mirror of
https://github.com/paperless-ngx/paperless-ngx.git
synced 2026-08-27 05:03:20 +00:00
Compare commits
4
Commits
| Author | SHA1 | Date | |
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f2250ef96d | ||
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50043ddb66 | ||
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15a5618a6e | ||
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34a01a5bd6 |
@@ -2,12 +2,15 @@ from __future__ import annotations
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import logging
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import pickle
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import time
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from binascii import hexlify
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from collections import OrderedDict
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from dataclasses import dataclass
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from hashlib import sha256
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from typing import TYPE_CHECKING
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from typing import Any
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from typing import Final
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from uuid import uuid4
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from django.conf import settings
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from django.core.cache import cache
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@@ -16,6 +19,7 @@ from django.core.cache import caches
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from documents.models import Document
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if TYPE_CHECKING:
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from django.contrib.auth.models import User
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from django.core.cache.backends.base import BaseCache
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from documents.classifier import DocumentClassifier
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@@ -52,6 +56,9 @@ CLASSIFIER_MODIFIED_KEY: Final[str] = "classifier_modified"
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# [...]} per taxonomy field (#13676)
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LLM_CACHE_CLASSIFIER_VERSION: Final[int] = 1001
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# How often a request waiting on llm generation re-checks the cache
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LLM_SUGGESTION_POLL_INTERVAL: Final[float] = 0.5
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CACHE_1_MINUTE: Final[int] = 60
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CACHE_5_MINUTES: Final[int] = 5 * CACHE_1_MINUTE
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CACHE_50_MINUTES: Final[int] = 50 * CACHE_1_MINUTE
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@@ -223,6 +230,68 @@ def get_llm_suggestion_cache(
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return None
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def retrieve_llm_suggestions(
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document: Document,
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user: User | None,
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output_language: str | None,
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*,
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backend: str,
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lock_timeout: int,
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) -> dict:
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"""Return cached LLM suggestions, generating them once across workers."""
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# Lazy import to avoid pulling in the whole AI stuff
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from paperless_ai.ai_classifier import get_ai_document_classification
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from paperless_ai.exceptions import LLMTimeoutError
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lock_key = (
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f"{get_suggestion_cache_key(document.pk)}_llm_lock_"
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f"{sha256(backend.encode()).hexdigest()}"
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)
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waited = False
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while True:
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cached = get_llm_suggestion_cache(document.pk, backend=backend)
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if cached is not None:
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refresh_suggestions_cache(document.pk)
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return cached.suggestions
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lock_token = uuid4().hex
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if cache.add(lock_key, lock_token, lock_timeout):
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if waited:
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# The generation we were waiting on has ended without caching
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# anything so it either failed or outlived its lock. Give up
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# rather than re-running it
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cache.delete(lock_key)
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raise LLMTimeoutError
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try:
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# The cache may have been populated while acquiring the lock.
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cached = get_llm_suggestion_cache(document.pk, backend=backend)
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if cached is not None:
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refresh_suggestions_cache(document.pk)
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return cached.suggestions
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suggestions = get_ai_document_classification(
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document,
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user,
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output_language,
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)
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set_llm_suggestions_cache(
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document.pk,
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suggestions,
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backend=backend,
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)
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return suggestions
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finally:
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# Don't remove lock if this one expired while generation was still running
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if cache.get(lock_key) == lock_token:
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cache.delete(lock_key)
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waited = True
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# Another worker is generating suggestions, poll to avoid another LLM request
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time.sleep(LLM_SUGGESTION_POLL_INTERVAL)
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def set_llm_suggestions_cache(
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document_id: int,
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suggestions: dict,
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@@ -2486,7 +2486,7 @@ class TestDocumentApi(DirectoriesMixin, ConsumeTaskMixin, APITestCase):
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response = self.client.get("/api/documents/34676/suggestions/")
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self.assertEqual(response.status_code, status.HTTP_404_NOT_FOUND)
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@mock.patch("documents.views.get_ai_document_classification")
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@mock.patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(AI_ENABLED=True)
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def test_suggestions_still_uses_classifier_when_ai_enabled(
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self,
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@@ -1,6 +1,13 @@
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import pickle
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from concurrent.futures import ThreadPoolExecutor
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from threading import Event
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from threading import Lock
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import pytest
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from documents.caching import StoredLRUCache
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from documents.caching import retrieve_llm_suggestions
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from paperless_ai.exceptions import LLMTimeoutError
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def test_lru_cache_entries() -> None:
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@@ -43,3 +50,119 @@ def test_stored_lru_cache_key_ttl(mocker) -> None:
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assert key == "test_key"
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assert timeout == 321
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assert pickle.loads(data) == {"x": "X", "y": "Y"}
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def test_llm_suggestions_are_generated_once_for_concurrent_requests(mocker) -> None:
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generation_started = Event()
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finish_generation = Event()
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waiter_started = Event()
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call_lock = Lock()
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calls = 0
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suggestions = {"title": "Generated once"}
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document = mocker.Mock(pk=42)
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user = mocker.Mock()
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def generate(*args) -> dict:
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nonlocal calls
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with call_lock:
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calls += 1
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generation_started.set()
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assert finish_generation.wait(timeout=2)
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return suggestions
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def wait_for_generation(_interval: float) -> None:
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waiter_started.set()
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assert finish_generation.wait(timeout=2)
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mock_get_classification = mocker.patch(
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"paperless_ai.ai_classifier.get_ai_document_classification",
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side_effect=generate,
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)
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mocker.patch("documents.caching.time.sleep", side_effect=wait_for_generation)
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with ThreadPoolExecutor(max_workers=2) as executor:
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first = executor.submit(
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retrieve_llm_suggestions,
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document,
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user,
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None,
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backend="ollama:model",
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lock_timeout=10,
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)
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assert generation_started.wait(timeout=2)
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second = executor.submit(
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retrieve_llm_suggestions,
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document,
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user,
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None,
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backend="ollama:model",
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lock_timeout=10,
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)
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assert waiter_started.wait(timeout=2)
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finish_generation.set()
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assert first.result(timeout=2) == suggestions
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assert second.result(timeout=2) == suggestions
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assert calls == 1
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mock_get_classification.assert_called_once_with(document, user, None)
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def test_llm_suggestions_waiter_does_not_rerun_a_failed_generation(mocker) -> None:
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"""
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A request queued behind a generation that fails should give up, not take
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its turn at re-running a query that just failed.
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"""
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generation_started = Event()
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fail_generation = Event()
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waiter_started = Event()
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call_lock = Lock()
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calls = 0
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document = mocker.Mock(pk=43)
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user = mocker.Mock()
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def generate(*args) -> dict:
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nonlocal calls
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with call_lock:
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calls += 1
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generation_started.set()
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assert fail_generation.wait(timeout=2)
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raise ValueError("Unknown model")
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def wait_for_generation(_interval: float) -> None:
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waiter_started.set()
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assert fail_generation.wait(timeout=2)
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mocker.patch(
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"paperless_ai.ai_classifier.get_ai_document_classification",
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side_effect=generate,
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)
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mocker.patch("documents.caching.time.sleep", side_effect=wait_for_generation)
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with ThreadPoolExecutor(max_workers=2) as executor:
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first = executor.submit(
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retrieve_llm_suggestions,
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document,
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user,
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None,
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backend="ollama:model",
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lock_timeout=10,
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)
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assert generation_started.wait(timeout=2)
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second = executor.submit(
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retrieve_llm_suggestions,
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document,
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user,
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None,
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backend="ollama:model",
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lock_timeout=10,
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)
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assert waiter_started.wait(timeout=2)
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fail_generation.set()
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with pytest.raises(ValueError, match="Unknown model"):
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first.result(timeout=2)
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with pytest.raises(LLMTimeoutError):
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second.result(timeout=2)
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assert calls == 1
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@@ -441,7 +441,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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self.assertEqual(response.json()["tags"], [])
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self.assertEqual(response.json()["suggested_tags"], [])
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -491,7 +491,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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None,
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -529,7 +529,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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"KI Title",
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -568,7 +568,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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"Titre IA",
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -604,7 +604,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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),
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="openai-like",
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@@ -633,7 +633,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="openai-like",
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@@ -660,7 +660,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
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)
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -698,7 +698,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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self.assertEqual(response.json()["tags"], [self.tag1.pk])
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self.assertEqual(response.json()["suggested_tags"], ["Follow-up"])
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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@@ -737,7 +737,7 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
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self.assertEqual(response.json()["tags"], [self.tag1.pk])
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self.assertEqual(response.json()["suggested_tags"], [])
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@patch("documents.views.get_ai_document_classification")
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@patch("paperless_ai.ai_classifier.get_ai_document_classification")
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@override_settings(
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AI_ENABLED=True,
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LLM_BACKEND="mock_backend",
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+8
-11
@@ -115,7 +115,7 @@ from documents.caching import get_metadata_cache
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from documents.caching import get_suggestion_cache
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from documents.caching import refresh_metadata_cache
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from documents.caching import refresh_suggestions_cache
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from documents.caching import set_llm_suggestions_cache
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from documents.caching import retrieve_llm_suggestions
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from documents.caching import set_metadata_cache
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from documents.caching import set_suggestions_cache
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from documents.classifier import load_classifier
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@@ -246,7 +246,6 @@ from paperless.parsers.remote import RemoteEngineConfig
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from paperless.serialisers import GroupSerializer
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from paperless.serialisers import UserSerializer
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from paperless.views import StandardPagination
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from paperless_ai.ai_classifier import get_ai_document_classification
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from paperless_ai.ai_classifier import get_llm_output_language
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from paperless_ai.chat import stream_chat_with_documents
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from paperless_ai.exceptions import LLMTimeoutError
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@@ -1560,10 +1559,13 @@ class DocumentViewSet(
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llm_suggestions = cached_llm_suggestions.suggestions
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else:
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try:
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llm_suggestions = get_ai_document_classification(
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doc,
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request.user,
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output_language,
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llm_suggestions = retrieve_llm_suggestions(
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document=doc,
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user=request.user,
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output_language=output_language,
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backend=llm_cache_backend,
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# Classification, localization + 30s
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lock_timeout=(2 * ai_config.llm_request_timeout) + 30,
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)
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except ValueError as exc:
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logger.exception(
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@@ -1588,11 +1590,6 @@ class DocumentViewSet(
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{"ai": [_("AI backend request timed out.")]},
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status=status.HTTP_503_SERVICE_UNAVAILABLE,
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)
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set_llm_suggestions_cache(
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doc.pk,
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llm_suggestions,
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backend=llm_cache_backend,
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)
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tags_choice: TaxonomyChoiceDict = llm_suggestions["tags"]
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correspondents_choice: TaxonomyChoiceDict = llm_suggestions["correspondents"]
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Reference in New Issue
Block a user