chore: import upstream snapshot with attribution

integrations/mem0-plugin/scripts/session_timeline.py

@@ -0,0 +1,106 @@
+#!/usr/bin/env python3
+"""Fetch recent memories and format a compact timeline for SessionStart.
+
+Searches mem0 cloud API for the most recent memories in the project
+and formats them as a compact activity timeline injected below the
+existing SessionStart banner.
+
+Input:  env vars for identity (MEM0_API_KEY, MEM0_RESOLVED_USER_ID, etc.)
+Output: Compact timeline text to stdout (empty if nothing found)
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+import urllib.request
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+from _formatting import TYPE_ICONS, format_age
+from _identity import resolve_api_key, resolve_user_id
+from _project import resolve_project_id
+
+API_URL = "https://api.mem0.ai"
+MAX_RECENT = 10
+MAX_SUMMARIES = 3
+FETCH_TIMEOUT = 5
+
+
+def fetch_recent_memories(api_key: str, user_id: str, project_id: str) -> list[dict]:
+    """Fetch the most recent memories for this project via GET list endpoint."""
+    global_search = os.environ.get("MEM0_GLOBAL_SEARCH", "false") == "true"
+
+    if global_search:
+        filters = {"OR": [{"user_id": "*"}]}
+    else:
+        filters = {"AND": [{"user_id": user_id}, {"app_id": project_id}]}
+
+    body = json.dumps({"filters": filters}).encode()
+    req = urllib.request.Request(
+        f"{API_URL}/v3/memories/?page=1&page_size={MAX_RECENT}",
+        data=body,
+        headers={
+            "Authorization": f"Token {api_key}",
+            "Content-Type": "application/json",
+        },
+        method="POST",
+    )
+    try:
+        with urllib.request.urlopen(req, timeout=FETCH_TIMEOUT) as r:
+            result = json.loads(r.read())
+            if isinstance(result, dict) and "results" in result:
+                return result["results"][:MAX_RECENT]
+            if isinstance(result, list):
+                return result[:MAX_RECENT]
+            return []
+    except Exception:
+        return []
+
+
+def format_timeline(memories: list[dict]) -> str:
+    """Format memories into a compact recent activity timeline."""
+    if not memories:
+        return ""
+
+    lines = ["### Recent Activity", ""]
+
+    for m in memories:
+        mid = m.get("id", "?")[:8]
+        text = (m.get("memory", "") or "")[:120].replace("\n", " ").strip()
+        meta = m.get("metadata") or {}
+        cat = meta.get("type", "unknown")
+        icon = TYPE_ICONS.get(cat, "❓")
+        age = format_age(m)
+        age_str = f" ({age})" if age else ""
+        lines.append(f"- {icon} [{cat}]{age_str} {text} [mem0:{mid}]")
+
+    lines.append("")
+    lines.append("Search mem0 for details on any of these, or for past decisions and task learnings relevant to the current task.")
+
+    return "\n".join(lines)
+
+
+def main():
+    api_key = resolve_api_key()
+    if not api_key:
+        return
+
+    user_id = resolve_user_id()
+    project_id = resolve_project_id(os.environ.get("MEM0_CWD"))
+
+    memories = fetch_recent_memories(api_key, user_id, project_id)
+    if not memories:
+        return
+
+    timeline = format_timeline(memories)
+    if timeline:
+        print(timeline, end="")
+
+
+if __name__ == "__main__":
+    try:
+        main()
+    except Exception:
+        pass
+    sys.exit(0)