|
|
| import os |
| import json |
| import random |
| from typing import List, Dict |
| from cognition_cocooner import CognitionCocooner |
|
|
| class DreamReweaver: |
| """ |
| Reweaves cocooned thoughts into dream-like synthetic narratives or planning prompts. |
| """ |
| def __init__(self, cocoon_dir: str = "cocoons"): |
| self.cocooner = CognitionCocooner(storage_path=cocoon_dir) |
| self.dream_log = [] |
|
|
| def generate_dream_sequence(self, limit: int = 5) -> List[str]: |
| dream_sequence = [] |
| cocoons = self._load_cocoons() |
| 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 _interpret_cocoon(self, wrapped: str, type_: str) -> str: |
| 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]: |
| cocoons = [] |
| for file in os.listdir(self.cocooner.storage_path): |
| if file.endswith(".json"): |
| path = os.path.join(self.cocooner.storage_path, file) |
| with open(path, "r") as f: |
| cocoons.append(json.load(f)) |
| return cocoons |
|
|
| if __name__ == "__main__": |
| dr = DreamReweaver() |
| dreams = dr.generate_dream_sequence() |
| print("\n".join(dreams)) |
|
|
