analyze.py

Pfad: /var/www/scripts/pipeline/analyze.py
Namespace: pipeline
Zeilen: 57 | Größe: 1,614 Bytes
Geändert: 2025-12-25 18:29:01 | Gescannt: 2025-12-31 10:22:15

Code Hygiene Score: 75

Dependencies: 0 (25%)
LOC: 100 (20%)
Methods: 100 (20%)
Secrets: 100 (15%)
Classes: 100 (10%)
Magic Numbers: 100 (10%)

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Dependencies 15

use analyzers.analyze_chunk_semantics
use analyzers.analyze_chunk_statements
use analyzers.analyze_chunks_semantics
use analyzers.analyze_document
use analyzers.analyze_document_statements
use analyzers.classify_taxonomy
use analyzers.extract_entities_anthropic
use analyzers.extract_entities_ollama
use analyzers.extract_relations
use analyzers.extract_statements
use analyzers.find_entity_by_name
use analyzers.get_anthropic_client
use analyzers.link_chunk_entities
use analyzers.store_entities
use analyzers.store_statements

Code

"""
Semantic analysis for KI-System Pipeline.
Entity extraction, taxonomy classification, ontology mapping.

BACKWARD COMPATIBILITY WRAPPER - All logic moved to analyzers/ module.
"""

# Re-export all functions from analyzers module for backward compatibility
from analyzers import (
    analyze_chunk_semantics,
    analyze_chunk_statements,
    analyze_chunks_semantics,
    analyze_document,
    analyze_document_statements,
    classify_taxonomy,
    extract_entities_anthropic,
    extract_entities_ollama,
    extract_relations,
    extract_statements,
    find_entity_by_name,
    get_anthropic_client,
    link_chunk_entities,
    store_entities,
    store_statements,
)

__all__ = [
    "get_anthropic_client",
    "extract_entities_ollama",
    "extract_entities_anthropic",
    "store_entities",
    "find_entity_by_name",
    "extract_relations",
    "classify_taxonomy",
    "analyze_chunk_semantics",
    "analyze_chunks_semantics",
    "extract_statements",
    "store_statements",
    "analyze_chunk_statements",
    "analyze_document_statements",
    "analyze_document",
    "link_chunk_entities",
]

if __name__ == "__main__":
    test_text = """
    Carl Rogers entwickelte die klientenzentrierte Gesprächstherapie.
    Diese Methode basiert auf Empathie, Kongruenz und bedingungsloser Wertschätzung.
    Sie wird heute weltweit in der Psychotherapie eingesetzt.
    """

    print("Testing entity extraction with Ollama...")
    entities = extract_entities_ollama(test_text)
    print(f"Found {len(entities)} entities:")
    for e in entities:
        print(f"  - {e['name']} ({e['type']})")

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