Updates test

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

.github/workflows/ci-backend.yml

@@ -106,6 +106,7 @@ jobs:
           enable-cache: true
           python-version: ${{ steps.setup-python.outputs.python-version }}
       - name: Install system dependencies
+        timeout-minutes: 10
         run: |
           sudo apt-get update -qq
           sudo apt-get install -qq --no-install-recommends \

.github/workflows/ci-release.yml

@@ -23,7 +23,7 @@ jobs:
         uses: lewagon/wait-on-check-action@9312864dfbc9fd208e9c0417843430751c042800 # v1.7.0
         with:
           ref: ${{ github.sha }}
-          check-name: 'Build Docker Image'
+          check-name: 'Merge and Push Manifest'
           repo-token: ${{ secrets.GITHUB_TOKEN }}
           wait-interval: 60
   build-release:
@@ -177,7 +177,7 @@ jobs:
           version: ${{ steps.get-version.outputs.version }}
           prerelease: ${{ steps.get-version.outputs.prerelease }}
           publish: true
-          commitish: main
+          commitish: ${{ steps.get-version.outputs.prerelease == 'true' && 'dev' || 'main' }}
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
       - name: Upload release archive

Dockerfile

@@ -236,6 +236,8 @@ RUN set -eux \
     && mkdir -m700 --verbose /usr/src/paperless/.gnupg \
   && echo "Adjusting all permissions" \
     && chown --from root:root --changes --recursive paperless:paperless /usr/src/paperless \
+  && echo "Making fontconfig cache writable for arbitrary container UIDs" \
+    && chmod 1777 /var/cache/fontconfig \
   && echo "Collecting static files" \
     && PAPERLESS_SECRET_KEY=build-time-dummy s6-setuidgid paperless python3 manage.py collectstatic --clear --no-input --link \
     && PAPERLESS_SECRET_KEY=build-time-dummy s6-setuidgid paperless python3 manage.py compilemessages \

docs/configuration.md

@@ -2014,8 +2014,8 @@ suggestions. This setting is required to be set to true in order to use the AI f
 
 #### [`PAPERLESS_AI_LLM_EMBEDDING_BACKEND=<str>`](#PAPERLESS_AI_LLM_EMBEDDING_BACKEND) {#PAPERLESS_AI_LLM_EMBEDDING_BACKEND}
 
-: The embedding backend to use for RAG. This can be either "openai-like" or "huggingface". The
-"openai-like" backend uses an OpenAI-compatible embeddings API.
+: The embedding backend to use for RAG. This can be "openai-like", "huggingface", or
+"ollama". The "openai-like" backend uses an OpenAI-compatible embeddings API.
 
     Defaults to None.
 
@@ -2023,8 +2023,15 @@ suggestions. This setting is required to be set to true in order to use the AI f
 
 : The model to use for the embedding backend for RAG. This can be set to any of the embedding
 models supported by the current embedding backend. If not supplied, defaults to
-"text-embedding-3-small" for the OpenAI-compatible backend and
-"sentence-transformers/all-MiniLM-L6-v2" for Huggingface.
+"text-embedding-3-small" for the OpenAI-compatible backend,
+"sentence-transformers/all-MiniLM-L6-v2" for Huggingface, and "embeddinggemma" for Ollama.
+
+    Defaults to None.
+
+#### [`PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT=<str>`](#PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT) {#PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT}
+
+: The endpoint / url to use for the embedding backend. If not supplied, embeddings use
+`PAPERLESS_AI_LLM_ENDPOINT`.
 
     Defaults to None.
 

docs/migration-v3.md

@@ -1,5 +1,9 @@
 # v3 Migration Guide
 
+## Pre-Requisites
+
+Upgrading to Paperless-ngx v3 can only be performed from version 2.20.15. If you are running an older version, please upgrade to v2.20.15 before proceeding with the v3 upgrade.
+
 ## Secret Key is Now Required
 
 The `PAPERLESS_SECRET_KEY` environment variable is now required. This is a critical security setting used for cryptographic signing and should be set to a long, random value.
@@ -37,6 +41,10 @@ separating the directory ignore from the file ignore.
 | `CONSUMER_IGNORE_PATTERNS`     | [`CONSUMER_IGNORE_PATTERNS`](configuration.md#PAPERLESS_CONSUMER_IGNORE_PATTERNS)   | **Now regex, not fnmatch**; user patterns are added to (not replacing) default ones  |
 | _New_                          | [`CONSUMER_IGNORE_DIRS`](configuration.md#PAPERLESS_CONSUMER_IGNORE_DIRS)           | Additional directories to ignore; user entries are added to (not replacing) defaults |
 
+## Duplicate Handling Changes
+
+Paperless-ngx v3 no longer rejects duplicate documents by default. Instead, it now allows duplicates but adds a way to identify them via the UI. To (re-)enable duplicate rejection, set `PAPERLESS_CONSUMER_DELETE_DUPLICATES=true` in your environment.
+
 ## Encryption Support
 
 Document and thumbnail encryption is no longer supported. This was previously deprecated in [paperless-ng 0.9.3](https://github.com/paperless-ngx/paperless-ngx/blob/dev/docs/changelog.md#paperless-ng-093)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "paperless-ngx"
-version = "2.20.15"
+version = "3.0.0"
 description = "A community-supported supercharged document management system: scan, index and archive all your physical documents"
 readme = "README.md"
 requires-python = ">=3.11"
@@ -25,7 +25,7 @@ dependencies = [
   # WARNING: django does not use semver.
   #          Only patch versions are guaranteed to not introduce breaking changes.
   "django~=5.2.13",
-  "django-allauth[mfa,socialaccount]~=65.15.0",
+  "django-allauth[mfa,socialaccount]~=65.16.0",
   "django-auditlog~=3.4.1",
   "django-cachalot~=2.9.0",
   "django-compression-middleware~=0.5.0",
@@ -40,7 +40,7 @@ dependencies = [
   "djangorestframework~=3.16",
   "djangorestframework-guardian~=0.4.0",
   "drf-spectacular~=0.28",
-  "drf-spectacular-sidecar~=2026.4.14",
+  "drf-spectacular-sidecar~=2026.5.1",
   "drf-writable-nested~=0.7.1",
   "faiss-cpu>=1.10",
   "filelock~=3.29.0",
@@ -53,6 +53,7 @@ dependencies = [
   "langdetect~=1.0.9",
   "llama-index-core>=0.14.21",
   "llama-index-embeddings-huggingface>=0.6.1",
+  "llama-index-embeddings-ollama>=0.9",
   "llama-index-embeddings-openai-like>=0.2.2",
   "llama-index-llms-ollama>=0.9.1",
   "llama-index-llms-openai-like>=0.7.1",

src-ui/package.json

@@ -1,6 +1,6 @@
 {
   "name": "paperless-ngx-ui",
-  "version": "2.20.15",
+  "version": "3.0.0",
   "scripts": {
     "preinstall": "npx only-allow pnpm",
     "ng": "ng",

src-ui/pnpm-lock.yaml

@@ -1027,8 +1027,8 @@ packages:
     peerDependencies:
       '@babel/core': ^7.0.0-0
 
-  '@babel/plugin-transform-modules-systemjs@7.29.4':
-    resolution: {integrity: sha512-N7QmZ0xRZfjHOfZeQLJjwgX2zS9pdGHSVl/cjSGlo4dXMqvurfxXDMKY4RqEKzPozV78VMcd0lxyG13mlbKc4w==}
+  '@babel/plugin-transform-modules-systemjs@7.29.0':
+    resolution: {integrity: sha512-PrujnVFbOdUpw4UHiVwKvKRLMMic8+eC0CuNlxjsyZUiBjhFdPsewdXCkveh2KqBA9/waD0W1b4hXSOBQJezpQ==}
     engines: {node: '>=6.9.0'}
     peerDependencies:
       '@babel/core': ^7.0.0-0
@@ -3262,7 +3262,6 @@ packages:
 
   '@ungap/structured-clone@1.3.0':
     resolution: {integrity: sha512-WmoN8qaIAo7WTYWbAZuG8PYEhn5fkz7dZrqTBZ7dtt//lL2Gwms1IcnQ5yHqjDfX8Ft5j4YzDM23f87zBfDe9g==}
-    deprecated: Potential CWE-502 - Update to 1.3.1 or higher
 
   '@unrs/resolver-binding-android-arm-eabi@1.11.1':
     resolution: {integrity: sha512-ppLRUgHVaGRWUx0R0Ut06Mjo9gBaBkg3v/8AxusGLhsIotbBLuRk51rAzqLC8gq6NyyAojEXglNjzf6R948DNw==}
@@ -4313,8 +4312,8 @@ packages:
   fast-levenshtein@2.0.6:
     resolution: {integrity: sha512-DCXu6Ifhqcks7TZKY3Hxp3y6qphY5SJZmrWMDrKcERSOXWQdMhU9Ig/PYrzyw/ul9jOIyh0N4M0tbC5hodg8dw==}
 
-  fast-uri@3.1.2:
-    resolution: {integrity: sha512-rVjf7ArG3LTk+FS6Yw81V1DLuZl1bRbNrev6Tmd/9RaroeeRRJhAt7jg/6YFxbvAQXUCavSoZhPPj6oOx+5KjQ==}
+  fast-uri@3.1.1:
+    resolution: {integrity: sha512-h2r7rcm6Ee/J8o0LD5djLuFVcfbZxhvho4vvsbeV0aMvXjUgqv4YpxpkEx0d68l6+IleVfLAdVEfhR7QNMkGHQ==}
 
   faye-websocket@0.11.4:
     resolution: {integrity: sha512-CzbClwlXAuiRQAlUyfqPgvPoNKTckTPGfwZV4ZdAhVcP2lh9KUxJg2b5GkE7XbjKQ3YJnQ9z6D9ntLAlB+tP8g==}
@@ -5436,8 +5435,8 @@ packages:
       '@angular/core': ^21.1.0
       '@ng-bootstrap/ng-bootstrap': ^20.0.0
 
-  node-abi@3.92.0:
-    resolution: {integrity: sha512-KdHvFWZjEKDf0cakgFjebl371GPsISX2oZHcuyKqM7DtogIsHrqKeLTo8wBHxaXRAQlY2PsPlZmfo+9ZCxEREQ==}
+  node-abi@3.90.0:
+    resolution: {integrity: sha512-pZNQT7UnYlMwMBy5N1lV5X/YLTbZM5ncytN3xL7CHEzhDN8uVe0u55yaPUJICIJjaCW8NrM5BFdqr7HLweStNA==}
     engines: {node: '>=10'}
 
   node-addon-api@6.1.0:
@@ -6069,11 +6068,6 @@ packages:
     engines: {node: '>=10'}
     hasBin: true
 
-  semver@7.8.0:
-    resolution: {integrity: sha512-AcM7dV/5ul4EekoQ29Agm5vri8JNqRyj39o0qpX6vDF2GZrtutZl5RwgD1XnZjiTAfncsJhMI48QQH3sN87YNA==}
-    engines: {node: '>=10'}
-    hasBin: true
-
   send@0.19.2:
     resolution: {integrity: sha512-VMbMxbDeehAxpOtWJXlcUS5E8iXh6QmN+BkRX1GARS3wRaXEEgzCcB10gTQazO42tpNIya8xIyNx8fll1OFPrg==}
     engines: {node: '>= 0.8.0'}
@@ -8115,7 +8109,7 @@ snapshots:
     transitivePeerDependencies:
       - supports-color
 
-  '@babel/plugin-transform-modules-systemjs@7.29.4(@babel/core@7.28.5)':
+  '@babel/plugin-transform-modules-systemjs@7.29.0(@babel/core@7.28.5)':
     dependencies:
       '@babel/core': 7.28.5
       '@babel/helper-module-transforms': 7.28.6(@babel/core@7.28.5)
@@ -8333,7 +8327,7 @@ snapshots:
       '@babel/plugin-transform-member-expression-literals': 7.27.1(@babel/core@7.28.5)
       '@babel/plugin-transform-modules-amd': 7.27.1(@babel/core@7.28.5)
       '@babel/plugin-transform-modules-commonjs': 7.28.6(@babel/core@7.28.5)
-      '@babel/plugin-transform-modules-systemjs': 7.29.4(@babel/core@7.28.5)
+      '@babel/plugin-transform-modules-systemjs': 7.29.0(@babel/core@7.28.5)
       '@babel/plugin-transform-modules-umd': 7.27.1(@babel/core@7.28.5)
       '@babel/plugin-transform-named-capturing-groups-regex': 7.29.0(@babel/core@7.28.5)
       '@babel/plugin-transform-new-target': 7.27.1(@babel/core@7.28.5)
@@ -10402,21 +10396,21 @@ snapshots:
   ajv@8.17.1:
     dependencies:
       fast-deep-equal: 3.1.3
-      fast-uri: 3.1.2
+      fast-uri: 3.1.1
       json-schema-traverse: 1.0.0
       require-from-string: 2.0.2
 
   ajv@8.18.0:
     dependencies:
       fast-deep-equal: 3.1.3
-      fast-uri: 3.1.2
+      fast-uri: 3.1.1
       json-schema-traverse: 1.0.0
       require-from-string: 2.0.2
 
   ajv@8.20.0:
     dependencies:
       fast-deep-equal: 3.1.3
-      fast-uri: 3.1.2
+      fast-uri: 3.1.1
       json-schema-traverse: 1.0.0
       require-from-string: 2.0.2
 
@@ -11398,7 +11392,7 @@ snapshots:
 
   fast-levenshtein@2.0.6: {}
 
-  fast-uri@3.1.2: {}
+  fast-uri@3.1.1: {}
 
   faye-websocket@0.11.4:
     dependencies:
@@ -12752,9 +12746,9 @@ snapshots:
       - '@angular/router'
       - rxjs
 
-  node-abi@3.92.0:
+  node-abi@3.90.0:
     dependencies:
-      semver: 7.8.0
+      semver: 7.7.4
     optional: true
 
   node-addon-api@6.1.0:
@@ -13133,7 +13127,7 @@ snapshots:
       minimist: 1.2.8
       mkdirp-classic: 0.5.3
       napi-build-utils: 2.0.0
-      node-abi: 3.92.0
+      node-abi: 3.90.0
       pump: 3.0.4
       rc: 1.2.8
       simple-get: 4.0.1
@@ -13473,9 +13467,6 @@ snapshots:
 
   semver@7.7.4: {}
 
-  semver@7.8.0:
-    optional: true
-
   send@0.19.2:
     dependencies:
       debug: 2.6.9

src-ui/src/app/data/paperless-config.ts

@@ -57,6 +57,7 @@ export const ConfigCategory = {
 export const LLMEmbeddingBackendConfig = {
   OPENAI_LIKE: 'openai-like',
   HUGGINGFACE: 'huggingface',
+  OLLAMA: 'ollama',
 }
 
 export const LLMBackendConfig = {
@@ -301,6 +302,13 @@ export const PaperlessConfigOptions: ConfigOption[] = [
     config_key: 'PAPERLESS_AI_LLM_EMBEDDING_MODEL',
     category: ConfigCategory.AI,
   },
+  {
+    key: 'llm_embedding_endpoint',
+    title: $localize`LLM Embedding Endpoint`,
+    type: ConfigOptionType.String,
+    config_key: 'PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT',
+    category: ConfigCategory.AI,
+  },
   {
     key: 'llm_backend',
     title: $localize`LLM Backend`,
@@ -363,6 +371,7 @@ export interface PaperlessConfig extends ObjectWithId {
   ai_enabled: boolean
   llm_embedding_backend: string
   llm_embedding_model: string
+  llm_embedding_endpoint: string
   llm_backend: string
   llm_model: string
   llm_api_key: string

src-ui/src/environments/environment.prod.ts

@@ -6,7 +6,7 @@ export const environment = {
   apiVersion: '10', // match src/paperless/settings.py
   appTitle: 'Paperless-ngx',
   tag: 'prod',
-  version: '2.20.15',
+  version: '3.0.0',
   webSocketHost: window.location.host,
   webSocketProtocol: window.location.protocol == 'https:' ? 'wss:' : 'ws:',
   webSocketBaseUrl: base_url.pathname + 'ws/',

src/documents/conditionals.py

@@ -117,6 +117,17 @@ def preview_last_modified(request, pk: int) -> datetime | None:
     return doc.modified
 
 
+def thumbnail_etag(request: Any, pk: int) -> str | None:
+    """
+    Thumbnails are version-dependent, so use the effective document checksum as
+    the ETag to invalidate cache when the latest version changes.
+    """
+    doc = resolve_effective_document_by_pk(pk, request).document
+    if doc is None:
+        return None
+    return doc.checksum
+
+
 def thumbnail_last_modified(request: Any, pk: int) -> datetime | None:
     """
     Returns the filesystem last modified either from cache or from filesystem.

src/documents/management/commands/document_importer.py

@@ -30,6 +30,7 @@ from django.db.models import Model
 from django.db.models.signals import m2m_changed
 from django.db.models.signals import post_save
 from filelock import FileLock
+from guardian.shortcuts import clear_ct_cache
 
 from documents.file_handling import create_source_path_directory
 from documents.management.commands.base import PaperlessCommand
@@ -429,6 +430,12 @@ class Command(CryptMixin, PaperlessCommand):
             self.stdout.write(self.style.ERROR(self._import_error_context_message()))
             raise
 
+        # ContentType/Permission rows were deleted and reinserted above; stale
+        # in-process caches must be invalidated so permission checks use the
+        # new IDs rather than pre-import PKs.
+        ContentType.objects.clear_cache()
+        clear_ct_cache()
+
     def handle(self, *args, **options) -> None:
         logging.getLogger().handlers[0].level = logging.ERROR
 

src/documents/search/_query.py

@@ -71,7 +71,16 @@ _WHOOSH_REL_RANGE_RE = regex.compile(
 )
 # Whoosh-style 8-digit date: field:YYYYMMDD — field-aware so timezone can be applied correctly
 _DATE8_RE = regex.compile(r"(?P<field>\w+):(?P<date8>\d{8})\b")
+_YEAR_RANGE_RE = regex.compile(
+    r"(?P<field>\w+):\[(?P<y1>\d{4})\s+TO\s+(?P<y2>\d{4})\]",
+    regex.IGNORECASE,
+)
 _SIMPLE_QUERY_TOKEN_RE = regex.compile(r"\S+")
+# Tantivy syntax error: " - " and " + " with spaces on both sides are invalid because
+# the NOT/MUST operators require no space between the operator and the term.
+# In natural-language queries (e.g., "H52.1 - Kurzsichtigkeit"), the dash is a separator.
+_SPACED_OPERATOR_RE = regex.compile(r"\s+[-+]\s+")
+_TRAILING_OPERATOR_RE = regex.compile(r"\s+[-+]+\s*$")
 
 
 def _fmt(dt: datetime) -> str:
@@ -336,6 +345,26 @@ def _rewrite_8digit_date(query: str, tz: tzinfo) -> str:
         )
 
 
+def _rewrite_year_range(query: str) -> str:
+    """Rewrite Whoosh-style year-only date ranges to ISO 8601 UTC boundaries.
+
+    Converts ``field:[YYYY TO YYYY]`` to a full ISO 8601 datetime range.
+    The upper bound is the start of the year after the end year (exclusive),
+    matching the Whoosh convention of treating year-only ranges as full-year spans.
+    """
+
+    def _sub(m: regex.Match[str]) -> str:
+        field = m.group("field")
+        lo = datetime(int(m.group("y1")), 1, 1, tzinfo=UTC)
+        hi = datetime(int(m.group("y2")) + 1, 1, 1, tzinfo=UTC)
+        return f"{field}:[{_fmt(lo)} TO {_fmt(hi)}]"
+
+    try:
+        return _YEAR_RANGE_RE.sub(_sub, query, timeout=_REGEX_TIMEOUT)
+    except TimeoutError:  # pragma: no cover
+        raise ValueError("Query too complex to process (year range rewrite timed out)")
+
+
 def rewrite_natural_date_keywords(query: str, tz: tzinfo) -> str:
     """
     Rewrite natural date syntax to ISO 8601 format for Tantivy compatibility.
@@ -359,6 +388,7 @@ def rewrite_natural_date_keywords(query: str, tz: tzinfo) -> str:
     """
     query = _rewrite_compact_date(query)
     query = _rewrite_whoosh_relative_range(query)
+    query = _rewrite_year_range(query)
     query = _rewrite_8digit_date(query, tz)
     query = _rewrite_relative_range(query)
 
@@ -405,7 +435,14 @@ def normalize_query(query: str) -> str:
             query,
             timeout=_REGEX_TIMEOUT,
         )
-        return regex.sub(r" {2,}", " ", query, timeout=_REGEX_TIMEOUT).strip()
+        query = regex.sub(r" {2,}", " ", query, timeout=_REGEX_TIMEOUT).strip()
+        # Strip trailing dangling operators before Tantivy sees them.
+        query = _TRAILING_OPERATOR_RE.sub("", query, timeout=_REGEX_TIMEOUT).strip()
+        # Replace " - " / " + " with a space: Tantivy requires no space between
+        # the operator and its operand (-term / +term), so spaces on both sides
+        # means this is a natural-language separator, not a query operator.
+        query = _SPACED_OPERATOR_RE.sub(" ", query, timeout=_REGEX_TIMEOUT).strip()
+        return query
     except TimeoutError:  # pragma: no cover
         raise ValueError("Query too complex to process (normalization timed out)")
 

src/documents/tests/conftest.py

@@ -8,6 +8,8 @@ from typing import TYPE_CHECKING
 import filelock
 import pytest
 from django.contrib.auth import get_user_model
+from django.contrib.contenttypes.models import ContentType
+from guardian.shortcuts import clear_ct_cache
 from pytest_django.fixtures import SettingsWrapper
 from rest_framework.test import APIClient
 
@@ -158,6 +160,19 @@ def user_client(rest_api_client: APIClient, regular_user: UserModelT) -> APIClie
     return rest_api_client
 
 
+@pytest.fixture(autouse=True)
+def _clear_content_type_caches() -> None:
+    """Clear Django's ContentType cache and guardian's lru_cache before each test.
+
+    Tests that delete and reinsert ContentType/Permission rows (e.g. the
+    importer) corrupt both caches. Without this fixture a subsequent test on
+    the same xdist worker sees stale ContentType objects and guardian raises
+    MixedContentTypeError.
+    """
+    ContentType.objects.clear_cache()
+    clear_ct_cache()
+
+
 @pytest.fixture(scope="session", autouse=True)
 def faker_session_locale():
     """Set Faker locale for reproducibility."""

src/documents/tests/search/test_query.py

@@ -443,6 +443,102 @@ class TestParseUserQuery:
             q = parse_user_query(query_index, "created:today", UTC)
         assert isinstance(q, tantivy.Query)
 
+    @pytest.mark.parametrize(
+        "raw_query",
+        [
+            pytest.param("h52.1 - kurzsichtigkeit", id="icd_code_dash_description"),
+            pytest.param("H52.1 - asd", id="icd_code_uppercase"),
+            pytest.param("h52.1 -", id="trailing_minus"),
+            pytest.param(". -", id="dot_trailing_minus"),
+            pytest.param("h52. -", id="partial_code_trailing_minus"),
+            pytest.param(".12 -", id="dot_number_trailing_minus"),
+            pytest.param("h52.1 - ku", id="partial_word_after_dash"),
+        ],
+    )
+    def test_spaced_dash_queries_do_not_raise(
+        self,
+        query_index: tantivy.Index,
+        raw_query: str,
+    ) -> None:
+        assert isinstance(parse_user_query(query_index, raw_query, UTC), tantivy.Query)
+
+
+class TestYearRangeRewriting:
+    """Whoosh-style year-only date ranges must be rewritten to ISO 8601."""
+
+    @pytest.mark.parametrize(
+        ("query", "field", "expected_lo", "expected_hi"),
+        [
+            pytest.param(
+                "created:[2020 TO 2020]",
+                "created",
+                "2020-01-01T00:00:00Z",
+                "2021-01-01T00:00:00Z",
+                id="single_year_created",
+            ),
+            pytest.param(
+                "created:[2018 TO 2021]",
+                "created",
+                "2018-01-01T00:00:00Z",
+                "2022-01-01T00:00:00Z",
+                id="multi_year_range_created",
+            ),
+            pytest.param(
+                "added:[2022 TO 2023]",
+                "added",
+                "2022-01-01T00:00:00Z",
+                "2024-01-01T00:00:00Z",
+                id="added_field",
+            ),
+            pytest.param(
+                "modified:[2021 TO 2021]",
+                "modified",
+                "2021-01-01T00:00:00Z",
+                "2022-01-01T00:00:00Z",
+                id="modified_field",
+            ),
+            pytest.param(
+                "created:[2020 to 2020]",
+                "created",
+                "2020-01-01T00:00:00Z",
+                "2021-01-01T00:00:00Z",
+                id="lowercase_to_keyword",
+            ),
+        ],
+    )
+    def test_year_range_rewritten(
+        self,
+        query: str,
+        field: str,
+        expected_lo: str,
+        expected_hi: str,
+    ) -> None:
+        result = rewrite_natural_date_keywords(query, UTC)
+        lo, hi = _range(result, field)
+        assert lo == expected_lo
+        assert hi == expected_hi
+
+    def test_year_range_in_complex_boolean_query(self) -> None:
+        query = "tag:steuer AND (title:2020 OR (NOT title:2019 AND NOT title:2018 AND created:[2020 TO 2020]))"
+        result = rewrite_natural_date_keywords(query, UTC)
+        lo, hi = _range(result, "created")
+        assert lo == "2020-01-01T00:00:00Z"
+        assert hi == "2021-01-01T00:00:00Z"
+        assert "title:2020" in result
+        assert "title:2019" in result
+        assert "title:2018" in result
+
+    def test_already_iso_date_range_passes_through_unchanged(self) -> None:
+        original = "created:[2020-01-01T00:00:00Z TO 2021-01-01T00:00:00Z]"
+        assert rewrite_natural_date_keywords(original, UTC) == original
+
+    def test_8digit_in_brackets_not_matched_as_year_range(self) -> None:
+        # [YYYYMMDD TO YYYYMMDD] has 8-digit values - must not be caught by year rewriter
+        original = "created:[20200101 TO 20201231]"
+        result = rewrite_natural_date_keywords(original, UTC)
+        assert "20200101" in result or "2020-01-01" in result
+        assert "20201231" in result or "2020-12-31" in result
+
 
 class TestPassthrough:
     """Queries without field prefixes or unrelated content pass through unchanged."""
@@ -471,10 +567,65 @@ class TestNormalizeQuery:
     def test_normalize_no_commas_unchanged(self) -> None:
         assert normalize_query("bank statement") == "bank statement"
 
+    @pytest.mark.parametrize(
+        ("raw", "expected"),
+        [
+            pytest.param(
+                "h52.1 - kurzsichtigkeit",
+                "h52.1 kurzsichtigkeit",
+                id="icd_code_dash_description",
+            ),
+            pytest.param(
+                "H52.1 - asd",
+                "H52.1 asd",
+                id="icd_code_uppercase_dash",
+            ),
+            pytest.param(
+                "h52.1 -",
+                "h52.1",
+                id="trailing_minus",
+            ),
+            pytest.param(
+                ". -",
+                ".",
+                id="dot_trailing_minus",
+            ),
+            pytest.param(
+                "h52. -",
+                "h52.",
+                id="partial_code_trailing_minus",
+            ),
+            pytest.param(
+                "foo - bar - baz",
+                "foo bar baz",
+                id="multiple_dashes",
+            ),
+            pytest.param(
+                "foo + bar",
+                "foo bar",
+                id="spaced_plus_operator",
+            ),
+        ],
+    )
+    def test_normalize_strips_dangling_operators(self, raw: str, expected: str) -> None:
+        assert normalize_query(raw) == expected
+
+    @pytest.mark.parametrize(
+        "query",
+        [
+            pytest.param("term -other", id="adjacent_not_operator"),
+            pytest.param("-term", id="leading_not_operator"),
+            pytest.param("+term", id="leading_must_operator"),
+            pytest.param("foo -bar +baz", id="mixed_adjacent_operators"),
+        ],
+    )
+    def test_normalize_preserves_valid_operators(self, query: str) -> None:
+        assert normalize_query(query) == query
+
 
 class TestPermissionFilter:
     """
-    build_permission_filter tests use an in-memory index — no DB access needed.
+    build_permission_filter tests use an in-memory index - no DB access needed.
 
     Users are constructed as unsaved model instances (django_user_model(pk=N))
     so no database round-trip occurs; only .pk is read by build_permission_filter.

src/documents/tests/test_api_app_config.py

@@ -74,6 +74,7 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
                 "ai_enabled": False,
                 "llm_embedding_backend": None,
                 "llm_embedding_model": None,
+                "llm_embedding_endpoint": None,
                 "llm_backend": None,
                 "llm_model": None,
                 "llm_api_key": None,
@@ -868,3 +869,19 @@ class TestApiAppConfig(DirectoriesMixin, APITestCase):
         )
         self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
         self.assertIn("non-public address", str(response.data).lower())
+
+    @override_settings(LLM_ALLOW_INTERNAL_ENDPOINTS=False)
+    def test_update_llm_embedding_endpoint_blocks_internal_endpoint_when_disallowed(
+        self,
+    ) -> None:
+        response = self.client.patch(
+            f"{self.ENDPOINT}1/",
+            json.dumps(
+                {
+                    "llm_embedding_endpoint": "http://127.0.0.1:11434",
+                },
+            ),
+            content_type="application/json",
+        )
+        self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
+        self.assertIn("non-public address", str(response.data).lower())

src/documents/tests/test_api_document_versions.py

@@ -464,6 +464,40 @@ class TestDocumentVersioningApi(DirectoriesMixin, APITestCase):
         self.assertEqual(resp.status_code, status.HTTP_200_OK)
         self.assertEqual(read_streaming_response(resp), b"thumb")
 
+    def test_thumb_etag_changes_when_latest_version_is_deleted(self) -> None:
+        root = self._create_pdf(title="root", checksum="root")
+        v1 = self._create_pdf(
+            title="v1",
+            checksum="v1",
+            root_document=root,
+        )
+        v2 = self._create_pdf(
+            title="v2",
+            checksum="v2",
+            root_document=root,
+        )
+        self._write_file(v1.thumbnail_path, b"thumb-v1")
+        self._write_file(v2.thumbnail_path, b"thumb-v2")
+
+        resp = self.client.get(f"/api/documents/{root.id}/thumb/")
+        self.assertEqual(resp.status_code, status.HTTP_200_OK)
+        self.assertEqual(read_streaming_response(resp), b"thumb-v2")
+        self.assertEqual(resp.headers["ETag"], '"v2"')
+
+        with mock.patch("documents.search.get_backend"):
+            delete_resp = self.client.delete(
+                f"/api/documents/{root.id}/versions/{v2.id}/",
+            )
+        self.assertEqual(delete_resp.status_code, status.HTTP_200_OK)
+
+        resp = self.client.get(
+            f"/api/documents/{root.id}/thumb/",
+            HTTP_IF_NONE_MATCH='"v2"',
+        )
+        self.assertEqual(resp.status_code, status.HTTP_200_OK)
+        self.assertEqual(resp.headers["ETag"], '"v1"')
+        self.assertEqual(read_streaming_response(resp), b"thumb-v1")
+
     def test_metadata_version_param_uses_version(self) -> None:
         root = Document.objects.create(
             title="root",

src/documents/tests/test_api_documents.py

@@ -485,6 +485,42 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
         response = self.client.get(f"/api/documents/{doc.pk}/thumb/")
         self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND)
 
+    def test_document_actions_trashed_document(self) -> None:
+        """
+        GIVEN:
+            - Document with files exists
+        WHEN:
+            - Document is soft-deleted (moved to trash)
+            - Preview and thumb endpoints are requested
+        THEN:
+            - HTTP 200 OK for both (trashed documents remain previewable)
+        """
+        _, filename = tempfile.mkstemp(dir=self.dirs.originals_dir)
+        content = b"This is a test"
+        content_thumbnail = b"thumbnail content"
+
+        with Path(filename).open("wb") as f:
+            f.write(content)
+
+        doc = Document.objects.create(
+            title="none",
+            filename=Path(filename).name,
+            mime_type="application/pdf",
+        )
+
+        with (self.dirs.thumbnail_dir / f"{doc.pk:07d}.webp").open("wb") as f:
+            f.write(content_thumbnail)
+
+        doc.delete()
+
+        response = self.client.get(f"/api/documents/{doc.pk}/preview/")
+        self.assertEqual(response.status_code, status.HTTP_200_OK)
+        self.assertEqual(read_streaming_response(response), content)
+
+        response = self.client.get(f"/api/documents/{doc.pk}/thumb/")
+        self.assertEqual(response.status_code, status.HTTP_200_OK)
+        self.assertEqual(read_streaming_response(response), content_thumbnail)
+
     def test_document_history_action(self) -> None:
         """
         GIVEN:
@@ -1305,6 +1341,35 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
         self.assertEqual(response.data["document_type_count"], 1)
         self.assertEqual(response.data["storage_path_count"], 2)
 
+    def test_statistics_excludes_document_versions(self) -> None:
+        root = Document.objects.create(
+            title="root",
+            checksum="A",
+            mime_type="application/pdf",
+            content="root",
+        )
+        version = Document.objects.create(
+            title="version",
+            checksum="B",
+            mime_type="application/pdf",
+            content="version",
+            root_document=root,
+            version_index=1,
+        )
+        tag_inbox = Tag.objects.create(name="t1", is_inbox_tag=True)
+        version.tags.add(tag_inbox)
+
+        response = self.client.get("/api/statistics/")
+
+        self.assertEqual(response.status_code, status.HTTP_200_OK)
+        self.assertEqual(response.data["documents_total"], 1)
+        self.assertEqual(response.data["documents_inbox"], 0)
+        self.assertEqual(response.data["character_count"], 4)
+        self.assertEqual(
+            response.data["document_file_type_counts"][0]["mime_type_count"],
+            1,
+        )
+
     def test_statistics_no_inbox_tag(self) -> None:
         Document.objects.create(title="none1", checksum="A")
 
@@ -3047,6 +3112,46 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
         # modified was updated to today
         self.assertEqual(doc.modified.day, timezone.now().day)
 
+    def test_create_note_only_saves_document_modified_field(self) -> None:
+        """
+        GIVEN:
+            - Existing document with a created date
+        WHEN:
+            - API request is made to add a note
+        THEN:
+            - Only the document modified field is persisted by the note endpoint
+            - Other document fields are not rewritten by the note endpoint
+        """
+        doc = Document.objects.create(
+            title="test",
+            mime_type="application/pdf",
+            content="this is a document which will have notes added",
+            created=datetime.date(2026, 3, 31),
+        )
+        original_save = Document.save
+
+        with mock.patch.object(
+            Document,
+            "save",
+            autospec=True,
+            side_effect=original_save,
+        ) as save_mock:
+            resp = self.client.post(
+                f"/api/documents/{doc.pk}/notes/",
+                data={"note": "this is a posted note"},
+            )
+
+        self.assertEqual(resp.status_code, status.HTTP_200_OK)
+        doc.refresh_from_db()
+        self.assertEqual(doc.created, datetime.date(2026, 3, 31))
+        self.assertTrue(
+            any(
+                call.kwargs.get("update_fields") == ["modified"]
+                for call in save_mock.call_args_list
+                if call.args and call.args[0].pk == doc.pk
+            ),
+        )
+
     def test_notes_permissions_aware(self) -> None:
         """
         GIVEN:

src/documents/tests/test_version_conditionals.py

@@ -5,6 +5,7 @@ from django.test import TestCase
 
 from documents.conditionals import metadata_etag
 from documents.conditionals import preview_etag
+from documents.conditionals import thumbnail_etag
 from documents.conditionals import thumbnail_last_modified
 from documents.models import Document
 from documents.tests.utils import DirectoriesMixin
@@ -30,6 +31,7 @@ class TestConditionals(DirectoriesMixin, TestCase):
 
         self.assertEqual(metadata_etag(request, root.id), latest.checksum)
         self.assertEqual(preview_etag(request, root.id), latest.archive_checksum)
+        self.assertEqual(thumbnail_etag(request, root.id), latest.checksum)
 
     def test_resolve_effective_doc_returns_none_for_invalid_or_unrelated_version(
         self,

src/documents/tests/test_workflows.py

@@ -4164,7 +4164,7 @@ class TestWorkflows(
         )
         action = WorkflowAction.objects.create(
             type=WorkflowAction.WorkflowActionType.PASSWORD_REMOVAL,
-            passwords="wrong, right\n extra ",
+            passwords=["wrong", "right", "extra"],
         )
         workflow = Workflow.objects.create(name="Password workflow")
         workflow.triggers.add(trigger)
@@ -4218,7 +4218,7 @@ class TestWorkflows(
         )
         action = WorkflowAction.objects.create(
             type=WorkflowAction.WorkflowActionType.PASSWORD_REMOVAL,
-            passwords=" \n , ",
+            passwords=[" ", "  "],
         )
         workflow = Workflow.objects.create(name="Password workflow missing passwords")
         workflow.triggers.add(trigger)
@@ -4276,7 +4276,7 @@ class TestWorkflows(
         """
         action = WorkflowAction.objects.create(
             type=WorkflowAction.WorkflowActionType.PASSWORD_REMOVAL,
-            passwords="first, second",
+            passwords=["first", "second"],
         )
 
         temp_dir = Path(tempfile.mkdtemp())

src/documents/views.py

@@ -67,7 +67,6 @@ from django.views import View
 from django.views.decorators.cache import cache_control
 from django.views.decorators.csrf import ensure_csrf_cookie
 from django.views.decorators.http import condition
-from django.views.decorators.http import last_modified
 from django.views.generic import TemplateView
 from django_filters.rest_framework import DjangoFilterBackend
 from drf_spectacular.openapi import AutoSchema
@@ -124,6 +123,7 @@ from documents.conditionals import preview_etag
 from documents.conditionals import preview_last_modified
 from documents.conditionals import suggestions_etag
 from documents.conditionals import suggestions_last_modified
+from documents.conditionals import thumbnail_etag
 from documents.conditionals import thumbnail_last_modified
 from documents.data_models import ConsumableDocument
 from documents.data_models import DocumentMetadataOverrides
@@ -1542,7 +1542,7 @@ class DocumentViewSet(
         condition(etag_func=preview_etag, last_modified_func=preview_last_modified),
     )
     def preview(self, request, pk=None):
-        resolved = self._resolve_request_and_root_doc(pk, request)
+        resolved = self._resolve_request_and_root_doc(pk, request, include_deleted=True)
         if isinstance(resolved, HttpResponseForbidden):
             return resolved
 
@@ -1564,9 +1564,14 @@ class DocumentViewSet(
 
     @action(methods=["get"], detail=True, filter_backends=[])
     @method_decorator(cache_control(no_cache=True))
-    @method_decorator(last_modified(thumbnail_last_modified))
+    @method_decorator(
+        condition(
+            etag_func=thumbnail_etag,
+            last_modified_func=thumbnail_last_modified,
+        ),
+    )
     def thumb(self, request, pk=None):
-        resolved = self._resolve_request_and_root_doc(pk, request)
+        resolved = self._resolve_request_and_root_doc(pk, request, include_deleted=True)
         if isinstance(resolved, HttpResponseForbidden):
             return resolved
 
@@ -1653,7 +1658,7 @@ class DocumentViewSet(
                     )
 
                 doc.modified = timezone.now()
-                doc.save()
+                doc.save(update_fields=["modified"])
 
                 from documents.search import get_backend
 
@@ -1697,7 +1702,7 @@ class DocumentViewSet(
             note.delete()
 
             doc.modified = timezone.now()
-            doc.save()
+            doc.save(update_fields=["modified"])
 
             from documents.search import get_backend
 
@@ -3614,7 +3619,7 @@ class StatisticsView(GenericAPIView[Any]):
                 "documents.view_document",
                 Document,
             )
-        )
+        ).filter(root_document__isnull=True)
         tags = (
             Tag.objects.all()
             if can_view_global_stats

src/documents/workflows/actions.py

@@ -1,5 +1,4 @@
 import logging
-import re
 import uuid
 from pathlib import Path
 
@@ -290,11 +289,7 @@ def execute_password_removal_action(
         )
         return
 
-    passwords = [
-        password.strip()
-        for password in re.split(r"[,\n]", passwords)
-        if password.strip()
-    ]
+    passwords = [p.strip() for p in passwords if p.strip()]
 
     if isinstance(document, ConsumableDocument):
         # hook the consumption-finished signal to attempt password removal later

src/paperless/checks.py

@@ -1,3 +1,4 @@
+import logging
 import os
 import shutil
 import stat
@@ -202,10 +203,10 @@ def check_v3_minimum_upgrade_version(
     **kwargs: object,
 ) -> list[Error]:
     """
-    Enforce that upgrades to v3 must start from v2.20.10.
+    Enforce that upgrades to v3 must start from v2.20.15.
 
     v3 squashes all prior migrations into 0001_squashed and 0002_squashed.
-    If a user skips v2.20.10, the data migration in 1075_workflowaction_order
+    If a user skips v2.20.15, the data migration in 1075_workflowaction_order
     never runs and the squash may apply schema changes against an incomplete
     database state.
     """
@@ -232,19 +233,28 @@ def check_v3_minimum_upgrade_version(
         if {"0001_squashed", "0002_squashed"} & applied:
             return []
 
-        # On v2.20.10 exactly — squash will pick up cleanly from here
+        # On v2.20.15 exactly — squash will pick up cleanly from here
         if "1075_workflowaction_order" in applied:
             return []
 
     except (DatabaseError, OperationalError):
         return []
 
+    logger = logging.getLogger(__name__)
+    last_applied = sorted(applied)[-1] if applied else "(none)"
+    logger.error(
+        "V3 upgrade check failed: last applied documents migration is %r. "
+        "Expected '1075_workflowaction_order' (v2.20.15). "
+        "Ensure you have upgraded to v2.20.15 and run 'manage.py migrate' before upgrading to v3.",
+        last_applied,
+    )
+
     return [
         Error(
             "Cannot upgrade to Paperless-ngx v3 from this version.",
             hint=(
-                "Upgrading to v3 can only be performed from v2.20.10."
-                "Please upgrade to v2.20.10, run migrations, then upgrade to v3."
+                "Upgrading to v3 can only be performed from v2.20.15. "
+                "Please upgrade to v2.20.15, run migrations, then upgrade to v3. "
                 "See https://docs.paperless-ngx.com/setup/#upgrading for details."
             ),
             id="paperless.E002",

src/paperless/config.py

@@ -194,6 +194,7 @@ class AIConfig(BaseConfig):
     ai_enabled: bool = dataclasses.field(init=False)
     llm_embedding_backend: str = dataclasses.field(init=False)
     llm_embedding_model: str = dataclasses.field(init=False)
+    llm_embedding_endpoint: str = dataclasses.field(init=False)
     llm_backend: str = dataclasses.field(init=False)
     llm_model: str = dataclasses.field(init=False)
     llm_api_key: str = dataclasses.field(init=False)
@@ -210,6 +211,9 @@ class AIConfig(BaseConfig):
         self.llm_embedding_model = (
             app_config.llm_embedding_model or settings.LLM_EMBEDDING_MODEL
         )
+        self.llm_embedding_endpoint = (
+            app_config.llm_embedding_endpoint or settings.LLM_EMBEDDING_ENDPOINT
+        )
         self.llm_backend = app_config.llm_backend or settings.LLM_BACKEND
         self.llm_model = app_config.llm_model or settings.LLM_MODEL
         self.llm_api_key = app_config.llm_api_key or settings.LLM_API_KEY

src/paperless/migrations/0010_alter_applicationconfiguration_llm_embedding_backend.py

@@ -0,0 +1,38 @@
+# Generated by Django 5.2.6 on 2026-05-08 00:00
+
+from django.db import migrations
+from django.db import models
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("paperless", "0009_alter_applicationconfiguration_options"),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name="applicationconfiguration",
+            name="llm_embedding_backend",
+            field=models.CharField(
+                blank=True,
+                choices=[
+                    ("openai-like", "OpenAI-compatible"),
+                    ("huggingface", "Huggingface"),
+                    ("ollama", "Ollama"),
+                ],
+                max_length=128,
+                null=True,
+                verbose_name="Sets the LLM embedding backend",
+            ),
+        ),
+        migrations.AddField(
+            model_name="applicationconfiguration",
+            name="llm_embedding_endpoint",
+            field=models.CharField(
+                blank=True,
+                max_length=256,
+                null=True,
+                verbose_name="Sets the LLM embedding endpoint, optional",
+            ),
+        ),
+    ]

src/paperless/models.py

@@ -77,6 +77,7 @@ class ColorConvertChoices(models.TextChoices):
 class LLMEmbeddingBackend(models.TextChoices):
     OPENAI_LIKE = ("openai-like", _("OpenAI-compatible"))
     HUGGINGFACE = ("huggingface", _("Huggingface"))
+    OLLAMA = ("ollama", _("Ollama"))
 
 
 class LLMBackend(models.TextChoices):
@@ -310,6 +311,13 @@ class ApplicationConfiguration(AbstractSingletonModel):
         max_length=128,
     )
 
+    llm_embedding_endpoint = models.CharField(
+        verbose_name=_("Sets the LLM embedding endpoint, optional"),
+        blank=True,
+        null=True,
+        max_length=256,
+    )
+
     llm_backend = models.CharField(
         verbose_name=_("Sets the LLM backend"),
         blank=True,

src/paperless/serialisers.py

@@ -291,6 +291,8 @@ class ApplicationConfigurationSerializer(
 
         return value
 
+    validate_llm_embedding_endpoint = validate_llm_endpoint
+
     class Meta:
         model = ApplicationConfiguration
         fields = "__all__"

src/paperless/settings/__init__.py

@@ -650,6 +650,11 @@ logging.config.dictConfig(LOGGING)
 # https://docs.celeryq.dev/en/stable/userguide/configuration.html
 
 CELERY_BROKER_URL = _CELERY_REDIS_URL
+CELERY_RESULT_BACKEND = _CELERY_REDIS_URL
+CELERY_RESULT_SERIALIZER = "signed-pickle"
+# Results are only needed for chord synchronization
+# a short TTL avoids Redis memory accumulation.
+CELERY_RESULT_EXPIRES = 3600
 CELERY_TIMEZONE = TIME_ZONE
 
 CELERY_WORKER_HIJACK_ROOT_LOGGER = False
@@ -1173,8 +1178,9 @@ REMOTE_OCR_ENDPOINT = os.getenv("PAPERLESS_REMOTE_OCR_ENDPOINT")
 AI_ENABLED = get_bool_from_env("PAPERLESS_AI_ENABLED", "NO")
 LLM_EMBEDDING_BACKEND = os.getenv(
     "PAPERLESS_AI_LLM_EMBEDDING_BACKEND",
-)  # "huggingface" or "openai-like"
+)  # "huggingface", "openai-like", or "ollama"
 LLM_EMBEDDING_MODEL = os.getenv("PAPERLESS_AI_LLM_EMBEDDING_MODEL")
+LLM_EMBEDDING_ENDPOINT = os.getenv("PAPERLESS_AI_LLM_EMBEDDING_ENDPOINT")
 LLM_BACKEND = os.getenv("PAPERLESS_AI_LLM_BACKEND")  # "ollama" or "openai-like"
 LLM_MODEL = os.getenv("PAPERLESS_AI_LLM_MODEL")
 LLM_API_KEY = os.getenv("PAPERLESS_AI_LLM_API_KEY")

src/paperless/tests/test_checks.py

@@ -584,11 +584,11 @@ class TestV3MinimumUpgradeVersionCheck:
     ) -> None:
         """
         GIVEN:
-            - DB is on an old v2 version (pre-v2.20.10)
+            - DB is on an old v2 version (pre-v2.20.15)
         WHEN:
             - The v3 upgrade check runs
         THEN:
-            - The error hint explicitly references v2.20.10 so users know what to do
+            - The error hint explicitly references v2.20.15 so users know what to do
         """
         mocker.patch.dict(
             "paperless.checks.connections",
@@ -596,7 +596,7 @@ class TestV3MinimumUpgradeVersionCheck:
         )
         result = check_v3_minimum_upgrade_version(None)
         assert len(result) == 1
-        assert "v2.20.10" in result[0].hint
+        assert "v2.20.15" in result[0].hint
 
     def test_db_error_is_swallowed(self, mocker: MockerFixture) -> None:
         """

src/paperless/version.py

@@ -1,6 +1,6 @@
 from typing import Final
 
-__version__: Final[tuple[int, int, int]] = (2, 20, 15)
+__version__: Final[tuple[int, int, int]] = (3, 0, 0)
 # Version string like X.Y.Z
 __full_version_str__: Final[str] = ".".join(map(str, __version__))
 # Version string like X.Y

src/paperless_ai/chat.py

@@ -4,14 +4,14 @@ import sys
 
 from documents.models import Document
 from paperless_ai.client import AIClient
+from paperless_ai.indexing import get_rag_prompt_helper
 from paperless_ai.indexing import load_or_build_index
 
 logger = logging.getLogger("paperless_ai.chat")
 
-MAX_SINGLE_DOC_CONTEXT_CHARS = 15000
-SINGLE_DOC_SNIPPET_CHARS = 800
 CHAT_METADATA_DELIMITER = "\n\n__PAPERLESS_CHAT_METADATA__"
 MAX_CHAT_REFERENCES = 3
+CHAT_RETRIEVER_TOP_K = 5
 
 CHAT_PROMPT_TMPL = """Context information is below.
     ---------------------
@@ -89,66 +89,39 @@ def stream_chat_with_documents(query_str: str, documents: list[Document]):
     from llama_index.core import VectorStoreIndex
     from llama_index.core.prompts import PromptTemplate
     from llama_index.core.query_engine import RetrieverQueryEngine
+    from llama_index.core.response_synthesizers import get_response_synthesizer
 
     local_index = VectorStoreIndex(nodes=nodes)
     retriever = local_index.as_retriever(
-        similarity_top_k=3 if len(documents) == 1 else 5,
+        similarity_top_k=CHAT_RETRIEVER_TOP_K,
     )
 
-    if len(documents) == 1:
-        # Just one doc — provide full content
-        doc = documents[0]
-        references = [_build_document_reference(doc)]
-        # TODO: include document metadata in the context
-        content = doc.content or ""
-        context_body = content
+    top_nodes = retriever.retrieve(query_str)
+    if len(top_nodes) == 0:
+        logger.warning("Retriever returned no nodes for the given documents.")
+        yield "Sorry, I couldn't find any content to answer your question."
+        return
 
-        if len(content) > MAX_SINGLE_DOC_CONTEXT_CHARS:
-            logger.info(
-                "Truncating single-document context from %s to %s characters",
-                len(content),
-                MAX_SINGLE_DOC_CONTEXT_CHARS,
-            )
-            context_body = content[:MAX_SINGLE_DOC_CONTEXT_CHARS]
-
-            top_nodes = retriever.retrieve(query_str)
-            if len(top_nodes) > 0:
-                snippets = "\n\n".join(
-                    f"TITLE: {node.metadata.get('title')}\n{node.text[:SINGLE_DOC_SNIPPET_CHARS]}"
-                    for node in top_nodes
-                )
-                context_body = f"{context_body}\n\nTOP MATCHES:\n{snippets}"
-
-        context = f"TITLE: {doc.title or doc.filename}\n{context_body}"
-    else:
-        top_nodes = retriever.retrieve(query_str)
-
-        if len(top_nodes) == 0:
-            logger.warning("Retriever returned no nodes for the given documents.")
-            yield "Sorry, I couldn't find any content to answer your question."
-            return
-
-        references = _get_document_references(documents, top_nodes)
-        context = "\n\n".join(
-            f"TITLE: {node.metadata.get('title')}\n{node.text[:SINGLE_DOC_SNIPPET_CHARS]}"
-            for node in top_nodes
-        )
+    references = _get_document_references(documents, top_nodes)
 
     prompt_template = PromptTemplate(template=CHAT_PROMPT_TMPL)
-    prompt = prompt_template.partial_format(
-        context_str=context,
-        query_str=query_str,
-    ).format(llm=client.llm)
+    response_synthesizer = get_response_synthesizer(
+        llm=client.llm,
+        prompt_helper=get_rag_prompt_helper(),
+        text_qa_template=prompt_template,
+        streaming=True,
+    )
 
     query_engine = RetrieverQueryEngine.from_args(
         retriever=retriever,
         llm=client.llm,
+        response_synthesizer=response_synthesizer,
         streaming=True,
     )
 
-    logger.debug("Document chat prompt: %s", prompt)
+    logger.debug("Document chat query: %s", query_str)
 
-    response_stream = query_engine.query(prompt)
+    response_stream = query_engine.query(query_str)
 
     for chunk in response_stream.response_gen:
         yield chunk

src/paperless_ai/client.py

@@ -73,6 +73,7 @@ class AIClient:
             tools=[tool],
             user_msg=user_msg,
             chat_history=[],
+            allow_parallel_tool_calls=True,
         )
         tool_calls = self.llm.get_tool_calls_from_response(
             result,

src/paperless_ai/embedding.py

@@ -22,7 +22,7 @@ def get_embedding_model() -> "BaseEmbedding":
         case LLMEmbeddingBackend.OPENAI_LIKE:
             from llama_index.embeddings.openai_like import OpenAILikeEmbedding
 
-            endpoint = config.llm_endpoint or None
+            endpoint = config.llm_embedding_endpoint or config.llm_endpoint or None
             if endpoint:
                 validate_outbound_http_url(
                     endpoint,
@@ -39,6 +39,23 @@ def get_embedding_model() -> "BaseEmbedding":
             return HuggingFaceEmbedding(
                 model_name=config.llm_embedding_model
                 or "sentence-transformers/all-MiniLM-L6-v2",
+                cache_folder=str(settings.DATA_DIR / "hf_cache"),
+            )
+        case LLMEmbeddingBackend.OLLAMA:
+            from llama_index.embeddings.ollama import OllamaEmbedding
+
+            endpoint = (
+                config.llm_embedding_endpoint
+                or config.llm_endpoint
+                or "http://localhost:11434"
+            )
+            validate_outbound_http_url(
+                endpoint,
+                allow_internal=config.llm_allow_internal_endpoints,
+            )
+            return OllamaEmbedding(
+                model_name=config.llm_embedding_model or "embeddinggemma",
+                base_url=endpoint,
             )
         case _:
             raise ValueError(
@@ -52,11 +69,15 @@ def get_embedding_dim() -> int:
     from a dummy embedding and stores it for future use.
     """
     config = AIConfig()
-    model = config.llm_embedding_model or (
-        "text-embedding-3-small"
-        if config.llm_embedding_backend == LLMEmbeddingBackend.OPENAI_LIKE
-        else "sentence-transformers/all-MiniLM-L6-v2"
+    default_model = {
+        LLMEmbeddingBackend.OPENAI_LIKE: "text-embedding-3-small",
+        LLMEmbeddingBackend.HUGGINGFACE: "sentence-transformers/all-MiniLM-L6-v2",
+        LLMEmbeddingBackend.OLLAMA: "embeddinggemma",
+    }.get(
+        config.llm_embedding_backend,
+        "sentence-transformers/all-MiniLM-L6-v2",
     )
+    model = config.llm_embedding_model or default_model
 
     meta_path: Path = settings.LLM_INDEX_DIR / "meta.json"
     if meta_path.exists():

src/paperless_ai/indexing.py

@@ -22,6 +22,11 @@ if TYPE_CHECKING:
 
 logger = logging.getLogger("paperless_ai.indexing")
 
+RAG_CONTEXT_WINDOW = 8192
+RAG_NUM_OUTPUT = 512
+RAG_CHUNK_SIZE = 1024
+RAG_CHUNK_OVERLAP = 200
+
 
 def queue_llm_index_update_if_needed(*, rebuild: bool, reason: str) -> bool:
     from documents.tasks import llmindex_index
@@ -65,6 +70,7 @@ def get_or_create_storage_context(*, rebuild=False):
         from llama_index.core.storage.index_store import SimpleIndexStore
         from llama_index.vector_stores.faiss import FaissVectorStore
 
+        settings.LLM_INDEX_DIR.mkdir(parents=True, exist_ok=True)
         embedding_dim = get_embedding_dim()
         faiss_index = faiss.IndexFlatL2(embedding_dim)
         vector_store = FaissVectorStore(faiss_index=faiss_index)
@@ -111,7 +117,10 @@ def build_document_node(document: Document) -> list["BaseNode"]:
     from llama_index.core.node_parser import SimpleNodeParser
 
     doc = LlamaDocument(text=text, metadata=metadata)
-    parser = SimpleNodeParser()
+    parser = SimpleNodeParser(
+        chunk_size=RAG_CHUNK_SIZE,
+        chunk_overlap=get_rag_chunk_overlap(),
+    )
     return parser.get_nodes_from_documents([doc])
 
 
@@ -168,6 +177,21 @@ def vector_store_file_exists():
     return Path(settings.LLM_INDEX_DIR / "default__vector_store.json").exists()
 
 
+def get_rag_chunk_overlap() -> int:
+    return min(RAG_CHUNK_OVERLAP, RAG_CHUNK_SIZE - 1)
+
+
+def get_rag_prompt_helper():
+    from llama_index.core.indices.prompt_helper import PromptHelper
+
+    return PromptHelper(
+        context_window=RAG_CONTEXT_WINDOW,
+        num_output=RAG_NUM_OUTPUT,
+        chunk_overlap_ratio=0.1,
+        chunk_size_limit=RAG_CHUNK_SIZE,
+    )
+
+
 def update_llm_index(
     *,
     iter_wrapper: IterWrapper[Document] = identity,
@@ -277,17 +301,15 @@ def llm_index_remove_document(document: Document):
 
 
 def truncate_content(content: str) -> str:
-    from llama_index.core.indices.prompt_helper import PromptHelper
     from llama_index.core.prompts import PromptTemplate
     from llama_index.core.text_splitter import TokenTextSplitter
 
-    prompt_helper = PromptHelper(
-        context_window=8192,
-        num_output=512,
-        chunk_overlap_ratio=0.1,
-        chunk_size_limit=None,
+    prompt_helper = get_rag_prompt_helper()
+    splitter = TokenTextSplitter(
+        separator=" ",
+        chunk_size=RAG_CHUNK_SIZE,
+        chunk_overlap=get_rag_chunk_overlap(),
     )
-    splitter = TokenTextSplitter(separator=" ", chunk_size=512, chunk_overlap=50)
     content_chunks = splitter.split_text(content)
     truncated_chunks = prompt_helper.truncate(
         prompt=PromptTemplate(template="{content}"),

src/paperless_ai/tests/test_ai_indexing.py

@@ -58,6 +58,24 @@ def test_build_document_node(real_document) -> None:
     assert nodes[0].metadata["document_id"] == str(real_document.id)
 
 
+@pytest.mark.django_db
+def test_build_document_node_uses_rag_chunk_settings(real_document) -> None:
+    with patch("llama_index.core.node_parser.SimpleNodeParser") as mock_parser:
+        mock_parser.return_value.get_nodes_from_documents.return_value = []
+
+        indexing.build_document_node(real_document)
+
+        mock_parser.assert_called_once_with(chunk_size=1024, chunk_overlap=200)
+
+
+def test_get_rag_chunk_overlap_clamps_to_chunk_size() -> None:
+    with (
+        patch("paperless_ai.indexing.RAG_CHUNK_SIZE", 64),
+        patch("paperless_ai.indexing.RAG_CHUNK_OVERLAP", 128),
+    ):
+        assert indexing.get_rag_chunk_overlap() == 63
+
+
 @pytest.mark.django_db
 def test_update_llm_index(
     temp_llm_index_dir,

src/paperless_ai/tests/test_chat.py

@@ -57,7 +57,7 @@ def assert_chat_output(
     }
 
 
-def test_stream_chat_with_one_document_full_content(mock_document) -> None:
+def test_stream_chat_with_one_document_retrieval(mock_document) -> None:
     with (
         patch("paperless_ai.chat.AIClient") as mock_client_cls,
         patch("paperless_ai.chat.load_or_build_index") as mock_load_index,
@@ -85,6 +85,7 @@ def test_stream_chat_with_one_document_full_content(mock_document) -> None:
 
         output = list(stream_chat_with_documents("What is this?", [mock_document]))
 
+        mock_query_engine.query.assert_called_once_with("What is this?")
         assert_chat_output(
             output,
             expected_chunks=["chunk1", "chunk2"],
@@ -154,6 +155,7 @@ def test_stream_chat_with_multiple_documents_retrieval(patch_embed_nodes) -> Non
 
         output = list(stream_chat_with_documents("What's up?", [doc1, doc2]))
 
+        mock_query_engine.query.assert_called_once_with("What's up?")
         assert_chat_output(
             output,
             expected_chunks=["chunk1", "chunk2"],

src/paperless_ai/tests/test_embedding.py

@@ -3,6 +3,7 @@ from unittest.mock import MagicMock
 from unittest.mock import patch
 
 import pytest
+from django.conf import settings
 
 from documents.models import Document
 from paperless.models import LLMEmbeddingBackend
@@ -14,6 +15,7 @@ from paperless_ai.embedding import get_embedding_model
 @pytest.fixture
 def mock_ai_config():
     with patch("paperless_ai.embedding.AIConfig") as MockAIConfig:
+        MockAIConfig.return_value.llm_embedding_endpoint = None
         MockAIConfig.return_value.llm_allow_internal_endpoints = True
         yield MockAIConfig
 
@@ -71,6 +73,25 @@ def test_get_embedding_model_openai(mock_ai_config):
         assert model == MockOpenAIEmbedding.return_value
 
 
+def test_get_embedding_model_openai_prefers_embedding_endpoint(mock_ai_config):
+    mock_ai_config.return_value.llm_embedding_backend = LLMEmbeddingBackend.OPENAI_LIKE
+    mock_ai_config.return_value.llm_embedding_model = "text-embedding-3-small"
+    mock_ai_config.return_value.llm_api_key = "test_api_key"
+    mock_ai_config.return_value.llm_embedding_endpoint = "http://embedding-url"
+    mock_ai_config.return_value.llm_endpoint = "http://test-url"
+
+    with patch(
+        "llama_index.embeddings.openai_like.OpenAILikeEmbedding",
+    ) as MockOpenAIEmbedding:
+        model = get_embedding_model()
+        MockOpenAIEmbedding.assert_called_once_with(
+            model_name="text-embedding-3-small",
+            api_key="test_api_key",
+            api_base="http://embedding-url",
+        )
+        assert model == MockOpenAIEmbedding.return_value
+
+
 def test_get_embedding_model_openai_blocks_internal_endpoint_when_disallowed(
     mock_ai_config,
 ):
@@ -96,10 +117,56 @@ def test_get_embedding_model_huggingface(mock_ai_config):
         model = get_embedding_model()
         MockHuggingFaceEmbedding.assert_called_once_with(
             model_name="sentence-transformers/all-MiniLM-L6-v2",
+            cache_folder=str(settings.DATA_DIR / "hf_cache"),
         )
         assert model == MockHuggingFaceEmbedding.return_value
 
 
+def test_get_embedding_model_ollama(mock_ai_config):
+    mock_ai_config.return_value.llm_embedding_backend = LLMEmbeddingBackend.OLLAMA
+    mock_ai_config.return_value.llm_embedding_model = "embeddinggemma"
+    mock_ai_config.return_value.llm_endpoint = "http://test-url"
+
+    with patch(
+        "llama_index.embeddings.ollama.OllamaEmbedding",
+    ) as MockOllamaEmbedding:
+        model = get_embedding_model()
+        MockOllamaEmbedding.assert_called_once_with(
+            model_name="embeddinggemma",
+            base_url="http://test-url",
+        )
+        assert model == MockOllamaEmbedding.return_value
+
+
+def test_get_embedding_model_ollama_prefers_embedding_endpoint(mock_ai_config):
+    mock_ai_config.return_value.llm_embedding_backend = LLMEmbeddingBackend.OLLAMA
+    mock_ai_config.return_value.llm_embedding_model = "embeddinggemma"
+    mock_ai_config.return_value.llm_embedding_endpoint = "http://embedding-url"
+    mock_ai_config.return_value.llm_endpoint = "http://test-url"
+
+    with patch(
+        "llama_index.embeddings.ollama.OllamaEmbedding",
+    ) as MockOllamaEmbedding:
+        model = get_embedding_model()
+        MockOllamaEmbedding.assert_called_once_with(
+            model_name="embeddinggemma",
+            base_url="http://embedding-url",
+        )
+        assert model == MockOllamaEmbedding.return_value
+
+
+def test_get_embedding_model_ollama_blocks_internal_endpoint_when_disallowed(
+    mock_ai_config,
+):
+    mock_ai_config.return_value.llm_embedding_backend = LLMEmbeddingBackend.OLLAMA
+    mock_ai_config.return_value.llm_embedding_model = "embeddinggemma"
+    mock_ai_config.return_value.llm_endpoint = "http://127.0.0.1:11434"
+    mock_ai_config.return_value.llm_allow_internal_endpoints = False
+
+    with pytest.raises(ValueError, match="non-public address"):
+        get_embedding_model()
+
+
 def test_get_embedding_model_invalid_backend(mock_ai_config):
     mock_ai_config.return_value.llm_embedding_backend = "INVALID_BACKEND"
 

uv.lock

@@ -277,19 +277,18 @@ wheels = [
 
 [[package]]
 name = "banks"
-version = "2.4.2"
+version = "2.3.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "deprecated", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
-    { name = "filetype", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "griffe", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "jinja2", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "platformdirs", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "pydantic", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/bd/51/08fb68d23f4b0f6256fe85dc86e9576941550f890b079352fba719e07b39/banks-2.4.2.tar.gz", hash = "sha256:cda6013bd377ea7b701933578bfb9370fc21ad70bc13cedfc3f5cb2c034ca3dc", size = 188633, upload-time = "2026-04-27T12:15:22.021Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/ca/64/9a4e17dfe7dc172594ffb877a287859edb40d59e0564bc930941e6c5df9d/banks-2.3.0.tar.gz", hash = "sha256:1ecb439a0b340588fcf9a8072d806540aad03c4b874ab9aff59ac8bc08c112ff", size = 182736, upload-time = "2026-01-21T10:03:15.114Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/b6/8dc5477681b782e2f99de703e7a99828883364b9e03a60d3e2c47053d56a/banks-2.4.2-py3-none-any.whl", hash = "sha256:5fe407cc48c101f3e13d1cf732b83b8246003337612f13c0705d2e81f6faffb7", size = 35050, upload-time = "2026-04-27T12:15:20.785Z" },
+    { url = "https://files.pythonhosted.org/packages/27/d6/ccceb03dd5193d180e28411c9f880f2cc9a574251de94b9b8a21ebdf51ec/banks-2.3.0-py3-none-any.whl", hash = "sha256:ac6a5800d468f26a0d80e091c0c6971b69457d580ce34c0217ee2bf6c3f07271", size = 32748, upload-time = "2026-01-21T10:03:14.251Z" },
 ]
 
 [[package]]
@@ -384,7 +383,7 @@ wheels = [
 
 [[package]]
 name = "celery"
-version = "5.6.2"
+version = "5.6.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "billiard", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
@@ -397,9 +396,9 @@ dependencies = [
     { name = "tzlocal", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
     { name = "vine", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/8f/9d/3d13596519cfa7207a6f9834f4b082554845eb3cd2684b5f8535d50c7c44/celery-5.6.2.tar.gz", hash = "sha256:4a8921c3fcf2ad76317d3b29020772103581ed2454c4c042cc55dcc43585009b", size = 1718802, upload-time = "2026-01-04T12:35:58.012Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e8/b4/a1233943ab5c8ea05fb877a88a0a0622bf47444b99e4991a8045ac37ea1d/celery-5.6.3.tar.gz", hash = "sha256:177006bd2054b882e9f01be59abd8529e88879ef50d7918a7050c5a9f4e12912", size = 1742243, upload-time = "2026-03-26T12:14:51.76Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/dd/bd/9ecd619e456ae4ba73b6583cc313f26152afae13e9a82ac4fe7f8856bfd1/celery-5.6.2-py3-none-any.whl", hash = "sha256:3ffafacbe056951b629c7abcf9064c4a2366de0bdfc9fdba421b97ebb68619a5", size = 445502, upload-time = "2026-01-04T12:35:55.894Z" },
+    { url = "https://files.pythonhosted.org/packages/cf/c9/6eccdda96e098f7ae843162db2d3c149c6931a24fda69fe4ab84d0027eb5/celery-5.6.3-py3-none-any.whl", hash = "sha256:0808f42f80909c4d5833202360ffafb2a4f83f4d8e23e1285d926610e9a7afa6", size = 451235, upload-time = "2026-03-26T12:14:49.491Z" },
 ]
 
 [package.optional-dependencies]
@@ -724,54 +723,54 @@ toml = [
 
 [[package]]
 name = "cryptography"
-version = "46.0.7"
+version = "48.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "cffi", marker = "(platform_python_implementation != 'PyPy' and sys_platform == 'darwin') or (platform_python_implementation != 'PyPy' and sys_platform == 'linux')" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/47/93/ac8f3d5ff04d54bc814e961a43ae5b0b146154c89c61b47bb07557679b18/cryptography-46.0.7.tar.gz", hash = "sha256:e4cfd68c5f3e0bfdad0d38e023239b96a2fe84146481852dffbcca442c245aa5", size = 750652, upload-time = "2026-04-08T01:57:54.692Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/9f/a9/db8f313fdcd85d767d4973515e1db101f9c71f95fced83233de224673757/cryptography-48.0.0.tar.gz", hash = "sha256:5c3932f4436d1cccb036cb0eaef46e6e2db91035166f1ad6505c3c9d5a635920", size = 832984, upload-time = "2026-05-04T22:59:38.133Z" }
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