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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))
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