src/compressor.py

"""
Compressor — collapses all sensory streams into one compact state.

vision + motion + audio + diarization + retrieval → one compact state
"""

import json
import time
from .stream_state import SessionState, sha256_text


def compress_state(state: SessionState) -> dict:
    """Compress rolling sensory state into a compact observer input.

    This is the shadow-dimensionality reduction step:
    many sensory streams → one dense state vector.
    """
    frames = list(state.frames)
    recent_frames = frames[-4:] if frames else []

    # Visual compression
    visual = {
        "frame_count": len(frames),
        "avg_entropy": round(sum(f.entropy for f in recent_frames) / max(1, len(recent_frames)), 4),
        "avg_motion": round(sum(f.motion_score for f in recent_frames) / max(1, len(recent_frames)), 4),
        "last_frame_hash": state.last_frame_hash,
        "frame_hashes": [f.sha256 for f in recent_frames],
    }

    # Audio compression — speaker-separated evidence ledger with full transcripts
    audio = {
        "speakers": {},
        "chunk_count": len(state.audio_chunks),
        "recent_transcripts": [],
    }
    for speaker, info in state.speakers.items():
        audio["speakers"][speaker] = {
            "transcript": info["transcript"][-500:],
            "confidence": info["confidence"],
            "chunk_count": info["chunk_count"],
        }
    # Include last 5 audio chunks as raw evidence
    recent_chunks = list(state.audio_chunks)[-5:]
    for c in recent_chunks:
        audio["recent_transcripts"].append({
            "speaker": c.speaker,
            "text": c.transcript,
            "ts": round(c.ts, 2),
        })

    # Intent — inferred by LLM, not typed by user
    intent = {
        "mode": state.mode,
        "note": "Intent must be inferred from camera + audio evidence, not from typed instructions.",
    }

    # Compressed state
    compact = {
        "timestamp": time.time(),
        "session_id": state.session_id,
        "visual": visual,
        "audio": audio,
        "intent": intent,
        "motion_score": state.motion_score,
        "novelty_score": state.novelty_score,
        "state_hash": "",
    }

    compact["state_hash"] = sha256_text(json.dumps(compact, sort_keys=True, default=str))
    return compact