Bump pytest-factoryboy from 2.3.1 to 2.6.0

Bumps [pytest-factoryboy](https://github.com/pytest-dev/pytest-factoryboy) from 2.3.1 to 2.6.0.
- [Changelog](https://github.com/pytest-dev/pytest-factoryboy/blob/master/CHANGES.rst)
- [Commits](https://github.com/pytest-dev/pytest-factoryboy/compare/2.3.1...2.6.0)

---
updated-dependencies:
- dependency-name: pytest-factoryboy
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

akarpov/files/services/lema.py

@@ -0,0 +1,37 @@
+from nltk.corpus import stopwords
+from nltk.stem import WordNetLemmatizer
+from nltk.tokenize import word_tokenize
+from pymorphy3 import MorphAnalyzer
+
+# Set up stop words
+english_stopwords = set(stopwords.words("english"))
+russian_stopwords = set(stopwords.words("russian"))
+
+# Set up lemmatizers
+english_lemmatizer = WordNetLemmatizer()
+russian_lemmatizer = MorphAnalyzer()
+
+
+def lemmatize_and_remove_stopwords(text, language="english"):
+    # Tokenize the text
+    tokens = word_tokenize(text)
+
+    # Lemmatize each token based on the specified language
+    lemmatized_tokens = []
+    for token in tokens:
+        if language == "russian":
+            lemmatized_token = russian_lemmatizer.parse(token)[0].normal_form
+        else:  # Default to English
+            lemmatized_token = english_lemmatizer.lemmatize(token)
+        lemmatized_tokens.append(lemmatized_token)
+
+    # Remove stop words
+    filtered_tokens = [
+        token
+        for token in lemmatized_tokens
+        if token not in english_stopwords and token not in russian_stopwords
+    ]
+
+    # Reconstruct the text
+    filtered_text = " ".join(filtered_tokens)
+    return filtered_text

akarpov/files/services/search.py

@@ -3,13 +3,14 @@
 from typing import BinaryIO
 
 from django.conf import settings
-from django.contrib.postgres.lookups import Unaccent
 from django.contrib.postgres.search import TrigramSimilarity
-from django.db.models import Q, QuerySet
+from django.db.models import F, Func, Q, QuerySet
 from haystack.query import SearchQuerySet
 
 from akarpov.files.models import File
 
+from .lema import lemmatize_and_remove_stopwords
+
 
 class BaseSearch:
     def __init__(self, queryset: QuerySet | None = None):
@@ -76,6 +77,17 @@ def _byte_search_in_file(file: BinaryIO, byte_sequence: bytes) -> bool:
                 return False
 
 
+class UnaccentLower(Func):
+    function = "UNACCENT"
+
+    def as_sql(self, compiler, connection):
+        unaccented_sql, unaccented_params = compiler.compile(
+            self.get_source_expressions()[0]
+        )
+        lower_unaccented_sql = f"LOWER({unaccented_sql})"
+        return lower_unaccented_sql, unaccented_params
+
+
 class SimilaritySearch(BaseSearch):
     def __init__(self, queryset: QuerySet[File] | None = None):
         super().__init__(queryset)
@@ -84,18 +96,40 @@ def search(self, query: str) -> QuerySet[File]:
         if self.queryset is None:
             raise ValueError("Queryset cannot be None for similarity search")
 
-        # Perform a similarity search using trigram comparison
+        # Detect language and preprocess the query
-        return (
+        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_unaccent=Unaccent("name"),
+                name_similarity=TrigramSimilarity(
-                description_unaccent=Unaccent("description"),
+                    UnaccentLower("name"), filtered_query
-                content_unaccent=Unaccent("content"),
+                ),
+                description_similarity=TrigramSimilarity(
+                    UnaccentLower("description"), filtered_query
+                ),
+                content_similarity=TrigramSimilarity(
+                    UnaccentLower("content"), filtered_query
+                ),
             )
             .annotate(
-                similarity=TrigramSimilarity("name_unaccent", query)
+                combined_similarity=(
-                + TrigramSimilarity("description_unaccent", query)
+                    F("name_similarity")
-                + TrigramSimilarity("content_unaccent", query)
+                    + F("description_similarity")
+                    + F("content_similarity")
                 )
-            .filter(similarity__gt=0.1)
+                / 3
-            .order_by("-similarity")
             )
+            .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/views.py

@@ -65,7 +65,6 @@ def filter(self, queryset):
                     queryset=File.objects.filter(user=self.request.user)
                 )
                 queryset = search_instance.search(query)
-                print(queryset, query)
         return queryset
 
 

compose/local/django/Dockerfile

@@ -38,6 +38,7 @@ RUN python -m venv /venv
 
 COPY pyproject.toml poetry.lock /app/
 RUN poetry export --without-hashes -f requirements.txt | /venv/bin/pip install -r /dev/stdin
+RUN python -m nltk.downloader punkt stopwords wordnet
 
 COPY . .
 RUN poetry build && /venv/bin/pip install dist/*.whl

config/settings/base.py

@@ -107,6 +107,7 @@
 ]
 
 THIRD_PARTY_APPS = [
+    "django.contrib.postgres",
     "crispy_forms",
     "crispy_bootstrap5",
     "allauth",

poetry.lock

@@ -1512,6 +1512,17 @@ twisted = {version = ">=22.4", extras = ["tls"]}
 [package.extras]
 tests = ["django", "hypothesis", "pytest", "pytest-asyncio"]
 
+[[package]]
+name = "dawg-python"
+version = "0.7.2"
+description = "Pure-python reader for DAWGs (DAFSAs) created by dawgdic C++ library or DAWG Python extension."
+optional = false
+python-versions = "*"
+files = [
+    {file = "DAWG-Python-0.7.2.tar.gz", hash = "sha256:4a5e3286e6261cca02f205cfd5516a7ab10190fa30c51c28d345808f595e3421"},
+    {file = "DAWG_Python-0.7.2-py2.py3-none-any.whl", hash = "sha256:4941d5df081b8d6fcb4597e073a9f60d5c1ccc9d17cd733e8744d7ecfec94ef3"},
+]
+
 [[package]]
 name = "decorator"
 version = "5.1.1"
@@ -2140,6 +2151,17 @@ compatible-mypy = ["mypy (>=0.991,<0.1000)"]
 coreapi = ["coreapi (>=2.0.0)"]
 markdown = ["types-Markdown (>=0.1.5)"]
 
+[[package]]
+name = "docopt-ng"
+version = "0.9.0"
+description = "Jazzband-maintained fork of docopt, the humane command line arguments parser."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "docopt_ng-0.9.0-py3-none-any.whl", hash = "sha256:bfe4c8b03f9fca424c24ee0b4ffa84bf7391cb18c29ce0f6a8227a3b01b81ff9"},
+    {file = "docopt_ng-0.9.0.tar.gz", hash = "sha256:91c6da10b5bb6f2e9e25345829fb8278c78af019f6fc40887ad49b060483b1d7"},
+]
+
 [[package]]
 name = "docutils"
 version = "0.20.1"
@@ -3082,6 +3104,17 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "joblib"
+version = "1.3.2"
+description = "Lightweight pipelining with Python functions"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "joblib-1.3.2-py3-none-any.whl", hash = "sha256:ef4331c65f239985f3f2220ecc87db222f08fd22097a3dd5698f693875f8cbb9"},
+    {file = "joblib-1.3.2.tar.gz", hash = "sha256:92f865e621e17784e7955080b6d042489e3b8e294949cc44c6eac304f59772b1"},
+]
+
 [[package]]
 name = "jsonfield"
 version = "3.1.0"
@@ -3911,6 +3944,31 @@ doc = ["nb2plots (>=0.6)", "numpydoc (>=1.5)", "pillow (>=9.4)", "pydata-sphinx-
 extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.10)", "sympy (>=1.10)"]
 test = ["codecov (>=2.1)", "pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
+[[package]]
+name = "nltk"
+version = "3.8.1"
+description = "Natural Language Toolkit"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "nltk-3.8.1-py3-none-any.whl", hash = "sha256:fd5c9109f976fa86bcadba8f91e47f5e9293bd034474752e92a520f81c93dda5"},
+    {file = "nltk-3.8.1.zip", hash = "sha256:1834da3d0682cba4f2cede2f9aad6b0fafb6461ba451db0efb6f9c39798d64d3"},
+]
+
+[package.dependencies]
+click = "*"
+joblib = "*"
+regex = ">=2021.8.3"
+tqdm = "*"
+
+[package.extras]
+all = ["matplotlib", "numpy", "pyparsing", "python-crfsuite", "requests", "scikit-learn", "scipy", "twython"]
+corenlp = ["requests"]
+machine-learning = ["numpy", "python-crfsuite", "scikit-learn", "scipy"]
+plot = ["matplotlib"]
+tgrep = ["pyparsing"]
+twitter = ["twython"]
+
 [[package]]
 name = "nodeenv"
 version = "1.8.0"
@@ -4793,6 +4851,36 @@ files = [
 [package.dependencies]
 pylint = ">=1.7"
 
+[[package]]
+name = "pymorphy3"
+version = "1.2.1"
+description = "Morphological analyzer (POS tagger + inflection engine) for Russian language."
+optional = false
+python-versions = "*"
+files = [
+    {file = "pymorphy3-1.2.1-py3-none-any.whl", hash = "sha256:88700966f55e77e3d2aedf194fa00bb4a175c2626017fe423e94ce11bc98f1ff"},
+    {file = "pymorphy3-1.2.1.tar.gz", hash = "sha256:0cc186a3b0716129dd45e3b89f5e8339e5943d9013f93cfd4c58e5335daf296d"},
+]
+
+[package.dependencies]
+dawg-python = ">=0.7.1"
+docopt-ng = ">=0.6"
+pymorphy3-dicts-ru = "*"
+
+[package.extras]
+fast = ["DAWG (>=0.8)"]
+
+[[package]]
+name = "pymorphy3-dicts-ru"
+version = "2.4.417150.4580142"
+description = "Russian dictionaries for pymorphy2"
+optional = false
+python-versions = "*"
+files = [
+    {file = "pymorphy3-dicts-ru-2.4.417150.4580142.tar.gz", hash = "sha256:39ab379d4ca905bafed50f5afc3a3de6f9643605776fbcabc4d3088d4ed382b0"},
+    {file = "pymorphy3_dicts_ru-2.4.417150.4580142-py2.py3-none-any.whl", hash = "sha256:718bac64c73c10c16073a199402657283d9b64c04188b694f6d3e9b0d85440f4"},
+]
+
 [[package]]
 name = "pyopenssl"
 version = "23.2.0"
@@ -7678,4 +7766,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.11"
-content-hash = "96905e9613ee78eb47461e88acc8fe40b481de95425960bb71a559c368f942bb"
+content-hash = "66f69d7c71004c0446a51845aa50a5f3e4a7fda401e8f18a9684ae5e34e6be75"

pyproject.toml

@@ -110,6 +110,9 @@ uuid6 = "^2023.5.2"
 fastapi = "0.86.0"
 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"
 
 
 [build-system]

search/pyproject.toml

@@ -7,12 +7,12 @@ readme = "README.md"
 
 [tool.poetry.dependencies]
 python = "^3.11"
-farm-haystack = "^1.21.2"
 fastapi = "0.99.1"
 pydantic = "1.10.13"
-milvus-haystack = "^0.0.2"
+transformers = {version = "4.34.1", extras = ["torch"]}
-
+torch = ">=2.0.0, !=2.0.1, !=2.1.0"
+farm-haystack = {extras = ["faiss"], version = "^1.21.2"}
 
 [build-system]
-requires = ["poetry-core"]
+requires = ["poetry-core>=1.0.0"]
 build-backend = "poetry.core.masonry.api"