chore: improve recommendation weights and refactor

Author: TimilsinaBimal

app/services/recommendation_service.py

@@ -155,10 +155,13 @@ async def _fetch_details(tmdb_id: int):
             # Extract IMDB ID from external_ids
             external_ids = details.get("external_ids", {})
             imdb_id = external_ids.get("imdb_id")
-            tmdb_id = details.get("id")
+            # tmdb_id = details.get("id")
 
             # Prefer IMDB ID, fallback to TMDB ID
-            stremio_id = imdb_id if imdb_id else f"tmdb:{tmdb_id}"
+            if imdb_id:
+                stremio_id = imdb_id
+            else:  # skip content if imdb id is not available
+                continue
 
             # Construct Stremio meta object
             title = details.get("title") or details.get("name")
@@ -179,6 +182,7 @@ async def _fetch_details(tmdb_id: int):
 
             meta_data = {
                 "id": stremio_id,
+                "imdb_id": stremio_id,
                 "type": "series" if media_type in ["tv", "series"] else "movie",
                 "name": title,
                 "poster": poster_url,

app/services/row_generator.py

@@ -3,7 +3,8 @@
 from pydantic import BaseModel
 
 from app.models.profile import UserTasteProfile
-from app.services.tmdb.genre import movie_genres, series_genres
+from app.services.tmdb.countries import COUNTRY_ADJECTIVES
+from app.services.tmdb.genre import GENRE_ADJECTIVES, movie_genres, series_genres
 from app.services.tmdb_service import TMDBService
 
 
@@ -32,45 +33,6 @@ class RowGeneratorService:
     def __init__(self, tmdb_service: TMDBService | None = None):
         self.tmdb_service = tmdb_service or TMDBService()
 
-    # Adjectives to spice up titles based on genres
-    GENRE_ADJECTIVES = {
-        28: ["Adrenaline-Pumping", "Explosive", "Hard-Hitting"],  # Action
-        12: ["Epic", "Globe-Trotting", "Daring"],  # Adventure
-        878: ["Mind-Bending", "Futuristic", "Dystopian"],  # Sci-Fi
-        27: ["Bone-Chilling", "Nightmarish", "Terrifying"],  # Horror
-        53: ["Edge-of-your-Seat", "Suspenseful", "Slow-Burn"],  # Thriller
-        10749: ["Heartwarming", "Passionate", "Bittersweet"],  # Romance
-        35: ["Laugh-Out-Loud", "Witty", "Feel-Good"],  # Comedy
-        18: ["Critically Acclaimed", "Powerful", "Emotional"],  # Drama
-        14: ["Magical", "Otherworldly", "Enchanting"],  # Fantasy
-        9648: ["Mysterious", "Puzzle-Box", "Twisted"],  # Mystery
-        80: ["Gritty", "Noir", "Underworld"],  # Crime
-    }
-
-    # Country Name Map
-    COUNTRY_NAMES = {
-        "US": "American",
-        "GB": "British",
-        "FR": "French",
-        "DE": "French",
-        "JP": "Japanese",
-        "KR": "Korean",
-        "IN": "Indian",
-        "CN": "Chinese",
-        "ES": "Spanish",
-        "IT": "Spanish",
-        "CA": "Canadian",
-        "AU": "Australian",
-        "HK": "Hong Kong",
-        "TW": "Hong Kong",
-        "RU": "Russian",
-        "BR": "Brazilian",
-        "MX": "Brazilian",
-        "SE": "Swedish",
-        "DK": "Swedish",
-        "NO": "Danish",
-    }
-
     async def generate_rows(self, profile: UserTasteProfile, content_type: str = "movie") -> list[RowDefinition]:
         """
         Generate a diverse set of 3-5 thematic rows.
@@ -91,12 +53,15 @@ def get_gname(gid):
             return genre_map.get(gid, "Movies")
 
         def get_cname(code):
-            return self.COUNTRY_NAMES.get(code, "")
+            adjectives = COUNTRY_ADJECTIVES.get(code, [])
+            if adjectives:
+                return random.choice(adjectives)
+            return ""
 
         # Strategy 1: Genre + Mood (Adjective)
         if top_genres:
             g_id = top_genres[0][0]
-            adj = random.choice(self.GENRE_ADJECTIVES.get(g_id, ["Essential"]))
+            adj = random.choice(GENRE_ADJECTIVES.get(g_id, ["Essential"]))
             rows.append(
                 RowDefinition(
                     title=f"{adj} {get_gname(g_id)}",

app/services/scoring.py

@@ -9,12 +9,13 @@ class ScoringService:
     It consumes raw dictionary data or Pydantic models and returns enriched ScoredItems.
     """
 
-    # TODO: Handle this for series
+    # TODO: Make this a bit more complex based on more parameters.
+    # Rewatch, How many times? Watched but duration?? What if user stopped watching in middle?
 
     # Weights for different factors
-    WEIGHT_WATCH_PERCENTAGE = 0.35
-    WEIGHT_REWATCH = 0.15
-    WEIGHT_RECENCY = 0.15
+    WEIGHT_WATCH_PERCENTAGE = 0.25
+    WEIGHT_REWATCH = 0.20
+    WEIGHT_RECENCY = 0.20
     WEIGHT_EXPLICIT_RATING = 0.3
     ADDED_TO_LIBRARY_WEIGHT = 0.05
 

app/services/stremio_service.py

@@ -1,17 +1,14 @@
 import asyncio
 
 import httpx
+from async_lru import alru_cache
 from loguru import logger
 
 from app.core.config import settings
 
 BASE_CATALOGS = [
     {"type": "movie", "id": "watchly.rec", "name": "Top Picks for You", "extra": []},
     {"type": "series", "id": "watchly.rec", "name": "Top Picks for You", "extra": []},
-    {"type": "movie", "id": "watchly.trending", "name": "Trending Movies", "extra": []},
-    {"type": "series", "id": "watchly.trending", "name": "Trending Series", "extra": []},
-    {"type": "movie", "id": "watchly.gems", "name": "Hidden Gems", "extra": []},
-    {"type": "series", "id": "watchly.gems", "name": "Hidden Gems", "extra": []},
 ]
 
 
@@ -137,6 +134,24 @@ async def is_loved(self, auth_key: str, imdb_id: str, media_type: str) -> tuple[
             )
             return False, False
 
+    @alru_cache(maxsize=1000, ttl=3600)
+    async def get_loved_items(self, auth_token: str, media_type: str) -> list[dict]:
+        async with httpx.AsyncClient() as client:
+            url = f"https://likes.stremio.com/addons/loved/movies-shows/{auth_token}/catalog/{media_type}/stremio-loved-{media_type.lower()}.json"  # noqa: E501
+            response = await client.get(url)
+            response.raise_for_status()
+            metas = response.json().get("metas", [])
+            return [meta.get("id") for meta in metas]
+
+    @alru_cache(maxsize=1000, ttl=3600)
+    async def get_liked_items(self, auth_token: str, media_type: str) -> list[dict]:
+        async with httpx.AsyncClient() as client:
+            url = f"https://likes.stremio.com/addons/liked/movies-shows/{auth_token}/catalog/{media_type}/stremio-liked-{media_type.lower()}.json"  # noqa: E501
+            response = await client.get(url)
+            response.raise_for_status()
+            metas = response.json().get("metas", [])
+            return [meta.get("id") for meta in metas]
+
     async def get_library_items(self) -> dict[str, list[dict]]:
         """
         Fetch library items from Stremio once and return both watched and loved items.