
+        }
+
+    def compute_session_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .options(joinedload(PlayHistory.track))
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at < period_end,
+            )
+            .order_by(PlayHistory.played_at.asc())
+        )
+        plays = query.all()
+
+        if not plays:
+            return self._empty_session_stats()
+
+        sessions = []
+        current_session = [plays[0]]
+
+        for i in range(1, len(plays)):
+            diff = (plays[i].played_at - plays[i - 1].played_at).total_seconds() / 60
+            if diff > 20:
+                sessions.append(current_session)
+                current_session = []
+            current_session.append(plays[i])
+        sessions.append(current_session)
+
+        lengths_min = []
+        micro_sessions = 0
+        marathon_sessions = 0
+        energy_arcs = {"rising": 0, "falling": 0, "flat": 0, "unknown": 0}
+        start_hour_dist = [0] * 24
+
+        session_list = []
+
+        for sess in sessions:
+            start_t = sess[0].played_at
+            end_t = sess[-1].played_at
+            start_hour_dist[start_t.hour] += 1
+
+            if len(sess) > 1:
+                duration = (end_t - start_t).total_seconds() / 60
+                lengths_min.append(duration)
+            else:
+                duration = 3.0
+                lengths_min.append(duration)
+
+            sess_type = "Standard"
+            if len(sess) <= 3:
+                micro_sessions += 1
+                sess_type = "Micro"
+            elif len(sess) >= 20:
+                marathon_sessions += 1
+                sess_type = "Marathon"
+
+            session_list.append(
+                {
+                    "start_time": start_t.isoformat(),
+                    "end_time": end_t.isoformat(),
+                    "duration_minutes": round(duration, 1),
+                    "track_count": len(sess),
+                    "type": sess_type,
+                }
+            )
+
+            first_t = sess[0].track
+            last_t = sess[-1].track
+            if (
+                first_t
+                and last_t
+                and getattr(first_t, "energy", None) is not None
+                and getattr(last_t, "energy", None) is not None
+            ):
+                diff = last_t.energy - first_t.energy
+                if diff > 0.1:
+                    energy_arcs["rising"] += 1
+                elif diff < -0.1:
+                    energy_arcs["falling"] += 1
+                else:
+                    energy_arcs["flat"] += 1
+            else:
+                energy_arcs["unknown"] += 1
+
+        avg_min = np.mean(lengths_min) if lengths_min else 0
+        median_min = np.median(lengths_min) if lengths_min else 0
+        active_days = len(set(p.played_at.date() for p in plays))
+        sessions_per_day = len(sessions) / active_days if active_days else 0
+
+        return {
+            "count": len(sessions),
+            "avg_tracks": round(len(plays) / len(sessions), 1),
+            "avg_minutes": round(float(avg_min), 1),
+            "median_minutes": round(float(median_min), 1),
+            "longest_session_minutes": round(max(lengths_min), 1) if lengths_min else 0,
+            "sessions_per_day": round(sessions_per_day, 1),
+            "start_hour_distribution": start_hour_dist,
+            "micro_session_rate": round(micro_sessions / len(sessions), 2),
+            "marathon_session_rate": round(marathon_sessions / len(sessions), 2),
+            "energy_arcs": energy_arcs,
+            "session_list": session_list,
+        }
+
+    def compute_vibe_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        plays = (
+            self.db.query(PlayHistory)
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at < period_end,
+            )
+            .order_by(PlayHistory.played_at.asc())
+            .all()
+        )
+
+        if not plays:
+            return self._empty_vibe_stats()
+
+        track_ids = list(set([p.track_id for p in plays]))
+        tracks = self.db.query(Track).filter(Track.id.in_(track_ids)).all()
+        track_map = {t.id: t for t in tracks}
+
+        feature_keys = [
+            "energy",
+            "valence",
+            "danceability",
+            "tempo",
+            "acousticness",
+            "instrumentalness",
+            "liveness",
+            "speechiness",
+            "loudness",
+        ]
+        features = {k: [] for k in feature_keys}
+        cluster_data = []
+        keys = []
+        modes = []
+        tempo_zones = {"chill": 0, "groove": 0, "hype": 0}
+        transitions = {"tempo": [], "energy": [], "valence": []}
+        previous_track = None
+
+        for i, p in enumerate(plays):
+            t = track_map.get(p.track_id)
+            if not t:
+                continue
+
+            for key in feature_keys:
+                val = getattr(t, key, None)
+                if val is not None:
+                    features[key].append(val)
+
+            if all(
+                getattr(t, k, None) is not None
+                for k in ["energy", "valence", "danceability", "acousticness"]
+            ):
+                cluster_data.append(
+                    [t.energy, t.valence, t.danceability, t.acousticness]
+                )
+
+            if getattr(t, "key", None) is not None:
+                keys.append(t.key)
+            if getattr(t, "mode", None) is not None:
+                modes.append(t.mode)
+
+            if getattr(t, "tempo", None) is not None:
+                if t.tempo < 100:
+                    tempo_zones["chill"] += 1
+                elif t.tempo < 130:
+                    tempo_zones["groove"] += 1
+                else:
+                    tempo_zones["hype"] += 1
+
+            if i > 0 and previous_track:
+                time_diff = (p.played_at - plays[i - 1].played_at).total_seconds()
+                if time_diff < 300:
+                    if (
+                        getattr(t, "tempo", None) is not None
+                        and getattr(previous_track, "tempo", None) is not None
+                    ):
+                        transitions["tempo"].append(abs(t.tempo - previous_track.tempo))
+                    if (
+                        getattr(t, "energy", None) is not None
+                        and getattr(previous_track, "energy", None) is not None
+                    ):
+                        transitions["energy"].append(
+                            abs(t.energy - previous_track.energy)
+                        )
+                    if (
+                        getattr(t, "valence", None) is not None
+                        and getattr(previous_track, "valence", None) is not None
+                    ):
+                        transitions["valence"].append(
+                            abs(t.valence - previous_track.valence)
+                        )
+
+            previous_track = t
+
+        stats_res = {}
+        for key, values in features.items():
+            valid = [v for v in values if v is not None]
+            if valid:
+                avg_val = float(np.mean(valid))
+                stats_res[key] = round(avg_val, 3)
+                stats_res[f"avg_{key}"] = avg_val
+                stats_res[f"std_{key}"] = float(np.std(valid))
+                stats_res[f"p10_{key}"] = float(np.percentile(valid, 10))
+                stats_res[f"p50_{key}"] = float(np.percentile(valid, 50))
+                stats_res[f"p90_{key}"] = float(np.percentile(valid, 90))
+            else:
+                stats_res[key] = 0.0
+                stats_res[f"avg_{key}"] = None
+
+        if (
+            stats_res.get("avg_energy") is not None
+            and stats_res.get("avg_valence") is not None
+        ):
+            stats_res["mood_quadrant"] = {
+                "x": round(stats_res["avg_valence"], 2),
+                "y": round(stats_res["avg_energy"], 2),
+            }
+            avg_std = (
+                stats_res.get("std_energy", 0) + stats_res.get("std_valence", 0)
+            ) / 2
+            stats_res["consistency_score"] = round(1.0 - avg_std, 2)
+
+        if (
+            stats_res.get("avg_tempo") is not None
+            and stats_res.get("avg_danceability") is not None
+        ):
+            stats_res["rhythm_profile"] = {
+                "avg_tempo": round(stats_res["avg_tempo"], 1),
+                "avg_danceability": round(stats_res["avg_danceability"], 2),
+            }
+
+        if (
+            stats_res.get("avg_acousticness") is not None
+            and stats_res.get("avg_instrumentalness") is not None
+        ):
+            stats_res["texture_profile"] = {
+                "acousticness": round(stats_res["avg_acousticness"], 2),
+                "instrumentalness": round(stats_res["avg_instrumentalness"], 2),
+            }
+
+        stats_res["whiplash"] = {}
+        for k in ["tempo", "energy", "valence"]:
+            if transitions[k]:
+                stats_res["whiplash"][k] = round(float(np.mean(transitions[k])), 2)
+            else:
+                stats_res["whiplash"][k] = 0
+
+        total_tempo = sum(tempo_zones.values())
+        if total_tempo > 0:
+            stats_res["tempo_zones"] = {
+                k: round(v / total_tempo, 2) for k, v in tempo_zones.items()
+            }
+        else:
+            stats_res["tempo_zones"] = {}
+
+        if modes:
+            major_count = len([m for m in modes if m == 1])
+            stats_res["harmonic_profile"] = {
+                "major_pct": round(major_count / len(modes), 2),
+                "minor_pct": round((len(modes) - major_count) / len(modes), 2),
+            }
+
+        if keys:
+            pitch_class = [
+                "C",
+                "C#",
+                "D",
+                "D#",
+                "E",
+                "F",
+                "F#",
+                "G",
+                "G#",
+                "A",
+                "A#",
+                "B",
+            ]
+            key_counts = {}
+            for k in keys:
+                if 0 <= k < 12:
+                    label = pitch_class[k]
+                    key_counts[label] = key_counts.get(label, 0) + 1
+            stats_res["top_keys"] = [
+                {"key": k, "count": v}
+                for k, v in sorted(
+                    key_counts.items(), key=lambda x: x[1], reverse=True
+                )[:3]
+            ]
+
+        if len(cluster_data) >= 5:
+            try:
+                kmeans = KMeans(n_clusters=3, random_state=42, n_init="auto")
+                labels = kmeans.fit_predict(cluster_data)
+                clusters = []
+                for i in range(3):
+                    mask = labels == i
+                    count = np.sum(mask)
+                    if count == 0:
+                        continue
+                    centroid = kmeans.cluster_centers_[i]
+                    share = count / len(cluster_data)
+                    c_energy, c_valence, c_dance, c_acoustic = centroid
+                    name = "Mixed Vibe"
+                    if c_energy > 0.7:
+                        name = "High Energy"
+                    elif c_acoustic > 0.7:
+                        name = "Acoustic / Chill"
+                    elif c_valence < 0.3:
+                        name = "Melancholy"
+                    elif c_dance > 0.7:
+                        name = "Dance / Groove"
+                    clusters.append(
+                        {
+                            "name": name,
+                            "share": round(share, 2),
+                            "features": {
+                                "energy": round(c_energy, 2),
+                                "valence": round(c_valence, 2),
+                                "danceability": round(c_dance, 2),
+                                "acousticness": round(c_acoustic, 2),
+                            },
+                        }
+                    )
+                stats_res["clusters"] = sorted(
+                    clusters, key=lambda x: x["share"], reverse=True
+                )
+            except Exception as e:
+                print(f"Clustering failed: {e}")
+                stats_res["clusters"] = []
+        else:
+            stats_res["clusters"] = []
+
+        return stats_res
+
+    def compute_era_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .options(joinedload(PlayHistory.track))
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at < period_end,
+            )
+        )
+        plays = query.all()
+
+        years = []
+        for p in plays:
+            t = p.track
+            if t and t.raw_data and "album" in t.raw_data:
+                rd = t.raw_data["album"].get("release_date")
+                if rd:
+                    try:
+                        years.append(int(rd.split("-")[0]))
+                    except:
+                        pass
+
+        if not years:
+            return {"musical_age": None}
+
+        avg_year = sum(years) / len(years)
+        current_year = datetime.utcnow().year
+
+        decades = {}
+        for y in years:
+            dec = (y // 10) * 10
+            label = f"{dec}s"
+            decades[label] = decades.get(label, 0) + 1
+
+        total = len(years)
+        dist = {k: round(v / total, 3) for k, v in decades.items()}
+
+        return {
+            "musical_age": int(avg_year),
+            "nostalgia_gap": int(current_year - avg_year),
+            "freshness_score": dist.get(f"{int(current_year / 10) * 10}s", 0),
+            "decade_distribution": dist,
+        }
+
+    def compute_skip_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at <= period_end,
+            )
+            .order_by(PlayHistory.played_at.asc())
+        )
+        plays = query.all()
+
+        if len(plays) < 2:
+            return {"skip_rate": 0, "total_skips": 0}
+
+        skips = 0
+        track_ids = list(set([p.track_id for p in plays]))
+        tracks = self.db.query(Track).filter(Track.id.in_(track_ids)).all()
+        track_map = {t.id: t for t in tracks}
+
+        for i in range(len(plays) - 1):
+            current_play = plays[i]
+            next_play = plays[i + 1]
+            track = track_map.get(current_play.track_id)
+
+            if not track or not getattr(track, "duration_ms", None):
+                continue
+
+            diff_seconds = (
+                next_play.played_at - current_play.played_at
+            ).total_seconds()
+            duration_sec = track.duration_ms / 1000.0
+
+            if diff_seconds < (duration_sec - 10):
+                skips += 1
+
+        return {"total_skips": skips, "skip_rate": round(skips / len(plays), 3)}
+
+    def compute_context_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = self.db.query(PlayHistory).filter(
+            PlayHistory.played_at >= period_start, PlayHistory.played_at <= period_end
+        )
+        plays = query.all()
+
+        if not plays:
+            return {}
+
+        context_counts = {
+            "playlist": 0,
+            "album": 0,
+            "artist": 0,
+            "collection": 0,
+            "unknown": 0,
+        }
+        unique_contexts = {}
+
+        for p in plays:
+            if not p.context_uri:
+                context_counts["unknown"] += 1
+                continue
+
+            unique_contexts[p.context_uri] = unique_contexts.get(p.context_uri, 0) + 1
+
+            if "playlist" in p.context_uri:
+                context_counts["playlist"] += 1
+            elif "album" in p.context_uri:
+                context_counts["album"] += 1
+            elif "artist" in p.context_uri:
+                context_counts["artist"] += 1
+            elif "collection" in p.context_uri:
+                context_counts["collection"] += 1
+            else:
+                context_counts["unknown"] += 1
+
+        total = len(plays)
+        breakdown = {k: round(v / total, 2) for k, v in context_counts.items()}
+        sorted_contexts = sorted(
+            unique_contexts.items(), key=lambda x: x[1], reverse=True
+        )[:5]
+
+        return {
+            "type_breakdown": breakdown,
+            "album_purist_score": breakdown.get("album", 0),
+            "playlist_dependency": breakdown.get("playlist", 0),
+            "context_loyalty": round(len(plays) / len(unique_contexts), 2)
+            if unique_contexts
+            else 0,
+            "top_context_uris": [{"uri": k, "count": v} for k, v in sorted_contexts],
+        }
+
+    def compute_taste_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = self.db.query(PlayHistory).filter(
+            PlayHistory.played_at >= period_start, PlayHistory.played_at <= period_end
+        )
+        plays = query.all()
+        if not plays:
+            return {}
+
+        track_ids = list(set([p.track_id for p in plays]))
+        tracks = self.db.query(Track).filter(Track.id.in_(track_ids)).all()
+        track_map = {t.id: t for t in tracks}
+
+        pop_values = []
+        for p in plays:
+            t = track_map.get(p.track_id)
+            if t and getattr(t, "popularity", None) is not None:
+                pop_values.append(t.popularity)
+
+        if not pop_values:
+            return {"avg_popularity": 0, "hipster_score": 0}
+
+        avg_pop = float(np.mean(pop_values))
+        underground_plays = len([x for x in pop_values if x < 30])
+        mainstream_plays = len([x for x in pop_values if x > 70])
+
+        return {
+            "avg_popularity": round(avg_pop, 1),
+            "hipster_score": round((underground_plays / len(pop_values)) * 100, 1),
+            "mainstream_score": round((mainstream_plays / len(pop_values)) * 100, 1),
+            "obscurity_rating": round(100 - avg_pop, 1),
+        }
+
+    def compute_lifecycle_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        current_plays = (
+            self.db.query(PlayHistory)
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at <= period_end,
+            )
+            .all()
+        )
+
+        if not current_plays:
+            return {}
+
+        current_track_ids = set([p.track_id for p in current_plays])
+        old_tracks_query = self.db.query(distinct(PlayHistory.track_id)).filter(
+            PlayHistory.track_id.in_(current_track_ids),
+            PlayHistory.played_at < period_start,
+        )
+        old_track_ids = set([r[0] for r in old_tracks_query.all()])
+
+        new_discoveries = current_track_ids - old_track_ids
+        discovery_count = len(new_discoveries)
+        plays_on_new = len([p for p in current_plays if p.track_id in new_discoveries])
+        total_plays = len(current_plays)
+
+        return {
+            "discovery_count": discovery_count,
+            "discovery_rate": round(plays_on_new / total_plays, 3)
+            if total_plays > 0
+            else 0,
+            "recurrence_rate": round((total_plays - plays_on_new) / total_plays, 3)
+            if total_plays > 0
+            else 0,
+        }
+
+    def compute_explicit_stats(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        query = (
+            self.db.query(PlayHistory)
+            .options(joinedload(PlayHistory.track))
+            .filter(
+                PlayHistory.played_at >= period_start,
+                PlayHistory.played_at <= period_end,
+            )
+        )
+        plays = query.all()
+
+        if not plays:
+            return {"explicit_rate": 0, "hourly_explicit_distribution": []}
+
+        total_plays = len(plays)
+        explicit_count = 0
+        hourly_explicit = [0] * 24
+        hourly_total = [0] * 24
+
+        for p in plays:
+            h = p.played_at.hour
+            hourly_total[h] += 1
+            t = p.track
+            if t and t.raw_data and t.raw_data.get("explicit"):
+                explicit_count += 1
+                hourly_explicit[h] += 1
+
+        hourly_rates = []
+        for i in range(24):
+            if hourly_total[i] > 0:
+                hourly_rates.append(round(hourly_explicit[i] / hourly_total[i], 2))
+            else:
+                hourly_rates.append(0.0)
+
+        return {
+            "explicit_rate": round(explicit_count / total_plays, 3),
+            "total_explicit_plays": explicit_count,
+            "hourly_explicit_distribution": hourly_rates,
+        }
+
+    def generate_full_report(
+        self, period_start: datetime, period_end: datetime
+    ) -> Dict[str, Any]:
+        current_stats = {
+            "period": {
+                "start": period_start.isoformat(),
+                "end": period_end.isoformat(),
+            },
+            "volume": self.compute_volume_stats(period_start, period_end),
+            "time_habits": self.compute_time_stats(period_start, period_end),
+            "sessions": self.compute_session_stats(period_start, period_end),
+            "context": self.compute_context_stats(period_start, period_end),
+            "vibe": self.compute_vibe_stats(period_start, period_end),
+            "era": self.compute_era_stats(period_start, period_end),
+            "taste": self.compute_taste_stats(period_start, period_end),
+            "lifecycle": self.compute_lifecycle_stats(period_start, period_end),
+            "flags": self.compute_explicit_stats(period_start, period_end),
+            "skips": self.compute_skip_stats(period_start, period_end),
+        }
+
+        current_stats["comparison"] = self.compute_comparison(
+            current_stats, period_start, period_end
+        )
+
+        return current_stats
+
+    def _empty_volume_stats(self):
+        return {
+            "total_plays": 0,
+            "estimated_minutes": 0,
+            "unique_tracks": 0,
+            "unique_artists": 0,
+            "unique_albums": 0,
+            "unique_genres": 0,
+            "top_tracks": [],
+            "top_artists": [],
+            "top_albums": [],
+            "top_genres": [],
+            "repeat_rate": 0,
+            "one_and_done_rate": 0,
+            "concentration": {
+                "hhi": 0,
+                "gini": 0,
+                "top_1_share": 0,
+                "top_5_share": 0,
+                "genre_entropy": 0,
+            },
+        }
+
+    def _empty_time_stats(self):
+        return {
+            "heatmap": [],
+            "heatmap_compressed": [],
+            "block_labels": [],
+            "hourly_distribution": [0] * 24,
+            "peak_hour": None,
+            "weekday_distribution": [0] * 7,
+            "daily_distribution": [0] * 7,
+            "weekend_share": 0,
+            "part_of_day": {"morning": 0, "afternoon": 0, "evening": 0, "night": 0},
+            "listening_streak": 0,
+            "longest_streak": 0,
+            "active_days": 0,
+            "avg_plays_per_active_day": 0,
+        }
+
+    def _empty_session_stats(self):
+        return {
+            "count": 0,
+            "avg_tracks": 0,
+            "avg_minutes": 0,
+            "median_minutes": 0,
+            "longest_session_minutes": 0,
+            "sessions_per_day": 0,
+            "start_hour_distribution": [0] * 24,
+            "micro_session_rate": 0,
+            "marathon_session_rate": 0,
+            "energy_arcs": {"rising": 0, "falling": 0, "flat": 0, "unknown": 0},
+            "session_list": [],
+        }
+
+    def _empty_vibe_stats(self):
+        return {
+            "avg_energy": 0,
+            "avg_valence": 0,
+            "mood_quadrant": {"x": 0, "y": 0},
+            "clusters": [],
+        }
+
+    def _pct_change(self, curr, prev):
+        if prev == 0:
+            return 100.0 if curr > 0 else 0.0
+        return round(((curr - prev) / prev) * 100, 1)

backend/backend.log

@@ -0,0 +1,10 @@
+INFO:     Started server process [9223]
+INFO:     Waiting for application startup.
+INFO:     Application startup complete.
+INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
+INFO:     127.0.0.1:35326 - "GET /history?limit=100 HTTP/1.1" 200 OK
+INFO:     127.0.0.1:35342 - "GET /history?limit=100 HTTP/1.1" 200 OK
+INFO:     Shutting down
+INFO:     Waiting for application shutdown.
+INFO:     Application shutdown complete.
+INFO:     Finished server process [9223]

backend/entrypoint.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+set -e
+
+echo "=== MusicAnalyser Backend Starting ==="
+
+# Run Alembic migrations
+echo "Running database migrations..."
+alembic upgrade head
+
+# Start the worker in background (polls Spotify every 60s)
+echo "Starting Spotify ingestion worker..."
+python run_worker.py &
+WORKER_PID=$!
+
+# Start the API server in foreground
+echo "Starting API server on port 8000..."
+exec uvicorn app.main:app --host 0.0.0.0 --port 8000

backend/requirements.txt

@@ -1,11 +1,16 @@
 fastapi==0.109.2
 uvicorn==0.27.1
-sqlalchemy==2.0.27
-httpx==0.26.0
+sqlalchemy==2.0.45
+httpx==0.28.1
 python-dotenv==1.0.1
-pydantic==2.6.1
-pydantic-settings==2.1.0
-google-generativeai==0.3.2
+pydantic==2.12.5
+pydantic-core==2.41.5
+pydantic-settings==2.12.0
 tenacity==8.2.3
 python-dateutil==2.9.0.post0
 requests==2.31.0
+alembic==1.13.1
+psycopg2-binary==2.9.9
+scikit-learn==1.4.0
+google-genai==1.56.0
+openai>=1.0.0

backend/run_analysis.py

@@ -0,0 +1,82 @@
+import os
+import sys
+import json
+from datetime import datetime, timedelta
+from app.database import SessionLocal
+from app.services.stats_service import StatsService
+from app.services.narrative_service import NarrativeService
+from app.models import AnalysisSnapshot
+
+def run_analysis_pipeline(days: int = 30, model_name: str = "gemini-2.5-flash"):
+    db = SessionLocal()
+    try:
+        end_date = datetime.utcnow()
+        start_date = end_date - timedelta(days=days)
+
+        print(f"--- Starting Analysis for period: {start_date} to {end_date} ---")
+
+        # 1. Compute Stats
+        print("Calculating metrics...")
+        stats_service = StatsService(db)
+        stats_json = stats_service.generate_full_report(start_date, end_date)
+
+        # Check if we have enough data
+        if stats_json["volume"]["total_plays"] == 0:
+            print("No plays found in this period. Skipping LLM analysis.")
+            return
+
+        print(f"Stats computed. Total Plays: {stats_json['volume']['total_plays']}")
+        print(f"Top Artist: {stats_json['volume']['top_artists'][0]['name'] if stats_json['volume']['top_artists'] else 'N/A'}")
+
+        # 2. Generate Narrative
+        print(f"Generating Narrative with {model_name}...")
+        narrative_service = NarrativeService(model_name=model_name)
+        narrative_json = narrative_service.generate_full_narrative(stats_json)
+
+        if "error" in narrative_json:
+            print(f"LLM Error: {narrative_json['error']}")
+        else:
+            print("Narrative generated successfully.")
+            print(f"Persona: {narrative_json.get('persona')}")
+
+        # 3. Save Snapshot
+        print("Saving snapshot to database...")
+        snapshot = AnalysisSnapshot(
+            period_start=start_date,
+            period_end=end_date,
+            period_label=f"last_{days}_days",
+            metrics_payload=stats_json,
+            narrative_report=narrative_json,
+            model_used=model_name
+        )
+        db.add(snapshot)
+        db.commit()
+        print(f"Snapshot saved with ID: {snapshot.id}")
+
+        # 4. Output to file for easy inspection
+        output = {
+            "snapshot_id": snapshot.id,
+            "metrics": stats_json,
+            "narrative": narrative_json
+        }
+        with open("latest_analysis.json", "w") as f:
+            json.dump(output, f, indent=2)
+        print("Full report saved to latest_analysis.json")
+
+    except Exception as e:
+        print(f"Pipeline Failed: {e}")
+        import traceback
+        traceback.print_exc()
+    finally:
+        db.close()
+
+if __name__ == "__main__":
+    # Allow arguments?
+    days = 30
+    if len(sys.argv) > 1:
+        try:
+            days = int(sys.argv[1])
+        except:
+            pass
+
+    run_analysis_pipeline(days=days)

backend/run_scheduler.py

@@ -0,0 +1,16 @@
+import schedule
+import time
+from run_analysis import run_analysis_pipeline
+
+def job():
+    print("Running daily analysis...")
+    # Analyze last 24 hours
+    run_analysis_pipeline(days=1)
+
+# Schedule for 03:00 AM
+schedule.every().day.at("03:00").do(job)
+
+print("Scheduler started...")
+while True:
+    schedule.run_pending()
+    time.sleep(60)

backend/scripts/get_refresh_token.py

@@ -16,8 +16,9 @@ from http.server import HTTPServer, BaseHTTPRequestHandler
 # CONFIGURATION - You can hardcode these or input them when prompted
 SPOTIFY_CLIENT_ID = input("Enter your Spotify Client ID: ").strip()
 SPOTIFY_CLIENT_SECRET = input("Enter your Spotify Client Secret: ").strip()
-REDIRECT_URI = "http://localhost:8888/callback"
-SCOPE = "user-read-recently-played user-read-playback-state"
+REDIRECT_URI = "http://127.0.0.1:8888/callback"
+SCOPE = "user-read-recently-played user-read-playback-state playlist-modify-public playlist-modify-private"
+
 
 class RequestHandler(BaseHTTPRequestHandler):
     def do_GET(self):
@@ -36,6 +37,7 @@ class RequestHandler(BaseHTTPRequestHandler):
             # Shut down server
             raise KeyboardInterrupt
 
+
 def get_token(code):
     url = "https://accounts.spotify.com/api/token"
     payload = {
@@ -49,24 +51,27 @@ def get_token(code):
     response = requests.post(url, data=payload)
     if response.status_code == 200:
         data = response.json()
-        print("\n" + "="*50)
+        print("\n" + "=" * 50)
         print("SUCCESS! HERE ARE YOUR CREDENTIALS")
-        print("="*50)
+        print("=" * 50)
         print(f"\nSPOTIFY_REFRESH_TOKEN={data['refresh_token']}")
         print(f"SPOTIFY_CLIENT_ID={SPOTIFY_CLIENT_ID}")
         print(f"SPOTIFY_CLIENT_SECRET={SPOTIFY_CLIENT_SECRET}")
         print("\nSave these in your .env file or share them with the agent.")
-        print("="*50 + "\n")
+        print("=" * 50 + "\n")
     else:
         print("Error getting token:", response.text)
 
+
 def start_auth():
-    auth_url = "https://accounts.spotify.com/authorize?" + urllib.parse.urlencode({
-        "response_type": "code",
-        "client_id": SPOTIFY_CLIENT_ID,
-        "scope": SCOPE,
-        "redirect_uri": REDIRECT_URI,
-    })
+    auth_url = "https://accounts.spotify.com/authorize?" + urllib.parse.urlencode(
+        {
+            "response_type": "code",
+            "client_id": SPOTIFY_CLIENT_ID,
+            "scope": SCOPE,
+            "redirect_uri": REDIRECT_URI,
+        }
+    )
 
     print(f"Opening browser to: {auth_url}")
     try:
@@ -74,7 +79,7 @@ def start_auth():
     except:
         print(f"Could not open browser. Please manually visit: {auth_url}")
 
-    server_address = ('', 8888)
+    server_address = ("", 8888)
     httpd = HTTPServer(server_address, RequestHandler)
     print("Listening on port 8888...")
     try:
@@ -83,5 +88,6 @@ def start_auth():
         pass
     httpd.server_close()
 
+
 if __name__ == "__main__":
     start_auth()

backend/scripts/reset_db_with_dummy_data.py

@@ -0,0 +1,31 @@
+from sqlalchemy.orm import Session
+from app.database import SessionLocal, engine, Base
+from app.models import Track, PlayHistory
+from datetime import datetime, timedelta
+
+Base.metadata.create_all(bind=engine)
+db = SessionLocal()
+
+# clear
+db.query(PlayHistory).delete()
+db.query(Track).delete()
+db.commit()
+
+# Create tracks
+t1 = Track(id="t1", name="Midnight City", artist="M83", album="Hurry Up, We're Dreaming", duration_ms=243000, danceability=0.6, energy=0.8, valence=0.5, raw_data={})
+t2 = Track(id="t2", name="Weightless", artist="Marconi Union", album="Weightless", duration_ms=480000, danceability=0.2, energy=0.1, valence=0.1, raw_data={})
+t3 = Track(id="t3", name="Levitating", artist="Dua Lipa", album="Future Nostalgia", duration_ms=203000, danceability=0.8, energy=0.9, valence=0.9, raw_data={})
+
+db.add_all([t1, t2, t3])
+db.commit()
+
+# Create history
+ph1 = PlayHistory(track_id="t1", played_at=datetime.utcnow() - timedelta(minutes=10))
+ph2 = PlayHistory(track_id="t2", played_at=datetime.utcnow() - timedelta(minutes=30))
+ph3 = PlayHistory(track_id="t3", played_at=datetime.utcnow() - timedelta(minutes=60))
+
+db.add_all([ph1, ph2, ph3])
+db.commit()
+
+print("Data populated")
+db.close()

backend/seed_data.py

@@ -0,0 +1,78 @@
+from datetime import datetime, timedelta
+import random
+from app.database import SessionLocal
+from app.models import Track, Artist, PlayHistory
+from app.services.stats_service import StatsService
+
+def seed_db():
+    db = SessionLocal()
+
+    # 1. Create Artists
+    artists = []
+    for i in range(10):
+        a = Artist(
+            id=f"artist_{i}",
+            name=f"Artist {i}",
+            genres=[random.choice(["pop", "rock", "jazz", "edm", "hip-hop"]) for _ in range(2)]
+        )
+        db.merge(a) # merge handles insert/update
+        artists.append(a)
+
+    db.commit()
+    print(f"Seeded {len(artists)} artists.")
+
+    # 2. Create Tracks
+    tracks = []
+    for i in range(50):
+        # Random artist
+        artist = random.choice(artists)
+
+        t = Track(
+            id=f"track_{i}",
+            name=f"Track {i}",
+            artist=artist.name, # Legacy
+            album=f"Album {i % 10}",
+            duration_ms=random.randint(180000, 300000), # 3-5 mins
+            popularity=random.randint(10, 90),
+            danceability=random.uniform(0.3, 0.9),
+            energy=random.uniform(0.3, 0.9),
+            valence=random.uniform(0.1, 0.9),
+            tempo=random.uniform(80, 160),
+            raw_data={"album": {"id": f"album_{i%10}", "release_date": f"{random.randint(2000, 2023)}-01-01"}}
+        )
+        # Link artist
+        t.artists.append(artist)
+        db.merge(t)
+        tracks.append(t)
+
+    db.commit()
+    print(f"Seeded {len(tracks)} tracks.")
+
+    # 3. Create Play History (Last 30 days)
+    plays = []
+    base_time = datetime.utcnow() - timedelta(days=25)
+
+    for i in range(200):
+        # Create sessions
+        # 80% chance next play is soon (2-5 mins), 20% chance gap (30-600 mins)
+        gap = random.randint(2, 6) if random.random() > 0.2 else random.randint(30, 600)
+        base_time += timedelta(minutes=gap)
+
+        if base_time > datetime.utcnow():
+            break
+
+        track = random.choice(tracks)
+
+        p = PlayHistory(
+            track_id=track.id,
+            played_at=base_time,
+            context_uri="spotify:playlist:fake"
+        )
+        db.add(p)
+
+    db.commit()
+    print(f"Seeded play history until {base_time}.")
+    db.close()
+
+if __name__ == "__main__":
+    seed_db()

backend/tests/conftest.py

@@ -0,0 +1,5 @@
+import pytest
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent.parent))

backend/tests/test_ingest.py

@@ -0,0 +1,113 @@
+import pytest
+from unittest.mock import MagicMock, AsyncMock, patch
+from datetime import datetime, timedelta
+
+from app.ingest import PlaybackTracker, finalize_track
+
+
+class TestPlaybackTracker:
+    def test_initial_state(self):
+        tracker = PlaybackTracker()
+        assert tracker.current_track_id is None
+        assert tracker.track_start_time is None
+        assert tracker.accumulated_listen_ms == 0
+        assert tracker.last_progress_ms == 0
+        assert tracker.is_paused is False
+
+
+class TestFinalizeTrack:
+    def test_finalize_creates_play_history_when_not_exists(self):
+        mock_db = MagicMock()
+        mock_db.query.return_value.filter.return_value.first.return_value = None
+
+        tracker = PlaybackTracker()
+        tracker.current_track_id = "track123"
+        tracker.track_start_time = datetime(2024, 1, 1, 10, 0, 0)
+        tracker.accumulated_listen_ms = 60000
+
+        finalize_track(mock_db, tracker)
+
+        mock_db.add.assert_called_once()
+        mock_db.commit.assert_called_once()
+
+        assert tracker.current_track_id is None
+        assert tracker.accumulated_listen_ms == 0
+
+    def test_finalize_marks_skip_when_under_30s(self):
+        mock_db = MagicMock()
+        mock_db.query.return_value.filter.return_value.first.return_value = None
+
+        tracker = PlaybackTracker()
+        tracker.current_track_id = "track123"
+        tracker.track_start_time = datetime(2024, 1, 1, 10, 0, 0)
+        tracker.accumulated_listen_ms = 15000
+
+        finalize_track(mock_db, tracker)
+
+        call_args = mock_db.add.call_args[0][0]
+        assert call_args.skipped is True
+
+    def test_finalize_updates_existing_play(self):
+        mock_existing = MagicMock()
+        mock_existing.listened_ms = None
+
+        mock_db = MagicMock()
+        mock_db.query.return_value.filter.return_value.first.return_value = (
+            mock_existing
+        )
+
+        tracker = PlaybackTracker()
+        tracker.current_track_id = "track123"
+        tracker.track_start_time = datetime(2024, 1, 1, 10, 0, 0)
+        tracker.accumulated_listen_ms = 120000
+
+        finalize_track(mock_db, tracker)
+
+        assert mock_existing.listened_ms == 120000
+        assert mock_existing.skipped is False
+        mock_db.commit.assert_called_once()
+
+
+class TestReccoBeatsClient:
+    @pytest.mark.asyncio
+    async def test_extracts_spotify_id_from_href(self):
+        from app.services.reccobeats_client import ReccoBeatsClient
+
+        with patch("httpx.AsyncClient") as mock_client:
+            mock_response = MagicMock()
+            mock_response.status_code = 200
+            mock_response.json.return_value = {
+                "content": [
+                    {
+                        "id": "uuid-here",
+                        "href": "https://open.spotify.com/track/abc123xyz",
+                        "energy": 0.8,
+                        "valence": 0.6,
+                    }
+                ]
+            }
+
+            mock_client.return_value.__aenter__.return_value.get = AsyncMock(
+                return_value=mock_response
+            )
+
+            client = ReccoBeatsClient()
+            result = await client.get_audio_features(["abc123xyz"])
+
+            assert len(result) == 1
+            assert result[0]["spotify_id"] == "abc123xyz"
+            assert result[0]["energy"] == 0.8
+
+    @pytest.mark.asyncio
+    async def test_returns_empty_on_error(self):
+        from app.services.reccobeats_client import ReccoBeatsClient
+
+        with patch("httpx.AsyncClient") as mock_client:
+            mock_client.return_value.__aenter__.return_value.get = AsyncMock(
+                side_effect=Exception("Network error")
+            )
+
+            client = ReccoBeatsClient()
+            result = await client.get_audio_features(["test123"])
+
+            assert result == []

backend/tests/test_main.py

@@ -0,0 +1,49 @@
+import pytest
+from unittest.mock import MagicMock, patch, AsyncMock
+from datetime import datetime
+
+
+@pytest.fixture
+def mock_db():
+    return MagicMock()
+
+
+class TestSnapshotsEndpoint:
+    def test_snapshots_endpoint_exists(self, mock_db):
+        with patch("app.main.SessionLocal", return_value=mock_db):
+            from fastapi.testclient import TestClient
+            from app.main import app
+
+            mock_db.query.return_value.order_by.return_value.limit.return_value.all.return_value = []
+
+            with TestClient(app) as client:
+                response = client.get("/snapshots?limit=1")
+                assert response.status_code == 200
+
+
+class TestListeningLogEndpoint:
+    def test_listening_log_endpoint_exists(self, mock_db):
+        with patch("app.main.SessionLocal", return_value=mock_db):
+            from fastapi.testclient import TestClient
+            from app.main import app
+
+            mock_db.query.return_value.options.return_value.filter.return_value.order_by.return_value.limit.return_value.all.return_value = []
+
+            with TestClient(app) as client:
+                response = client.get("/listening-log?days=7&limit=100")
+                assert response.status_code == 200
+
+
+class TestSessionsEndpoint:
+    def test_sessions_endpoint_exists(self, mock_db):
+        with patch("app.main.SessionLocal", return_value=mock_db):
+            from fastapi.testclient import TestClient
+            from app.main import app
+
+            mock_db.query.return_value.options.return_value.filter.return_value.order_by.return_value.all.return_value = []
+
+            with TestClient(app) as client:
+                response = client.get("/sessions?days=7")
+                assert response.status_code == 200
+                data = response.json()
+                assert "session_list" in data

backend/tests/test_playlist_service.py

@@ -0,0 +1,126 @@
+import pytest
+from unittest.mock import Mock, AsyncMock, MagicMock
+from datetime import datetime
+from app.services.playlist_service import PlaylistService
+from app.models import PlaylistConfig, Track
+
+
+@pytest.fixture
+def mock_db():
+    session = MagicMock()
+    # Mock query return values
+    session.query.return_value.filter.return_value.first.return_value = None
+    return session
+
+
+@pytest.fixture
+def mock_spotify():
+    client = AsyncMock()
+    client.create_playlist.return_value = {"id": "new_playlist_id"}
+    client.get_tracks.return_value = []
+    return client
+
+
+@pytest.fixture
+def mock_recco():
+    client = AsyncMock()
+    return client
+
+
+@pytest.fixture
+def mock_narrative():
+    service = Mock()
+    service.generate_playlist_theme.return_value = {
+        "theme_name": "Test Theme",
+        "description": "Test Description",
+        "curated_tracks": [],
+    }
+    return service
+
+
+@pytest.fixture
+def playlist_service(mock_db, mock_spotify, mock_recco, mock_narrative):
+    return PlaylistService(mock_db, mock_spotify, mock_recco, mock_narrative)
+
+
+@pytest.mark.asyncio
+async def test_ensure_playlists_exist_creates_new(
+    playlist_service, mock_db, mock_spotify
+):
+    # Setup: DB empty, Env vars assumed empty (or mocked)
+    mock_db.query.return_value.filter.return_value.first.return_value = None
+
+    result = await playlist_service.ensure_playlists_exist("user123")
+
+    assert result["six_hour_id"] == "new_playlist_id"
+    assert result["daily_id"] == "new_playlist_id"
+    assert mock_spotify.create_playlist.call_count == 2
+    # Verify persistence call
+    assert mock_db.add.call_count == 2  # Once for each
+    assert mock_db.commit.call_count == 2
+
+
+@pytest.mark.asyncio
+async def test_ensure_playlists_exist_loads_from_db(
+    playlist_service, mock_db, mock_spotify
+):
+    # Setup: DB has configs
+    mock_six = PlaylistConfig(key="six_hour", spotify_id="db_six_id")
+    mock_daily = PlaylistConfig(key="daily", spotify_id="db_daily_id")
+
+    # Mock return values for separate queries
+    # This is tricky with MagicMock chains.
+
+    # Simpler approach: Assuming the service calls query(PlaylistConfig).filter(...)
+    # We can just check the result logic without complex DB mocking if we abstract the DB access.
+    # But let's try to mock the specific return values based on call order if possible.
+    mock_query = mock_db.query.return_value
+    mock_filter = mock_query.filter
+
+    # Configure filter().first() to return mock_six then mock_daily
+    # But ensure_playlists_exist calls filter twice.
+    # mock_filter.return_value is the same object.
+    # mock_filter.return_value.first.side_effect = [mock_six, mock_daily]
+    # This assumes sequential execution order which is fragile but works for unit test.
+    # IMPORTANT: Ensure filter side_effect is cleared if set previously
+    mock_filter.side_effect = None
+    mock_filter.return_value.first.side_effect = [mock_six, mock_daily]
+
+    result = await playlist_service.ensure_playlists_exist("user123")
+
+    assert result["six_hour_id"] == "db_six_id"
+    assert result["daily_id"] == "db_daily_id"
+    mock_spotify.create_playlist.assert_not_called()
+
+
+def test_optimize_playlist_flow(playlist_service):
+    tracks = [
+        {"id": "1", "energy": 0.8},  # High
+        {"id": "2", "energy": 0.2},  # Low
+        {"id": "3", "energy": 0.5},  # Medium
+        {"id": "4", "energy": 0.9},  # High
+        {"id": "5", "energy": 0.3},  # Low
+    ]
+
+    # Expected sort: Low, Low, Medium, High, High
+    # Then split:
+    # Sorted: 2(0.2), 5(0.3), 3(0.5), 1(0.8), 4(0.9)
+    # Len 5.
+    # Low end: 5 * 0.3 = 1.5 -> 1. (Index 1) -> [2]
+    # High start: 5 * 0.7 = 3.5 -> 3. (Index 3) -> [1, 4]
+    # Medium: [5, 3]
+    # Result: Low + High + Medium = [2] + [1, 4] + [5, 3]
+    # Order: 2, 1, 4, 5, 3
+    # Energies: 0.2, 0.8, 0.9, 0.3, 0.5
+
+    optimized = playlist_service._optimize_playlist_flow(tracks)
+
+    ids = [t["id"] for t in optimized]
+    # Check if High energy tracks are in the middle/early part (Ramp Up)
+    # The current logic is Low -> High -> Medium.
+    # So we expect High energy block (1, 4) to be in the middle?
+    # Wait, code was: low_energy + high_energy + medium_energy
+
+    assert ids == ["2", "1", "4", "5", "3"]
+    assert optimized[0]["energy"] == 0.2
+    assert optimized[1]["energy"] == 0.8

backend/tests/test_stats.py

@@ -0,0 +1,69 @@
+import unittest
+from datetime import datetime, timedelta
+from unittest.mock import MagicMock
+from app.services.stats_service import StatsService
+from app.models import PlayHistory, Track, Artist
+
+class TestStatsService(unittest.TestCase):
+    def setUp(self):
+        self.mock_db = MagicMock()
+        self.service = StatsService(self.mock_db)
+
+    def test_compute_volume_stats_empty(self):
+        # Mock empty query result
+        self.mock_db.query.return_value.filter.return_value.all.return_value = []
+
+        start = datetime.utcnow()
+        end = datetime.utcnow()
+        stats = self.service.compute_volume_stats(start, end)
+
+        self.assertEqual(stats["total_plays"], 0)
+        self.assertEqual(stats["unique_tracks"], 0)
+
+    def test_compute_session_stats(self):
+        # Create dummy plays
+        t1 = datetime(2023, 1, 1, 10, 0, 0)
+        t2 = datetime(2023, 1, 1, 10, 5, 0) # 5 min gap (same session)
+        t3 = datetime(2023, 1, 1, 12, 0, 0) # 1h 55m gap (new session)
+
+        plays = [
+            PlayHistory(played_at=t1, track_id="1"),
+            PlayHistory(played_at=t2, track_id="2"),
+            PlayHistory(played_at=t3, track_id="3"),
+        ]
+
+        # Mock the query chain
+        # service.db.query().filter().order_by().all()
+        query_mock = self.mock_db.query.return_value.filter.return_value.order_by.return_value
+        query_mock.all.return_value = plays
+
+        stats = self.service.compute_session_stats(datetime.utcnow(), datetime.utcnow())
+
+        # Expected: 2 sessions ([t1, t2], [t3])
+        self.assertEqual(stats["count"], 2)
+        # Avg tracks: 3 plays / 2 sessions = 1.5
+        self.assertEqual(stats["avg_tracks"], 1.5)
+
+    def test_compute_skip_stats(self):
+        # Track duration = 30s
+        track = Track(id="t1", duration_ms=30000)
+
+        # Play 1: 10:00:00
+        # Play 2: 10:00:10 (Diff 10s. Duration 30s. 10 < 20 (30-10) -> Skip)
+        p1 = PlayHistory(played_at=datetime(2023, 1, 1, 10, 0, 0), track_id="t1")
+        p2 = PlayHistory(played_at=datetime(2023, 1, 1, 10, 0, 10), track_id="t1")
+
+        plays = [p1, p2]
+
+        query_mock = self.mock_db.query.return_value.filter.return_value.order_by.return_value
+        query_mock.all.return_value = plays
+
+        # Mock track lookup
+        self.mock_db.query.return_value.filter.return_value.all.return_value = [track]
+
+        stats = self.service.compute_skip_stats(datetime.utcnow(), datetime.utcnow())
+
+        self.assertEqual(stats["total_skips"], 1)
+
+if __name__ == '__main__':
+    unittest.main()

docker-compose.template.yml

@@ -0,0 +1,67 @@
+# MusicAnalyser Docker Compose Template
+# Copy this file to docker-compose.yml and fill in your values
+# Or use environment variables / .env file
+
+version: '3.8'
+
+services:
+  backend:
+    build:
+      context: ./backend
+    image: ghcr.io/bnair123/musicanalyser:latest
+    container_name: music-analyser-backend
+    restart: unless-stopped
+    volumes:
+      - music_data:/app/data
+    environment:
+      - DATABASE_URL=sqlite:////app/data/music.db
+      # Required: Spotify API credentials
+      - SPOTIFY_CLIENT_ID=your_spotify_client_id_here
+      - SPOTIFY_CLIENT_SECRET=your_spotify_client_secret_here
+      - SPOTIFY_REFRESH_TOKEN=your_spotify_refresh_token_here
+      # Required: AI API key (choose one)
+      - OPENAI_API_KEY=your_openai_api_key_here
+      # OR
+      - GEMINI_API_KEY=your_gemini_api_key_here
+      # Optional: Genius for lyrics
+      - GENIUS_ACCESS_TOKEN=your_genius_token_here
+      # Optional: Spotify Playlist IDs (will be created if not provided)
+      - SIX_HOUR_PLAYLIST_ID=your_playlist_id_here
+      - DAILY_PLAYLIST_ID=your_playlist_id_here
+    ports:
+      - '8000:8000'
+    networks:
+      - dockernet
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/snapshots?limit=1"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s
+
+  frontend:
+    build:
+      context: ./frontend
+    image: ghcr.io/bnair123/musicanalyser-frontend:latest
+    container_name: music-analyser-frontend
+    restart: unless-stopped
+    ports:
+      - '8991:80'
+    networks:
+      - dockernet
+    depends_on:
+      backend:
+        condition: service_healthy
+
+volumes:
+  music_data:
+    driver: local
+
+networks:
+  dockernet:
+    external: true
+    # If you don't have an external dockernet, create it with:
+    # docker network create dockernet
+    # Or change to:
+    # dockernet:
+    #   driver: bridge

docker-compose.yml

@@ -0,0 +1,41 @@
+version: '3.8'
+
+services:
+  backend:
+    build:
+      context: ./backend
+    image: ghcr.io/bnair123/musicanalyser:latest
+    container_name: music-analyser-backend
+    restart: unless-stopped
+    env_file:
+      - .env
+    environment:
+      - DATABASE_URL=postgresql://bnair:Bharath2002@music_db:5432/music_db
+    ports:
+      - '8088:8000'
+    networks:
+      - dockernet
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/snapshots?limit=1"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s
+
+  frontend:
+    build:
+      context: ./frontend
+    image: ghcr.io/bnair123/musicanalyser-frontend:latest
+    container_name: music-analyser-frontend
+    restart: unless-stopped
+    ports:
+      - '8991:80'
+    networks:
+      - dockernet
+    depends_on:
+      backend:
+        condition: service_healthy
+
+networks:
+  dockernet:
+    external: true

docs/API.md

@@ -0,0 +1,125 @@
+# API Documentation
+
+The MusicAnalyser Backend is built with FastAPI. It provides endpoints for data ingestion, listening history retrieval, and AI-powered analysis.
+
+## Base URL
+Default local development: `http://localhost:8000`
+Docker environment: Proxied via Nginx at `http://localhost:8991/api`
+
+---
+
+## Endpoints
+
+### 1. Root / Health Check
+- **URL**: `/`
+- **Method**: `GET`
+- **Response**:
+  ```json
+  {
+    "status": "ok",
+    "message": "Music Analyser API is running"
+  }
+  ```
+
+### 2. Get Recent History
+Returns a flat list of recently played tracks.
+- **URL**: `/history`
+- **Method**: `GET`
+- **Query Parameters**:
+  - `limit` (int, default=50): Number of items to return.
+- **Response**: List of PlayHistory objects with nested Track data.
+
+### 3. Get Tracks
+Returns a list of unique tracks in the database.
+- **URL**: `/tracks`
+- **Method**: `GET`
+- **Query Parameters**:
+  - `limit` (int, default=50): Number of tracks to return.
+
+### 4. Trigger Spotify Ingestion
+Manually triggers a background task to poll Spotify for recently played tracks.
+- **URL**: `/trigger-ingest`
+- **Method**: `POST`
+- **Response**:
+  ```json
+  {
+    "status": "Ingestion started in background"
+  }
+  ```
+
+### 5. Trigger Analysis Pipeline
+Runs the full stats calculation and AI narrative generation for a specific timeframe.
+- **URL**: `/trigger-analysis`
+- **Method**: `POST`
+- **Query Parameters**:
+  - `days` (int, default=30): Number of past days to analyze.
+  - `model_name` (str): LLM model to use.
+- **Response**:
+  ```json
+  {
+    "status": "success",
+    "snapshot_id": 1,
+    "period": { "start": "...", "end": "..." },
+    "metrics": { ... },
+    "narrative": { ... }
+  }
+  ```
+
+### 6. Get Analysis Snapshots
+Retrieves previously saved analysis reports.
+- **URL**: `/snapshots`
+- **Method**: `GET`
+- **Query Parameters**:
+  - `limit` (int, default=10): Number of snapshots to return.
+
+### 7. Detailed Listening Log
+Returns a refined listening log with skip detection and listening duration calculations.
+- **URL**: `/listening-log`
+- **Method**: `GET`
+- **Query Parameters**:
+  - `days` (int, 1-365, default=7): Timeframe.
+  - `limit` (int, 1-1000, default=200): Max plays to return.
+- **Response**:
+  ```json
+  {
+    "plays": [
+      {
+        "id": 123,
+        "track_name": "Song Name",
+        "artist": "Artist Name",
+        "played_at": "ISO-TIMESTAMP",
+        "listened_ms": 180000,
+        "skipped": false,
+        "image": "..."
+      }
+    ],
+    "period": { "start": "...", "end": "..." }
+  }
+  ```
+
+### 8. Session Statistics
+Groups plays into listening sessions (Marathon, Standard, Micro).
+- **URL**: `/sessions`
+- **Method**: `GET`
+- **Query Parameters**:
+  - `days` (int, 1-365, default=7): Timeframe.
+- **Response**:
+  ```json
+  {
+    "sessions": [
+      {
+        "start_time": "...",
+        "end_time": "...",
+        "duration_minutes": 45,
+        "track_count": 12,
+        "type": "Standard"
+      }
+    ],
+    "summary": {
+      "count": 10,
+      "avg_minutes": 35,
+      "micro_rate": 0.1,
+      "marathon_rate": 0.05
+    }
+  }
+  ```

docs/ARCHITECTURE.md

@@ -0,0 +1,43 @@
+# Architecture Overview
+
+MusicAnalyser is a full-stack personal analytics platform designed to collect, store, and analyze music listening habits using the Spotify API and Google Gemini AI.
+
+## System Components
+
+### 1. Backend (FastAPI)
+- **API Layer**: Handles requests from the frontend, manages the database, and triggers analysis.
+- **Database**: SQLite used for local storage of listening history, track metadata, and AI snapshots.
+- **ORM**: SQLAlchemy manages the data models and relationships.
+- **Services**:
+  - `SpotifyClient`: Handles OAuth2 flow and API requests.
+  - `StatsService`: Computes complex metrics (heatmaps, sessions, top tracks, hipster scores).
+  - `NarrativeService`: Interfaces with Google Gemini to generate text-based insights.
+  - `IngestService`: Manages the logic of fetching and deduplicating Spotify "recently played" data.
+
+### 2. Background Worker
+- A standalone Python script (`run_worker.py`) that polls the Spotify API every 60 seconds.
+- Ensures a continuous record of listening history even when the dashboard is not open.
+
+### 3. Frontend (React)
+- **Framework**: Vite + React.
+- **Styling**: Tailwind CSS for a modern, dark-themed dashboard.
+- **Visualizations**: Recharts for radar and heatmaps; Framer Motion for animations.
+- **State**: Managed via standard React hooks (`useState`, `useEffect`) and local storage for caching.
+
+### 4. External Integrations
+- **Spotify API**: Primary data source for tracks, artists, and listening history.
+- **ReccoBeats API**: Used for fetching audio features (BPM, Energy, Mood) for tracks.
+- **Genius API**: Used for fetching song lyrics to provide deep content analysis.
+- **Google Gemini**: Large Language Model used to "roast" the user's taste and generate personas.
+
+## Data Flow
+
+1. **Ingestion**: `Background Worker` → `Spotify API` → `Database (PlayHistory)`.
+2. **Enrichment**: `Ingest Logic` → `ReccoBeats/Genius/Spotify` → `Database (Track/Artist)`.
+3. **Analysis**: `Frontend` → `Backend API` → `StatsService` → `NarrativeService (Gemini)` → `Database (Snapshot)`.
+4. **Visualization**: `Frontend` ← `Backend API` ← `Database (Snapshot/Log)`.
+
+## Deployment
+- **Containerization**: Both Backend and Frontend are containerized using Docker.
+- **Docker Compose**: Orchestrates the backend (including worker) and frontend (Nginx proxy) services.
+- **CI/CD**: GitHub Actions builds multi-arch images (amd64/arm64) and pushes to GHCR.

docs/DATABASE.md

@@ -0,0 +1,271 @@
+# Database Documentation
+
+## PostgreSQL Connection Details
+
+| Property | Value |
+|----------|-------|
+| Host | `100.91.248.114` |
+| Port | `5433` |
+| User | `bnair` |
+| Password | `Bharath2002` |
+| Database | `music_db` |
+| Data Location (on server) | `/opt/DB/MusicDB/pgdata` |
+
+### Connection String
+```
+postgresql://bnair:Bharath2002@100.91.248.114:5433/music_db
+```
+
+## Schema Overview
+
+```
+┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
+│     artists     │     │   track_artists  │     │     tracks      │
+├─────────────────┤     ├──────────────────┤     ├─────────────────┤
+│ id (PK)         │◄────┤ artist_id (FK)   │     │ id (PK)         │
+│ name            │     │ track_id (FK)    │────►│ reccobeats_id   │
+│ genres (JSON)   │     └──────────────────┘     │ name            │
+│ image_url       │                              │ artist          │
+└─────────────────┘                              │ album           │
+                                                 │ image_url       │
+                                                 │ duration_ms     │
+                                                 │ popularity      │
+                                                 │ raw_data (JSON) │
+                                                 │ danceability    │
+                                                 │ energy          │
+                                                 │ key             │
+                                                 │ ... (audio)     │
+                                                 │ genres (JSON)   │
+                                                 │ lyrics          │
+                                                 │ created_at      │
+                                                 │ updated_at      │
+                                                 └─────────────────┘
+                                                         │
+                                                         │
+                                                         ▼
+┌─────────────────────┐                          ┌─────────────────┐
+│ analysis_snapshots  │                          │  play_history   │
+├─────────────────────┤                          ├─────────────────┤
+│ id (PK)             │                          │ id (PK)         │
+│ date                │                          │ track_id (FK)   │
+│ period_start        │                          │ played_at       │
+│ period_end          │                          │ context_uri     │
+│ period_label        │                          │ listened_ms     │
+│ metrics_payload     │                          │ skipped         │
+│ narrative_report    │                          │ source          │
+│ model_used          │                          └─────────────────┘
+│ playlist_theme      │
+│ ... (playlist)      │
+│ playlist_composition│
+└─────────────────────┘
+
+┌─────────────────────┐
+│   playlist_config   │
+├─────────────────────┤
+│ key (PK)            │
+│ spotify_id          │
+│ last_updated        │
+│ current_theme       │
+│ description         │
+│ composition (JSON)  │
+└─────────────────────┘
+```
+
+## Tables
+
+### `tracks`
+Central entity storing Spotify track metadata and enriched audio features.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | VARCHAR | Spotify track ID (primary key) |
+| `reccobeats_id` | VARCHAR | ReccoBeats UUID for audio features |
+| `name` | VARCHAR | Track title |
+| `artist` | VARCHAR | Display artist string (e.g., "Drake, Future") |
+| `album` | VARCHAR | Album name |
+| `image_url` | VARCHAR | Album art URL |
+| `duration_ms` | INTEGER | Track duration in milliseconds |
+| `popularity` | INTEGER | Spotify popularity score (0-100) |
+| `raw_data` | JSON | Full Spotify API response |
+| `danceability` | FLOAT | Audio feature (0.0-1.0) |
+| `energy` | FLOAT | Audio feature (0.0-1.0) |
+| `key` | INTEGER | Musical key (0-11) |
+| `loudness` | FLOAT | Audio feature (dB) |
+| `mode` | INTEGER | Major (1) or minor (0) |
+| `speechiness` | FLOAT | Audio feature (0.0-1.0) |
+| `acousticness` | FLOAT | Audio feature (0.0-1.0) |
+| `instrumentalness` | FLOAT | Audio feature (0.0-1.0) |
+| `liveness` | FLOAT | Audio feature (0.0-1.0) |
+| `valence` | FLOAT | Audio feature (0.0-1.0) |
+| `tempo` | FLOAT | BPM |
+| `time_signature` | INTEGER | Beats per bar |
+| `genres` | JSON | Genre tags (deprecated, use Artist.genres) |
+| `lyrics` | TEXT | Full lyrics from Genius |
+| `lyrics_summary` | VARCHAR | AI-generated summary |
+| `genre_tags` | VARCHAR | AI-generated tags |
+| `created_at` | TIMESTAMP | Record creation time |
+| `updated_at` | TIMESTAMP | Last update time |
+
+### `artists`
+Artist entities with genre information.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | VARCHAR | Spotify artist ID (primary key) |
+| `name` | VARCHAR | Artist name |
+| `genres` | JSON | List of genre strings |
+| `image_url` | VARCHAR | Artist profile image URL |
+
+### `track_artists`
+Many-to-many relationship between tracks and artists.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `track_id` | VARCHAR | Foreign key to tracks.id |
+| `artist_id` | VARCHAR | Foreign key to artists.id |
+
+### `play_history`
+Immutable log of listening events.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | INTEGER | Auto-increment primary key |
+| `track_id` | VARCHAR | Foreign key to tracks.id |
+| `played_at` | TIMESTAMP | When the track was played |
+| `context_uri` | VARCHAR | Spotify context (playlist, album, etc.) |
+| `listened_ms` | INTEGER | Duration actually listened |
+| `skipped` | BOOLEAN | Whether track was skipped |
+| `source` | VARCHAR | Source of the play event |
+
+### `analysis_snapshots`
+Stores computed statistics and AI-generated narratives.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | INTEGER | Auto-increment primary key |
+| `date` | TIMESTAMP | When analysis was run |
+| `period_start` | TIMESTAMP | Analysis period start |
+| `period_end` | TIMESTAMP | Analysis period end |
+| `period_label` | VARCHAR | Label (e.g., "last_30_days") |
+| `metrics_payload` | JSON | StatsService output |
+| `narrative_report` | JSON | NarrativeService output |
+| `model_used` | VARCHAR | LLM model name |
+| `playlist_theme` | VARCHAR | AI-generated theme name |
+| `playlist_theme_reasoning` | TEXT | AI explanation for theme |
+| `six_hour_playlist_id` | VARCHAR | Spotify playlist ID |
+| `daily_playlist_id` | VARCHAR | Spotify playlist ID |
+| `playlist_composition` | JSON | Track list at snapshot time |
+
+### `playlist_config`
+Configuration for managed Spotify playlists.
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `key` | VARCHAR | Config key (primary key, e.g., "six_hour") |
+| `spotify_id` | VARCHAR | Spotify playlist ID |
+| `last_updated` | TIMESTAMP | Last update time |
+| `current_theme` | VARCHAR | Current playlist theme |
+| `description` | VARCHAR | Playlist description |
+| `composition` | JSON | Current track list |
+
+## Schema Modifications (Alembic)
+
+All schema changes MUST go through Alembic migrations.
+
+### Creating a New Migration
+
+```bash
+cd backend
+source venv/bin/activate
+
+# Auto-generate migration from model changes
+alembic revision --autogenerate -m "description_of_change"
+
+# Or create empty migration for manual SQL
+alembic revision -m "description_of_change"
+```
+
+### Applying Migrations
+
+```bash
+# Apply all pending migrations
+alembic upgrade head
+
+# Apply specific migration
+alembic upgrade <revision_id>
+
+# Rollback one migration
+alembic downgrade -1
+
+# Rollback to specific revision
+alembic downgrade <revision_id>
+```
+
+### Migration Best Practices
+
+1. **Test locally first** - Always test migrations on a dev database
+2. **Backup before migrating** - `pg_dump -h 100.91.248.114 -p 5433 -U bnair music_db > backup.sql`
+3. **One change per migration** - Keep migrations atomic
+4. **Include rollback logic** - Implement `downgrade()` function
+5. **Review autogenerated migrations** - They may miss nuances
+
+### Example Migration
+
+```python
+# alembic/versions/xxxx_add_new_column.py
+from alembic import op
+import sqlalchemy as sa
+
+revision = 'xxxx'
+down_revision = 'yyyy'
+
+def upgrade():
+    op.add_column('tracks', sa.Column('new_column', sa.String(), nullable=True))
+
+def downgrade():
+    op.drop_column('tracks', 'new_column')
+```
+
+## Direct Database Access
+
+### Using psql
+```bash
+psql -h 100.91.248.114 -p 5433 -U bnair -d music_db
+```
+
+### Using Python
+```python
+import psycopg2
+conn = psycopg2.connect(
+    host='100.91.248.114',
+    port=5433,
+    user='bnair',
+    password='Bharath2002',
+    dbname='music_db'
+)
+```
+
+### Common Queries
+
+```sql
+-- Recent plays
+SELECT t.name, t.artist, ph.played_at 
+FROM play_history ph 
+JOIN tracks t ON ph.track_id = t.id 
+ORDER BY ph.played_at DESC 
+LIMIT 10;
+
+-- Top tracks by play count
+SELECT t.name, t.artist, COUNT(*) as plays 
+FROM play_history ph 
+JOIN tracks t ON ph.track_id = t.id 
+GROUP BY t.id, t.name, t.artist 
+ORDER BY plays DESC 
+LIMIT 10;
+
+-- Genre distribution
+SELECT genre, COUNT(*) 
+FROM artists, jsonb_array_elements_text(genres::jsonb) AS genre 
+GROUP BY genre 
+ORDER BY count DESC;
+```

docs/DATA_MODEL.md

@@ -0,0 +1,89 @@
+# Data Model Documentation
+
+This document describes the database schema for the MusicAnalyser project. The project uses SQLite with SQLAlchemy as the ORM.
+
+## Entity Relationship Diagram Overview
+
+- **Artist** (Many-to-Many) **Track**
+- **Track** (One-to-Many) **PlayHistory**
+- **AnalysisSnapshot** (Independent)
+
+---
+
+## Tables
+
+### `artists`
+Stores unique artists retrieved from Spotify.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | String | Spotify ID (Primary Key) |
+| `name` | String | Artist name |
+| `genres` | JSON | List of genre strings |
+| `image_url` | String | URL to artist profile image |
+
+### `tracks`
+Stores unique tracks retrieved from Spotify, enriched with audio features and lyrics.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | String | Spotify ID (Primary Key) |
+| `name` | String | Track name |
+| `artist` | String | Display string for artists (e.g., "Artist A, Artist B") |
+| `album` | String | Album name |
+| `image_url` | String | URL to album art |
+| `duration_ms` | Integer | Track duration in milliseconds |
+| `popularity` | Integer | Spotify popularity score (0-100) |
+| `raw_data` | JSON | Full raw response from Spotify API for future-proofing |
+| `danceability` | Float | Audio feature: Danceability (0.0 to 1.0) |
+| `energy` | Float | Audio feature: Energy (0.0 to 1.0) |
+| `key` | Integer | Audio feature: Key |
+| `loudness` | Float | Audio feature: Loudness in dB |
+| `mode` | Integer | Audio feature: Mode (0 for Minor, 1 for Major) |
+| `speechiness` | Float | Audio feature: Speechiness (0.0 to 1.0) |
+| `acousticness` | Float | Audio feature: Acousticness (0.0 to 1.0) |
+| `instrumentalness` | Float | Audio feature: Instrumentalness (0.0 to 1.0) |
+| `liveness` | Float | Audio feature: Liveness (0.0 to 1.0) |
+| `valence` | Float | Audio feature: Valence (0.0 to 1.0) |
+| `tempo` | Float | Audio feature: Tempo in BPM |
+| `time_signature` | Integer | Audio feature: Time signature |
+| `lyrics` | Text | Full lyrics retrieved from Genius |
+| `lyrics_summary` | String | AI-generated summary of lyrics |
+| `genre_tags` | String | Combined genre tags for the track |
+| `created_at` | DateTime | Timestamp of record creation |
+| `updated_at` | DateTime | Timestamp of last update |
+
+### `play_history`
+Stores individual listening instances.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | Integer | Primary Key (Auto-increment) |
+| `track_id` | String | Foreign Key to `tracks.id` |
+| `played_at` | DateTime | Timestamp when the track was played |
+| `context_uri` | String | Spotify context URI (e.g., playlist or album URI) |
+| `listened_ms` | Integer | Computed duration the track was actually heard |
+| `skipped` | Boolean | Whether the track was likely skipped |
+| `source` | String | Ingestion source (e.g., "spotify_recently_played") |
+
+### `analysis_snapshots`
+Stores periodic analysis results generated by the AI service.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | Integer | Primary Key |
+| `date` | DateTime | When the analysis was performed |
+| `period_start` | DateTime | Start of the analyzed period |
+| `period_end` | DateTime | End of the analyzed period |
+| `period_label` | String | Label for the period (e.g., "last_30_days") |
+| `metrics_payload` | JSON | Computed statistics used as input for the AI |
+| `narrative_report` | JSON | AI-generated narrative and persona |
+| `model_used` | String | LLM model identifier (e.g., "gemini-1.5-flash") |
+
+### `track_artists` (Association Table)
+Facilitates the many-to-many relationship between tracks and artists.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `track_id` | String | Foreign Key to `tracks.id` |
+| `artist_id` | String | Foreign Key to `artists.id` |

docs/FRONTEND.md

@@ -0,0 +1,61 @@
+# Frontend Documentation
+
+The frontend is a React application built with Vite and Tailwind CSS. It uses Ant Design for some UI components and Recharts for data visualization.
+
+## Main Components
+
+### `Dashboard.jsx`
+The primary layout component that manages data fetching and state.
+- **Features**: 
+  - Handles API calls to `/snapshots` and `/trigger-analysis`.
+  - Implements local storage caching to reduce API load.
+  - Displays a global loading state during analysis.
+  - Contains the main header with a refresh trigger.
+
+### `NarrativeSection.jsx`
+Displays the AI-generated qualitative analysis.
+- **Props**:
+  - `narrative`: Object containing `persona`, `vibe_check_short`, and `roast`.
+  - `vibe`: Object containing audio features used to generate dynamic tags.
+- **Purpose**: Gives the user a "identity" based on their music taste (e.g., "THE MELANCHOLIC ARCHITECT").
+
+### `StatsGrid.jsx`
+A grid of high-level metric cards.
+- **Props**:
+  - `metrics`: The `metrics_payload` from a snapshot.
+- **Displays**:
+  - **Minutes Listened**: Total listening time converted to days.
+  - **Obsession**: The #1 most played track with album art background.
+  - **Unique Artists**: Count of different artists encountered.
+  - **Hipster Score**: A percentage indicating how obscure the user's taste is.
+
+### `VibeRadar.jsx`
+Visualizes the "Sonic DNA" of the user.
+- **Props**:
+  - `vibe`: Audio feature averages (acousticness, danceability, energy, etc.).
+- **Visuals**:
+  - **Radar Chart**: Shows the balance of audio features.
+  - **Mood Clusters**: Floating bubbles representing "Party", "Focus", and "Chill" percentages.
+  - **Whiplash Meter**: Shows volatility in tempo, energy, and valence between consecutive tracks.
+
+### `TopRotation.jsx`
+A horizontal scrolling list of the most played tracks.
+- **Props**:
+  - `volume`: Object containing `top_tracks` array.
+- **Purpose**: Quick view of recent favorites.
+
+### `HeatMap.jsx`
+Visualizes when the user listens to music.
+- **Props**:
+  - `timeHabits`: Compressed heatmap data (7x6 grid for days/time blocks).
+  - `sessions`: List of recent listening sessions.
+- **Visuals**:
+  - **Grid**: Days of the week vs. Time blocks (12am, 4am, etc.).
+  - **Session Timeline**: Vertical list of recent listening bouts with session type (Marathon vs. Micro).
+
+### `ListeningLog.jsx`
+A detailed view of individual plays.
+- **Features**:
+  - **Timeline View**: Visualizes listening sessions across the day for the last 7 days.
+  - **List View**: A table of individual plays with skip status detection.
+  - **Timeframe Filter**: Toggle between 24h, 7d, 14d, and 30d views.

frontend/.gitignore

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

frontend/Dockerfile

@@ -0,0 +1,14 @@
+# Stage 1: Build the React app
+FROM node:18 as build
+WORKDIR /app
+COPY package*.json ./
+RUN npm install
+COPY . .
+RUN npm run build
+
+# Stage 2: Serve with Nginx
+FROM nginx:alpine
+COPY --from=build /app/dist /usr/share/nginx/html
+COPY nginx.conf /etc/nginx/conf.d/default.conf
+EXPOSE 80
+CMD ["nginx", "-g", "daemon off;"]

frontend/README.md

@@ -0,0 +1,16 @@
+# React + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) (or [oxc](https://oxc.rs) when used in [rolldown-vite](https://vite.dev/guide/rolldown)) for Fast Refresh
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh
+
+## React Compiler
+
+The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
+
+## Expanding the ESLint configuration
+
+If you are developing a production application, we recommend using TypeScript with type-aware lint rules enabled. Check out the [TS template](https://github.com/vitejs/vite/tree/main/packages/create-vite/template-react-ts) for information on how to integrate TypeScript and [`typescript-eslint`](https://typescript-eslint.io) in your project.

frontend/eslint.config.js

@@ -0,0 +1,29 @@
+import js from '@eslint/js'
+import globals from 'globals'
+import reactHooks from 'eslint-plugin-react-hooks'
+import reactRefresh from 'eslint-plugin-react-refresh'
+import { defineConfig, globalIgnores } from 'eslint/config'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{js,jsx}'],
+    extends: [
+      js.configs.recommended,
+      reactHooks.configs.flat.recommended,
+      reactRefresh.configs.vite,
+    ],
+    languageOptions: {
+      ecmaVersion: 2020,
+      globals: globals.browser,
+      parserOptions: {
+        ecmaVersion: 'latest',
+        ecmaFeatures: { jsx: true },
+        sourceType: 'module',
+      },
+    },
+    rules: {
+      'no-unused-vars': ['error', { varsIgnorePattern: '^[A-Z_]' }],
+    },
+  },
+])

frontend/index.html

@@ -0,0 +1,16 @@
+<!doctype html>
+<html lang="en" class="dark">
+  <head>
+    <meta charset="UTF-8" />
+    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>SonicStats - Your Vibe Report</title>
+    <!-- Google Fonts & Icons -->
+    <link href="https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@300;400;500;600;700&display=swap" rel="stylesheet">
+    <link href="https://fonts.googleapis.com/css2?family=Material+Symbols+Outlined:wght,FILL@100..700,0..1&display=swap" rel="stylesheet">
+  </head>
+  <body class="bg-background-light dark:bg-background-dark text-slate-900 dark:text-white font-display overflow-x-hidden min-h-screen flex flex-col">
+    <div id="root"></div>
+    <script type="module" src="/src/main.jsx"></script>
+  </body>
+</html>

frontend/nginx.conf

@@ -0,0 +1,22 @@
+server {
+    listen 80;
+
+    location / {
+        root /usr/share/nginx/html;
+        index index.html index.htm;
+        try_files $uri $uri/ /index.html;
+    }
+
+    # Proxy API requests to backend
+    location /api/ {
+        # 'backend' is the service name in docker-compose
+        # We strip the /api/ prefix if the backend doesn't expect it,
+        # but in this setup the backend routes are /history, /tracks etc.
+        # It's cleaner to keep /api prefix in frontend and rewrite here or configure backend to serve on /api
+        # For simplicity, let's proxy /api/ to /
+        rewrite ^/api/(.*) /$1 break;
+        proxy_pass http://backend:8000;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+    }
+}

frontend/package.json

@@ -0,0 +1,38 @@
+{
+  "name": "frontend",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "lint": "eslint .",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "@ant-design/icons": "^6.1.0",
+    "antd": "^6.1.2",
+    "axios": "^1.13.2",
+    "date-fns": "^4.1.0",
+    "framer-motion": "^12.23.26",
+    "lucide-react": "^0.562.0",
+    "react": "^19.2.0",
+    "react-dom": "^19.2.0",
+    "react-router-dom": "^7.11.0",
+    "recharts": "^3.6.0"
+  },
+  "devDependencies": {
+    "@eslint/js": "^9.39.1",
+    "@types/react": "^19.2.5",
+    "@types/react-dom": "^19.2.3",
+    "@vitejs/plugin-react": "^5.1.1",
+    "autoprefixer": "^10.4.23",
+    "eslint": "^9.39.1",
+    "eslint-plugin-react-hooks": "^7.0.1",
+    "eslint-plugin-react-refresh": "^0.4.24",
+    "globals": "^16.5.0",
+    "postcss": "^8.5.6",
+    "tailwindcss": "^3.4.19",
+    "vite": "^7.2.4"
+  }
+}

frontend/postcss.config.js

@@ -0,0 +1,6 @@
+export default {
+  plugins: {
+    tailwindcss: {},
+    autoprefixer: {},
+  },
+}

frontend/public/vite.svg

@@ -0,0 +1 @@
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frontend/src/App.jsx

@@ -0,0 +1,17 @@
+import React from 'react';
+import { BrowserRouter, Routes, Route } from 'react-router-dom';
+import Dashboard from './components/Dashboard';
+import Archives from './components/Archives';
+
+function App() {
+  return (
+    <BrowserRouter>
+      <Routes>
+        <Route path="/" element={<Dashboard />} />
+        <Route path="/archives" element={<Archives />} />
+      </Routes>
+    </BrowserRouter>
+  );
+}
+
+export default App;

frontend/src/assets/react.svg

@@ -0,0 +1 @@
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frontend/src/components/AGENTS.md

@@ -0,0 +1,34 @@
+# FRONTEND COMPONENTS KNOWLEDGE BASE
+
+**Directory:** `frontend/src/components`
+
+## OVERVIEW
+
+This directory contains the primary UI components for the MusicAnalyser dashboard. The architecture follows a **Presentational & Container pattern**, where `Dashboard.jsx` acts as the main container orchestrating data fetching and state, while sub-components handle specific visualizations and data displays.
+
+The UI is built with **React (Vite)**, utilizing **Tailwind CSS** for custom layouts/styling and **Ant Design** for basic UI primitives. Data visualization is powered by **Recharts** and custom SVG/Tailwind grid implementations.
+
+## WHERE TO LOOK
+
+| Component | Role | Complexity |
+|-----------|------|------------|
+| `Dashboard.jsx` | Main entry point. Handles API interaction (`/api/snapshots`), data caching (`localStorage`), and layout. | High |
+| `VibeRadar.jsx` | Uses `Recharts` RadarChart to visualize "Sonic DNA" (acousticness, energy, valence, etc.). | High |
+| `HeatMap.jsx` | Custom grid implementation for "Chronobiology" (listening density across days/time blocks). | Medium |
+| `StatsGrid.jsx` | Renders high-level metrics (Minutes Listened, "Obsession" Track, Hipster Score) in a responsive grid. | Medium |
+| `ListeningLog.jsx` | Displays a detailed list of recently played tracks. | Low |
+| `NarrativeSection.jsx` | Renders AI-generated narratives, "vibe checks", and "roasts". | Low |
+| `TopRotation.jsx` | Displays top artists and tracks with counts and popularity bars. | Medium |
+
+## CONVENTIONS
+
+- **Styling**: Leverages Tailwind utility classes.
+    - **Key Colors**: `primary` (#256af4), `card-dark` (#1e293b), `card-darker` (#0f172a).
+    - **Glassmorphism**: Use `glass-panel` for semi-transparent headers and panels.
+- **Icons**: Standardized on **Google Material Symbols** (`material-symbols-outlined`).
+- **Data Flow**: Unidirectional. `Dashboard.jsx` fetches data and passes specific slices down to sub-components via props.
+- **Caching**: API responses are cached in `localStorage` with a date-based key (`sonicstats_v2_YYYY-MM-DD`) to minimize redundant requests.
+- **Visualizations**: 
+    - Use `Recharts` for standard charts (Radar, Line).
+    - Use Tailwind grid and relative/absolute positioning for custom visualizations (HeatMap, Mood Clusters).
+- **Responsiveness**: Use responsive grid prefixes (`grid-cols-1 md:grid-cols-2 lg:grid-cols-4`) to ensure dashboard works across devices.

frontend/src/components/Archives.jsx

@@ -0,0 +1,209 @@
+import React, { useState, useEffect } from 'react';
+import axios from 'axios';
+import { Card, Typography, Spin, Drawer, Empty, Tag, Button } from 'antd';
+import { CalendarOutlined, RightOutlined, HistoryOutlined, RobotOutlined } from '@ant-design/icons';
+import NarrativeSection from './NarrativeSection';
+import StatsGrid from './StatsGrid';
+import TrackList from './TrackList';
+import Navbar from './Navbar';
+
+const { Title, Text } = Typography;
+
+const Archives = () => {
+  const [snapshots, setSnapshots] = useState([]);
+  const [loading, setLoading] = useState(true);
+  const [selectedSnapshot, setSelectedSnapshot] = useState(null);
+  const [drawerVisible, setDrawerVisible] = useState(false);
+
+  const fetchSnapshots = async () => {
+    setLoading(true);
+    try {
+      const response = await axios.get('/api/snapshots');
+      setSnapshots(response.data);
+    } catch (error) {
+      console.error('Failed to fetch snapshots:', error);
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  useEffect(() => {
+    fetchSnapshots();
+  }, []);
+
+  const handleSnapshotClick = (snapshot) => {
+    setSelectedSnapshot(snapshot);
+    setDrawerVisible(true);
+  };
+
+  const closeDrawer = () => {
+    setDrawerVisible(false);
+    setSelectedSnapshot(null);
+  };
+
+  // Helper to safely parse JSON if it comes as string (though axios usually handles it)
+  const safeParse = (data) => {
+    if (typeof data === 'string') {
+      try {
+        return JSON.parse(data);
+      } catch (e) {
+        return null;
+      }
+    }
+    return data;
+  };
+
+  return (
+    <>
+      <Navbar showRefresh={false} />
+      
+      <main className="w-full max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8 space-y-8">
+        <div className="flex items-center justify-between">
+          <Title level={2} className="text-white !mb-0 flex items-center gap-3">
+            <HistoryOutlined className="text-primary" />
+            Archives
+          </Title>
+          <Text className="text-slate-400">
+            {snapshots.length} Snapshot{snapshots.length !== 1 && 's'} Found
+          </Text>
+        </div>
+
+        {loading ? (
+          <div className="flex justify-center p-12">
+            <Spin size="large" />
+          </div>
+        ) : snapshots.length === 0 ? (
+          <div className="glass-panel p-12 text-center rounded-xl border border-dashed border-slate-700">
+            <Empty description={<span className="text-slate-400">No archives found yet.</span>} />
+          </div>
+        ) : (
+          <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-6">
+            {snapshots.map((snap) => {
+              const narrative = safeParse(snap.narrative_report);
+              const metrics = safeParse(snap.metrics_payload);
+              const date = new Date(snap.created_at);
+              
+              return (
+                <Card 
+                  key={snap.id}
+                  hoverable
+                  className="bg-slate-800 border-slate-700 shadow-xl transition-all duration-300 hover:border-primary/50 group"
+                  onClick={() => handleSnapshotClick(snap)}
+                >
+                  <div className="flex items-start justify-between mb-4">
+                    <Tag icon={<CalendarOutlined />} color="blue">
+                      {date.toLocaleDateString(undefined, { weekday: 'short', year: 'numeric', month: 'short', day: 'numeric' })}
+                    </Tag>
+                    <Text className="text-slate-500 text-xs font-mono">
+                      {date.toLocaleTimeString(undefined, { hour: '2-digit', minute: '2-digit' })}
+                    </Text>
+                  </div>
+                  
+                  <div className="space-y-3">
+                    <div>
+                      <Text className="text-slate-400 text-xs uppercase tracking-wider block mb-1">Vibe</Text>
+                      <Title level={4} className="!mt-0 !mb-1 text-white truncate">
+                        {metrics?.vibe || 'Unknown Vibe'}
+                      </Title>
+                    </div>
+
+                    <div>
+                      <Text className="text-slate-400 text-xs uppercase tracking-wider block mb-1">Musical Era</Text>
+                      <div className="flex items-center gap-2">
+                         <span className="text-primary font-bold">
+                           {metrics?.era?.musical_age || 'N/A'}
+                         </span>
+                      </div>
+                    </div>
+
+                    <div className="pt-4 border-t border-slate-700/50 flex justify-end">
+                      <Button type="text" className="text-slate-400 group-hover:text-primary flex items-center gap-1 pl-0">
+                        View Details <RightOutlined className="text-xs" />
+                      </Button>
+                    </div>
+                  </div>
+                </Card>
+              );
+            })}
+          </div>
+        )}
+
+        <Drawer
+          title={
+            <div className="flex items-center gap-3">
+              <CalendarOutlined className="text-primary" />
+              <span className="text-white">
+                Snapshot: {selectedSnapshot && new Date(selectedSnapshot.created_at).toLocaleDateString()}
+              </span>
+            </div>
+          }
+          placement="right"
+          width={800} // Wide drawer
+          onClose={closeDrawer}
+          open={drawerVisible}
+          className="bg-[#0f172a] text-white"
+          styles={{
+            header: { background: '#1e293b', borderBottom: '1px solid #334155' },
+            body: { background: '#0f172a', padding: '24px' },
+            mask: { backdropFilter: 'blur(4px)' }
+          }}
+        >
+          {selectedSnapshot && (
+            <div className="space-y-8">
+              {/* Reuse components but pass the specific snapshot data */}
+              <NarrativeSection 
+                narrative={safeParse(selectedSnapshot.narrative_report)} 
+                vibe={safeParse(selectedSnapshot.metrics_payload)?.vibe} 
+              />
+              
+              <StatsGrid metrics={safeParse(selectedSnapshot.metrics_payload)} />
+              
+              {/* Playlist Compositions if available */}
+              {selectedSnapshot.playlist_composition && (
+                <div className="space-y-6">
+                  <div className="flex items-center gap-2 mb-4">
+                    <HistoryOutlined className="text-blue-400 text-xl" />
+                    <Title level={3} className="!mb-0 text-white">Archived Playlists</Title>
+                  </div>
+                  
+                  {/* We need to parse playlist composition if it's stored as JSON string */}
+                  {(() => {
+                    const playlists = safeParse(selectedSnapshot.playlist_composition);
+                    if (!playlists) return <Text className="text-slate-500">No playlist data archived.</Text>;
+                    
+                    return (
+                      <div className="grid grid-cols-1 gap-6">
+                        {playlists.six_hour && (
+                          <Card className="bg-slate-800 border-slate-700" title={<span className="text-blue-400">Short & Sweet (6h)</span>}>
+                            <div className="mb-4">
+                              <Text className="text-gray-400 text-xs uppercase tracking-wider block mb-1">Theme</Text>
+                              <Text className="text-white font-medium block">{playlists.six_hour.theme}</Text>
+                              <Paragraph className="text-gray-400 text-sm italic mt-1">{playlists.six_hour.reasoning}</Paragraph>
+                            </div>
+                            <TrackList tracks={playlists.six_hour.composition} />
+                          </Card>
+                        )}
+                        
+                        {playlists.daily && (
+                          <Card className="bg-slate-800 border-slate-700" title={<span className="text-purple-400">Daily Devotion</span>}>
+                             <div className="mb-4">
+                              <Text className="text-gray-400 text-xs uppercase tracking-wider block mb-1">Strategy</Text>
+                              <Text className="text-white font-medium block">Daily Mix</Text>
+                            </div>
+                            <TrackList tracks={playlists.daily.composition} />
+                          </Card>
+                        )}
+                      </div>
+                    );
+                  })()}
+                </div>
+              )}
+            </div>
+          )}
+        </Drawer>
+      </main>
+    </>
+  );
+};
+
+export default Archives;

frontend/src/components/Dashboard.jsx

@@ -0,0 +1,167 @@
+import React, { useState, useEffect } from 'react';
+import axios from 'axios';
+import NarrativeSection from './NarrativeSection';
+import StatsGrid from './StatsGrid';
+import PlaylistsSection from './PlaylistsSection';
+import VibeRadar from './VibeRadar';
+import HeatMap from './HeatMap';
+import TopRotation from './TopRotation';
+import ListeningLog from './ListeningLog';
+import Navbar from './Navbar';
+import { Spin } from 'antd';
+
+const API_BASE_URL = '/api';
+
+const Dashboard = () => {
+    const [data, setData] = useState(null);
+    const [loading, setLoading] = useState(true);
+
+    const getTodayKey = () => `sonicstats_v2_${new Date().toISOString().split('T')[0]}`;
+
+    const fetchData = async (forceRefresh = false) => {
+        setLoading(true);
+        const todayKey = getTodayKey();
+
+        if (!forceRefresh) {
+            const cached = localStorage.getItem(todayKey);
+            if (cached) {
+                console.log("Loading from cache");
+                setData(JSON.parse(cached));
+                setLoading(false);
+                return;
+            }
+        }
+
+        try {
+            let payload;
+            if (forceRefresh) {
+                const res = await axios.post(`${API_BASE_URL}/trigger-analysis?days=30`);
+                payload = res.data;
+            } else {
+                const snapRes = await axios.get(`${API_BASE_URL}/snapshots?limit=1`);
+                if (snapRes.data && snapRes.data.length > 0) {
+                    const latest = snapRes.data[0];
+                    payload = {
+                        metrics: latest.metrics_payload,
+                        narrative: latest.narrative_report
+                    };
+                } else {
+                    const res = await axios.post(`${API_BASE_URL}/trigger-analysis?days=30`);
+                    payload = res.data;
+                }
+            }
+
+            if (payload) {
+                setData(payload);
+                localStorage.setItem(todayKey, JSON.stringify(payload));
+            }
+
+        } catch (error) {
+            console.error("Failed to fetch data", error);
+        } finally {
+            setLoading(false);
+        }
+    };
+
+    useEffect(() => {
+        fetchData();
+    }, []);
+
+    if (loading && !data) {
+        return (
+            <div className="min-h-screen bg-background-dark flex flex-col items-center justify-center text-white">
+                <Spin size="large" />
+                <p className="mt-4 text-slate-400 animate-pulse">Analyzing your auditory aura...</p>
+            </div>
+        );
+    }
+
+    const vibeCheckFull = data?.narrative?.vibe_check || "";
+    const patterns = data?.narrative?.patterns || [];
+
+    return (
+        <>
+            <Navbar onRefresh={() => fetchData(true)} />
+
+            <main className="flex-grow w-full max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8 space-y-8">
+                <NarrativeSection narrative={data?.narrative} vibe={data?.metrics?.vibe} />
+                
+                <StatsGrid metrics={data?.metrics} />
+
+                <PlaylistsSection />
+
+                <div className="grid grid-cols-1 lg:grid-cols-3 gap-8">
+                    <div className="lg:col-span-2 space-y-8">
+                        <VibeRadar vibe={data?.metrics?.vibe} />
+                        <TopRotation volume={data?.metrics?.volume} />
+                    </div>
+
+                    <div className="lg:col-span-1 space-y-8">
+                        <HeatMap timeHabits={data?.metrics?.time_habits} sessions={data?.metrics?.sessions} />
+                    </div>
+                </div>
+
+                <ListeningLog />
+
+                {(vibeCheckFull || patterns.length > 0) && (
+                    <div className="bg-card-dark border border-[#222f49] rounded-xl p-6">
+                        <h3 className="text-xl font-bold text-white mb-4 flex items-center gap-2">
+                            <span className="material-symbols-outlined text-primary">psychology</span>
+                            Full Analysis
+                        </h3>
+                        
+                        {vibeCheckFull && (
+                            <div className="prose prose-invert max-w-none mb-6">
+                                <p className="text-slate-300 leading-relaxed whitespace-pre-line">{vibeCheckFull}</p>
+                            </div>
+                        )}
+
+                        {patterns.length > 0 && (
+                            <div className="mt-4">
+                                <h4 className="text-sm text-slate-400 uppercase font-medium mb-3">Patterns Detected</h4>
+                                <ul className="space-y-2">
+                                    {patterns.map((pattern, idx) => (
+                                        <li key={idx} className="flex items-start gap-2 text-slate-300">
+                                            <span className="material-symbols-outlined text-primary text-sm mt-0.5">insights</span>
+                                            {pattern}
+                                        </li>
+                                    ))}
+                                </ul>
+                            </div>
+                        )}
+                    </div>
+                )}
+
+                {data?.narrative?.roast && (
+                    <footer className="pb-8">
+                        <div className="paper-texture rounded-xl p-8 border border-white/10 relative overflow-hidden group">
+                            <div className="relative z-10 flex flex-col md:flex-row gap-8 items-start md:items-center justify-between">
+                                <div className="max-w-md">
+                                    <div className="text-xs font-mono text-gray-500 mb-2 uppercase tracking-widest">Analysis Complete</div>
+                                    <h2 className="text-3xl font-black text-gray-900 leading-tight">
+                                        Your Musical Age is <span className="text-primary underline decoration-wavy">{data?.metrics?.era?.musical_age || "Unknown"}</span>.
+                                    </h2>
+                                    <p className="text-gray-600 mt-2 font-medium">
+                                        {data?.narrative?.era_insight || "You are timeless."}
+                                    </p>
+                                </div>
+                                <div className="flex-1 bg-white p-6 rounded-lg shadow-sm border border-gray-200 transform rotate-1 md:group-hover:rotate-0 transition-transform duration-300">
+                                    <div className="flex items-start gap-3">
+                                        <span className="material-symbols-outlined text-gray-400">smart_toy</span>
+                                        <div>
+                                            <p className="font-mono text-sm text-gray-800 leading-relaxed">
+                                                "{data.narrative.roast}"
+                                            </p>
+                                        </div>
+                                    </div>
+                                </div>
+                            </div>
+                        </div>
+                    </footer>
+                )}
+            </main>
+        </>
+    );
+};
+
+export default Dashboard;

frontend/src/components/HeatMap.jsx

@@ -0,0 +1,117 @@
+import React from 'react';
+import { format, parseISO } from 'date-fns';
+
+const HeatMap = ({ timeHabits, sessions }) => {
+    if (!timeHabits) return null;
+
+    const heatmapCompressed = timeHabits.heatmap_compressed || timeHabits.heatmap || [];
+    const blockLabels = timeHabits.block_labels || ["12am-4am", "4am-8am", "8am-12pm", "12pm-4pm", "4pm-8pm", "8pm-12am"];
+    const sessionList = sessions?.session_list || [];
+    
+    const days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'];
+    const blocks = blockLabels.length > 0 ? blockLabels : Array.from({ length: 6 }, (_, i) => `${i*4}h-${(i+1)*4}h`);
+    
+    const maxVal = Math.max(...heatmapCompressed.flat(), 1);
+
+    const getIntensityClass = (val) => {
+        if (val === 0) return "bg-[#1e293b]";
+        const ratio = val / maxVal;
+        if (ratio > 0.8) return "bg-primary";
+        if (ratio > 0.6) return "bg-primary/80";
+        if (ratio > 0.4) return "bg-primary/60";
+        if (ratio > 0.2) return "bg-primary/40";
+        return "bg-primary/20";
+    };
+
+    const recentSessions = sessionList.slice(-5).reverse();
+
+    const formatSessionTime = (isoString) => {
+        try {
+            return format(parseISO(isoString), 'MMM d, h:mm a');
+        } catch {
+            return isoString;
+        }
+    };
+
+    const getSessionTypeColor = (type) => {
+        if (type === "Marathon") return "bg-primary";
+        if (type === "Micro") return "bg-slate-600";
+        return "bg-primary/50";
+    };
+
+    return (
+        <div className="bg-card-dark border border-[#222f49] rounded-xl p-6 h-full">
+            <h3 className="text-xl font-bold text-white mb-6 flex items-center gap-2">
+                <span className="material-symbols-outlined text-primary">history</span>
+                Chronobiology
+            </h3>
+
+            <div className="mb-8">
+                <h4 className="text-sm text-slate-400 mb-3 font-medium">Listening Heatmap</h4>
+                
+                <div className="flex gap-2">
+                    <div className="flex flex-col justify-between text-[10px] text-slate-500 pr-1 py-1">
+                        {blocks.map((label, i) => (
+                            <span key={i} className="leading-tight">{label.split('-')[0]}</span>
+                        ))}
+                    </div>
+                    
+                    <div className="flex-1">
+                        <div className="grid grid-cols-7 gap-1 mb-2">
+                            {days.map((d, i) => (
+                                <div key={i} className="text-[10px] text-center text-slate-500 font-medium">{d}</div>
+                            ))}
+                        </div>
+                        
+                        <div className="grid grid-cols-7 gap-1">
+                            {blocks.map((block, blockIdx) => (
+                                days.map((day, dayIdx) => {
+                                    const val = heatmapCompressed[dayIdx]?.[blockIdx] || 0;
+                                    return (
+                                        <div 
+                                            key={`${dayIdx}-${blockIdx}`} 
+                                            className={`h-6 rounded ${getIntensityClass(val)} transition-colors hover:ring-2 hover:ring-primary/50`}
+                                            title={`${day} ${block} - ${val} plays`}
+                                        />
+                                    );
+                                })
+                            )).flat()}
+                        </div>
+                    </div>
+                </div>
+                
+                <div className="flex justify-end gap-1 mt-3 items-center">
+                    <span className="text-[9px] text-slate-500">Less</span>
+                    <div className="w-3 h-3 rounded-sm bg-primary/20"></div>
+                    <div className="w-3 h-3 rounded-sm bg-primary/40"></div>
+                    <div className="w-3 h-3 rounded-sm bg-primary/60"></div>
+                    <div className="w-3 h-3 rounded-sm bg-primary/80"></div>
+                    <div className="w-3 h-3 rounded-sm bg-primary"></div>
+                    <span className="text-[9px] text-slate-500">More</span>
+                </div>
+            </div>
+
+            <div>
+                <h4 className="text-sm text-slate-400 mb-4 font-medium">Recent Sessions</h4>
+                {recentSessions.length > 0 ? (
+                    <div className="relative pl-4 border-l border-[#334155] space-y-4">
+                        {recentSessions.map((session, idx) => (
+                            <div key={idx} className="relative">
+                                <span className={`absolute -left-[21px] top-1 h-2.5 w-2.5 rounded-full ${getSessionTypeColor(session.type)} ring-4 ring-card-dark`}></span>
+                                <p className="text-xs text-slate-400">{formatSessionTime(session.start_time)}</p>
+                                <p className="text-white font-bold text-sm">{session.type} Session</p>
+                                <p className="text-xs text-primary mt-0.5">
+                                    {session.duration_minutes}m · {session.track_count} tracks
+                                </p>
+                            </div>
+                        ))}
+                    </div>
+                ) : (
+                    <p className="text-sm text-slate-500">No session data yet</p>
+                )}
+            </div>
+        </div>
+    );
+};
+
+export default HeatMap;

frontend/src/components/ListeningLog.jsx

@@ -0,0 +1,202 @@
+import React, { useState, useEffect } from 'react';
+import axios from 'axios';
+import { format, parseISO, differenceInMinutes, startOfDay, endOfDay } from 'date-fns';
+
+const API_BASE_URL = '/api';
+
+const ListeningLog = () => {
+    const [plays, setPlays] = useState([]);
+    const [sessions, setSessions] = useState([]);
+    const [days, setDays] = useState(7);
+    const [loading, setLoading] = useState(true);
+    const [view, setView] = useState('timeline');
+
+    useEffect(() => {
+        fetchData();
+    }, [days]);
+
+    const fetchData = async () => {
+        setLoading(true);
+        try {
+            const [logRes, sessRes] = await Promise.all([
+                axios.get(`${API_BASE_URL}/listening-log?days=${days}&limit=500`),
+                axios.get(`${API_BASE_URL}/sessions?days=${days}`)
+            ]);
+            setPlays(logRes.data.plays || []);
+            setSessions(sessRes.data.sessions || []);
+        } catch (error) {
+            console.error("Failed to fetch listening log", error);
+        } finally {
+            setLoading(false);
+        }
+    };
+
+    const formatTime = (isoString) => {
+        try {
+            return format(parseISO(isoString), 'MMM d, h:mm a');
+        } catch {
+            return isoString;
+        }
+    };
+
+    const formatDuration = (ms) => {
+        if (!ms) return '-';
+        const mins = Math.round(ms / 60000);
+        return `${mins}m`;
+    };
+
+    const groupSessionsByDay = () => {
+        const dayMap = {};
+        sessions.forEach(session => {
+            const dayKey = format(parseISO(session.start_time), 'yyyy-MM-dd');
+            if (!dayMap[dayKey]) dayMap[dayKey] = [];
+            dayMap[dayKey].push(session);
+        });
+        return dayMap;
+    };
+
+    const sessionsByDay = groupSessionsByDay();
+    const sortedDays = Object.keys(sessionsByDay).sort().reverse().slice(0, 7);
+
+    const getSessionPosition = (session) => {
+        const start = parseISO(session.start_time);
+        const startMinutes = start.getHours() * 60 + start.getMinutes();
+        const leftPct = (startMinutes / 1440) * 100;
+        const widthPct = Math.max((session.duration_minutes / 1440) * 100, 1);
+        return { left: `${leftPct}%`, width: `${Math.min(widthPct, 100 - leftPct)}%` };
+    };
+
+    const getSessionColor = (type) => {
+        if (type === 'Marathon') return 'bg-primary';
+        if (type === 'Micro') return 'bg-slate-500';
+        return 'bg-primary/70';
+    };
+
+    return (
+        <div className="bg-card-dark border border-[#222f49] rounded-xl p-6">
+            <div className="flex items-center justify-between mb-6">
+                <h3 className="text-xl font-bold text-white flex items-center gap-2">
+                    <span className="material-symbols-outlined text-primary">library_music</span>
+                    Listening Log
+                </h3>
+                <div className="flex gap-2">
+                    <select 
+                        value={days}
+                        onChange={(e) => setDays(Number(e.target.value))}
+                        className="bg-card-darker border border-[#334155] rounded px-3 py-1 text-sm text-white"
+                    >
+                        <option value={1}>Last 24h</option>
+                        <option value={7}>Last 7 days</option>
+                        <option value={14}>Last 14 days</option>
+                        <option value={30}>Last 30 days</option>
+                    </select>
+                    <div className="flex border border-[#334155] rounded overflow-hidden">
+                        <button 
+                            onClick={() => setView('timeline')}
+                            className={`px-3 py-1 text-sm ${view === 'timeline' ? 'bg-primary text-white' : 'bg-card-darker text-slate-400'}`}
+                        >
+                            Timeline
+                        </button>
+                        <button 
+                            onClick={() => setView('list')}
+                            className={`px-3 py-1 text-sm ${view === 'list' ? 'bg-primary text-white' : 'bg-card-darker text-slate-400'}`}
+                        >
+                            List
+                        </button>
+                    </div>
+                </div>
+            </div>
+
+            {loading ? (
+                <div className="text-slate-400 text-center py-8">Loading...</div>
+            ) : view === 'timeline' ? (
+                <div className="space-y-4">
+                    <div className="flex text-[10px] text-slate-500 mb-2">
+                        <div className="w-20"></div>
+                        <div className="flex-1 flex justify-between">
+                            <span>12am</span>
+                            <span>6am</span>
+                            <span>12pm</span>
+                            <span>6pm</span>
+                            <span>12am</span>
+                        </div>
+                    </div>
+                    {sortedDays.map(day => (
+                        <div key={day} className="flex items-center gap-2">
+                            <div className="w-20 text-xs text-slate-400 shrink-0">
+                                {format(parseISO(day), 'EEE, MMM d')}
+                            </div>
+                            <div className="flex-1 h-8 bg-card-darker rounded relative">
+                                {sessionsByDay[day]?.map((session, idx) => {
+                                    const pos = getSessionPosition(session);
+                                    return (
+                                        <div
+                                            key={idx}
+                                            className={`absolute h-full rounded ${getSessionColor(session.type)} opacity-80 hover:opacity-100 cursor-pointer transition-opacity`}
+                                            style={{ left: pos.left, width: pos.width }}
+                                            title={`${session.type}: ${session.track_count} tracks, ${session.duration_minutes}m`}
+                                        />
+                                    );
+                                })}
+                            </div>
+                        </div>
+                    ))}
+                    <div className="flex gap-4 mt-4 text-xs text-slate-400">
+                        <div className="flex items-center gap-2">
+                            <div className="w-3 h-3 rounded bg-primary"></div>
+                            <span>Marathon (20+ tracks)</span>
+                        </div>
+                        <div className="flex items-center gap-2">
+                            <div className="w-3 h-3 rounded bg-primary/70"></div>
+                            <span>Standard</span>
+                        </div>
+                        <div className="flex items-center gap-2">
+                            <div className="w-3 h-3 rounded bg-slate-500"></div>
+                            <span>Micro (1-3 tracks)</span>
+                        </div>
+                    </div>
+                </div>
+            ) : (
+                <div className="overflow-x-auto">
+                    <table className="w-full text-sm">
+                        <thead>
+                            <tr className="text-left text-slate-400 border-b border-[#334155]">
+                                <th className="pb-2 font-medium">Track</th>
+                                <th className="pb-2 font-medium">Artist</th>
+                                <th className="pb-2 font-medium">Played</th>
+                                <th className="pb-2 font-medium">Listened</th>
+                                <th className="pb-2 font-medium">Status</th>
+                            </tr>
+                        </thead>
+                        <tbody>
+                            {plays.slice(0, 50).map((play, idx) => (
+                                <tr key={idx} className="border-b border-[#222f49] hover:bg-card-darker/50">
+                                    <td className="py-3">
+                                        <div className="flex items-center gap-3">
+                                            {play.image && (
+                                                <img src={play.image} alt="" className="w-10 h-10 rounded object-cover" />
+                                            )}
+                                            <span className="text-white font-medium truncate max-w-[200px]">{play.track_name}</span>
+                                        </div>
+                                    </td>
+                                    <td className="py-3 text-slate-400 truncate max-w-[150px]">{play.artist}</td>
+                                    <td className="py-3 text-slate-400">{formatTime(play.played_at)}</td>
+                                    <td className="py-3 text-slate-400">{formatDuration(play.listened_ms)}</td>
+                                    <td className="py-3">
+                                        {play.skipped ? (
+                                            <span className="px-2 py-0.5 rounded text-xs bg-red-500/20 text-red-400">Skipped</span>
+                                        ) : (
+                                            <span className="px-2 py-0.5 rounded text-xs bg-green-500/20 text-green-400">Played</span>
+                                        )}
+                                    </td>
+                                </tr>
+                            ))}
+                        </tbody>
+                    </table>
+                </div>
+            )}
+        </div>
+    );
+};
+
+export default ListeningLog;

frontend/src/components/NarrativeSection.jsx

@@ -0,0 +1,67 @@
+import React from 'react';
+import { motion } from 'framer-motion';
+
+const NarrativeSection = ({ narrative, vibe }) => {
+    if (!narrative) return null;
+
+    const persona = narrative.persona || "THE UNKNOWN LISTENER";
+    const vibeCheckShort = narrative.vibe_check_short || narrative.vibe_check?.substring(0, 120) + "..." || "Analyzing auditory aura...";
+
+    const getTags = () => {
+        if (!vibe) return [];
+        const tags = [];
+        const valence = vibe.valence || 0;
+        const energy = vibe.energy || 0;
+        const danceability = vibe.danceability || 0;
+
+        if (valence > 0.6) tags.push({ text: "HIGH VALENCE", color: "primary" });
+        else if (valence < 0.4) tags.push({ text: "MELANCHOLIC", color: "accent-purple" });
+        
+        if (energy > 0.6) tags.push({ text: "HIGH ENERGY", color: "accent-neon" });
+        else if (energy < 0.4) tags.push({ text: "CHILL VIBES", color: "accent-purple" });
+        
+        if (danceability > 0.7) tags.push({ text: "DANCEABLE", color: "primary" });
+        
+        return tags.slice(0, 3);
+    };
+
+    const tags = getTags();
+
+    if (tags.length === 0) {
+        tags.push({ text: "ECLECTIC", color: "primary" });
+        tags.push({ text: "MYSTERIOUS", color: "accent-purple" });
+    }
+
+    return (
+        <section className="relative rounded-2xl overflow-hidden min-h-[300px] flex items-center justify-center p-8 bg-card-dark border border-[#222f49]">
+            <div className="absolute inset-0 mood-gradient"></div>
+            
+            <div className="relative z-10 flex flex-col items-center text-center max-w-2xl gap-4">
+                <motion.div 
+                    initial={{ scale: 0.9, opacity: 0 }}
+                    animate={{ scale: 1, opacity: 1 }}
+                    transition={{ duration: 0.5 }}
+                    className="holographic-badge px-8 py-4 rounded-full border border-primary/30"
+                >
+                    <h1 className="text-3xl md:text-5xl font-black tracking-tight text-white drop-shadow-[0_0_15px_rgba(37,106,244,0.5)] uppercase">
+                        {persona}
+                    </h1>
+                </motion.div>
+                
+                <div className="font-mono text-primary/80 text-base md:text-lg font-medium tracking-wide max-w-lg">
+                    <span className="typing-cursor">{vibeCheckShort}</span>
+                </div>
+                
+                <div className="mt-2 flex gap-3 flex-wrap justify-center">
+                    {tags.map((tag, i) => (
+                        <span key={i} className={`px-3 py-1 rounded-full text-xs font-bold bg-${tag.color}/20 text-${tag.color} border border-${tag.color}/20`}>
+                            {tag.text}
+                        </span>
+                    ))}
+                </div>
+            </div>
+        </section>
+    );
+};
+
+export default NarrativeSection;

frontend/src/components/Navbar.jsx

@@ -0,0 +1,61 @@
+import React from 'react';
+import { NavLink } from 'react-router-dom';
+
+const Navbar = ({ onRefresh, showRefresh = true }) => {
+  return (
+    <header className="sticky top-0 z-50 glass-panel border-b border-[#222f49] backdrop-blur-md bg-[#0f172a]/80">
+      <div className="max-w-7xl mx-auto px-6 py-4 flex items-center justify-between">
+        <div className="flex items-center gap-8">
+          <NavLink to="/" className="flex items-center gap-3 hover:opacity-80 transition-opacity">
+            <div className="size-8 text-primary flex items-center justify-center">
+              <span className="material-symbols-outlined !text-3xl">equalizer</span>
+            </div>
+            <h2 className="text-xl font-bold tracking-tight text-white">SonicStats</h2>
+          </NavLink>
+          
+          <nav className="hidden md:flex items-center gap-1 bg-slate-800/50 p-1 rounded-lg border border-white/5">
+            <NavLink 
+              to="/" 
+              className={({ isActive }) => 
+                `px-4 py-1.5 rounded-md text-sm font-medium transition-all ${
+                  isActive 
+                    ? 'bg-primary text-white shadow-lg shadow-primary/25' 
+                    : 'text-slate-400 hover:text-white hover:bg-white/5'
+                }`
+              }
+            >
+              Dashboard
+            </NavLink>
+            <NavLink 
+              to="/archives" 
+              className={({ isActive }) => 
+                `px-4 py-1.5 rounded-md text-sm font-medium transition-all ${
+                  isActive 
+                    ? 'bg-primary text-white shadow-lg shadow-primary/25' 
+                    : 'text-slate-400 hover:text-white hover:bg-white/5'
+                }`
+              }
+            >
+              Archives
+            </NavLink>
+          </nav>
+        </div>
+
+        <div className="flex items-center gap-4">
+          {showRefresh && (
+            <button 
+              onClick={onRefresh}
+              className="size-10 flex items-center justify-center rounded-xl bg-card-dark hover:bg-card-darker transition-colors text-white border border-[#222f49]"
+              title="Refresh Data"
+            >
+              <span className="material-symbols-outlined text-[20px]">refresh</span>
+            </button>
+          )}
+          <div className="size-10 rounded-full bg-cover bg-center border-2 border-[#222f49]" style={{ backgroundImage: "url('https://api.dicebear.com/7.x/avataaars/svg?seed=Sonic')" }}></div>
+        </div>
+      </div>
+    </header>
+  );
+};
+
+export default Navbar;

frontend/src/components/PlaylistsSection.jsx

@@ -0,0 +1,255 @@
+import React, { useState, useEffect } from 'react';
+import axios from 'axios';
+import { Card, Button, Typography, Space, Spin, message, Tooltip as AntTooltip, Collapse, Empty } from 'antd';
+import { 
+  PlayCircleOutlined, 
+  ReloadOutlined, 
+  HistoryOutlined, 
+  InfoCircleOutlined,
+  CustomerServiceOutlined,
+  CalendarOutlined,
+  DownOutlined
+} from '@ant-design/icons';
+import Tooltip from './Tooltip';
+import TrackList from './TrackList';
+
+const { Title, Text, Paragraph } = Typography;
+
+const PlaylistsSection = () => {
+  const [loading, setLoading] = useState(true);
+  const [refreshing, setRefreshing] = useState({ sixHour: false, daily: false });
+  const [playlists, setPlaylists] = useState(null);
+  
+  const [history, setHistory] = useState([]);
+  const [loadingHistory, setLoadingHistory] = useState(false);
+  const [showHistory, setShowHistory] = useState(false);
+
+  const fetchPlaylists = async () => {
+    try {
+      const response = await axios.get('/api/playlists');
+      setPlaylists(response.data);
+    } catch (error) {
+      console.error('Failed to fetch playlists:', error);
+      message.error('Failed to load playlist metadata');
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  const fetchHistory = async () => {
+    if (loadingHistory) return;
+    setLoadingHistory(true);
+    try {
+      const response = await axios.get('/api/playlists/history');
+      setHistory(response.data.history || []);
+    } catch (error) {
+      console.error('Failed to fetch playlist history:', error);
+      message.error('Failed to load playlist history');
+    } finally {
+      setLoadingHistory(false);
+    }
+  };
+
+  useEffect(() => {
+    fetchPlaylists();
+  }, []);
+
+  useEffect(() => {
+    if (showHistory && history.length === 0) {
+      fetchHistory();
+    }
+  }, [showHistory]);
+
+  const handleRefresh = async (type) => {
+    const isSixHour = type === 'six-hour';
+    setRefreshing(prev => ({ ...prev, [isSixHour ? 'sixHour' : 'daily']: true }));
+    
+    try {
+      const endpoint = isSixHour ? '/api/playlists/refresh/six-hour' : '/api/playlists/refresh/daily';
+      await axios.post(endpoint);
+      message.success(`${isSixHour ? '6-Hour' : 'Daily'} playlist refreshed!`);
+      await fetchPlaylists();
+      if (showHistory) fetchHistory();
+    } catch (error) {
+      console.error(`Refresh failed for ${type}:`, error);
+      message.error(`Failed to refresh ${type} playlist`);
+    } finally {
+      setRefreshing(prev => ({ ...prev, [isSixHour ? 'sixHour' : 'daily']: false }));
+    }
+  };
+
+  if (loading) return <div className="flex justify-center p-8"><Spin size="large" /></div>;
+
+  const historyItems = history.map((item) => ({
+    key: item.id,
+    label: (
+      <div className="flex justify-between items-center w-full">
+        <div className="flex items-center space-x-3">
+          <Text className="text-gray-400 font-mono text-xs">
+            {new Date(item.date).toLocaleDateString(undefined, { month: 'short', day: 'numeric' })}
+          </Text>
+          <Text className="text-white font-medium">{item.theme}</Text>
+          <span className="px-2 py-0.5 rounded text-[10px] bg-slate-700 text-blue-300 border border-slate-600">
+            {item.period_label || '6h'}
+          </span>
+        </div>
+        <Text className="text-gray-500 text-xs">{item.composition?.length || 0} tracks</Text>
+      </div>
+    ),
+    children: (
+      <div className="pl-2">
+        <Paragraph className="text-gray-300 text-sm italic mb-2 border-l-2 border-blue-500 pl-3 py-1">
+          "{item.reasoning}"
+        </Paragraph>
+        <TrackList tracks={item.composition} maxHeight="max-h-96" />
+      </div>
+    ),
+  }));
+
+  return (
+    <div className="mt-8 space-y-6">
+      <div className="flex items-center space-x-2">
+        <Title level={3} className="!mb-0 text-white flex items-center">
+          <CustomerServiceOutlined className="mr-2 text-blue-400" />
+          AI Curated Playlists
+        </Title>
+        <Tooltip text="Dynamic playlists that evolve with your taste. Refreshed automatically, or trigger manually here.">
+          <InfoCircleOutlined className="text-gray-400 cursor-help" />
+        </Tooltip>
+      </div>
+
+      <div className="grid grid-cols-1 md:grid-cols-2 gap-6">
+        {/* 6-Hour Playlist */}
+        <Card 
+          className="bg-slate-800 border-slate-700 shadow-xl"
+          title={<span className="text-blue-400 flex items-center"><HistoryOutlined className="mr-2" /> Short & Sweet (6h)</span>}
+          extra={
+            <Button 
+              type="text" 
+              icon={<ReloadOutlined spin={refreshing.sixHour} />} 
+              onClick={() => handleRefresh('six-hour')}
+              className="text-gray-400 hover:text-white"
+              disabled={refreshing.sixHour}
+            />
+          }
+        >
+          <div className="space-y-4">
+            <div>
+              <Text className="text-gray-400 text-xs uppercase tracking-wider block mb-1">Current Theme</Text>
+              <Title level={4} className="!mt-0 !mb-1 text-white">{playlists?.six_hour?.theme || 'Calculating...'}</Title>
+              <Paragraph className="text-gray-300 text-sm italic mb-0">
+                "{playlists?.six_hour?.reasoning || 'Analyzing your recent listening patterns to find the perfect vibe.'}"
+              </Paragraph>
+              
+              <TrackList tracks={playlists?.six_hour?.composition} />
+            </div>
+            
+            <div className="flex items-center justify-between pt-2 border-t border-slate-700">
+              <div className="flex flex-col">
+                <Text className="text-gray-500 text-xs">Last Updated</Text>
+                <Text className="text-gray-300 text-xs font-mono">
+                  {playlists?.six_hour?.last_refresh ? new Date(playlists.six_hour.last_refresh).toLocaleString() : 'Never'}
+                </Text>
+              </div>
+              
+              <Button 
+                type="primary" 
+                shape="round" 
+                icon={<PlayCircleOutlined />}
+                href={`https://open.spotify.com/playlist/${playlists?.six_hour?.id}`}
+                target="_blank"
+                disabled={!playlists?.six_hour?.id}
+                className="bg-blue-600 hover:bg-blue-500 border-none"
+              >
+                Open Spotify
+              </Button>
+            </div>
+          </div>
+        </Card>
+
+        {/* Daily Playlist */}
+        <Card 
+          className="bg-slate-800 border-slate-700 shadow-xl"
+          title={<span className="text-purple-400 flex items-center"><PlayCircleOutlined className="mr-2" /> Proof of Commitment (24h)</span>}
+          extra={
+            <Button 
+              type="text" 
+              icon={<ReloadOutlined spin={refreshing.daily} />} 
+              onClick={() => handleRefresh('daily')}
+              className="text-gray-400 hover:text-white"
+              disabled={refreshing.daily}
+            />
+          }
+        >
+          <div className="space-y-4">
+            <div>
+              <Text className="text-gray-400 text-xs uppercase tracking-wider block mb-1">Daily Mix Strategy</Text>
+              <Title level={4} className="!mt-0 !mb-1 text-white">Daily Devotion Mix</Title>
+              <Paragraph className="text-gray-300 text-sm mb-0">
+                A blend of 30 all-time favorites and 20 recent discoveries to keep your rotation fresh but familiar.
+              </Paragraph>
+
+              <TrackList tracks={playlists?.daily?.composition} />
+            </div>
+            
+            <div className="flex items-center justify-between pt-2 border-t border-slate-700">
+              <div className="flex flex-col">
+                <Text className="text-gray-500 text-xs">Last Updated</Text>
+                <Text className="text-gray-300 text-xs font-mono">
+                  {playlists?.daily?.last_refresh ? new Date(playlists.daily.last_refresh).toLocaleString() : 'Never'}
+                </Text>
+              </div>
+              
+              <Button 
+                type="primary" 
+                shape="round" 
+                icon={<PlayCircleOutlined />}
+                href={`https://open.spotify.com/playlist/${playlists?.daily?.id}`}
+                target="_blank"
+                disabled={!playlists?.daily?.id}
+                className="bg-purple-600 hover:bg-purple-500 border-none"
+              >
+                Open Spotify
+              </Button>
+            </div>
+          </div>
+        </Card>
+      </div>
+
+      <div className="mt-8 border-t border-slate-700 pt-6">
+        <Button 
+          type="text" 
+          onClick={() => setShowHistory(!showHistory)}
+          className="flex items-center text-gray-400 hover:text-white p-0 text-lg font-medium mb-4 transition-colors"
+        >
+          <CalendarOutlined className="mr-2" />
+          Playlist Archives
+          <DownOutlined className={`ml-2 text-xs transition-transform duration-300 ${showHistory ? 'rotate-180' : ''}`} />
+        </Button>
+
+        {showHistory && (
+          <div className="animate-fade-in">
+            {loadingHistory ? (
+              <div className="flex justify-center p-8"><Spin /></div>
+            ) : history.length > 0 ? (
+              <Collapse 
+                items={historyItems} 
+                bordered={false} 
+                className="bg-transparent"
+                expandIconPosition="end"
+                ghost
+                theme="dark"
+                itemLayout="horizontal"
+                style={{ background: 'transparent' }}
+              />
+            ) : (
+              <Empty description={<span className="text-gray-500">No playlist history available yet</span>} />
+            )}
+          </div>
+        )}
+      </div>
+    </div>
+  );
+};
+
+export default PlaylistsSection;

frontend/src/components/StatsGrid.jsx

@@ -0,0 +1,93 @@
+import React from 'react';
+import Tooltip from './Tooltip';
+
+const StatsGrid = ({ metrics }) => {
+    if (!metrics) return null;
+
+    const totalMinutes = Math.round((metrics.volume?.estimated_minutes || 0));
+    const daysListened = (totalMinutes / (24 * 60)).toFixed(1);
+
+    const obsessionTrack = metrics.volume?.top_tracks?.[0];
+    const obsessionName = obsessionTrack ? obsessionTrack.name : "N/A";
+    const obsessionArtist = obsessionTrack ? obsessionTrack.artist : "N/A";
+    const obsessionCount = obsessionTrack ? obsessionTrack.count : 0;
+    const obsessionImage = obsessionTrack?.image || "https://images.unsplash.com/photo-1614613535308-eb5fbd3d2c17?q=80&w=400&auto=format&fit=crop";
+
+    const uniqueArtists = metrics.volume?.unique_artists || 0;
+    
+    const concentration = metrics.volume?.concentration?.hhi || 0;
+    const diversity = metrics.volume?.concentration?.gini || 0;
+    const peakHour = metrics.time_habits?.peak_hour !== undefined ? `${metrics.time_habits.peak_hour}:00` : "N/A";
+
+    return (
+        <section className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-4">
+            <div className="bg-card-dark border border-[#222f49] rounded-xl p-6 flex flex-col justify-between h-full min-h-[200px] group hover:border-primary/50 transition-colors">
+                <div className="flex items-start justify-between">
+                    <span className="text-slate-400 text-sm font-medium uppercase tracking-wider">Minutes Listened</span>
+                    <span className="material-symbols-outlined text-primary">schedule</span>
+                </div>
+                <div>
+                    <div className="text-4xl lg:text-5xl font-bold text-white mb-2">{totalMinutes.toLocaleString()}</div>
+                    <div className="text-accent-neon text-sm font-medium flex items-center gap-1">
+                        <span className="material-symbols-outlined text-sm">trending_up</span>
+                        That's {daysListened} days straight
+                    </div>
+                </div>
+            </div>
+
+            <div className="bg-card-dark border border-[#222f49] rounded-xl relative overflow-hidden h-full min-h-[200px] group lg:col-span-2">
+                <div 
+                    className="absolute inset-0 bg-cover bg-center transition-transform duration-700 group-hover:scale-105" 
+                    style={{ backgroundImage: `url('${obsessionImage}')` }}
+                >
+                    <div className="absolute inset-0 bg-gradient-to-t from-black via-black/50 to-transparent"></div>
+                </div>
+                <div className="relative z-10 p-6 flex flex-col justify-end h-full">
+                    <div className="flex justify-between items-end">
+                        <div>
+                            <span className="inline-block px-2 py-1 rounded bg-primary/80 text-white text-[10px] font-bold tracking-widest mb-2">OBSESSION</span>
+                            <h3 className="text-2xl font-bold text-white leading-tight truncate max-w-[200px] md:max-w-[300px]">{obsessionName}</h3>
+                            <p className="text-slate-300">{obsessionArtist}</p>
+                        </div>
+                        <div className="text-right hidden sm:block">
+                            <div className="text-3xl font-bold text-white">{obsessionCount}</div>
+                            <div className="text-xs text-slate-400 uppercase">Plays this month</div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <div className="flex flex-col gap-4 h-full">
+                <div className="bg-card-dark border border-[#222f49] rounded-xl p-5 flex-1 flex flex-col justify-center items-center text-center group">
+                    <div className="flex items-center gap-2 mb-1">
+                        <div className="text-3xl font-bold text-white">{uniqueArtists}</div>
+                        <Tooltip text="The number of unique artists you've listened to in this period.">
+                            <span className="material-symbols-outlined text-slate-500 text-sm cursor-help">info</span>
+                        </Tooltip>
+                    </div>
+                    <div className="text-slate-400 text-xs uppercase tracking-wider">Unique Artists</div>
+                </div>
+                
+                <div className="bg-card-dark border border-[#222f49] rounded-xl p-5 flex-1 flex flex-col justify-center items-center group">
+                    <div className="flex items-center gap-4">
+                        <div className="text-center">
+                            <Tooltip text="Concentration score (HHI). High means you focus on few artists, low means you spread your listening.">
+                                <div className="text-xl font-bold text-white">{(1 - concentration).toFixed(2)}</div>
+                                <div className="text-slate-500 text-[9px] uppercase tracking-tighter">Variety</div>
+                            </Tooltip>
+                        </div>
+                        <div className="w-px h-8 bg-slate-700"></div>
+                        <div className="text-center">
+                            <Tooltip text={`Your peak listening time is around ${peakHour}.`}>
+                                <div className="text-xl font-bold text-white">{peakHour}</div>
+                                <div className="text-slate-500 text-[9px] uppercase tracking-tighter">Peak Time</div>
+                            </Tooltip>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </section>
+    );
+};
+
+export default StatsGrid;

frontend/src/components/Tooltip.jsx

@@ -0,0 +1,25 @@
+import React, { useState } from 'react';
+
+const Tooltip = ({ text, children }) => {
+  const [isVisible, setIsVisible] = useState(false);
+
+  return (
+    <div 
+      className="relative flex items-center group"
+      onMouseEnter={() => setIsVisible(true)}
+      onMouseLeave={() => setIsVisible(false)}
+      onFocus={() => setIsVisible(true)}
+      onBlur={() => setIsVisible(false)}
+    >
+      {children}
+      {isVisible && (
+        <div className="absolute z-50 px-3 py-2 text-sm font-medium text-white transition-opacity duration-300 bg-gray-900 rounded-lg shadow-sm opacity-100 -top-12 left-1/2 -translate-x-1/2 whitespace-nowrap dark:bg-gray-700">
+          {text}
+          <div className="absolute w-2 h-2 bg-gray-900 rotate-45 -bottom-1 left-1/2 -translate-x-1/2 dark:bg-gray-700"></div>
+        </div>
+      )}
+    </div>
+  );
+};
+
+export default Tooltip;

frontend/src/components/TopRotation.jsx

@@ -0,0 +1,41 @@
+import React from 'react';
+
+const TopRotation = ({ volume }) => {
+    if (!volume || !volume.top_tracks) return null;
+
+    const fallbackImage = "https://images.unsplash.com/photo-1619983081563-430f63602796?q=80&w=200&auto=format&fit=crop";
+
+    return (
+        <div className="bg-card-dark border border-[#222f49] rounded-xl p-6 overflow-hidden">
+            <div className="flex items-center justify-between mb-4">
+                <h3 className="text-xl font-bold text-white">Top Rotation</h3>
+                <div className="flex gap-2">
+                    <span className="size-2 rounded-full bg-primary"></span>
+                    <span className="size-2 rounded-full bg-slate-600"></span>
+                </div>
+            </div>
+            
+            <div className="flex gap-4 overflow-x-auto no-scrollbar pb-2">
+                {volume.top_tracks.slice(0, 5).map((track, i) => {
+                     const name = track.name || "Unknown";
+                     const artist = track.artist || "Unknown";
+                     const image = track.image || fallbackImage;
+                     
+                     return (
+                        <div key={i} className={`min-w-[140px] flex flex-col gap-2 group cursor-pointer ${i === 0 ? 'min-w-[180px]' : 'opacity-80 hover:opacity-100 transition-opacity pt-4'}`}>
+                            <div 
+                                className={`w-full aspect-square rounded-lg bg-cover bg-center ${i === 0 ? 'shadow-lg shadow-black/50 transition-transform group-hover:scale-105' : ''}`} 
+                                style={{ backgroundImage: `url('${image}')` }}
+                            ></div>
+                            <p className={`text-white font-medium truncate ${i === 0 ? 'font-bold' : 'text-sm'}`}>{name}</p>
+                            <p className="text-xs text-slate-400 truncate">{artist}</p>
+                            <p className="text-xs text-primary">{track.count} plays</p>
+                        </div>
+                    );
+                })}
+            </div>
+        </div>
+    );
+};
+
+export default TopRotation;

frontend/src/components/TrackList.jsx

@@ -0,0 +1,61 @@
+import React from 'react';
+import { Button, Typography, Tooltip as AntTooltip, Avatar } from 'antd';
+import { 
+  PlayCircleOutlined, 
+  HistoryOutlined, 
+  CustomerServiceOutlined,
+  RobotOutlined
+} from '@ant-design/icons';
+
+const { Text } = Typography;
+
+const TrackList = ({ tracks, maxHeight = "max-h-60" }) => {
+  if (!tracks || tracks.length === 0) return <div className="text-gray-500 text-sm py-4 text-center">No tracks available</div>;
+
+  return (
+    <div className={`${maxHeight} overflow-y-auto custom-scrollbar pr-2 -mr-2 my-4 space-y-2`}>
+      {tracks.map((track, idx) => (
+        <div key={`${track.id}-${idx}`} className="flex items-center p-2 rounded-lg bg-slate-700/50 hover:bg-slate-700 transition-colors group">
+          <div className="flex-shrink-0 relative">
+            <Avatar shape="square" size={40} src={track.image_url} icon={<CustomerServiceOutlined />} />
+            <div className="absolute -top-1 -right-1">
+              {track.source === 'recommendation' ? (
+                <AntTooltip title="AI Recommendation">
+                  <div className="bg-purple-500 rounded-full p-0.5 w-4 h-4 flex items-center justify-center">
+                    <RobotOutlined className="text-white text-[10px]" />
+                  </div>
+                </AntTooltip>
+              ) : (
+                <AntTooltip title="From History">
+                  <div className="bg-blue-500 rounded-full p-0.5 w-4 h-4 flex items-center justify-center">
+                    <HistoryOutlined className="text-white text-[10px]" />
+                  </div>
+                </AntTooltip>
+              )}
+            </div>
+          </div>
+          <div className="ml-3 flex-grow min-w-0">
+            <Text className="text-white text-sm font-medium truncate block" title={track.name}>
+              {track.name}
+            </Text>
+            <Text className="text-gray-400 text-xs truncate block" title={track.artist}>
+              {track.artist}
+            </Text>
+          </div>
+          <div className="ml-2 opacity-0 group-hover:opacity-100 transition-opacity">
+            <Button 
+              type="text" 
+              size="small" 
+              icon={<PlayCircleOutlined />} 
+              href={`https://open.spotify.com/track/${track.id}`}
+              target="_blank"
+              className="text-gray-400 hover:text-white"
+            />
+          </div>
+        </div>
+      ))}
+    </div>
+  );
+};
+
+export default TrackList;

frontend/src/components/VibeRadar.jsx

@@ -0,0 +1,128 @@
+import React from 'react';
+import { Radar, RadarChart, PolarGrid, PolarAngleAxis, PolarRadiusAxis, ResponsiveContainer } from 'recharts';
+
+const VibeRadar = ({ vibe }) => {
+    if (!vibe) return null;
+
+    const data = [
+        { subject: 'Acoustic', A: vibe.acousticness || 0, fullMark: 1 },
+        { subject: 'Dance', A: vibe.danceability || 0, fullMark: 1 },
+        { subject: 'Energy', A: vibe.energy || 0, fullMark: 1 },
+        { subject: 'Instrumental', A: vibe.instrumentalness || 0, fullMark: 1 },
+        { subject: 'Valence', A: vibe.valence || 0, fullMark: 1 },
+        { subject: 'Live', A: vibe.liveness || 0, fullMark: 1 },
+    ];
+
+    const energy = vibe.energy || 0;
+    const danceability = vibe.danceability || 0;
+    const instrumentalness = vibe.instrumentalness || 0;
+    const valence = vibe.valence || 0;
+    const acousticness = vibe.acousticness || 0;
+
+    const partyScore = Math.round(((energy + danceability) / 2) * 100);
+    const focusScore = Math.round(((instrumentalness + (1 - valence)) / 2) * 100);
+    const chillScore = Math.round(((acousticness + (1 - energy)) / 2) * 100);
+    
+    const total = partyScore + focusScore + chillScore || 1;
+    const partyPct = Math.round((partyScore / total) * 100);
+    const focusPct = Math.round((focusScore / total) * 100);
+    const chillPct = 100 - partyPct - focusPct;
+
+    const whiplash = vibe.whiplash || {};
+    const maxWhiplash = Math.max(
+        whiplash.tempo || 0,
+        (whiplash.energy || 0) * 100,
+        (whiplash.valence || 0) * 100
+    );
+    const volatilityLevel = maxWhiplash > 25 ? "HIGH" : maxWhiplash > 12 ? "MEDIUM" : "LOW";
+    const volatilityColor = volatilityLevel === "HIGH" ? "text-red-400" : volatilityLevel === "MEDIUM" ? "text-yellow-400" : "text-green-400";
+
+    return (
+        <div className="bg-card-dark border border-[#222f49] rounded-xl p-6">
+            <div className="flex items-center justify-between mb-6">
+                <h3 className="text-xl font-bold text-white flex items-center gap-2">
+                    <span className="material-symbols-outlined text-primary">fingerprint</span> 
+                    Sonic DNA
+                </h3>
+            </div>
+            
+            <div className="grid grid-cols-1 md:grid-cols-2 gap-8">
+                <div className="aspect-square relative flex items-center justify-center bg-card-darker rounded-lg border border-[#222f49]/50 p-4">
+                    <ResponsiveContainer width="100%" height={200} minHeight={200}>
+                        <RadarChart cx="50%" cy="50%" outerRadius="70%" data={data}>
+                            <PolarGrid stroke="#334155" />
+                            <PolarAngleAxis dataKey="subject" tick={{ fill: '#94a3b8', fontSize: 12 }} />
+                            <PolarRadiusAxis angle={30} domain={[0, 1]} tick={false} axisLine={false} />
+                            <Radar
+                                name="My Vibe"
+                                dataKey="A"
+                                stroke="#256af4"
+                                strokeWidth={2}
+                                fill="rgba(37, 106, 244, 0.4)"
+                                fillOpacity={0.4}
+                            />
+                        </RadarChart>
+                    </ResponsiveContainer>
+                </div>
+
+                <div className="flex flex-col gap-6">
+                    <div className="flex-1 flex flex-col justify-center">
+                        <h4 className="text-sm text-slate-400 mb-4 font-medium uppercase">Mood Clusters</h4>
+                        <div className="relative h-40 w-full rounded-lg border border-dashed border-[#334155] bg-card-darker/50">
+                            <div className="absolute top-1/2 left-1/4 -translate-x-1/2 -translate-y-1/2 size-20 rounded-full bg-primary/20 border border-primary text-primary flex items-center justify-center text-xs font-bold text-center p-1 cursor-pointer hover:bg-primary hover:text-white transition-colors z-10">
+                                Party<br/>{partyPct}%
+                            </div>
+                            <div className="absolute top-1/3 right-1/4 size-14 rounded-full bg-accent-purple/20 border border-accent-purple text-accent-purple flex items-center justify-center text-[10px] font-bold text-center p-1 cursor-pointer hover:bg-accent-purple hover:text-white transition-colors">
+                                Focus<br/>{focusPct}%
+                            </div>
+                            <div className="absolute bottom-4 right-1/3 size-12 rounded-full bg-accent-neon/20 border border-accent-neon text-accent-neon flex items-center justify-center text-[10px] font-bold text-center p-1 cursor-pointer hover:bg-accent-neon hover:text-black transition-colors">
+                                Chill<br/>{chillPct}%
+                            </div>
+                        </div>
+                    </div>
+
+                    <div>
+                        <div className="flex justify-between items-end mb-2">
+                            <h4 className="text-sm text-slate-400 font-medium uppercase">Whiplash Meter</h4>
+                            <span className={`text-xs font-bold ${volatilityColor}`}>{volatilityLevel} VOLATILITY</span>
+                        </div>
+                        <div className="space-y-2">
+                            <div className="flex items-center gap-2">
+                                <span className="text-xs text-slate-500 w-16">Tempo</span>
+                                <div className="flex-1 h-2 bg-card-darker rounded overflow-hidden">
+                                    <div 
+                                        className="h-full bg-gradient-to-r from-primary to-red-500 transition-all"
+                                        style={{ width: `${Math.min((whiplash.tempo || 0) / 40 * 100, 100)}%` }}
+                                    />
+                                </div>
+                                <span className="text-xs text-slate-400 w-12 text-right">{(whiplash.tempo || 0).toFixed(1)}</span>
+                            </div>
+                            <div className="flex items-center gap-2">
+                                <span className="text-xs text-slate-500 w-16">Energy</span>
+                                <div className="flex-1 h-2 bg-card-darker rounded overflow-hidden">
+                                    <div 
+                                        className="h-full bg-gradient-to-r from-primary to-yellow-500 transition-all"
+                                        style={{ width: `${Math.min((whiplash.energy || 0) * 100 / 0.4 * 100, 100)}%` }}
+                                    />
+                                </div>
+                                <span className="text-xs text-slate-400 w-12 text-right">{((whiplash.energy || 0) * 100).toFixed(0)}%</span>
+                            </div>
+                            <div className="flex items-center gap-2">
+                                <span className="text-xs text-slate-500 w-16">Valence</span>
+                                <div className="flex-1 h-2 bg-card-darker rounded overflow-hidden">
+                                    <div 
+                                        className="h-full bg-gradient-to-r from-primary to-green-500 transition-all"
+                                        style={{ width: `${Math.min((whiplash.valence || 0) * 100 / 0.4 * 100, 100)}%` }}
+                                    />
+                                </div>
+                                <span className="text-xs text-slate-400 w-12 text-right">{((whiplash.valence || 0) * 100).toFixed(0)}%</span>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    );
+};
+
+export default VibeRadar;

frontend/src/index.css

@@ -0,0 +1,88 @@
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+/* Custom Utilities from code.html */
+.glass-panel {
+    background: rgba(24, 34, 52, 0.6);
+    backdrop-filter: blur(12px);
+    -webkit-backdrop-filter: blur(12px);
+    border: 1px solid rgba(255, 255, 255, 0.08);
+}
+
+.holographic-badge {
+    background: linear-gradient(135deg, rgba(255, 255, 255, 0.1) 0%, rgba(255, 255, 255, 0.05) 100%);
+    box-shadow: 0 0 20px rgba(37, 106, 244, 0.3), inset 0 0 0 1px rgba(255, 255, 255, 0.2);
+    backdrop-filter: blur(8px);
+    position: relative;
+    overflow: hidden;
+}
+
+.holographic-badge::before {
+    content: "";
+    position: absolute;
+    top: -50%;
+    left: -50%;
+    width: 200%;
+    height: 200%;
+    background: linear-gradient(45deg, transparent, rgba(255, 255, 255, 0.1), transparent);
+    transform: rotate(45deg);
+    animation: holo-shine 3s infinite linear;
+}
+
+@keyframes holo-shine {
+    0% {
+        transform: translateX(-100%) rotate(45deg);
+    }
+    100% {
+        transform: translateX(100%) rotate(45deg);
+    }
+}
+
+.typing-cursor::after {
+    content: "|";
+    animation: blink 1s step-end infinite;
+}
+
+@keyframes blink {
+    50% {
+        opacity: 0;
+    }
+}
+
+.mood-gradient {
+    background: radial-gradient(circle at 50% 50%, rgba(37, 106, 244, 0.15), transparent 70%), radial-gradient(circle at 80% 20%, rgba(139, 92, 246, 0.1), transparent 50%);
+}
+
+/* Hide scrollbar for carousel */
+.no-scrollbar::-webkit-scrollbar {
+    display: none;
+}
+
+.no-scrollbar {
+    -ms-overflow-style: none;
+    scrollbar-width: none;
+}
+
+.radar-grid circle {
+    fill: none;
+    stroke: #334155;
+    stroke-width: 1;
+}
+
+.radar-grid line {
+    stroke: #334155;
+    stroke-width: 1;
+}
+
+.radar-area {
+    fill: rgba(37, 106, 244, 0.3);
+    stroke: #256af4;
+    stroke-width: 2;
+}
+
+/* Paper texture */
+.paper-texture {
+    background-color: #f0f0f0;
+    background-image: url(https://lh3.googleusercontent.com/aida-public/AB6AXuCxWgGFi3y5uU1Eo5AvX4bBjCZyqH_y2JcjejnbTD6deIOvWk3bplb-Bj1oFuS3P1LlYkmdnJOUkNL9g9L4yQd3Otfcz6qhp7psxQQqPTkZwV4myWl1ZoEp3ZQfBGYSI-nJnwMpWmwB1uO75co2eIFngOJE3Rn6JmLO_nOUKGhsut6iWdt_LKijBTH7SilsOX7HWTXfekHR2CwuUs4LJ6LkTMCVXS3R-aQTNfmsza_6PcRn40PTaBYS90sY9xtDPFcfgS2vzgPmPDZ6);
+}

frontend/src/main.jsx

@@ -0,0 +1,20 @@
+import React from 'react'
+import ReactDOM from 'react-dom/client'
+import App from './App.jsx'
+import './index.css';
+import { ConfigProvider, theme } from 'antd';
+
+ReactDOM.createRoot(document.getElementById('root')).render(
+  <React.StrictMode>
+    <ConfigProvider
+      theme={{
+        algorithm: theme.darkAlgorithm,
+        token: {
+            colorPrimary: '#1DB954', // Spotify Green
+        },
+      }}
+    >
+      <App />
+    </ConfigProvider>
+  </React.StrictMode>,
+)

frontend/tailwind.config.js

@@ -0,0 +1,34 @@
+/** @type {import('tailwindcss').Config} */
+export default {
+  content: [
+    "./index.html",
+    "./src/**/*.{js,ts,jsx,tsx}",
+  ],
+  darkMode: "class",
+  safelist: [
+    'bg-primary/20', 'text-primary', 'border-primary/20',
+    'bg-accent-purple/20', 'text-accent-purple', 'border-accent-purple/20',
+    'bg-accent-neon/20', 'text-accent-neon', 'border-accent-neon/20',
+  ],
+  theme: {
+    extend: {
+      colors: {
+        "primary": "#256af4",
+        "background-light": "#f5f6f8",
+        "background-dark": "#101622",
+        "card-dark": "#182234",
+        "card-darker": "#111927",
+        "accent-neon": "#0bda5e",
+        "accent-purple": "#8b5cf6",
+      },
+      fontFamily: {
+        "display": ["Space Grotesk", "sans-serif"],
+        "mono": ["Space Grotesk", "monospace"],
+      },
+      backgroundImage: {
+        'gradient-radial': 'radial-gradient(var(--tw-gradient-stops))',
+      }
+    },
+  },
+  plugins: [],
+}

frontend/vite.config.js

@@ -0,0 +1,16 @@
+import { defineConfig } from 'vite'
+import react from '@vitejs/plugin-react'
+
+// https://vitejs.dev/config/
+export default defineConfig({
+  plugins: [react()],
+  server: {
+    proxy: {
+      '/api': {
+        target: 'http://localhost:8000',
+        changeOrigin: true,
+        rewrite: (path) => path.replace(/^\/api/, ''),
+      },
+    },
+  },
+})