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no-multimedia-processing

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chigwell / concept-extractor

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A new package is designed to process complex conceptual prompts like "Dark Enlightenment" by leveraging language models with structured pattern matching. Users provide a descriptive text input related

theme-extraction llm-based-summarization concise-summary-generation structured-pattern-matching key-element-extraction conceptual-prompt-processing text-only-input-handling highly-reliable-output repeatable-summarization philosophical-analysis educational-insight analytical-contexts no-multimedia-processing structured-response-format pattern-matched-tokenization semantic-theme-categorization contextual-viewpoint-extraction
  • Updated Dec 21, 2025
  • Python

chigwell / phenomenon-interpreter

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phenomenon-interpreter analyzes textual descriptions of natural events to generate structured summaries or classifications automatically

classification automated-analysis categorization natural-phenomena domain-specific-insights structured-summary textual-input text-interpretation no-multimedia-processing impact-identification event-description free-form-descriptions scientific-phenomena text-based-processing
  • Updated Dec 21, 2025
  • Python

Joharskie / phenomenon-interpreter

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🌍 Interpret user-submitted text about natural phenomena, extracting insights and classifying events with ease using Python's powerful tools.

classification automated-analysis categorization natural-phenomena domain-specific-insights structured-summary textual-input text-interpretation no-multimedia-processing impact-identification event-description free-form-descriptions scientific-phenomena text-based-processing
  • Updated Jan 10, 2026
  • Python

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