9f6b2dca51
Docstrings generation was requested by @subhash-0000. * https://github.com/topoteretes/cognee/pull/1353#issuecomment-3287760071 The following files were modified: * `cognee/api/v1/cognify/cognify.py` * `cognee/tasks/translation/test_translation.py` * `cognee/tasks/translation/translate_content.py` * `examples/python/translation_example.py`
86 lines
3.6 KiB
Python
86 lines
3.6 KiB
Python
import asyncio
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import os
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import cognee
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from cognee.api.v1.search import SearchType
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from cognee.api.v1.cognify.cognify import get_default_tasks_with_translation
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from cognee.modules.pipelines.operations.pipeline import run_pipeline
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# Prerequisites:
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# 1. Set up your environment with API keys for your chosen translation provider.
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# - For OpenAI: OPENAI_API_KEY
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# - For Azure: AZURE_TRANSLATOR_KEY, AZURE_TRANSLATOR_ENDPOINT, AZURE_TRANSLATOR_REGION
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# 2. Specify the translation provider via an environment variable (optional, defaults to "noop"):
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# COGNEE_TRANSLATION_PROVIDER="openai" # Or "google", "azure", "langdetect"
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# 3. Install any required libraries for your provider:
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# - pip install langdetect googletrans==4.0.0rc1 azure-ai-translation-text
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async def main():
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"""
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Demonstrates an end-to-end translation-enabled Cognify workflow using the Cognee SDK.
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Performs three main steps:
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1. Resets the demo workspace by pruning stored data and system metadata.
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2. Seeds three multilingual documents, builds translation-enabled Cognify tasks using the
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provider specified by the COGNEE_TRANSLATION_PROVIDER environment variable (defaults to "noop"),
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and executes the pipeline to translate and process the documents.
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- If the selected provider is missing or invalid, the function prints the error and returns early.
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3. Issues an English search query (using SearchType.INSIGHTS) against the processed index and
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prints any returned result texts.
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Side effects:
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- Mutates persistent Cognee state (prune, add, cognify pipeline execution).
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- Prints status and result messages to stdout.
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Notes:
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- No return value.
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- Exceptions ValueError and ImportError are caught and handled by printing an error and exiting the function.
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"""
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# 1. Set up cognee and add multilingual content
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print("Setting up demo environment...")
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await cognee.prune.prune_data()
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await cognee.prune.prune_system(metadata=True)
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multilingual_texts = [
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"El procesamiento de lenguaje natural (PLN) es un subcampo de la IA.",
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"Le traitement automatique du langage naturel (TALN) est un sous-domaine de l'IA.",
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"Natural language processing (NLP) is a subfield of AI.",
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]
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print("Adding multilingual texts...")
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for text in multilingual_texts:
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await cognee.add(text)
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print("Texts added successfully.\n")
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# 2. Run the cognify pipeline with translation enabled
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provider = os.getenv('COGNEE_TRANSLATION_PROVIDER', 'noop').lower()
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print(f"Running cognify with translation provider: {provider}")
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try:
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# Build translation-enabled tasks and execute the pipeline
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translation_enabled_tasks = get_default_tasks_with_translation(
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translation_provider=provider
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)
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async for _ in run_pipeline(tasks=translation_enabled_tasks):
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pass
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print("Cognify pipeline with translation completed successfully.")
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except (ValueError, ImportError) as e:
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print(f"Error during cognify: {e}")
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print("Please ensure the selected provider is installed and configured correctly.")
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return
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# 3. Search for content in English
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query_text = "Tell me about NLP"
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print(f"\nSearching for: '{query_text}'")
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# The search should now return results from all documents, as they have been translated.
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search_results = await cognee.search(query_text, query_type=SearchType.INSIGHTS)
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print("\nSearch Results:")
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if search_results:
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for result in search_results:
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print(f"- {result.text}")
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else:
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print("No results found.")
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if __name__ == "__main__":
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asyncio.run(main())
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