first backend frontend split

with docker compose file
nextjs something something
also includes migrations

backend/playlist/tasks.py

@@ -0,0 +1,73 @@
+from celery import shared_task
+from .models import Track
+from django.core.files import File
+from django.core.files.uploadedfile import InMemoryUploadedFile
+from django.core.files.base import ContentFile
+
+import os
+import dotenv
+
+import json
+from requests import get, post
+from requests.exceptions import ConnectionError
+from PIL import Image
+from io import BytesIO
+
+dotenv.load_dotenv()
+
+@shared_task
+def get_banter(id):
+    """
+        Requests an AI model for some banter.
+        Currently expects an ollama instance to be running,
+        but might be possible to use OpenAI API in future.
+    """
+    track = Track.objects.get(pk=id)
+    track.banter = ""
+
+    try:
+        get(os.getenv('AI_ENDPOINT'))
+    except ConnectionError:
+        track.banter = "Error"
+        track.banter_done = True
+        track.save()
+        return f"{track}: AI endpoint not available."
+
+    try:
+        r = post(
+            os.getenv('AI_ENDPOINT'),
+            json={
+                'model': os.getenv('AI_MODEL'),
+                'prompt': str(track)
+            },
+            stream=True
+        )
+        r.raise_for_status()
+
+        for line in r.iter_lines():
+            body = json.loads(line)
+            if 'error' in body:
+                raise Exception(body['error'])
+            track.banter += body.get('response', '')
+
+            if body.get('done', False):
+                track.banter_done = True
+                track.save()
+                return f"{track}: {body['context']}"
+    except Exception as e:
+        track.banter_done = True
+        track.save()
+        return f"{track}: {e}"
+
+@shared_task
+def get_and_dither_image(url, instance, attribute):
+    """Expects a url, and a Django model cls with an ImageField attribute"""
+    print(f"Parsing {url} for {instance} with attribute {attribute}")
+    r = get(url)
+    i = Image.open(BytesIO(r.content))
+    i = i.resize(size=(256, 256)).convert("P").quantize(colors=32)
+    buffer = BytesIO()
+    i.save(fp=buffer, format='PNG')
+    file = InMemoryUploadedFile(ContentFile(buffer.getvalue()), None, instance.name + ".png", "image/png", buffer.tell, "utf-8")
+    instance.image = file
+    instance.save()