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test: remove cognify pipeline tests from translation integration tests

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Keep only standalone translation module tests (translate_text and
language detection) that don't depend on the cognify pipeline.
This commit is contained in:
andikarachman 2026-01-13 19:10:52 +07:00
parent d2f98fe880
commit eecebb9e2d
1 changed files with 1 additions and 179 deletions
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180
cognee/tests/tasks/translation/integration_test.py
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@ -1,14 +1,13 @@
"""
Integration tests for multilingual content translation feature.
Tests the full cognify pipeline with translation enabled.
Tests the translation module standalone functionality.
"""
import os
import pytest
from cognee import add, cognify, prune, search, SearchType
from cognee.tasks.translation import translate_text
from cognee.tasks.translation.detect_language import detect_language_async
@ -18,183 +17,6 @@ def has_llm_api_key():
return bool(os.environ.get("LLM_API_KEY"))
async def reset_engines():
"""Reset cached engines to avoid event loop issues between tests."""
from cognee.infrastructure.databases.graph.get_graph_engine import create_graph_engine
from cognee.infrastructure.databases.relational.create_relational_engine import (
create_relational_engine,
)
from cognee.infrastructure.databases.vector.create_vector_engine import create_vector_engine
create_graph_engine.cache_clear()
create_vector_engine.cache_clear()
create_relational_engine.cache_clear()
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_quick_translation():
"""Quick smoke test for translation feature"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
spanish_text = "La inteligencia artificial está transformando el mundo de la tecnología."
await add(spanish_text, dataset_name="spanish_test")
result = await cognify(
datasets=["spanish_test"],
auto_translate=True,
target_language="en",
translation_provider="llm",
)
assert result is not None
assert len(result) > 0
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_translation_basic():
"""Test basic translation functionality with English text"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
english_text = "Hello, this is a test document about artificial intelligence."
await add(english_text, dataset_name="test_english")
result = await cognify(
datasets=["test_english"],
auto_translate=True,
target_language="en",
translation_provider="llm",
)
assert result is not None
search_results = await search(
query_text="What is this document about?",
query_type=SearchType.SUMMARIES,
)
assert search_results is not None
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_translation_spanish():
"""Test translation with Spanish text"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
spanish_text = """
La inteligencia artificial es una rama de la informática que se centra en
crear sistemas capaces de realizar tareas que normalmente requieren inteligencia humana.
Estos sistemas pueden aprender, razonar y resolver problemas complejos.
"""
await add(spanish_text, dataset_name="test_spanish")
result = await cognify(
datasets=["test_spanish"],
auto_translate=True,
target_language="en",
translation_provider="llm",
)
assert result is not None
search_results = await search(
query_text="What is artificial intelligence?",
query_type=SearchType.SUMMARIES,
)
assert search_results is not None
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_translation_french():
"""Test translation with French text"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
french_text = """
L'apprentissage automatique est une méthode d'analyse de données qui
automatise la construction de modèles analytiques. C'est une branche
de l'intelligence artificielle basée sur l'idée que les systèmes peuvent
apprendre à partir de données, identifier des modèles et prendre des décisions.
"""
await add(french_text, dataset_name="test_french")
result = await cognify(
datasets=["test_french"],
auto_translate=True,
target_language="en",
)
assert result is not None
search_results = await search(
query_text="What is machine learning?",
query_type=SearchType.SUMMARIES,
)
assert search_results is not None
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_translation_disabled():
"""Test that cognify works without translation"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
text = "This is a baseline test without translation enabled."
await add(text, dataset_name="test_baseline")
result = await cognify(
datasets=["test_baseline"],
auto_translate=False,
)
assert result is not None
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_translation_mixed_languages():
"""Test with multiple documents in different languages"""
await reset_engines()
await prune.prune_data()
await prune.prune_system(metadata=True)
texts = [
"Artificial intelligence is transforming the world.",
"La tecnología está cambiando nuestras vidas.",
"Les ordinateurs deviennent de plus en plus puissants.",
]
for text in texts:
await add(text, dataset_name="test_mixed")
result = await cognify(
datasets=["test_mixed"],
auto_translate=True,
target_language="en",
)
assert result is not None
search_results = await search(
query_text="What topics are discussed?",
query_type=SearchType.SUMMARIES,
)
assert search_results is not None
@pytest.mark.asyncio
@pytest.mark.skipif(not has_llm_api_key(), reason="No LLM API key available")
async def test_direct_translation_function():