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5 changed files with 210 additions and 21 deletions
+69
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@@ -2,12 +2,15 @@ from __future__ import annotations
import logging
import pickle
import time
from binascii import hexlify
from collections import OrderedDict
from dataclasses import dataclass
from hashlib import sha256
from typing import TYPE_CHECKING
from typing import Any
from typing import Final
from uuid import uuid4
from django.conf import settings
from django.core.cache import cache
@@ -16,6 +19,7 @@ from django.core.cache import caches
from documents.models import Document
if TYPE_CHECKING:
from django.contrib.auth.models import User
from django.core.cache.backends.base import BaseCache
from documents.classifier import DocumentClassifier
@@ -52,6 +56,9 @@ CLASSIFIER_MODIFIED_KEY: Final[str] = "classifier_modified"
# [...]} per taxonomy field (#13676)
LLM_CACHE_CLASSIFIER_VERSION: Final[int] = 1001
# How often a request waiting on llm generation re-checks the cache
LLM_SUGGESTION_POLL_INTERVAL: Final[float] = 0.5
CACHE_1_MINUTE: Final[int] = 60
CACHE_5_MINUTES: Final[int] = 5 * CACHE_1_MINUTE
CACHE_50_MINUTES: Final[int] = 50 * CACHE_1_MINUTE
@@ -223,6 +230,68 @@ def get_llm_suggestion_cache(
return None
def retrieve_llm_suggestions(
document: Document,
user: User | None,
output_language: str | None,
*,
backend: str,
lock_timeout: int,
) -> dict:
"""Return cached LLM suggestions, generating them once across workers."""
# Lazy import to avoid pulling in the whole AI stuff
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.exceptions import LLMTimeoutError
lock_key = (
f"{get_suggestion_cache_key(document.pk)}_llm_lock_"
f"{sha256(backend.encode()).hexdigest()}"
)
waited = False
while True:
cached = get_llm_suggestion_cache(document.pk, backend=backend)
if cached is not None:
refresh_suggestions_cache(document.pk)
return cached.suggestions
lock_token = uuid4().hex
if cache.add(lock_key, lock_token, lock_timeout):
if waited:
# The generation we were waiting on has ended without caching
# anything so it either failed or outlived its lock. Give up
# rather than re-running it
cache.delete(lock_key)
raise LLMTimeoutError
try:
# The cache may have been populated while acquiring the lock.
cached = get_llm_suggestion_cache(document.pk, backend=backend)
if cached is not None:
refresh_suggestions_cache(document.pk)
return cached.suggestions
suggestions = get_ai_document_classification(
document,
user,
output_language,
)
set_llm_suggestions_cache(
document.pk,
suggestions,
backend=backend,
)
return suggestions
finally:
# Don't remove lock if this one expired while generation was still running
if cache.get(lock_key) == lock_token:
cache.delete(lock_key)
waited = True
# Another worker is generating suggestions, poll to avoid another LLM request
time.sleep(LLM_SUGGESTION_POLL_INTERVAL)
def set_llm_suggestions_cache(
document_id: int,
suggestions: dict,
+1 -1
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@@ -2486,7 +2486,7 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
response = self.client.get("/api/documents/34676/suggestions/")
self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND)
@mock.patch("documents.views.get_ai_document_classification")
@mock.patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(AI_ENABLED=True)
def test_suggestions_still_uses_classifier_when_ai_enabled(
self,
+123
View File
@@ -1,6 +1,13 @@
import pickle
from concurrent.futures import ThreadPoolExecutor
from threading import Event
from threading import Lock
import pytest
from documents.caching import StoredLRUCache
from documents.caching import retrieve_llm_suggestions
from paperless_ai.exceptions import LLMTimeoutError
def test_lru_cache_entries() -> None:
@@ -43,3 +50,119 @@ def test_stored_lru_cache_key_ttl(mocker) -> None:
assert key == "test_key"
assert timeout == 321
assert pickle.loads(data) == {"x": "X", "y": "Y"}
def test_llm_suggestions_are_generated_once_for_concurrent_requests(mocker) -> None:
generation_started = Event()
finish_generation = Event()
waiter_started = Event()
call_lock = Lock()
calls = 0
suggestions = {"title": "Generated once"}
document = mocker.Mock(pk=42)
user = mocker.Mock()
def generate(*args) -> dict:
nonlocal calls
with call_lock:
calls += 1
generation_started.set()
assert finish_generation.wait(timeout=2)
return suggestions
def wait_for_generation(_interval: float) -> None:
waiter_started.set()
assert finish_generation.wait(timeout=2)
mock_get_classification = mocker.patch(
"paperless_ai.ai_classifier.get_ai_document_classification",
side_effect=generate,
)
mocker.patch("documents.caching.time.sleep", side_effect=wait_for_generation)
with ThreadPoolExecutor(max_workers=2) as executor:
first = executor.submit(
retrieve_llm_suggestions,
document,
user,
None,
backend="ollama:model",
lock_timeout=10,
)
assert generation_started.wait(timeout=2)
second = executor.submit(
retrieve_llm_suggestions,
document,
user,
None,
backend="ollama:model",
lock_timeout=10,
)
assert waiter_started.wait(timeout=2)
finish_generation.set()
assert first.result(timeout=2) == suggestions
assert second.result(timeout=2) == suggestions
assert calls == 1
mock_get_classification.assert_called_once_with(document, user, None)
def test_llm_suggestions_waiter_does_not_rerun_a_failed_generation(mocker) -> None:
"""
A request queued behind a generation that fails should give up, not take
its turn at re-running a query that just failed.
"""
generation_started = Event()
fail_generation = Event()
waiter_started = Event()
call_lock = Lock()
calls = 0
document = mocker.Mock(pk=43)
user = mocker.Mock()
def generate(*args) -> dict:
nonlocal calls
with call_lock:
calls += 1
generation_started.set()
assert fail_generation.wait(timeout=2)
raise ValueError("Unknown model")
def wait_for_generation(_interval: float) -> None:
waiter_started.set()
assert fail_generation.wait(timeout=2)
mocker.patch(
"paperless_ai.ai_classifier.get_ai_document_classification",
side_effect=generate,
)
mocker.patch("documents.caching.time.sleep", side_effect=wait_for_generation)
with ThreadPoolExecutor(max_workers=2) as executor:
first = executor.submit(
retrieve_llm_suggestions,
document,
user,
None,
backend="ollama:model",
lock_timeout=10,
)
assert generation_started.wait(timeout=2)
second = executor.submit(
retrieve_llm_suggestions,
document,
user,
None,
backend="ollama:model",
lock_timeout=10,
)
assert waiter_started.wait(timeout=2)
fail_generation.set()
with pytest.raises(ValueError, match="Unknown model"):
first.result(timeout=2)
with pytest.raises(LLMTimeoutError):
second.result(timeout=2)
assert calls == 1
+9 -9
View File
@@ -441,7 +441,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
self.assertEqual(response.json()["tags"], [])
self.assertEqual(response.json()["suggested_tags"], [])
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -491,7 +491,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
None,
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -529,7 +529,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
"KI Title",
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -568,7 +568,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
"Titre IA",
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -604,7 +604,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
),
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="openai-like",
@@ -633,7 +633,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="openai-like",
@@ -660,7 +660,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -698,7 +698,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
self.assertEqual(response.json()["tags"], [self.tag1.pk])
self.assertEqual(response.json()["suggested_tags"], ["Follow-up"])
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
@@ -737,7 +737,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
self.assertEqual(response.json()["tags"], [self.tag1.pk])
self.assertEqual(response.json()["suggested_tags"], [])
@patch("documents.views.get_ai_document_classification")
@patch("paperless_ai.ai_classifier.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="mock_backend",
+8 -11
View File
@@ -115,7 +115,7 @@ from documents.caching import get_metadata_cache
from documents.caching import get_suggestion_cache
from documents.caching import refresh_metadata_cache
from documents.caching import refresh_suggestions_cache
from documents.caching import set_llm_suggestions_cache
from documents.caching import retrieve_llm_suggestions
from documents.caching import set_metadata_cache
from documents.caching import set_suggestions_cache
from documents.classifier import load_classifier
@@ -246,7 +246,6 @@ from paperless.parsers.remote import RemoteEngineConfig
from paperless.serialisers import GroupSerializer
from paperless.serialisers import UserSerializer
from paperless.views import StandardPagination
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.ai_classifier import get_llm_output_language
from paperless_ai.chat import stream_chat_with_documents
from paperless_ai.exceptions import LLMTimeoutError
@@ -1560,10 +1559,13 @@ class DocumentViewSet(
llm_suggestions = cached_llm_suggestions.suggestions
else:
try:
llm_suggestions = get_ai_document_classification(
doc,
request.user,
output_language,
llm_suggestions = retrieve_llm_suggestions(
document=doc,
user=request.user,
output_language=output_language,
backend=llm_cache_backend,
# Classification, localization + 30s
lock_timeout=(2 * ai_config.llm_request_timeout) + 30,
)
except ValueError as exc:
logger.exception(
@@ -1588,11 +1590,6 @@ class DocumentViewSet(
{"ai": [_("AI backend request timed out.")]},
status=status.HTTP_503_SERVICE_UNAVAILABLE,
)
set_llm_suggestions_cache(
doc.pk,
llm_suggestions,
backend=llm_cache_backend,
)
tags_choice: TaxonomyChoiceDict = llm_suggestions["tags"]
correspondents_choice: TaxonomyChoiceDict = llm_suggestions["correspondents"]