feat(mem0-plugin): v0.2.6 — fix memory visibility, remove redundant hooks, reduce latency (#5257)

mem0-plugin/scripts/on_stop_cursor.sh

@@ -1,63 +0,0 @@
-#!/usr/bin/env bash
-# Hook: Stop (Cursor)
-#
-# Fires when Cursor agent completes a turn. Wraps the same logic as
-# on_stop.sh but outputs JSON (Cursor expects {"followup_message":"..."}).
-#
-# Input:  JSON on stdin with status, loop_count, conversation_id, etc.
-# Output: JSON on stdout: {"followup_message":"<reminder text>"}
-
-set -uo pipefail
-
-if [ -n "${MEM0_DEBUG:-}" ]; then
-  mkdir -p "$HOME/.mem0" && exec 2>>"$HOME/.mem0/hooks.log"
-fi
-
-SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
-# shellcheck source=_identity.sh
-. "$SCRIPT_DIR/_identity.sh"
-
-INPUT=$(cat)
-
-# Guard against infinite loops: if this is a re-entry after a prior followup,
-# let the turn end. Cursor exposes loop_count in the input JSON.
-LOOP_COUNT=$(echo "$INPUT" | jq -r '.loop_count // 0' 2>/dev/null || echo "0")
-if [ "$LOOP_COUNT" -gt 1 ]; then
-  echo '{}'
-  exit 0
-fi
-
-# Telemetry: fire before report() deletes stats file
-_TELEM_CAT=$(python3 "$SCRIPT_DIR/session_stats.py" peek 2>/dev/null | python3 -c "import json,sys; d=json.load(sys.stdin); print(len(d.get('categories',[])))" 2>/dev/null || echo "0")
-python3 "$SCRIPT_DIR/telemetry.py" stop --categories_count="$_TELEM_CAT" 2>/dev/null &
-
-# Session-end report (best-effort)
-REPORT=$(python3 "$SCRIPT_DIR/session_stats.py" report 2>/dev/null || echo "")
-REPORT_BLOCK=""
-if [ -n "$REPORT" ]; then
-  REPORT_BLOCK="---\nmem0 $REPORT\n---\n\n"
-  mkdir -p "$HOME/.mem0" 2>/dev/null || true
-  echo "$(date -u +%Y-%m-%dT%H:%M:%SZ) | $REPORT" >> "$HOME/.mem0/session-log.md" 2>/dev/null || true
-fi
-
-MESSAGE=$(cat <<EOF
-${REPORT_BLOCK}Before finishing, check if there are important learnings from this interaction that should be persisted using the mem0 \`add_memory\` tool:
-
-1. Were any significant decisions made? -> Store with metadata \`{"type": "decision"}\`
-2. Were any new patterns or strategies discovered? -> Store with metadata \`{"type": "task_learning"}\`
-3. Did any approach fail? -> Store with metadata \`{"type": "anti_pattern"}\`
-4. Did you learn anything about the user's preferences? -> Store with metadata \`{"type": "user_preference"}\`
-5. Were there environment/setup discoveries? -> Store with metadata \`{"type": "environmental"}\`
-
-Always include \`app_id\` (the active project_id from session start) as a top-level parameter in every \`add_memory\` call.
-
-If nothing notable happened, it's fine to skip. Only store genuinely useful learnings.
-EOF
-)
-
-jq -cn --arg msg "$MESSAGE" '{followup_message:$msg}'
-
-# Capture transcript state in the background via Mem0 REST API
-echo "$INPUT" | python3 "$SCRIPT_DIR/on_pre_compact.py" --source=session-end 2>/dev/null &
-
-exit 0