Merge pull request #51 from StarDylan/cache-mood

added mood caching

schema.sql

@@ -91,6 +91,17 @@ create table
     constraint users_playlist_position_user_id_fkey foreign key (user_id) references users (id) on delete cascade
   ) tablespace pg_default;
 
+create table
+  public.user_moods (
+    user_id bigint generated by default as identity,
+    last_updated timestamp with time zone not null default now(),
+    mood text not null,
+    songs_played bigint not null,
+    constraint user_moods_pkey primary key (user_id),
+    constraint user_moods_user_id_key unique (user_id),
+    constraint user_moods_user_id_fkey foreign key (user_id) references users (id) on update cascade on delete cascade
+  ) tablespace pg_default;
+
   INSERT INTO songs (song_name, artist, album)
   VALUES ('Mr. Brightside', 'The Killers', 'Hot Fuss');
 

src/api/ollamarunner.py

@@ -0,0 +1,102 @@
+import sqlalchemy
+from src import database as db
+import json
+import requests
+import os
+import queue
+import threading
+
+q = queue.Queue()
+
+def gen_mood(user_id) -> str:
+    with db.engine.begin() as conn:
+        result = conn.execute(sqlalchemy.text("""
+                SELECT COUNT(*) FROM song_history
+                WHERE user_id = :user_id
+                """),
+                [{
+                    "user_id": user_id
+                }]).scalar_one()
+
+        if result < 5:
+            return None
+
+        result = conn.execute(sqlalchemy.text("""
+                SELECT song_name, artist
+                FROM song_history
+                JOIN songs ON song_history.song_id = songs.id
+                WHERE user_id = 23
+                ORDER BY song_history.created_at DESC
+                LIMIT 5
+                """)).all()
+
+    song_prompt = "Songs:\n"
+    for song in result:
+        song_prompt += song.song_name + " by " + song.artist + "\n"
+
+    payload = json.dumps({
+        "model": "llama2-uncensored",
+        "system": "Classify the user's mood based on the following song titles into only one of these emotions: Happy, Sad, Angry. Only include the classification as one word.",
+        "prompt": song_prompt,
+        "stream": False
+        })
+    headers = {
+    'Content-Type': 'application/json'
+    }
+
+    print("Getting Sentiment from OLLAMA")
+
+    response = requests.request("POST", os.environ.get("OLLAMA_URI"), headers=headers, data=payload)
+    response = response.json()
+    print(response)
+
+    mood = ""
+    if "happy" in response["response"].lower():
+        mood = "HAPPY"
+    elif "sad" in response["response"].lower():
+        mood = "SAD"
+    elif "angry" in response["response"].lower():
+        mood = "ANGRY"
+
+    if mood == "":
+        return None
+    return mood
+
+def thread_func(jobs=queue.Queue):
+    print("ollama runner daemon started...")
+    while True:
+        if not jobs.empty():
+            # there is a job
+            user_id = jobs.get()
+            with db.engine.begin() as conn:
+                result = conn.execute(sqlalchemy.text("""
+                    SELECT COUNT(*)
+                    FROM song_history
+                    WHERE user_id = :user_id
+                                                      """),
+                    [{
+                        "user_id":user_id
+                    }]).scalar_one_or_none()
+            if result is None or result < 5:
+                continue
+            else:
+                mood = gen_mood(user_id)
+                with db.engine.begin() as conn:
+                    conn.execute(sqlalchemy.text("""
+                    INSERT INTO user_moods(mood, songs_played,user_id)
+                    VALUES(:mood, 0, :user_id)
+                    ON CONFLICT (user_id)
+                    DO UPDATE SET 
+                        last_updated=now(), 
+                        mood=:mood, 
+                        songs_played=0
+                    WHERE user_moods.user_id = :user_id
+                                                    """
+                                                        ), [{
+                        "user_id": user_id,
+                        "mood":mood
+                    }])
+
+def start_daemon():
+    t = threading.Thread(daemon=True, target=thread_func, args=(q,))
+    t.start()

src/api/server.py

@@ -1,7 +1,7 @@
 from fastapi import FastAPI, exceptions
 from fastapi.responses import JSONResponse
 from pydantic import ValidationError
-from src.api import users, songs, playlists, ad
+from src.api import users, songs, playlists, ad, ollamarunner
 import json
 import logging
 
@@ -25,6 +25,8 @@
 app.include_router(playlists.router)
 app.include_router(ad.router)
 
+ollamarunner.start_daemon()
+
 @app.exception_handler(exceptions.RequestValidationError)
 @app.exception_handler(ValidationError)
 async def validation_exception_handler(request, exc):

src/api/songs.py

@@ -2,11 +2,10 @@
 from pydantic import BaseModel
 import sqlalchemy
 from src import database as db
-import json
-import requests
-import os
+from src.api.ollamarunner import q
 import random
 
+
 router = APIRouter(
     prefix="/song",
     tags=["song"],
@@ -181,56 +180,27 @@ def play_ad_if_needed(conn, user_id) -> str | None:
     if random.choice([True, False]):
         return None
 
+    # Check if mood is already cached
+
     result = conn.execute(sqlalchemy.text("""
-            SELECT COUNT(*) FROM song_history
-            WHERE user_id = :user_id
-            """),
-            [{
-                "user_id": user_id
-            }]).scalar_one()
-
-    if result < 5:
+        SELECT last_updated, mood, songs_played
+        FROM user_moods
+        WHERE user_id = :user_id
+                                          """
+                                            ), [{
+            "user_id": user_id
+        }]).one_or_none()
+    if result is None:
+        # no mood calculated
+        # mood = gen_mood(conn, user_id)
+        print("calling ollama")
+        q.put(user_id)
         return None
-
-    result = conn.execute(sqlalchemy.text("""
-            SELECT song_name, artist
-            FROM song_history
-            JOIN songs ON song_history.song_id = songs.id
-            WHERE user_id = 23
-            ORDER BY song_history.created_at DESC
-            LIMIT 5
-            """)).all()
-
-    song_prompt = "Songs:\n"
-    for song in result:
-        song_prompt += song.song_name + " by " + song.artist + "\n"
-
-    payload = json.dumps({
-        "model": "llama2-uncensored",
-        "system": "Classify the user's mood based on the following song titles into only one of these emotions: Happy, Sad, Angry. Only include the classification as one word.",
-        "prompt": song_prompt,
-        "stream": False
-        })
-    headers = {
-    'Content-Type': 'application/json'
-    }
-
-    print("Getting Sentiment from OLLAMA")
+    elif result.songs_played >= 5:
 
-    response = requests.request("POST", os.environ.get("OLLAMA_URI"), headers=headers, data=payload)
-    response = response.json()
-    print(response)
-
-    mood = ""
-    if "happy" in response["response"].lower():
-        mood = "HAPPY"
-    elif "sad" in response["response"].lower():
-        mood = "SAD"
-    elif "angry" in response["response"].lower():
-        mood = "ANGRY"
-
-    if mood == "":
-        return None
+        print("calling ollama")
+        q.put(user_id)
+    mood = result.mood
 
     result = conn.execute(sqlalchemy.text("""
             SELECT link FROM ad_campaigns
@@ -300,7 +270,10 @@ def play_song(song_id: int, user_id: str = Header(None)) -> SongResponse:
             return SongResponse(url=ad_link, is_ad=True)
 
         conn.execute(sqlalchemy.text("""
-          INSERT INTO song_history (user_id, song_id) VALUES (:user_id, :song_id)
+          INSERT INTO song_history (user_id, song_id) VALUES (:user_id, :song_id);
+          UPDATE user_moods
+          SET songs_played = songs_played + 1
+          WHERE user_id = :user_id
             """),
             [{
                 "song_id": song_id,