Implement Phase 2 Frontend and Phase 3 Data Enrichment

- Initialize React+Vite Frontend with Ant Design Dashboard.
- Implement Data Enrichment: ReccoBeats (Audio Features) and Spotify (Genres).
- Update Database Schema via Alembic Migrations.
- Add Docker support (Dockerfile, docker-compose.yml).
- Update README with hosting instructions.

.github/workflows/docker-publish.yml

@@ -6,9 +6,17 @@ on:
   pull_request:
     branches: [ "main" ]
 
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}
+
 jobs:
   build:
     runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
     steps:
     - uses: actions/checkout@v3
     
@@ -18,9 +26,32 @@ jobs:
     - 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 Docker
+      id: meta
+      uses: docker/metadata-action@v5
+      with:
+        images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+        tags: |
+          type=ref,event=branch
+          type=ref,event=pr
+          type=semver,pattern={{version}}
+          type=sha
+          latest
+      
     - name: Build and push
       uses: docker/build-push-action@v5
       with:
         context: ./backend
-        push: false
+        push: true
-        tags: user/app:latest
+        tags: ${{ steps.meta.outputs.tags }}
+        labels: ${{ steps.meta.outputs.labels }}
+        platforms: linux/amd64,linux/arm64
+        cache-from: type=gha
+        cache-to: type=gha,mode=max

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
+```

README.md

@@ -1,27 +1,37 @@
 # 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
 
 - `backend/`: FastAPI backend for data ingestion and API.
-  - `app/ingest.py`: Background worker that polls Spotify.
+  - `app/ingest.py`: Background worker that polls Spotify and enriches data via ReccoBeats.
-  - `app/services/`: Logic for Spotify and Gemini APIs.
+  - `app/services/`: Logic for Spotify, ReccoBeats, and Gemini APIs.
   - `app/models.py`: Database schema (Tracks, PlayHistory).
-- `frontend/`: (Coming Soon) React/Vite frontend.
+- `frontend/`: React + Vite frontend for visualizing the dashboard.
+- `docker-compose.yml`: For easy deployment.
 
-## Getting Started
+## Features
 
-### Prerequisites
+- **Continuous Ingestion**: Polls Spotify every 60 seconds to record your listening history.
+- **Data Enrichment**: Automatically fetches **Genres** (via Spotify) and **Audio Features** (Energy, BPM, Mood via ReccoBeats).
+- **Dashboard**: A responsive UI to view your history and stats.
+- **AI Ready**: Database schema and environment prepared for Gemini AI integration.
 
-- Docker & Docker Compose (optional, for containerization)
+## Hosting Guide (Docker)
-- Python 3.11+ (for local dev)
-- A Spotify Developer App (Client ID & Secret)
-- A Google Gemini API Key
 
-### 1. Setup Environment Variables
+This application is designed to run via Docker Compose.
 
-Create a `.env` file in the `backend/` directory:
+### 1. Prerequisites
+- Docker & Docker Compose installed.
+- **Spotify Developer Credentials** (Client ID & Secret).
+- **Spotify Refresh Token** (Run `backend/scripts/get_refresh_token.py` locally to generate this).
+- **Google Gemini API Key**.
+
+### 2. Deployment
+
+1.  **Clone the repository**.
+2.  **Create a `.env` file** in the root directory (or use environment variables directly):
 
     ```bash
     SPOTIFY_CLIENT_ID="your_client_id"
@@ -30,43 +40,48 @@ SPOTIFY_REFRESH_TOKEN="your_refresh_token"
     GEMINI_API_KEY="your_gemini_key"
     ```
 
-To get the `SPOTIFY_REFRESH_TOKEN`, run the helper script:
+3.  **Run with Docker Compose**:
 
     ```bash
-python backend/scripts/get_refresh_token.py
+    docker-compose up -d --build
     ```
 
-### 2. Run Locally
+    This will:
+    - Build and start the **Backend** (port 8000).
+    - Build and start the **Frontend** (port 8991).
+    - Create a **Persistent Volume** at `/opt/mySpotify` (mapped to the container's database) to ensure **no data loss** during updates.
 
-Install dependencies:
+4.  **Access the Dashboard**:
+    Open your browser to `http://localhost:8991` (or your server IP).
 
+### 3. Data Persistence & Updates
+
+- **Data**: All data is stored in `music.db` inside the container, which is mounted to `/opt/mySpotify/music.db` on your host machine.
+- **Migrations**: The project uses **Alembic** for database migrations. When you update the container image in the future, the backend will automatically apply any schema changes without deleting your data.
+
+### 4. Pulling from Registry (Alternative)
+
+If you prefer to pull the pre-built image instead of building locally:
+
+```bash
+docker pull ghcr.io/bnair123/musicanalyser:latest
+```
+
+(Note: You still need to mount the volume and pass environment variables as shown in `docker-compose.yml`).
+
+## Local Development
+
+1.  **Backend**:
     ```bash
     cd backend
     pip install -r requirements.txt
+    python run_worker.py  # Starts ingestion
+    uvicorn app.main:app --reload  # Starts API
     ```
 
-Run the server:
+2.  **Frontend**:
-
     ```bash
-uvicorn app.main:app --reload
+    cd frontend
-```
+    npm install
-
+    npm run dev
-The API will be available at `http://localhost:8000`.
-
-### 3. Run Ingestion (Manually)
-
-You can trigger the ingestion process via the API:
-
-```bash
-curl -X POST http://localhost:8000/trigger-ingest
-```
-
-Or run the ingestion logic directly via python shell (see `app/ingest.py`).
-
-### 4. Docker Build
-
-To build the image locally:
-
-```bash
-docker build -t music-analyser-backend ./backend
     ```

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 +1,87 @@
+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
+from app.models import * # Import models to register them
+
+# this is the Alembic Config object, which provides
+# access to the values within the .ini file in use.
+config = context.config
+
+# Interpret the config file for Python logging.
+# This line sets up loggers basically.
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+# add your model's MetaData object here
+# for 'autogenerate' support
+target_metadata = Base.metadata
+
+# other values from the config, defined by the needs of env.py,
+# can be acquired:
+# my_important_option = config.get_main_option("my_important_option")
+# ... etc.
+
+# Override sqlalchemy.url with our app's URL
+config.set_main_option("sqlalchemy.url", "sqlite:///./music.db")
+
+
+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/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/app/ingest.py

@@ -5,6 +5,7 @@ from sqlalchemy.orm import Session
 from .models import Track, PlayHistory
 from .database import SessionLocal
 from .services.spotify_client import SpotifyClient
+from .services.reccobeats_client import ReccoBeatsClient
 from dateutil import parser
 
 # Initialize Spotify Client (env vars will be populated later)
@@ -15,10 +16,93 @@ def get_spotify_client():
         refresh_token=os.getenv("SPOTIFY_REFRESH_TOKEN"),
     )
 
+def get_reccobeats_client():
+    return ReccoBeatsClient()
+
+async def enrich_tracks(db: Session, spotify_client: SpotifyClient, recco_client: ReccoBeatsClient):
+    """
+    Finds tracks missing genres (Spotify) or audio features (ReccoBeats) and enriches them.
+    """
+
+    # 1. Enrich Audio Features (via ReccoBeats)
+    tracks_missing_features = db.query(Track).filter(Track.danceability == None).limit(50).all()
+    print(f"DEBUG: Found {len(tracks_missing_features)} tracks missing audio features.")
+
+    if tracks_missing_features:
+        print(f"Enriching {len(tracks_missing_features)} tracks with audio features (ReccoBeats)...")
+        ids = [t.id for t in tracks_missing_features]
+
+        features_list = await recco_client.get_audio_features(ids)
+
+        features_map = {}
+        for f in features_list:
+            if "href" in f and "track/" in f["href"]:
+                tid = f["href"].split("track/")[1].split("?")[0]
+                features_map[tid] = f
+
+        updated_count = 0
+        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")
+                updated_count += 1
+
+        print(f"Updated {updated_count} tracks with audio features.")
+        db.commit()
+
+    # 2. Enrich Genres (via Spotify Artists)
+    tracks_missing_genres = db.query(Track).filter(Track.genres == None).limit(50).all()
+
+    if tracks_missing_genres:
+        print(f"Enriching {len(tracks_missing_genres)} tracks with genres (Spotify)...")
+
+        artist_ids = set()
+        track_artist_map = {}
+
+        for t in tracks_missing_genres:
+            if t.raw_data and "artists" in t.raw_data:
+                a_ids = [a["id"] for a in t.raw_data["artists"]]
+                artist_ids.update(a_ids)
+                track_artist_map[t.id] = a_ids
+
+        artist_ids_list = list(artist_ids)
+        artist_genre_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:
+                    artist_genre_map[a_data["id"]] = a_data.get("genres", [])
+
+        for t in tracks_missing_genres:
+            a_ids = track_artist_map.get(t.id, [])
+            combined_genres = set()
+            for a_id in a_ids:
+                genres = artist_genre_map.get(a_id, [])
+                combined_genres.update(genres)
+
+            t.genres = list(combined_genres)
+
+        db.commit()
+
+
 async def ingest_recently_played(db: Session):
-    client = get_spotify_client()
+    spotify_client = get_spotify_client()
+    recco_client = get_reccobeats_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
@@ -30,7 +114,6 @@ 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()
 
@@ -46,10 +129,8 @@ async def ingest_recently_played(db: Session):
                 raw_data=track_data
             )
             db.add(track)
-            db.commit() # Commit immediately so ID exists for foreign key
+            db.commit()
 
-        # 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
@@ -66,9 +147,13 @@ async def ingest_recently_played(db: Session):
 
     db.commit()
 
+    # Enrich
+    await enrich_tracks(db, spotify_client, recco_client)
+
 async def run_worker():
     """Simulates a background worker loop."""
     db = SessionLocal()
+
     try:
         while True:
             print("Worker: Polling Spotify...")

backend/app/models.py

@@ -1,4 +1,4 @@
-from sqlalchemy import Column, Integer, String, DateTime, JSON, ForeignKey, Boolean
+from sqlalchemy import Column, Integer, String, DateTime, JSON, ForeignKey, Float
 from sqlalchemy.orm import relationship
 from datetime import datetime
 from .database import Base
@@ -16,6 +16,24 @@ class Track(Base):
     # 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)
+    genres = Column(JSON, nullable=True)
+
     # AI Analysis fields
     lyrics_summary = Column(String, nullable=True)
     genre_tags = Column(String, nullable=True) # JSON list stored as string or just raw JSON

backend/app/services/reccobeats_client.py

@@ -0,0 +1,18 @@
+import httpx
+from typing import List, Dict, Any
+
+RECCOBEATS_API_URL = "https://api.reccobeats.com/v1/audio-features"
+
+class ReccoBeatsClient:
+    async def get_audio_features(self, spotify_ids: List[str]) -> List[Dict[str, Any]]:
+        if not spotify_ids:
+            return []
+        ids_param = ",".join(spotify_ids)
+        async with httpx.AsyncClient() as client:
+            try:
+                response = await client.get(RECCOBEATS_API_URL, params={"ids": ids_param})
+                if response.status_code != 200:
+                    return []
+                return response.json().get("content", [])
+            except Exception:
+                return []

backend/app/services/spotify_client.py

@@ -3,6 +3,7 @@ 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"
@@ -68,3 +69,26 @@ class SpotifyClient:
             if response.status_code != 200:
                 return None
             return response.json()
+
+    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", [])

backend/requirements.txt

@@ -9,3 +9,4 @@ google-generativeai==0.3.2
 tenacity==8.2.3
 python-dateutil==2.9.0.post0
 requests==2.31.0
+alembic==1.13.1

docker-compose.yml

@@ -0,0 +1,26 @@
+version: '3.8'
+services:
+  backend:
+    build:
+      context: ./backend
+    image: ghcr.io/bnair123/musicanalyser:latest
+    container_name: music-analyser-backend
+    restart: unless-stopped
+    volumes:
+      - /opt/mySpotify/music.db:/app/music.db
+    environment:
+      - SPOTIFY_CLIENT_ID=${SPOTIFY_CLIENT_ID}
+      - SPOTIFY_CLIENT_SECRET=${SPOTIFY_CLIENT_SECRET}
+      - SPOTIFY_REFRESH_TOKEN=${SPOTIFY_REFRESH_TOKEN}
+      - GEMINI_API_KEY=${GEMINI_API_KEY}
+    ports:
+      - '8000:8000'
+  frontend:
+    build:
+      context: ./frontend
+    container_name: music-analyser-frontend
+    restart: unless-stopped
+    ports:
+      - '8991:80'
+    depends_on:
+      - backend

frontend/Dockerfile

@@ -0,0 +1,11 @@
+FROM node:18-alpine as build
+WORKDIR /app
+COPY package*.json ./
+RUN npm install
+COPY . .
+RUN npm run build
+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/nginx.conf

@@ -0,0 +1,13 @@
+server {
+    listen 80;
+    location / {
+        root /usr/share/nginx/html;
+        index index.html index.htm;
+        try_files $uri $uri/ /index.html;
+    }
+    location /api/ {
+        proxy_pass http://backend:8000/;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+    }
+}