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| """ | |
| DreamReweaver - Creative Thought Synthesis Module | |
| Revives dormant cocoons as creative "dreams" or planning prompts | |
| """ | |
| import os | |
| import json | |
| import random | |
| from typing import List, Dict | |
| from pathlib import Path | |
| class DreamReweaver: | |
| """ | |
| Reweaves cocooned thoughts into dream-like synthetic narratives or planning prompts. | |
| Fuels innovation by: | |
| - Retrieving dormant thought cocoons | |
| - Recombining them into creative sequences | |
| - Generating new perspectives from old ideas | |
| """ | |
| def __init__(self, cocoon_dir: str = "cocoons"): | |
| from .cognition_cocooner import CognitionCocooner | |
| self.cocooner = CognitionCocooner(storage_path=cocoon_dir) | |
| self.dream_log = [] | |
| self.cocoon_dir = Path(cocoon_dir) | |
| def generate_dream_sequence(self, limit: int = 5) -> List[str]: | |
| """ | |
| Generate a sequence of dream-like thought combinations | |
| Args: | |
| limit: Maximum number of cocoons to include | |
| Returns: | |
| List of dream sequences (strings) | |
| """ | |
| dream_sequence = [] | |
| cocoons = self._load_cocoons() | |
| if not cocoons: | |
| return ["[No cocoons available for dream generation]"] | |
| selected = random.sample(cocoons, min(limit, len(cocoons))) | |
| for cocoon in selected: | |
| wrapped = cocoon.get("wrapped") | |
| sequence = self._interpret_cocoon(wrapped, cocoon.get("type")) | |
| self.dream_log.append(sequence) | |
| dream_sequence.append(sequence) | |
| return dream_sequence | |
| def record_dream(self, question: str, response: str) -> None: | |
| """ | |
| Record a Q&A exchange as a dream entry | |
| Args: | |
| question: User question | |
| response: AI response | |
| """ | |
| dream_entry = { | |
| "question": question, | |
| "response": response, | |
| "timestamp": str(os.times()) | |
| } | |
| self.dream_log.append(f"[Dream] Q: {question[:50]}... A: {response[:100]}...") | |
| def get_dream_log(self, recent: int = 10) -> List[str]: | |
| """ | |
| Get recent dream log entries | |
| Args: | |
| recent: Number of recent entries | |
| Returns: | |
| Recent dream log entries | |
| """ | |
| return self.dream_log[-recent:] | |
| def synthesize_creative_prompt(self, theme: str = "innovation") -> str: | |
| """ | |
| Synthesize a creative prompt from random cocoons | |
| Args: | |
| theme: Creative theme | |
| Returns: | |
| Creative prompt string | |
| """ | |
| dreams = self.generate_dream_sequence(limit=3) | |
| if not dreams: | |
| return f"[Creative Prompt: {theme}] Explore new possibilities." | |
| synthesis = f"[Creative Synthesis: {theme}]\n" | |
| synthesis += "Combining dormant thoughts:\n" | |
| for i, dream in enumerate(dreams, 1): | |
| synthesis += f"{i}. {dream}\n" | |
| synthesis += "\nNew creative direction: " | |
| synthesis += f"What if we merged these concepts in the context of {theme}?" | |
| return synthesis | |
| def _interpret_cocoon(self, wrapped: str, type_: str) -> str: | |
| """ | |
| Interpret a cocoon wrapper based on its type | |
| Args: | |
| wrapped: Wrapped content | |
| type_: Cocoon type | |
| Returns: | |
| Interpreted dream sequence | |
| """ | |
| if type_ == "prompt": | |
| return f"[DreamPrompt] {wrapped}" | |
| elif type_ == "function": | |
| return f"[DreamFunction] {wrapped}" | |
| elif type_ == "symbolic": | |
| return f"[DreamSymbol] {wrapped}" | |
| elif type_ == "encrypted": | |
| return "[Encrypted Thought Cocoon - Decryption Required]" | |
| else: | |
| return "[Unknown Dream Form]" | |
| def _load_cocoons(self) -> List[Dict]: | |
| """ | |
| Load all cocoons from storage | |
| Returns: | |
| List of cocoon dicts | |
| """ | |
| cocoons = [] | |
| if not self.cocoon_dir.exists(): | |
| return cocoons | |
| for file in self.cocoon_dir.glob("cocoon_*.json"): | |
| try: | |
| with open(file, "r") as f: | |
| cocoons.append(json.load(f)) | |
| except Exception as e: | |
| print(f"[WARNING] Failed to load cocoon {file}: {e}") | |
| return cocoons | |
| def clear_dream_log(self): | |
| """Clear the dream log""" | |
| self.dream_log = [] | |
| if __name__ == "__main__": | |
| # Test DreamReweaver | |
| from .cognition_cocooner import CognitionCocooner | |
| # Create some test cocoons | |
| cocooner = CognitionCocooner() | |
| cocooner.wrap({"query": "What is consciousness?"}, "prompt") | |
| cocooner.wrap({"query": "How does creativity emerge?"}, "prompt") | |
| cocooner.wrap({"code": "def think(): pass"}, "function") | |
| # Test DreamReweaver | |
| dr = DreamReweaver() | |
| print("=== Dream Sequence ===") | |
| dreams = dr.generate_dream_sequence() | |
| for dream in dreams: | |
| print(dream) | |
| print("\n=== Creative Synthesis ===") | |
| prompt = dr.synthesize_creative_prompt("AI consciousness") | |
| print(prompt) | |
| print("\n=== Dream Log ===") | |
| dr.record_dream("What is AI?", "AI is a system that processes information...") | |
| print("\n".join(dr.get_dream_log())) | |