updated elastic

akarpov/files/documents.py

@@ -0,0 +1,31 @@
+from django_elasticsearch_dsl import Document
+from django_elasticsearch_dsl.registries import registry
+
+from akarpov.files.models import File
+
+
+@registry.register_document
+class FileDocument(Document):
+    class Index:
+        name = "files"
+        settings = {"number_of_shards": 1, "number_of_replicas": 0}
+
+    class Django:
+        model = File
+        fields = [
+            "name",
+            "description",
+            "content",
+        ]
+
+    def prepare_description(self, instance):
+        # This method is called for every instance before indexing
+        return instance.description or ""
+
+    def prepare_content(self, instance):
+        # This method is called for every instance before indexing
+        return (
+            instance.content.decode("utf-8")
+            if isinstance(instance.content, bytes)
+            else instance.content
+        )

akarpov/files/search_indexes.py

@@ -1,17 +0,0 @@
-from haystack import indexes
-
-from .models import File
-
-
-class FileIndex(indexes.SearchIndex, indexes.Indexable):
-    text = indexes.CharField(document=True, use_template=True)
-    name = indexes.CharField(model_attr="name", default="")
-    description = indexes.CharField(model_attr="description", default="")
-    content = indexes.CharField(model_attr="content", default="")
-
-    def get_model(self):
-        return File
-
-    def index_queryset(self, using=None):
-        # Return the default queryset to be used for indexing.
-        return self.get_model().objects.all()

akarpov/files/services/search.py

@@ -4,11 +4,13 @@
 
 from django.conf import settings
 from django.contrib.postgres.search import TrigramSimilarity
-from django.db.models import F, Func, Q, QuerySet
-from haystack.query import SearchQuerySet
+from django.db.models import Case, F, FloatField, Func, Q, QuerySet, Value, When
+from django.db.models.functions import Coalesce
+from elasticsearch_dsl import Q as ES_Q
 
 from akarpov.files.models import File
 
+from ..documents import FileDocument
 from .lema import lemmatize_and_remove_stopwords
 
 
@@ -16,17 +18,55 @@ class BaseSearch:
     def __init__(self, queryset: QuerySet | None = None):
         self.queryset: QuerySet | None = queryset
 
-    def search(self, query: str) -> QuerySet | SearchQuerySet | list[File]:
+    def search(self, query: str) -> QuerySet | list[File]:
         raise NotImplementedError("Subclasses must implement this method")
 
 
 class NeuroSearch(BaseSearch):
-    def search(self, query: str) -> SearchQuerySet:
-        # Search across multiple fields
-        sqs: SearchQuerySet = SearchQuerySet().filter(content=query)
-        sqs = sqs.filter_or(name=query)
-        sqs = sqs.filter_or(description=query)
-        return sqs
+    def search(self, query: str):
+        if not self.queryset:
+            raise ValueError("Queryset cannot be None for search")
+
+        # Perform the Elasticsearch query using a combination of match, match_phrase_prefix, and wildcard queries
+        search = FileDocument.search()
+        search_query = ES_Q(
+            "bool",
+            should=[
+                ES_Q(
+                    "multi_match",
+                    query=query,
+                    fields=["name", "description", "content"],
+                    type="best_fields",
+                ),
+                ES_Q("match_phrase_prefix", name=query),
+                ES_Q("wildcard", name=f"*{query}*"),
+                ES_Q("wildcard", description=f"*{query}*"),
+                ES_Q("wildcard", content=f"*{query}*"),
+            ],
+            minimum_should_match=1,
+        )
+
+        search = search.query(search_query)
+
+        # Execute the search to get the results
+        response = search.execute()
+
+        # Check if there are hits, if not return an empty queryset
+        if not response.hits:
+            return self.queryset.none()
+
+        # Collect the IDs of the hits
+        hit_ids = [hit.meta.id for hit in response.hits]
+
+        # Use the hit IDs to filter the queryset and preserve the order
+        preserved_order = Case(
+            *[When(pk=pk, then=pos) for pos, pk in enumerate(hit_ids)]
+        )
+        relevant_queryset = self.queryset.filter(pk__in=hit_ids).order_by(
+            preserved_order
+        )
+
+        return relevant_queryset
 
 
 class CaseSensitiveSearch(BaseSearch):
@@ -89,28 +129,28 @@ def as_sql(self, compiler, connection):
 
 
 class SimilaritySearch(BaseSearch):
-    def __init__(self, queryset: QuerySet[File] | None = None):
-        super().__init__(queryset)
-
     def search(self, query: str) -> QuerySet[File]:
         if self.queryset is None:
             raise ValueError("Queryset cannot be None for similarity search")
 
-        # Detect language and preprocess the query
         language = "russian" if re.search("[а-яА-Я]", query) else "english"
         filtered_query = lemmatize_and_remove_stopwords(query, language=language)
-
-        # Annotate the queryset with similarity scores for each field
         queryset = (
             self.queryset.annotate(
-                name_similarity=TrigramSimilarity(
-                    UnaccentLower("name"), filtered_query
+                name_similarity=Coalesce(
+                    TrigramSimilarity(UnaccentLower("name"), filtered_query),
+                    Value(0),
+                    output_field=FloatField(),
                 ),
-                description_similarity=TrigramSimilarity(
-                    UnaccentLower("description"), filtered_query
+                description_similarity=Coalesce(
+                    TrigramSimilarity(UnaccentLower("description"), filtered_query),
+                    Value(0),
+                    output_field=FloatField(),
                 ),
-                content_similarity=TrigramSimilarity(
-                    UnaccentLower("content"), filtered_query
+                content_similarity=Coalesce(
+                    TrigramSimilarity(UnaccentLower("content"), filtered_query),
+                    Value(0),
+                    output_field=FloatField(),
                 ),
             )
             .annotate(
@@ -119,17 +159,9 @@ def search(self, query: str) -> QuerySet[File]:
                     + F("description_similarity")
                     + F("content_similarity")
                 )
-                / 3
             )
             .filter(combined_similarity__gt=0.1)
             .order_by("-combined_similarity")
         )
-        print(filtered_query)
-        print(queryset.query)
-        print(
-            queryset.values(
-                "name_similarity", "description_similarity", "content_similarity"
-            )
-        )
 
         return queryset

akarpov/files/tasks.py

@@ -3,9 +3,8 @@
 
 import structlog
 from celery import shared_task
+from django.core import management
 from django.core.files import File
-from haystack.management.commands import rebuild_index, update_index
-from haystack.query import SearchQuerySet
 
 from akarpov.files.models import File as FileModel
 from akarpov.files.services.preview import create_preview, get_file_mimetype
@@ -39,25 +38,10 @@ def process_file(pk: int):
     return pk
 
 
-@shared_task
-def task_rebuild_index():
-    start_time = time.time()
-    rebuild_index.Command().handle(interactive=False)
-    end_time = time.time()
-    duration = end_time - start_time
-
-    indexed_count = SearchQuerySet().all().count()
-
-    logger.info(
-        "index_rebuild_finished", duration=duration, indexed_count=indexed_count
-    )
-
-
 @shared_task
 def update_index_task():
     start_time = time.time()
-
-    update_index.Command().handle(interactive=False)
+    management.call_command("search_index", "--rebuild", "-f")
     end_time = time.time()
     duration = end_time - start_time
     logger.info("update_index_completed", duration=duration)

akarpov/files/views.py

@@ -70,7 +70,7 @@ def filter(self, queryset):
 
 class TopFolderView(LoginRequiredMixin, ListView, FileFilterView):
     template_name = "files/list.html"
-    paginate_by = 18
+    paginate_by = 38
     model = BaseFileItem
 
     def get_context_data(self, **kwargs):

config/settings/base.py

@@ -66,7 +66,7 @@
     "blog.post": {"ops": ("fetch", "get"), "timeout": 20 * 15},
     "themes.theme": {"ops": ("fetch", "get"), "timeout": 60 * 60},
     "gallery.*": {"ops": "all", "timeout": 60 * 15},
-    "files.*": {"ops": "all", "timeout": 60 * 5},
+    "files.*": {"ops": ("fetch", "get"), "timeout": 60 * 5},
     "auth.permission": {"ops": "all", "timeout": 60 * 15},
 }
 CACHEOPS_REDIS = env.str("REDIS_URL")
@@ -133,7 +133,7 @@
     "django_filters",
     "django_tables2",
     "location_field",
-    "haystack",
+    "django_elasticsearch_dsl",
 ]
 
 HEALTH_CHECKS = [
@@ -434,13 +434,9 @@
 CELERY_BEAT_SCHEDULER = "django_celery_beat.schedulers:DatabaseScheduler"
 CELERY_BEAT_SCHEDULE = {
     "update-index-every-hour": {
-        "task": "akarpov.files.tasks.task_rebuild_index",
+        "task": "akarpov.files.tasks.update_index_task",
         "schedule": crontab(minute="0"),
     },
-    "rebuild-index-every-day": {
-        "task": "akarpov.files.tasks.task_rebuild_index",
-        "schedule": crontab(hour="2", minute="0", day_of_week="*"),
-    },
 }
 
 
@@ -611,14 +607,8 @@
     )
 
 
-# HAYSTACK
+# ELASTICSEARCH
 # ------------------------------------------------------------------------------
-HAYSTACK_CONNECTIONS = {
-    "default": {
-        "ENGINE": "haystack.backends.elasticsearch7_backend.Elasticsearch7SearchEngine",
-        "URL": env("ELASTIC_SEARCH", default="http://127.0.0.1:9200/"),
-        "INDEX_NAME": "haystack",
-        "TIMEOUT": 60 * 5,
-        "BATCH_SIZE": 100,
-    },
+ELASTICSEARCH_DSL = {
+    "default": {"hosts": env("ELASTIC_SEARCH", default="http://127.0.0.1:9200/")},
 }

local.yml

@@ -100,18 +100,15 @@ services:
     command: /start-flower
 
   elasticsearch:
-    image: elasticsearch:7.17.14
-    container_name: elasticsearch
-    environment:
-      - cluster.name=docker-cluster
-      - bootstrap.memory_lock=true
-      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
-    ulimits:
-      memlock:
-        soft: -1
-        hard: -1
-    volumes:
-      - akarpov_local_elasticsearch_data:/usr/share/elasticsearch/data
+    image: elasticsearch:8.8.0
     ports:
       - "9200:9200"
       - "9300:9300"
+    environment:
+      - node.name=activity
+      - discovery.type=single-node
+      - cluster.name=ws-es-data-cluster
+      - bootstrap.memory_lock=true
+      - "ES_JAVA_OPTS=-Xms4g -Xmx4g"
+    volumes:
+      - akarpov_local_elasticsearch_data:/usr/share/elasticsearch/data

pyproject.toml

@@ -107,13 +107,15 @@ pgvector = "^0.2.2"
 pycld2 = "^0.41"
 textract = "^1.6.5"
 uuid6 = "^2023.5.2"
-django-haystack = {extras = ["elasticsearch"], version = "^3.2.1"}
 uvicorn = "^0.24.0.post1"
 nltk = "^3.8.1"
 pymorphy3 = "^1.2.1"
 pymorphy3-dicts-ru = "^2.4.417150.4580142"
 fastapi = "^0.104.1"
 pydantic-settings = "^2.0.3"
+django-elasticsearch-dsl = "^8.0"
+elasticsearch-dsl = "^8.11.0"
+numpy = "1.25.2"
 
 
 [build-system]