from typing import List, Dict, Any def summarize_text(text: str, max_length: int = 200) -> str: """ Summarizes a given text, ensuring the summary does not exceed max_length. """ if not text: return "" sentences = text.split(". ") summary = "" for sentence in sentences: if len(summary) + len(sentence) + 1 <= max_length: summary += sentence + ". " else: break return summary.strip() def extract_related_concepts(text: str) -> List[str]: """ Extracts a list of related concepts from the text, prioritizing those relevant to autaxys. """ relevant_concepts = [] if "self-organization" in text.lower() or "self-generating" in text.lower(): relevant_concepts.append("Self-Organization") if "pattern" in text.lower() or "structure" in text.lower(): relevant_concepts.append("Pattern Formation") if "emergence" in text.lower() or "emergent" in text.lower(): relevant_concepts.append("Emergence") if "dynamics" in text.lower() or "dynamic" in text.lower(): relevant_concepts.append("Dynamics") if "symmetry" in text.lower(): relevant_concepts.append("Symmetry (and Symmetry Breaking)") if "relation" in text.lower() or "relational" in text.lower(): relevant_concepts.append("Relationality") if "coherence" in text.lower(): relevant_concepts.append("Coherence") if "stability" in text.lower(): relevant_concepts.append("Stability") if "process" in text.lower() or "processual" in text.lower(): relevant_concepts.append("Process Philosophy") if "information" in text.lower(): relevant_concepts.append("Information") return relevant_concepts def create_json_summary(text: str) -> Dict[str, Any]: """ Creates a JSON summary of the text, including a concise summary and a list of related concepts. """ summary = summarize_text(text) related_concepts = extract_related_concepts(text) return {"summary": summary, "related_concepts": related_concepts} # Provide the text content text_content = """ The key takeaway is the critical need for tight coupling between conceptual development, operational definition, choice of appropriate formalism, and rigorous validation (computational and analytical) at every stage, guided by a strict methodology emphasizing falsification and adaptation. The most significant positive outcome was the standalone Emergent Quantization from Resolution (EQR) v1.0 framework. The IO/EQR project repeatedly failed to define and validate a specific substrate model (Fields, Graphs, Networks, Iteration Dynamics). Generating the specific complexity, stability, and diversity of observed physics (Standard Model, etc.) from simple rules proved extremely difficult. Axioms are Insufficient: Foundational logical axioms, while necessary for consistency, are insufficient on their own to guarantee a physically realistic theory. The specific content of the rules and the nature of the states are critical. The Formalism Gap is Real and Persistent: The gap between intuitive concepts and a working mathematical/computational formalism is often the largest hurdle. """ # Generate the JSON summary json_summary = create_json_summary(text_content) print(json_summary)