Feature/content to embedding model #18
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sudan45
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thenav56
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Sep 18, 2024
.flake8
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| @@ -7,3 +7,4 @@ max-complexity = 10 | |||
| per-file-ignores = | |||
| /**/tests/*_mock_data.py: E501 | |||
| **/snap_test_*.py: E501 | |||
| /**/apps.py: F401 | |||
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Ignore a line not the file itself.
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| CELERY_BROKER_URL = "redis://redis:6379/0" | ||
| CELERY_RESULT_BACKEND = "redis://redis:6379/0" | ||
| CELERY_ACCEPT_CONTENT = ["json"] | ||
| CELERY_TASK_SERIALIZER = "json" | ||
| CELERY_RESULT_SERIALIZER = "json" | ||
| CELERY_TIMEZONE = "UTC" |
docker-compose.yml
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| depends_on: | ||
| - redis | ||
| - web |
| depends_on: | ||
| - db | ||
| - redis | ||
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| volumes: | ||
| - .:/code | ||
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content/tasks.py
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| from .models import Content | ||
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| content = Content.objects.get(id=content_id) | ||
| url = settings.EMBEDDING_MODEL_URL |
content/signals.py
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| @receiver(post_save, sender=Content) | ||
| def content_handler(sender, instance, created, **kwargs): | ||
| create_embedding_for_content_task.delay(instance.id) |
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Let's move this to save, but for future use ModelForm (which will then be used in serializers)
content/tasks.py
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| for i in range(len(split_docs)) | ||
| ] | ||
| if response.status_code == 200: | ||
| db = QdrantDatabase(host="qdrant", port=settings.QDRANT_DB_PORT, collection_name=settings.QDRANT_DB_COLLECTION_NAME) |
| db.store_data(zip(response.json(), metadata)) | ||
| content.document_status = Content.DocumentStatus.ADDED_TO_VECTOR | ||
| else: | ||
| content.document_status = Content.DocumentStatus.FAILURE |
| data = OllamaHandler() | ||
| serializer = UserQuerySerializer(data=request.data) | ||
| if serializer.is_valid(): | ||
| result = data.execute_chain(request.data["query"]) |
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Check and add a note if we need async here?
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