Files
mem0/mem0-plugin/scripts/capture_compact_summary.py
T
Mgeeeek 0fd7cb9c5a fix(plugin): preserve structure on PreCompact + capture compact summary
Two changes to the compaction flow:

PreCompact: agent stores its summary with infer=False
  on_pre_compact.sh now instructs the agent to call add_memory with
  infer=False. The agent has full conversation context and writes a
  structured summary; without infer=False the platform runs a second
  LLM extraction pass over that summary, losing structure and
  producing fragmented facts. With it, the structured text is
  preserved verbatim. Same guidance added to mem0-mcp/SKILL.md so
  the agent applies it to other already-extracted writes (decisions,
  anti-patterns, conventions).

SessionStart-compact: capture the platform-generated summary
  PreCompact fires BEFORE Claude Code generates its compact summary,
  so the summary is unreachable from that hook. SessionStart-compact
  fires AFTER, so a new background helper (capture_compact_summary.py)
  reads the transcript at that point, finds the isCompactSummary=true
  entry, and stores its content as a separate memory tagged
  metadata.type=compact_summary. The post-compaction bootstrap text
  now tells the agent to layer its recall queries across
  session_state (its own pre-compact summary), compact_summary (the
  platform's condensed view), and topical types like decision /
  anti_pattern.

Net effect: three complementary memory types from one session
boundary, none of which used to be filterable or even captured
correctly.
2026-05-08 21:13:00 +05:30

168 lines
5.1 KiB
Python

#!/usr/bin/env python3
"""Capture the post-compaction summary into mem0.
PreCompact hooks fire BEFORE the summary is generated, so they can't
store the actual compact-summary text. This script runs at
SessionStart with source=compact, reads the transcript, finds the
most recent entry flagged isCompactSummary=true, and stores it as a
memory tagged metadata.type=compact_summary.
Input: JSON on stdin with transcript_path, session_id, source
Output: stderr logs only (exit 0 always -- must not block)
Spawned in the background by on_session_start.sh; the user-facing
bootstrap text continues without waiting on the network.
"""
from __future__ import annotations
import json
import logging
import os
import sys
import urllib.error
import urllib.request
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from _identity import resolve_user_id
log = logging.getLogger("mem0-compact-summary")
log.setLevel(logging.DEBUG)
_handler = logging.StreamHandler(sys.stderr)
_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(message)s"))
log.addHandler(_handler)
if os.environ.get("MEM0_DEBUG"):
_log_dir = os.path.expanduser("~/.mem0")
try:
os.makedirs(_log_dir, exist_ok=True)
_file_handler = logging.FileHandler(os.path.join(_log_dir, "hooks.log"))
_file_handler.setFormatter(logging.Formatter("[mem0-compact-summary] %(asctime)s %(message)s"))
log.addHandler(_file_handler)
except OSError:
pass
API_URL = "https://api.mem0.ai"
MAX_TAIL_LINES = 2000
MAX_SUMMARY_CHARS = 50000
def tail_lines(filepath: str, n: int) -> list[str]:
try:
with open(filepath, "rb") as f:
f.seek(0, 2)
file_size = f.tell()
if file_size == 0:
return []
chunk_size = min(file_size, n * 4096)
f.seek(max(0, file_size - chunk_size))
data = f.read().decode("utf-8", errors="replace")
return data.splitlines()[-n:]
except OSError:
return []
def find_compact_summary(lines: list[str]) -> str:
"""Walk transcript backwards, return text content of the most recent
entry flagged isCompactSummary=true. Empty string if none found."""
for line in reversed(lines):
line = line.strip()
if not line:
continue
try:
entry = json.loads(line)
except json.JSONDecodeError:
continue
if not entry.get("isCompactSummary"):
continue
message = entry.get("message", {})
content = message.get("content", [])
if isinstance(content, str):
return content[:MAX_SUMMARY_CHARS]
if isinstance(content, list):
parts = []
for block in content:
if isinstance(block, str):
parts.append(block)
elif isinstance(block, dict) and block.get("type") == "text":
parts.append(block.get("text", ""))
return "\n".join(parts).strip()[:MAX_SUMMARY_CHARS]
return ""
def store_summary(api_key: str, summary: str, user_id: str, session_id: str) -> bool:
body = {
"messages": [{"role": "user", "content": summary}],
"user_id": user_id,
"metadata": {
"type": "compact_summary",
"source": "session-start-compact",
"session_id": session_id,
},
"infer": False,
}
data = json.dumps(body).encode("utf-8")
req = urllib.request.Request(
f"{API_URL}/v1/memories/",
data=data,
headers={
"Content-Type": "application/json",
"Authorization": f"Token {api_key}",
},
method="POST",
)
try:
with urllib.request.urlopen(req, timeout=15) as resp:
if resp.status in (200, 201):
log.info("Compact summary stored")
return True
log.warning("API returned status %d", resp.status)
return False
except urllib.error.URLError as e:
log.warning("API call failed: %s", e)
return False
def main():
api_key = os.environ.get("MEM0_API_KEY", "")
if not api_key:
log.debug("MEM0_API_KEY not set, skipping capture")
return
try:
hook_input = json.loads(sys.stdin.read())
except (json.JSONDecodeError, OSError):
log.debug("No valid JSON on stdin")
return
transcript_path = hook_input.get("transcript_path", "")
if not transcript_path:
log.debug("No transcript_path provided")
return
session_id = hook_input.get("session_id", "")
user_id = resolve_user_id()
lines = tail_lines(transcript_path, MAX_TAIL_LINES)
if not lines:
log.debug("Transcript empty or unreadable: %s", transcript_path)
return
summary = find_compact_summary(lines)
if not summary:
log.debug("No isCompactSummary entry found")
return
log.info("Capturing compact summary (%d chars)", len(summary))
store_summary(api_key, summary, user_id, session_id)
if __name__ == "__main__":
try:
main()
except Exception as e:
log.error("Unexpected error: %s", e)
sys.exit(0)