#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import os
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from urllib import error, request

AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")

def truncate(text: str | None, max_chars: int = 220) -> str:
    value = (text or "").replace("\n", " ").replace("\r", " ").strip()
    if not value:
        return ""
    if len(value) <= max_chars:
        return value
    return value[: max_chars - 1].rstrip() + "…"

def build_memory(payload: dict[str, object]) -> dict[str, object]:
    cwd = str(payload.get("cwd") or "")
    session_file = str(payload.get("session_file") or "")
    session_id = str(payload.get("session_id") or "")
    reason = str(payload.get("reason") or "session_close")
    scope = str(payload.get("scope") or "global")
    user_messages = int(payload.get("user_messages") or 0)
    assistant_messages = int(payload.get("assistant_messages") or 0)
    last_user_text = truncate(str(payload.get("last_user_text") or ""), 400)
    last_assistant_text = truncate(str(payload.get("last_assistant_text") or ""), 400)

    session_name = Path(cwd).name or "session"
    title = f"Session summary: {session_name}"

    parts: list[str] = []
    parts.append(f"Session closed from {cwd or 'unknown cwd'} ({reason}).")
    parts.append(f"Conversation had {user_messages} user messages and {assistant_messages} assistant messages.")
    if last_user_text:
        parts.append(f"Last user signal: {last_user_text}.")
    if last_assistant_text:
        parts.append(f"Last assistant signal: {last_assistant_text}.")

    return {
        "type": "episode",
        "subtype": "session_close_summary",
        "scope": scope,
        "status": "active",
        "source_kind": "manual",
        "title": title,
        "content": "\n\n".join(parts),
        "source_ref": f"pi-session:{session_file or session_id or 'unknown'}",
        "origin_agent": "pi-session-memory-dispatcher",
        "metadata": {
            "reason": reason,
            "cwd": cwd,
            "session_file": session_file,
            "session_id": session_id,
            "user_messages": user_messages,
            "assistant_messages": assistant_messages,
            "trigger": str(payload.get("trigger") or "session-memory-dispatcher"),
        },
    }

def ingest(memory: dict[str, object]) -> dict[str, object]:
    req = request.Request(
        f"{AGENTS_DB_API}/api/ingest",
        method="POST",
        data=json.dumps(memory).encode(),
        headers={"Content-Type": "application/json"},
    )
    with request.urlopen(req, timeout=30) as resp:
        return json.loads(resp.read().decode("utf-8"))

class Handler(BaseHTTPRequestHandler):
    def do_POST(self):
        if self.path != "/api/session-memory":
            self.send_response(404)
            self.end_headers()
            return

        length = int(self.headers.get("Content-Length", "0") or "0")
        raw = self.rfile.read(length)
        try:
            payload = json.loads(raw.decode("utf-8"))
        except Exception as exc:
            self.send_response(400)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": f"invalid json: {exc}"}).encode())
            return

        try:
            memory = build_memory(payload)
            saved = ingest(memory)
            self.send_response(201)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps(saved).encode())
        except error.HTTPError as exc:
            body = exc.read()
            self.send_response(exc.code)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(body)
        except Exception as exc:
            self.send_response(502)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": str(exc)}).encode())

    def log_message(self, fmt, *args):
        return

def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--host", default="127.0.0.1")
    parser.add_argument("--port", type=int, default=17882)
    args = parser.parse_args()

    server = ThreadingHTTPServer((args.host, args.port), Handler)
    print(f"session-memory-dispatcher listening on http://{args.host}:{args.port}/api/session-memory", flush=True)
    try:
        server.serve_forever()
    except KeyboardInterrupt:
        return 0
    return 0

if __name__ == "__main__":
    raise SystemExit(main())


import path from "node:path";
import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";

const DISPATCH_URL = process.env.PI_SESSION_MEMORY_DISPATCH_URL || "http://127.0.0.1:17882/api/session-memory";
const PROMPT_SAVE = "Save durable memory";
const PROMPT_SKIP = "Continue without saving";
const PROMPT_CANCEL = "Cancel";

function textFromMessage(message: any): string {
	if (!message || !Array.isArray(message.content)) return "";
	return message.content
		.filter((part: any) => part?.type === "text" && typeof part.text === "string")
		.map((part: any) => part.text)
		.join("\n")
		.trim();
}

function truncate(text: string | undefined, max = 220): string {
	const value = (text || "").replace(/\s+/g, " ").trim();
	if (!value) return "";
	return value.length > max ? value.slice(0, max - 1) + "…" : value;
}

function inferScope(cwd: string): "global" | "project" {
	const home = path.resolve(process.env.HOME || "/home/sebas");
	const resolved = path.resolve(cwd);
	if (resolved === home) return "global";
	if (resolved.startsWith(path.join(home, ".pi"))) return "global";
	return "project";
}

function getSessionStats(ctx: any) {
	const branch = ctx.sessionManager.getBranch();
	let userCount = 0;
	let assistantCount = 0;
	let lastUserText = "";
	let lastAssistantText = "";

	for (const entry of branch) {
		if (entry?.type !== "message") continue;
		const message = entry.message;
		if (!message || typeof message !== "object" || !("role" in message)) continue;
		if (message.role === "user") {
			userCount += 1;
			lastUserText = textFromMessage(message) || lastUserText;
		}
		if (message.role === "assistant") {
			assistantCount += 1;
			lastAssistantText = textFromMessage(message) || lastAssistantText;
		}
	}

	return {
		branch,
		userCount,
		assistantCount,
		lastUserText,
		lastAssistantText,
		shouldPrompt: userCount > 0 && assistantCount > 0,
	};
}

function buildHookPayload(ctx: any, stats: ReturnType<typeof getSessionStats>, reason: string) {
	return {
		session_id: ctx.sessionManager.getLeafId?.() || null,
		session_file: ctx.sessionManager.getSessionFile?.() || null,
		reason,
		cwd: ctx.cwd,
		scope: inferScope(ctx.cwd),
		user_messages: stats.userCount,
		assistant_messages: stats.assistantCount,
		last_user_text: truncate(stats.lastUserText, 2000),
		last_assistant_text: truncate(stats.lastAssistantText, 2000),
		branch: stats.branch,
	};
}

async function dispatchMemory(payload: any) {
	const response = await fetch(DISPATCH_URL, {
		method: "POST",
		headers: { "Content-Type": "application/json" },
		body: JSON.stringify(payload),
	});
	if (!response.ok) {
		throw new Error(`session memory dispatcher failed: ${response.status} ${response.statusText}`);
	}
	return response.json();
}

export default function (pi: ExtensionAPI) {
	let promptHandledForCurrentSession = false;

	async function runPrompt(ctx: any, reason: string, options?: { allowCancel?: boolean; title?: string; timeoutMs?: number }) {
		if (promptHandledForCurrentSession) return { cancel: false, skipped: true };
		if (!ctx.hasUI) return { cancel: false, skipped: true };

		const stats = getSessionStats(ctx);
		if (!stats.shouldPrompt) return { cancel: false, skipped: true };

		const allowCancel = options?.allowCancel ?? false;
		const timeoutMs = options?.timeoutMs;
		const title = options?.title || "Before closing this session";
		const choices = allowCancel ? [PROMPT_SAVE, PROMPT_SKIP, PROMPT_CANCEL] : [PROMPT_SAVE, PROMPT_SKIP];
		const dialogOptions = timeoutMs ? { timeout: timeoutMs } : undefined;
		const choice = await ctx.ui.select(title, choices, dialogOptions);

		if (choice === PROMPT_CANCEL || (allowCancel && choice === undefined)) {
			promptHandledForCurrentSession = false;
			return { cancel: true, skipped: false };
		}

		if (choice !== PROMPT_SAVE) {
			promptHandledForCurrentSession = true;
			return { cancel: false, skipped: true };
		}

		const payload = buildHookPayload(ctx, stats, reason);
		try {
			const result = await dispatchMemory({
				...payload,
				trigger: "session-memory-dispatcher",
			});
			promptHandledForCurrentSession = true;
			ctx.ui.notify(`Memory saved: ${result.id}`, "info");
			return { cancel: false, skipped: false, memoryId: result.id };
		} catch (error) {
			promptHandledForCurrentSession = false;
			const message = error instanceof Error ? error.message : String(error);
			ctx.ui.notify(message, "error");
			if (!allowCancel) return { cancel: false, skipped: true, error: message };
			const ok = await ctx.ui.confirm("Memory save failed", "Continue closing this session without saving?", dialogOptions);
			if (!ok) return { cancel: true, skipped: false, error: message };
			promptHandledForCurrentSession = true;
			return { cancel: false, skipped: true, error: message };
		}
	}

	pi.on("session_before_switch", async (event, ctx) => {
		const result = await runPrompt(ctx, `before_switch:${event.reason}`, { allowCancel: true, title: "Before closing this session" });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_before_fork", async (_event, ctx) => {
		const result = await runPrompt(ctx, "before_fork", { allowCancel: true, title: "Before forking away from this session" });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_before_shutdown", async (event, ctx) => {
		const result = await runPrompt(ctx, `before_shutdown:${event.reason}`, { allowCancel: true, title: "Before exit: save durable memory?", timeoutMs: 12000 });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_shutdown", async (_event, ctx) => {
		await runPrompt(ctx, "shutdown_fallback", { allowCancel: false, title: "Before exit: save durable memory?", timeoutMs: 12000 });
	});

	pi.registerCommand("remember-session", {
		description: "Save a durable memory from the current session",
		handler: async (_args, ctx) => {
			promptHandledForCurrentSession = false;
			await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Save durable memory from this session" });
		},
	});
}


**Designing Analyzer Workflow**

I think I need to set up a worker service, or perhaps the dispatcher itself can spawn a subprocess for the analyzer script. The simplest way might be for the dispatcher to create a queue item as a JSON file and then spawn the analyzer subprocess. However, the user wants the analyzer to call `pi` in the background, so I should create a script that accepts a job file and a background flag. The dispatcher can write the job file and launch the analyzer smoothly.

**Considering Session Metadata Storage**

It seems like session metadata should be stored as a job queue artifact rather than in memory. The durable memory should only be created if the analyzer decides so. I think I’ll need to reintroduce the current `scripts/session-memory-analyzer.py` and update the README as well.

I might create a queue or job file storage. Using the tmp root could work, but perhaps a directory like `/mnt/rpi/pi-config/data/session-memory-jobs/` would be easier. I want to keep this organized without making it too complicated!

**Considering system processes**

I'm exploring whether I should adjust the use of result.id, and I’m thinking about whether I need to remove the analyzer file or perhaps recreate it instead. It seems like I might need to consider using a direct background process or perhaps a systemd service to meet the user's request for it to run in the background. So, I'm weighing my options for the best approach here.

**Exploring existing data**

I’m thinking I should check if there is any existing data or a state directory. My best move would be to use the "ls" command to list what’s available. This way, I can see what files or directories are present. It feels simple but effective to start here to gather the necessary information. I wonder what I’m going to find! It'll help me move forward with my task.

bash

find /mnt/rpi/pi-config -maxdepth 2 -type d | sed -n '1,200p'


/mnt/rpi/pi-config
/mnt/rpi/pi-config/.git
/mnt/rpi/pi-config/.git/refs
/mnt/rpi/pi-config/.git/info
/mnt/rpi/pi-config/.git/objects
/mnt/rpi/pi-config/.git/hooks
/mnt/rpi/pi-config/.git/logs
/mnt/rpi/pi-config/.git/branches
/mnt/rpi/pi-config/git
/mnt/rpi/pi-config/git/github.com
/mnt/rpi/pi-config/scripts
/mnt/rpi/pi-config/scripts/__pycache__
/mnt/rpi/pi-config/extensions
/mnt/rpi/pi-config/extensions/subagent
/mnt/rpi/pi-config/bin
/mnt/rpi/pi-config/sessions
/mnt/rpi/pi-config/sessions/--home-sebas-downloads-mp3-share--
/mnt/rpi/pi-config/sessions/--mnt-rpi-repos-ballbox--
/mnt/rpi/pi-config/sessions/--home-sebas--
/mnt/rpi/pi-config/sessions/--mnt-rpi-repos--
/mnt/rpi/pi-config/sessions/--mnt-rpi--


# Pi runtime state / secrets
/auth.json
/sessions/
/bin/*
!/bin/laptop-*
!/bin/browser-harness
!/bin/fd
!/bin/agent-tmp-run
!/bin/agent-tmp-gc

# Local runtime noise
*.log
*.tmp
*.swp
.DS_Store


**Evaluating job storage options**

I'm thinking about where to create a `.state` directory. We might consider using the sessions directory, but it's already gitignored, and that might not be best. I could use `/mnt/rpi/pi-config/.state/session-memory/` or the jobs directory for metadata. However, if the analyzer doesn't process jobs later, I wonder if that's a problem. Since we're fine with not having a persistent queue, maybe storing a job file in `/mnt/rpi/pi-config/sessions/session-memory-jobs` is okay. I might need to remove the old dispatcher version too.

**Planning analyzer script updates**

I think it’s unnecessary to mention certain things in the final answer. I need to create a new analyzer script, possibly keeping the same name as the removed one. I'll also update the extension to notify about queued tasks and might trigger the session-memory dispatcher. It’s important to include more relevant metadata in `buildHookPayload`, which the analyzer will use. For the output, I might go with plain text instructions for simplicity, but structured JSON could be beneficial for valuable memory. Using `pi --mode json` may work, but I’ll ensure the output remains strictly JSON for parsing later.

**Refining output settings**

I see that the default for `pi` is `-p --mode text`. I'll need to set the system prompt to output JSON only to make parsing easier from stdout. Ignoring extra output and extracting just the JSON substring might be a good approach. Additionally, I’m considering using `--model gpt-5.4-mini --thinking off` with `--provider openai-codex`, especially since the environment might default to using openai-codex. I want to ensure I'm getting the correct output format!

**Considering metadata storage**

I might consider storing raw session metadata as a `session_record` file outside the memory database, though the user mentioned just needing metadata sessions. Storing the job file in the repository doesn't seem urgent. The dispatcher shouldn’t save information to the agents' database, but the analyzer can decide to save memory, which is fine. I could create a job file as a metadata record and set up a new analyzer script to process it and return the necessary JSON format.

**Evaluating testing approach**

I need to ensure we have syntax checks in place. I might consider invoking with an environment override to use a dummy `pi` script earlier in the PATH. Testing via a stub `pi` in a temporary directory could help avoid making actual API calls. The dummy script would print JSON, which would validate the analyzer flow. I think writing a test harness command with the appropriate path could work effectively. I should also remember to adjust the script to use `pi` correctly from the PATH.

write

#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import os
import subprocess
import sys
from pathlib import Path
from typing import Any
from urllib import request

AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")
PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "openai-codex/gpt-5.4-mini")
PI_THINKING = os.environ.get("PI_SESSION_MEMORY_THINKING", "off")

def load_job(job_file: Path) -> dict[str, Any]:
    return json.loads(job_file.read_text(encoding="utf-8"))

def save_job(job_file: Path, payload: dict[str, Any]) -> None:
    job_file.write_text(json.dumps(payload, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")

def call_pi(prompt: str) -> str:
    cmd = [
        "pi",
        "-p",
        "--provider",
        "openai-codex",
        "--model",
        PI_MODEL,
        "--thinking",
        PI_THINKING,
        "--no-tools",
        "--no-session",
        prompt,
    ]
    proc = subprocess.run(cmd, capture_output=True, text=True)
    if proc.returncode != 0:
        raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f"pi failed ({proc.returncode})")
    return proc.stdout.strip()

def ingest(memory: dict[str, Any]) -> dict[str, Any]:
    req = request.Request(
        f"{AGENTS_DB_API}/api/ingest",
        method="POST",
        data=json.dumps(memory).encode(),
        headers={"Content-Type": "application/json"},
    )
    with request.urlopen(req, timeout=30) as resp:
        return json.loads(resp.read().decode("utf-8"))

def extract_json(text: str) -> dict[str, Any]:
    raw = text.strip()
    if raw.startswith("```"):
        raw = raw.strip("`")
        raw = raw.split("\n", 1)[-1] if "\n" in raw else raw
    start = raw.find("{")
    end = raw.rfind("}")
    if start >= 0 and end > start:
        raw = raw[start : end + 1]
    return json.loads(raw)

def build_prompt(job: dict[str, Any]) -> str:
    return f"""You are deciding whether a Pi session has durable value.

Rules:
- Prefer NOT saving anything unless it is durable and reusable.
- Session metadata alone is not enough.
- Save only if the session contains a stable preference, decision, project fact, reusable artifact, or a blocker that matters later.
- If nothing durable exists, return save=false.
- Output JSON only. No markdown. No extra text.

Return this schema:
{{
  "save": boolean,
  "type": "profile" | "decision" | "project" | "artifact" | "episode",
  "subtype": string | null,
  "scope": "global" | "project",
  "title": string,
  "content": string,
  "source_ref": string,
  "reason": string
}}

Session metadata:
- session_id: {job.get('session_id')}
- session_file: {job.get('session_file')}
- cwd: {job.get('cwd')}
- scope: {job.get('scope')}
- reason: {job.get('reason')}
- user_messages: {job.get('user_messages')}
- assistant_messages: {job.get('assistant_messages')}
- last_user_text: {str(job.get('last_user_text') or '')[:2000]}
- last_assistant_text: {str(job.get('last_assistant_text') or '')[:2000]}
- trigger: {job.get('trigger')}

Branch excerpt JSON:
{json.dumps(job.get('branch') or [], ensure_ascii=False)[:30000]}
"""

def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--job-file", required=True)
    args = parser.parse_args()

    job_file = Path(args.job_file)
    job = load_job(job_file)
    job.setdefault("analysis", {})
    job["analysis"]["status"] = "running"
    save_job(job_file, job)

    try:
        raw = call_pi(build_prompt(job))
        analysis = extract_json(raw)
        job["analysis"]["raw"] = raw
        job["analysis"]["result"] = analysis
        job["analysis"]["status"] = "completed"

        if analysis.get("save"):
            memory = {
                "type": analysis.get("type") or "episode",
                "subtype": analysis.get("subtype"),
                "scope": analysis.get("scope") or job.get("scope") or "global",
                "status": "active",
                "source_kind": "manual",
                "title": analysis.get("title") or "Session insight",
                "content": analysis.get("content") or "",
                "source_ref": analysis.get("source_ref") or f"pi-session:{job.get('session_file') or job.get('session_id') or 'unknown'}",
                "origin_agent": "pi-session-memory-analyzer",
                "metadata": {
                    "job_file": str(job_file),
                    "session_id": job.get("session_id"),
                    "session_file": job.get("session_file"),
                    "cwd": job.get("cwd"),
                    "reason": job.get("reason"),
                    "user_messages": job.get("user_messages"),
                    "assistant_messages": job.get("assistant_messages"),
                    "analysis_reason": analysis.get("reason"),
                    "trigger": job.get("trigger"),
                },
            }
            saved = ingest(memory)
            job["analysis"]["memory_id"] = saved.get("id")
            job["analysis"]["saved"] = True
        else:
            job["analysis"]["saved"] = False
            job["analysis"]["memory_id"] = None

        save_job(job_file, job)
        print(json.dumps(job["analysis"], ensure_ascii=False))
        return 0
    except Exception as exc:
        job["analysis"]["status"] = "failed"
        job["analysis"]["error"] = str(exc)
        save_job(job_file, job)
        print(json.dumps(job["analysis"], ensure_ascii=False), file=sys.stderr)
        return 1

if __name__ == "__main__":
    raise SystemExit(main())


Successfully wrote 5576 bytes to /mnt/rpi/pi-config/scripts/session-memory-analyzer.py


**Modifying dispatcher tasks**

I need to adjust the dispatcher to queue and spawn the analyzer. It seems like a rewrite is in order, but I want to keep it minimal. I might need to import subprocess, uuid, and datetime to make this work smoothly. This adjustment feels crucial for streamlining the process, and I'm eager to see how it all integrates once I implement these changes! Let's dive in and get started on this!

edit

import argparse
import json
import os
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from urllib import error, request

AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")

def truncate(text: str | None, max_chars: int = 220) -> str:
    value = (text or "").replace("\n", " ").replace("\r", " ").strip()
    if not value:
        return ""
    if len(value) <= max_chars:
        return value
    return value[: max_chars - 1].rstrip() + "…"

def build_memory(payload: dict[str, object]) -> dict[str, object]:
    cwd = str(payload.get("cwd") or "")
    session_file = str(payload.get("session_file") or "")
    session_id = str(payload.get("session_id") or "")
    reason = str(payload.get("reason") or "session_close")
    scope = str(payload.get("scope") or "global")
    user_messages = int(payload.get("user_messages") or 0)
    assistant_messages = int(payload.get("assistant_messages") or 0)
    last_user_text = truncate(str(payload.get("last_user_text") or ""), 400)
    last_assistant_text = truncate(str(payload.get("last_assistant_text") or ""), 400)

    session_name = Path(cwd).name or "session"
    title = f"Session summary: {session_name}"

    parts: list[str] = []
    parts.append(f"Session closed from {cwd or 'unknown cwd'} ({reason}).")
    parts.append(f"Conversation had {user_messages} user messages and {assistant_messages} assistant messages.")
    if last_user_text:
        parts.append(f"Last user signal: {last_user_text}.")
    if last_assistant_text:
        parts.append(f"Last assistant signal: {last_assistant_text}.")

    return {
        "type": "episode",
        "subtype": "session_close_summary",
        "scope": scope,
        "status": "active",
        "source_kind": "manual",
        "title": title,
        "content": "\n\n".join(parts),
        "source_ref": f"pi-session:{session_file or session_id or 'unknown'}",
        "origin_agent": "pi-session-memory-dispatcher",
        "metadata": {
            "reason": reason,
            "cwd": cwd,
            "session_file": session_file,
            "session_id": session_id,
            "user_messages": user_messages,
            "assistant_messages": assistant_messages,
            "trigger": str(payload.get("trigger") or "session-memory-dispatcher"),
        },
    }

def ingest(memory: dict[str, object]) -> dict[str, object]:
    req = request.Request(
        f"{AGENTS_DB_API}/api/ingest",
        method="POST",
        data=json.dumps(memory).encode(),
        headers={"Content-Type": "application/json"},
    )
    with request.urlopen(req, timeout=30) as resp:
        return json.loads(resp.read().decode("utf-8"))

import argparse
import json
import os
import subprocess
from datetime import datetime, timezone
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from urllib import error

BASE_DIR = Path(__file__).resolve().parent.parent
JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))

def truncate(text: str | None, max_chars: int = 220) -> str:
    value = (text or "").replace("\n", " ").replace("\r", " ").strip()
    if not value:
        return ""
    if len(value) <= max_chars:
        return value
    return value[: max_chars - 1].rstrip() + "…"

def write_job(payload: dict[str, object]) -> Path:
    JOB_DIR.mkdir(parents=True, exist_ok=True)
    job_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%S%fZ")
    job_file = JOB_DIR / f"{job_id}.json"
    job = {
        "job_id": job_id,
        "queued_at": datetime.now(timezone.utc).isoformat(),
        "status": "queued",
        "payload": payload,
    }
    job_file.write_text(json.dumps(job, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
    return job_file

def launch_analyzer(job_file: Path) -> None:
    subprocess.Popen(
        ["python3", str(ANALYZER), "--job-file", str(job_file)],
        stdout=subprocess.DEVNULL,
        stderr=subprocess.DEVNULL,
        start_new_session=True,
        close_fds=True,
    )


Successfully replaced 1 block(s) in /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py.

     ...
   3
   4 import argparse
   5 import json
   6 import os
+  7 import subprocess
+  8 from datetime import datetime, timezone
   7 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
   8 from pathlib import Path
-  9 from urllib import error, request
+ 11 from urllib import error
  10
- 11 AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")
+ 13 BASE_DIR = Path(__file__).resolve().parent.parent
+ 14 JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
+ 15 ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))
  12
  13
  14 def truncate(text: str | None, max_chars: int = 220) -> str:
  15     value = (text or "").replace("\n", " ").replace("\r", " ").strip()
     ...
  19         return value
  20     return value[: max_chars - 1].rstrip() + "…"
  21
  22
- 23 def build_memory(payload: dict[str, object]) -> dict[str, object]:
- 24     cwd = str(payload.get("cwd") or "")
- 25     session_file = str(payload.get("session_file") or "")
- 26     session_id = str(payload.get("session_id") or "")
- 27     reason = str(payload.get("reason") or "session_close")
- 28     scope = str(payload.get("scope") or "global")
- 29     user_messages = int(payload.get("user_messages") or 0)
- 30     assistant_messages = int(payload.get("assistant_messages") or 0)
- 31     last_user_text = truncate(str(payload.get("last_user_text") or ""), 400)
- 32     last_assistant_text = truncate(str(payload.get("last_assistant_text") or ""), 400)
- 33
- 34     session_name = Path(cwd).name or "session"
- 35     title = f"Session summary: {session_name}"
- 36
- 37     parts: list[str] = []
- 38     parts.append(f"Session closed from {cwd or 'unknown cwd'} ({reason}).")
- 39     parts.append(f"Conversation had {user_messages} user messages and {assistant_messages} assistant messages.")
- 40     if last_user_text:
- 41         parts.append(f"Last user signal: {last_user_text}.")
- 42     if last_assistant_text:
- 43         parts.append(f"Last assistant signal: {last_assistant_text}.")
- 44
- 45     return {
- 46         "type": "episode",
- 47         "subtype": "session_close_summary",
- 48         "scope": scope,
- 49         "status": "active",
- 50         "source_kind": "manual",
- 51         "title": title,
- 52         "content": "\n\n".join(parts),
- 53         "source_ref": f"pi-session:{session_file or session_id or 'unknown'}",
- 54         "origin_agent": "pi-session-memory-dispatcher",
- 55         "metadata": {
- 56             "reason": reason,
- 57             "cwd": cwd,
- 58             "session_file": session_file,
- 59             "session_id": session_id,
- 60             "user_messages": user_messages,
- 61             "assistant_messages": assistant_messages,
- 62             "trigger": str(payload.get("trigger") or "session-memory-dispatcher"),
- 63         },
+ 27 def write_job(payload: dict[str, object]) -> Path:
+ 28     JOB_DIR.mkdir(parents=True, exist_ok=True)
+ 29     job_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%S%fZ")
+ 30     job_file = JOB_DIR / f"{job_id}.json"
+ 31     job = {
+ 32         "job_id": job_id,
+ 33         "queued_at": datetime.now(timezone.utc).isoformat(),
+ 34         "status": "queued",
+ 35         "payload": payload,
  64     }
+ 37     job_file.write_text(json.dumps(job, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
+ 38     return job_file
  65
  66
- 67 def ingest(memory: dict[str, object]) -> dict[str, object]:
- 68     req = request.Request(
- 69         f"{AGENTS_DB_API}/api/ingest",
- 70         method="POST",
- 71         data=json.dumps(memory).encode(),
- 72         headers={"Content-Type": "application/json"},
+ 41 def launch_analyzer(job_file: Path) -> None:
+ 42     subprocess.Popen(
+ 43         ["python3", str(ANALYZER), "--job-file", str(job_file)],
+ 44         stdout=subprocess.DEVNULL,
+ 45         stderr=subprocess.DEVNULL,
+ 46         start_new_session=True,
+ 47         close_fds=True,
  73     )
- 74     with request.urlopen(req, timeout=30) as resp:
- 75         return json.loads(resp.read().decode("utf-8"))
  76
  77
  78 class Handler(BaseHTTPRequestHandler):
  79     def do_POST(self):
     ...


**Updating file references**

I need to go through the rest of the file to remove any references to "build_memory" and similar terms. It’s important that everything is consistent and up to date! I'll take my time to inspect the file and make sure I've got everything covered, checking for any lingering mentions. This way, the file should work seamlessly without any confusion. Let's make sure it's all clear and tidy!


#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import os
import subprocess
from datetime import datetime, timezone
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
from urllib import error

BASE_DIR = Path(__file__).resolve().parent.parent
JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))

def truncate(text: str | None, max_chars: int = 220) -> str:
    value = (text or "").replace("\n", " ").replace("\r", " ").strip()
    if not value:
        return ""
    if len(value) <= max_chars:
        return value
    return value[: max_chars - 1].rstrip() + "…"

def write_job(payload: dict[str, object]) -> Path:
    JOB_DIR.mkdir(parents=True, exist_ok=True)
    job_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%S%fZ")
    job_file = JOB_DIR / f"{job_id}.json"
    job = {
        "job_id": job_id,
        "queued_at": datetime.now(timezone.utc).isoformat(),
        "status": "queued",
        "payload": payload,
    }
    job_file.write_text(json.dumps(job, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
    return job_file

def launch_analyzer(job_file: Path) -> None:
    subprocess.Popen(
        ["python3", str(ANALYZER), "--job-file", str(job_file)],
        stdout=subprocess.DEVNULL,
        stderr=subprocess.DEVNULL,
        start_new_session=True,
        close_fds=True,
    )

class Handler(BaseHTTPRequestHandler):
    def do_POST(self):
        if self.path != "/api/session-memory":
            self.send_response(404)
            self.end_headers()
            return

        length = int(self.headers.get("Content-Length", "0") or "0")
        raw = self.rfile.read(length)
        try:
            payload = json.loads(raw.decode("utf-8"))
        except Exception as exc:
            self.send_response(400)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": f"invalid json: {exc}"}).encode())
            return

        try:
            memory = build_memory(payload)
            saved = ingest(memory)
            self.send_response(201)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps(saved).encode())
        except error.HTTPError as exc:
            body = exc.read()
            self.send_response(exc.code)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(body)
        except Exception as exc:
            self.send_response(502)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": str(exc)}).encode())

    def log_message(self, fmt, *args):
        return

def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--host", default="127.0.0.1")
    parser.add_argument("--port", type=int, default=17882)
    args = parser.parse_args()

    server = ThreadingHTTPServer((args.host, args.port), Handler)
    print(f"session-memory-dispatcher listening on http://{args.host}:{args.port}/api/session-memory", flush=True)
    try:
        server.serve_forever()
    except KeyboardInterrupt:
        return 0
    return 0

if __name__ == "__main__":
    raise SystemExit(main())


**Updating code logic**

I need to replace the do_POST block — that's a must. I’m also wondering if I should truncate something since it seems unused. It might be safe to delete it, but I could use it for logging. Hmm, that’s a bit unclear. Reducing unnecessary code could be beneficial, though. I definitely need to update it to use write_job and launch_analyzer, so it's time to edit and clean things up.

def truncate(text: str | None, max_chars: int = 220) -> str:
    value = (text or "").replace("\n", " ").replace("\r", " ").strip()
    if not value:
        return ""
    if len(value) <= max_chars:
        return value
    return value[: max_chars - 1].rstrip() + "…"

def write_job(payload: dict[str, object]) -> Path:

        try:
            memory = build_memory(payload)
            saved = ingest(memory)
            self.send_response(201)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps(saved).encode())
        except error.HTTPError as exc:
            body = exc.read()
            self.send_response(exc.code)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(body)
        except Exception as exc:
            self.send_response(502)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": str(exc)}).encode())

        try:
            job_file = write_job(payload)
            launch_analyzer(job_file)
            self.send_response(202)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"status": "queued", "job_file": str(job_file)}).encode())
        except Exception as exc:
            self.send_response(502)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": str(exc)}).encode())


Successfully replaced 2 block(s) in /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py.

     ...
  14 JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
  15 ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))
  16
  17
- 18 def truncate(text: str | None, max_chars: int = 220) -> str:
- 19     value = (text or "").replace("\n", " ").replace("\r", " ").strip()
- 20     if not value:
- 21         return ""
- 22     if len(value) <= max_chars:
- 23         return value
- 24     return value[: max_chars - 1].rstrip() + "…"
- 25
- 26
  27 def write_job(payload: dict[str, object]) -> Path:
  28     JOB_DIR.mkdir(parents=True, exist_ok=True)
  29     job_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%S%fZ")
  30     job_file = JOB_DIR / f"{job_id}.json"
     ...
  66             self.wfile.write(json.dumps({"error": f"invalid json: {exc}"}).encode())
  67             return
  68
  69         try:
- 70             memory = build_memory(payload)
- 71             saved = ingest(memory)
- 72             self.send_response(201)
+ 61             job_file = write_job(payload)
+ 62             launch_analyzer(job_file)
+ 63             self.send_response(202)
  73             self.send_header("Content-Type", "application/json")
  74             self.end_headers()
- 75             self.wfile.write(json.dumps(saved).encode())
- 76         except error.HTTPError as exc:
- 77             body = exc.read()
- 78             self.send_response(exc.code)
- 79             self.send_header("Content-Type", "application/json")
- 80             self.end_headers()
- 81             self.wfile.write(body)
+ 66             self.wfile.write(json.dumps({"status": "queued", "job_file": str(job_file)}).encode())
  82         except Exception as exc:
  83             self.send_response(502)
  84             self.send_header("Content-Type", "application/json")
  85             self.end_headers()
     ...


**Considering code cleanup**

I need to remove an unused import error since it's no longer being used. It could be okay to lint, but keeping it might lead to issues in the future. Maybe I should just edit the code to clean it up. It's always good to ensure that my code is neat and free of unnecessary errors, right? Reducing clutter helps make everything more manageable, so I think it's worth doing!


    ...
  7 import subprocess
  8 from datetime import datetime, timezone
  9 from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
 10 from pathlib import Path
-11 from urllib import error
 12
 13 BASE_DIR = Path(__file__).resolve().parent.parent
 14 JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
 15 ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))
    ...


**Considering extension updates**

I need to update the extension so it doesn't say "saved" but "queued" instead. I think this change could help clarify the status. I should also consider including a response when a job file is present. Okay, I'll make the necessary edits to reflect this new information in the interface. It feels satisfying to think about how these adjustments could improve user clarity!

			const result = await dispatchMemory({
				...payload,
				trigger: "session-memory-dispatcher",
			});
			promptHandledForCurrentSession = true;
			ctx.ui.notify(`Memory saved: ${result.id}`, "info");
			return { cancel: false, skipped: false, memoryId: result.id };

			const result = await dispatchMemory({
				...payload,
				trigger: "session-memory-dispatcher",
			});
			promptHandledForCurrentSession = true;
			ctx.ui.notify(`Session analysis queued: ${result.job_file || result.status || "ok"}`, "info");
			return { cancel: false, skipped: false, queued: true, jobFile: result.job_file };


Successfully replaced 1 block(s) in /mnt/rpi/pi-config/extensions/session-memory-dispatcher.ts.

     ...
 120 				...payload,
 121 				trigger: "session-memory-dispatcher",
 122 			});
 123 			promptHandledForCurrentSession = true;
-124 			ctx.ui.notify(`Memory saved: ${result.id}`, "info");
-125 			return { cancel: false, skipped: false, memoryId: result.id };
+124 			ctx.ui.notify(`Session analysis queued: ${result.job_file || result.status || "ok"}`, "info");
+125 			return { cancel: false, skipped: false, queued: true, jobFile: result.job_file };
 126 		} catch (error) {
 127 			promptHandledForCurrentSession = false;
 128 			const message = error instanceof Error ? error.message : String(error);
 129 			ctx.ui.notify(message, "error");
     ...


**Updating documentation**

I think I need to update the dispatchMemory typing. Also, the README could use some changes, especially to mention the analyzer. I should inspect the current README to see what it says. It seems like I only need to modify a few lines about the dispatcher. Plus, I should probably add a note about the model and my thinking process. Alright, I'll go ahead and make those edits!

- `scripts/session-memory-analyzer.py`
- `scripts/session-memory-dispatcher.py`
- `scripts/install-session-memory-dispatcher.service`

- Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context and the dispatcher turns that into a durable episode memory before ingest.
- Use `./scripts/install-session-memory-dispatcher.service` to keep the dispatcher alive under systemd user service if desired.

- Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context, the dispatcher enqueues metadata, and a background analyzer decides whether anything durable is worth saving.
- The analyzer uses `pi` in background with a cheap model (`gpt-5.4-mini`) and thinking off when possible.
- Use `./scripts/install-session-memory-dispatcher.service` to keep the dispatcher alive under systemd user service if desired.


Successfully replaced 2 block(s) in /mnt/rpi/pi-config/README.md.

    ...
  9 - `extensions/subagent/`
 10 - `extensions/questionnaire.ts`
 11 - `extensions/session-memory-prompt.ts`
 12 - `scripts/apply-pi-shutdown-hook-patch.py`
+13 - `scripts/session-memory-analyzer.py`
 13 - `scripts/session-memory-dispatcher.py`
 14 - `scripts/install-session-memory-dispatcher.service`
 15 - `TMP_CONTRACT.md`
 16 - `bin/agent-tmp-run` managed TMPDIR runner
    ...
 26 ## Notes
 27
 28 - Direct, compressed, low-noise communication is the default style.
 29 - Session close hook now prompts once before switch/fork/exit to encourage saving durable memory into agents-database.
-30 - Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context and the dispatcher turns that into a durable episode memory before ingest.
+31 - Session memory now uses an external local dispatcher on `127.0.0.1:17882`; the hook only captures session identity/context, the dispatcher enqueues metadata, and a background analyzer decides whether anything durable is worth saving.
+32 - The analyzer uses `pi` in background with a cheap model (`gpt-5.4-mini`) and thinking off when possible.
 31 - Use `./scripts/install-session-memory-dispatcher.service` to keep the dispatcher alive under systemd user service if desired.
 32 - The old `session_before_shutdown` runtime patch remains as fallback only if you choose to keep it enabled.
 33 - Reapply the runtime patch after Pi upgrades only if you still use that fallback: `./scripts/apply-pi-shutdown-hook-patch.py`
 34 - **Pending validation:** confirm the default communication mode auto-loads in every new Pi session.
    ...


#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import os
import subprocess
from datetime import datetime, timezone
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path

BASE_DIR = Path(__file__).resolve().parent.parent
JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
ANALYZER = Path(os.environ.get("PI_SESSION_MEMORY_ANALYZER", BASE_DIR / "scripts" / "session-memory-analyzer.py"))

def write_job(payload: dict[str, object]) -> Path:
    JOB_DIR.mkdir(parents=True, exist_ok=True)
    job_id = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%S%fZ")
    job_file = JOB_DIR / f"{job_id}.json"
    job = {
        "job_id": job_id,
        "queued_at": datetime.now(timezone.utc).isoformat(),
        "status": "queued",
        "payload": payload,
    }
    job_file.write_text(json.dumps(job, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
    return job_file

def launch_analyzer(job_file: Path) -> None:
    subprocess.Popen(
        ["python3", str(ANALYZER), "--job-file", str(job_file)],
        stdout=subprocess.DEVNULL,
        stderr=subprocess.DEVNULL,
        start_new_session=True,
        close_fds=True,
    )

class Handler(BaseHTTPRequestHandler):
    def do_POST(self):
        if self.path != "/api/session-memory":
            self.send_response(404)
            self.end_headers()
            return

        length = int(self.headers.get("Content-Length", "0") or "0")
        raw = self.rfile.read(length)
        try:
            payload = json.loads(raw.decode("utf-8"))
        except Exception as exc:
            self.send_response(400)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": f"invalid json: {exc}"}).encode())
            return

        try:
            job_file = write_job(payload)
            launch_analyzer(job_file)
            self.send_response(202)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"status": "queued", "job_file": str(job_file)}).encode())
        except Exception as exc:
            self.send_response(502)
            self.send_header("Content-Type", "application/json")
            self.end_headers()
            self.wfile.write(json.dumps({"error": str(exc)}).encode())

    def log_message(self, fmt, *args):
        return

def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--host", default="127.0.0.1")
    parser.add_argument("--port", type=int, default=17882)
    args = parser.parse_args()

    server = ThreadingHTTPServer((args.host, args.port), Handler)
    print(f"session-memory-dispatcher listening on http://{args.host}:{args.port}/api/session-memory", flush=True)
    try:
        server.serve_forever()
    except KeyboardInterrupt:
        return 0
    return 0

if __name__ == "__main__":
    raise SystemExit(main())


#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import os
import subprocess
import sys
from pathlib import Path
from typing import Any
from urllib import request

AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")
PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "openai-codex/gpt-5.4-mini")
PI_THINKING = os.environ.get("PI_SESSION_MEMORY_THINKING", "off")

def load_job(job_file: Path) -> dict[str, Any]:
    return json.loads(job_file.read_text(encoding="utf-8"))

def save_job(job_file: Path, payload: dict[str, Any]) -> None:
    job_file.write_text(json.dumps(payload, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")

def call_pi(prompt: str) -> str:
    cmd = [
        "pi",
        "-p",
        "--provider",
        "openai-codex",
        "--model",
        PI_MODEL,
        "--thinking",
        PI_THINKING,
        "--no-tools",
        "--no-session",
        prompt,
    ]
    proc = subprocess.run(cmd, capture_output=True, text=True)
    if proc.returncode != 0:
        raise RuntimeError(proc.stderr.strip() or proc.stdout.strip() or f"pi failed ({proc.returncode})")
    return proc.stdout.strip()

def ingest(memory: dict[str, Any]) -> dict[str, Any]:
    req = request.Request(
        f"{AGENTS_DB_API}/api/ingest",
        method="POST",
        data=json.dumps(memory).encode(),
        headers={"Content-Type": "application/json"},
    )
    with request.urlopen(req, timeout=30) as resp:
        return json.loads(resp.read().decode("utf-8"))

def extract_json(text: str) -> dict[str, Any]:
    raw = text.strip()
    if raw.startswith("```"):
        raw = raw.strip("`")
        raw = raw.split("\n", 1)[-1] if "\n" in raw else raw
    start = raw.find("{")
    end = raw.rfind("}")
    if start >= 0 and end > start:
        raw = raw[start : end + 1]
    return json.loads(raw)

def build_prompt(job: dict[str, Any]) -> str:
    return f"""You are deciding whether a Pi session has durable value.

Rules:
- Prefer NOT saving anything unless it is durable and reusable.
- Session metadata alone is not enough.
- Save only if the session contains a stable preference, decision, project fact, reusable artifact, or a blocker that matters later.
- If nothing durable exists, return save=false.
- Output JSON only. No markdown. No extra text.

Return this schema:
{{
  "save": boolean,
  "type": "profile" | "decision" | "project" | "artifact" | "episode",
  "subtype": string | null,
  "scope": "global" | "project",
  "title": string,
  "content": string,
  "source_ref": string,
  "reason": string
}}

Session metadata:
- session_id: {job.get('session_id')}
- session_file: {job.get('session_file')}
- cwd: {job.get('cwd')}
- scope: {job.get('scope')}
- reason: {job.get('reason')}
- user_messages: {job.get('user_messages')}
- assistant_messages: {job.get('assistant_messages')}
- last_user_text: {str(job.get('last_user_text') or '')[:2000]}
- last_assistant_text: {str(job.get('last_assistant_text') or '')[:2000]}
- trigger: {job.get('trigger')}

Branch excerpt JSON:
{json.dumps(job.get('branch') or [], ensure_ascii=False)[:30000]}
"""

def main() -> int:
    parser = argparse.ArgumentParser()
    parser.add_argument("--job-file", required=True)
    args = parser.parse_args()

    job_file = Path(args.job_file)
    job = load_job(job_file)
    job.setdefault("analysis", {})
    job["analysis"]["status"] = "running"
    save_job(job_file, job)

    try:
        raw = call_pi(build_prompt(job))
        analysis = extract_json(raw)
        job["analysis"]["raw"] = raw
        job["analysis"]["result"] = analysis
        job["analysis"]["status"] = "completed"

        if analysis.get("save"):
            memory = {
                "type": analysis.get("type") or "episode",
                "subtype": analysis.get("subtype"),
                "scope": analysis.get("scope") or job.get("scope") or "global",
                "status": "active",
                "source_kind": "manual",
                "title": analysis.get("title") or "Session insight",
                "content": analysis.get("content") or "",
                "source_ref": analysis.get("source_ref") or f"pi-session:{job.get('session_file') or job.get('session_id') or 'unknown'}",
                "origin_agent": "pi-session-memory-analyzer",
                "metadata": {
                    "job_file": str(job_file),
                    "session_id": job.get("session_id"),
                    "session_file": job.get("session_file"),
                    "cwd": job.get("cwd"),
                    "reason": job.get("reason"),
                    "user_messages": job.get("user_messages"),
                    "assistant_messages": job.get("assistant_messages"),
                    "analysis_reason": analysis.get("reason"),
                    "trigger": job.get("trigger"),
                },
            }
            saved = ingest(memory)
            job["analysis"]["memory_id"] = saved.get("id")
            job["analysis"]["saved"] = True
        else:
            job["analysis"]["saved"] = False
            job["analysis"]["memory_id"] = None

        save_job(job_file, job)
        print(json.dumps(job["analysis"], ensure_ascii=False))
        return 0
    except Exception as exc:
        job["analysis"]["status"] = "failed"
        job["analysis"]["error"] = str(exc)
        save_job(job_file, job)
        print(json.dumps(job["analysis"], ensure_ascii=False), file=sys.stderr)
        return 1

if __name__ == "__main__":
    raise SystemExit(main())


export default function (pi: ExtensionAPI) {
	let promptHandledForCurrentSession = false;

	async function runPrompt(ctx: any, reason: string, options?: { allowCancel?: boolean; title?: string; timeoutMs?: number }) {
		if (promptHandledForCurrentSession) return { cancel: false, skipped: true };
		if (!ctx.hasUI) return { cancel: false, skipped: true };

		const stats = getSessionStats(ctx);
		if (!stats.shouldPrompt) return { cancel: false, skipped: true };

		const allowCancel = options?.allowCancel ?? false;
		const timeoutMs = options?.timeoutMs;
		const title = options?.title || "Before closing this session";
		const choices = allowCancel ? [PROMPT_SAVE, PROMPT_SKIP, PROMPT_CANCEL] : [PROMPT_SAVE, PROMPT_SKIP];
		const dialogOptions = timeoutMs ? { timeout: timeoutMs } : undefined;
		const choice = await ctx.ui.select(title, choices, dialogOptions);

		if (choice === PROMPT_CANCEL || (allowCancel && choice === undefined)) {
			promptHandledForCurrentSession = false;
			return { cancel: true, skipped: false };
		}

		if (choice !== PROMPT_SAVE) {
			promptHandledForCurrentSession = true;
			return { cancel: false, skipped: true };
		}

		const payload = buildHookPayload(ctx, stats, reason);
		try {
			const result = await dispatchMemory({
				...payload,
				trigger: "session-memory-dispatcher",
			});
			promptHandledForCurrentSession = true;
			ctx.ui.notify(`Session analysis queued: ${result.job_file || result.status || "ok"}`, "info");
			return { cancel: false, skipped: false, queued: true, jobFile: result.job_file };
		} catch (error) {
			promptHandledForCurrentSession = false;
			const message = error instanceof Error ? error.message : String(error);
			ctx.ui.notify(message, "error");
			if (!allowCancel) return { cancel: false, skipped: true, error: message };
			const ok = await ctx.ui.confirm("Memory save failed", "Continue closing this session without saving?", dialogOptions);
			if (!ok) return { cancel: true, skipped: false, error: message };
			promptHandledForCurrentSession = true;
			return { cancel: false, skipped: true, error: message };
		}
	}

	pi.on("session_before_switch", async (event, ctx) => {
		const result = await runPrompt(ctx, `before_switch:${event.reason}`, { allowCancel: true, title: "Before closing this session" });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_before_fork", async (_event, ctx) => {
		const result = await runPrompt(ctx, "before_fork", { allowCancel: true, title: "Before forking away from this session" });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_before_shutdown", async (event, ctx) => {
		const result = await runPrompt(ctx, `before_shutdown:${event.reason}`, { allowCancel: true, title: "Before exit: save durable memory?", timeoutMs: 12000 });
		if (result.cancel) return { cancel: true };
		return undefined;
	});

	pi.on("session_shutdown", async (_event, ctx) => {
		await runPrompt(ctx, "shutdown_fallback", { allowCancel: false, title: "Before exit: save durable memory?", timeoutMs: 12000 });
	});

	pi.registerCommand("remember-session", {
		description: "Save a durable memory from the current session",
		handler: async (_args, ctx) => {
			promptHandledForCurrentSession = false;
			await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Save durable memory from this session" });
		},
	});
}


**Considering UI changes**

I’m thinking about renaming the "save failed" message to something like "Session analysis failed." That could be cleaner and more relevant. We could also notify that "Session metadata queued." The button labels might stay as save/skip, but perhaps I should rename that to "Queue analysis."

The UI prompt currently suggests saving durable memory, which might not align with a user’s intent if they only want metadata. Maybe updating those labels to "Queue analysis" and "Skip" would be more accurate.

**Updating prompt labels**

I’m considering updating the prompt text to "Queue session analysis." It might be good to have "Continue without queueing" as an option too. However, that change could affect the user experience since it’s about analysis, not memory. If the user clicks save, it should queue the analysis, so I want the labels to reflect that.

I'll adjust the internal constant names but change the user-visible text. If I add a cancel button, maybe I’ll title it "Before closing this session." I'll also ensure the notification uses "session analysis queued," and adjust the error message to "Session analysis failed."

const PROMPT_SAVE = "Save durable memory";
const PROMPT_SKIP = "Continue without saving";

const PROMPT_SAVE = "Queue session analysis";
const PROMPT_SKIP = "Continue without queueing";

const ok = await ctx.ui.confirm("Memory save failed", "Continue closing this session without saving?", dialogOptions);

const ok = await ctx.ui.confirm("Session analysis failed", "Continue closing this session without queueing?", dialogOptions);

description: "Save a durable memory from the current session",

description: "Queue a session analysis from the current session",

await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Save durable memory from this session" });

await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Queue session analysis from this session" });


Successfully replaced 4 block(s) in /mnt/rpi/pi-config/extensions/session-memory-dispatcher.ts.

   1 import path from "node:path";
   2 import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
   3
   4 const DISPATCH_URL = process.env.PI_SESSION_MEMORY_DISPATCH_URL || "http://127.0.0.1:17882/api/session-memory";
-  5 const PROMPT_SAVE = "Save durable memory";
-  6 const PROMPT_SKIP = "Continue without saving";
+  5 const PROMPT_SAVE = "Queue session analysis";
+  6 const PROMPT_SKIP = "Continue without queueing";
   7 const PROMPT_CANCEL = "Cancel";
   8
   9 function textFromMessage(message: any): string {
  10 	if (!message || !Array.isArray(message.content)) return "";
     ...
 127 			promptHandledForCurrentSession = false;
 128 			const message = error instanceof Error ? error.message : String(error);
 129 			ctx.ui.notify(message, "error");
 130 			if (!allowCancel) return { cancel: false, skipped: true, error: message };
-131 			const ok = await ctx.ui.confirm("Memory save failed", "Continue closing this session without saving?", dialogOptions);
+131 			const ok = await ctx.ui.confirm("Session analysis failed", "Continue closing this session without queueing?", dialogOptions);
 132 			if (!ok) return { cancel: true, skipped: false, error: message };
 133 			promptHandledForCurrentSession = true;
 134 			return { cancel: false, skipped: true, error: message };
 135 		}
     ...
 157 		await runPrompt(ctx, "shutdown_fallback", { allowCancel: false, title: "Before exit: save durable memory?", timeoutMs: 12000 });
 158 	});
 159
 160 	pi.registerCommand("remember-session", {
-161 		description: "Save a durable memory from the current session",
+161 		description: "Queue a session analysis from the current session",
 162 		handler: async (_args, ctx) => {
 163 			promptHandledForCurrentSession = false;
-164 			await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Save durable memory from this session" });
+164 			await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Queue session analysis from this session" });
 165 		},
 166 	});
 167 }


**Updating README and analyzer**

I'm considering updating some titles and strings in the README, which seems like an important task. I also need the patch analyzer to work with nested payloads and set the model to default. Editing these details is crucial to ensure everything functions smoothly. I'll tackle this because keeping documentation and tools in line is key for usability. Let’s get started on making these updates!

PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "openai-codex/gpt-5.4-mini")

PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "gpt-5.4-mini")

def call_pi(prompt: str) -> str:
    cmd = [
        "pi",
        "-p",
        "--provider",
        "openai-codex",
        "--model",
        PI_MODEL,
        "--thinking",
        PI_THINKING,
        "--no-tools",
        "--no-session",
        prompt,
    ]

def build_prompt(job: dict[str, Any]) -> str:
    return f"""You are deciding whether a Pi session has durable value.

def session_meta(job: dict[str, Any]) -> dict[str, Any]:
    payload = job.get("payload")
    if isinstance(payload, dict):
        return payload
    return job

def build_prompt(job: dict[str, Any]) -> str:
    meta = session_meta(job)
    return f"""You are deciding whether a Pi session has durable value.

- session_id: {job.get('session_id')}
- session_file: {job.get('session_file')}
- cwd: {job.get('cwd')}
- scope: {job.get('scope')}
- reason: {job.get('reason')}
- user_messages: {job.get('user_messages')}
- assistant_messages: {job.get('assistant_messages')}
- last_user_text: {str(job.get('last_user_text') or '')[:2000]}
- last_assistant_text: {str(job.get('last_assistant_text') or '')[:2000]}
- trigger: {job.get('trigger')}

Branch excerpt JSON:
{json.dumps(job.get('branch') or [], ensure_ascii=False)[:30000]}

- session_id: {meta.get('session_id')}
- session_file: {meta.get('session_file')}
- cwd: {meta.get('cwd')}
- scope: {meta.get('scope')}
- reason: {meta.get('reason')}
- user_messages: {meta.get('user_messages')}
- assistant_messages: {meta.get('assistant_messages')}
- last_user_text: {str(meta.get('last_user_text') or '')[:2000]}
- last_assistant_text: {str(meta.get('last_assistant_text') or '')[:2000]}
- trigger: {meta.get('trigger')}

Branch excerpt JSON:
{json.dumps(meta.get('branch') or [], ensure_ascii=False)[:30000]}

    job = load_job(job_file)
    job.setdefault("analysis", {})

    job = load_job(job_file)
    meta = session_meta(job)
    job.setdefault("analysis", {})

"scope": analysis.get("scope") or job.get("scope") or "global",

"scope": analysis.get("scope") or meta.get("scope") or "global",

"source_ref": analysis.get("source_ref") or f"pi-session:{job.get('session_file') or job.get('session_id') or 'unknown'}",

"source_ref": analysis.get("source_ref") or f"pi-session:{meta.get('session_file') or meta.get('session_id') or 'unknown'}",

                    "session_id": job.get("session_id"),
                    "session_file": job.get("session_file"),
                    "cwd": job.get("cwd"),
                    "reason": job.get("reason"),
                    "user_messages": job.get("user_messages"),
                    "assistant_messages": job.get("assistant_messages"),
                    "analysis_reason": analysis.get("reason"),
                    "trigger": job.get("trigger"),

                    "session_id": meta.get("session_id"),
                    "session_file": meta.get("session_file"),
                    "cwd": meta.get("cwd"),
                    "reason": meta.get("reason"),
                    "user_messages": meta.get("user_messages"),
                    "assistant_messages": meta.get("assistant_messages"),
                    "analysis_reason": analysis.get("reason"),
                    "trigger": meta.get("trigger"),


Successfully replaced 8 block(s) in /mnt/rpi/pi-config/scripts/session-memory-analyzer.py.

     ...
  10 from typing import Any
  11 from urllib import request
  12
  13 AGENTS_DB_API = os.environ.get("AGENTS_DB_API", "http://100.116.176.16:8091")
- 14 PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "openai-codex/gpt-5.4-mini")
+ 14 PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "gpt-5.4-mini")
  15 PI_THINKING = os.environ.get("PI_SESSION_MEMORY_THINKING", "off")
  16
  17
  18 def load_job(job_file: Path) -> dict[str, Any]:
     ...
  65         raw = raw[start : end + 1]
  66     return json.loads(raw)
  67
  68
+ 69 def session_meta(job: dict[str, Any]) -> dict[str, Any]:
+ 70     payload = job.get("payload")
+ 71     if isinstance(payload, dict):
+ 72         return payload
+ 73     return job
+ 74
+ 75
  69 def build_prompt(job: dict[str, Any]) -> str:
+ 77     meta = session_meta(job)
  70     return f"""You are deciding whether a Pi session has durable value.
  71
  72 Rules:
  73 - Prefer NOT saving anything unless it is durable and reusable.
     ...
  88   "reason": string
  89 }}
  90
  91 Session metadata:
- 92 - session_id: {job.get('session_id')}
- 93 - session_file: {job.get('session_file')}
- 94 - cwd: {job.get('cwd')}
- 95 - scope: {job.get('scope')}
- 96 - reason: {job.get('reason')}
- 97 - user_messages: {job.get('user_messages')}
- 98 - assistant_messages: {job.get('assistant_messages')}
- 99 - last_user_text: {str(job.get('last_user_text') or '')[:2000]}
-100 - last_assistant_text: {str(job.get('last_assistant_text') or '')[:2000]}
-101 - trigger: {job.get('trigger')}
+100 - session_id: {meta.get('session_id')}
+101 - session_file: {meta.get('session_file')}
+102 - cwd: {meta.get('cwd')}
+103 - scope: {meta.get('scope')}
+104 - reason: {meta.get('reason')}
+105 - user_messages: {meta.get('user_messages')}
+106 - assistant_messages: {meta.get('assistant_messages')}
+107 - last_user_text: {str(meta.get('last_user_text') or '')[:2000]}
+108 - last_assistant_text: {str(meta.get('last_assistant_text') or '')[:2000]}
+109 - trigger: {meta.get('trigger')}
 102
 103 Branch excerpt JSON:
-104 {json.dumps(job.get('branch') or [], ensure_ascii=False)[:30000]}
+112 {json.dumps(meta.get('branch') or [], ensure_ascii=False)[:30000]}
 105 """
 106
 107
 108 def main() -> int:
     ...
 111     args = parser.parse_args()
 112
 113     job_file = Path(args.job_file)
 114     job = load_job(job_file)
+123     meta = session_meta(job)
 115     job.setdefault("analysis", {})
 116     job["analysis"]["status"] = "running"
 117     save_job(job_file, job)
 118
     ...
 126         if analysis.get("save"):
 127             memory = {
 128                 "type": analysis.get("type") or "episode",
 129                 "subtype": analysis.get("subtype"),
-130                 "scope": analysis.get("scope") or job.get("scope") or "global",
+139                 "scope": analysis.get("scope") or meta.get("scope") or "global",
 131                 "status": "active",
 132                 "source_kind": "manual",
 133                 "title": analysis.get("title") or "Session insight",
 134                 "content": analysis.get("content") or "",
-135                 "source_ref": analysis.get("source_ref") or f"pi-session:{job.get('session_file') or job.get('session_id') or 'unknown'}",
+144                 "source_ref": analysis.get("source_ref") or f"pi-session:{meta.get('session_file') or meta.get('session_id') or 'unknown'}",
 136                 "origin_agent": "pi-session-memory-analyzer",
 137                 "metadata": {
 138                     "job_file": str(job_file),
-139                     "session_id": job.get("session_id"),
-140                     "session_file": job.get("session_file"),
-141                     "cwd": job.get("cwd"),
-142                     "reason": job.get("reason"),
-143                     "user_messages": job.get("user_messages"),
-144                     "assistant_messages": job.get("assistant_messages"),
+148                     "session_id": meta.get("session_id"),
+149                     "session_file": meta.get("session_file"),
+150                     "cwd": meta.get("cwd"),
+151                     "reason": meta.get("reason"),
+152                     "user_messages": meta.get("user_messages"),
+153                     "assistant_messages": meta.get("assistant_messages"),
 145                     "analysis_reason": analysis.get("reason"),
-146                     "trigger": job.get("trigger"),
+155                     "trigger": meta.get("trigger"),
 147                 },
 148             }
 149             saved = ingest(memory)
 150             job["analysis"]["memory_id"] = saved.get("id")
     ...


**Considering server setup**

I think using a short Python script server could be a good approach, even if it might seem unnecessary. I should compile and consider directing the analyzer with a fake PI to save false data. I also need to check on queueing and whether a dispatcher should spawn the analyzer. It could run with the fake PI, updating the job file, which would help validate the process. Let's move forward with the fake PI and a mock agents database, since the user only wants metadata and the analyzer won’t save information.

bash

python3 -m py_compile /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py /mnt/rpi/pi-config/scripts/session-memory-analyzer.py

rg -n "Session analysis queued|Queue session analysis|session-memory-jobs|gpt-5.4-mini|thinking off" /mnt/rpi/pi-config -S


(no output)


/mnt/rpi/pi-config/extensions/session-memory-dispatcher.ts:5:const PROMPT_SAVE = "Queue session analysis";
/mnt/rpi/pi-config/extensions/session-memory-dispatcher.ts:124:			ctx.ui.notify(`Session analysis queued: ${result.job_file || result.status || "ok"}`, "info");
/mnt/rpi/pi-config/extensions/session-memory-dispatcher.ts:164:			await runPrompt(ctx, "manual_command", { allowCancel: false, title: "Queue session analysis from this session" });
/mnt/rpi/pi-config/settings.json:4:  "defaultModel": "gpt-5.4-mini",
/mnt/rpi/pi-config/settings.json:9:    "openai-codex/gpt-5.4-mini",
/mnt/rpi/pi-config/scripts/session-memory-analyzer.py:14:PI_MODEL = os.environ.get("PI_SESSION_MEMORY_MODEL", "gpt-5.4-mini")
/mnt/rpi/pi-config/scripts/session-memory-dispatcher.py:13:JOB_DIR = Path(os.environ.get("PI_SESSION_MEMORY_JOB_DIR", BASE_DIR / "sessions" / "session-memory-jobs"))
/mnt/rpi/pi-config/README.md:32:- The analyzer uses `pi` in background with a cheap model (`gpt-5.4-mini`) and thinking off when possible.


set -euo pipefail
TMPDIR=$(mktemp -d)
FAKEBIN="$TMPDIR/bin"
mkdir -p "$FAKEBIN"
cat >"$FAKEBIN/pi" <<'SH'
#!/usr/bin/env bash
cat <<'JSON'
{"save":false,"type":"episode","subtype":null,"scope":"global","title":"ignore","content":"ignore","source_ref":"pi-session:fake","reason":"nothing durable"}
JSON
SH
chmod +x "$FAKEBIN/pi"
JOBDIR="$TMPDIR/jobs"
mkdir -p "$JOBDIR"
PATH="$FAKEBIN:$PATH" PI_SESSION_MEMORY_JOB_DIR="$JOBDIR" python3 /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py --host 127.0.0.1 --port 17883 >"$TMPDIR/dispatcher.log" 2>&1 &
DPID=$!
sleep 1
RESP=$(curl -fsS -X POST http://127.0.0.1:17883/api/session-memory -H 'Content-Type: application/json' -d '{"session_id":"test123","session_file":"/tmp/session.jsonl","cwd":"/home/sebas","reason":"reload","scope":"global","user_messages":2,"assistant_messages":3,"last_user_text":"hi","last_assistant_text":"ok","branch":[{"type":"message","message":{"role":"user","content":[{"type":"text","text":"hi"}]}}],"trigger":"session-memory-dispatcher"}')
sleep 2
cat "$TMPDIR/dispatcher.log"
echo "---RESP---"
echo "$RESP"
echo "---JOB---"
cat "$JOBDIR"/*.json
kill "$DPID" || true


session-memory-dispatcher listening on http://127.0.0.1:17883/api/session-memory
---RESP---
{"status": "queued", "job_file": "/tmp/tmp.nkGot85y0o/jobs/20260422T032311033960Z.json"}
---JOB---
{
  "job_id": "20260422T032311033960Z",
  "queued_at": "2026-04-22T03:23:11.034000+00:00",
  "status": "queued",
  "payload": {
    "session_id": "test123",
    "session_file": "/tmp/session.jsonl",
    "cwd": "/home/sebas",
    "reason": "reload",
    "scope": "global",
    "user_messages": 2,
    "assistant_messages": 3,
    "last_user_text": "hi",
    "last_assistant_text": "ok",
    "branch": [
      {
        "type": "message",
        "message": {
          "role": "user",
          "content": [
            {
              "type": "text",
              "text": "hi"
            }
          ]
        }
      }
    ],
    "trigger": "session-memory-dispatcher"
  },
  "analysis": {
    "status": "completed",
    "raw": "{\"save\":false,\"type\":\"episode\",\"subtype\":null,\"scope\":\"global\",\"title\":\"ignore\",\"content\":\"ignore\",\"source_ref\":\"pi-session:fake\",\"reason\":\"nothing durable\"}",
    "result": {
      "save": false,
      "type": "episode",
      "subtype": null,
      "scope": "global",
      "title": "ignore",
      "content": "ignore",
      "source_ref": "pi-session:fake",
      "reason": "nothing durable"
    },
    "saved": false,
    "memory_id": null
  }
}


**Addressing analyzer issues**

I need to check and possibly fix how the analyzer load utilizes job["payload"]. The user mentioned whether something valuable should be saved in memory. I also want to ensure the documentation for triggers, especially with the analyzer's name, is updated. I should verify the current running dispatcher on port 17882, as it may still be using an old version and will need a restart to take effect. It seems that the previous process might still be active, so that's something to monitor closely.

**Restarting the dispatcher process**

I need to determine whether we can manually kill and restart the service on port 17882 or if it’s managed differently since there’s no systemd service. The user mentioned “dejá el dispatcher,” so I think a restart will be better to ensure we're using the new version. I’ll find the PID of the current process and kill it. After that, I can start a new one, which should be straightforward. I'll use pgrep to locate it.

pgrep -af '/mnt/rpi/pi-config/scripts/session-memory-dispatcher.py --host 127.0.0.1 --port 17882' || true


State  Recv-Q Send-Q Local Address:Port  Peer Address:PortProcess
LISTEN 0      5          127.0.0.1:17882      0.0.0.0:*    users:(("python3",pid=426247,fd=3))


426247 python3 /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py --host 127.0.0.1 --port 17882
431074 /bin/bash -c pgrep -af '/mnt/rpi/pi-config/scripts/session-memory-dispatcher.py --host 127.0.0.1 --port 17882' || true


kill 426247 || true; sleep 1; python3 /mnt/rpi/pi-config/scripts/session-memory-dispatcher.py --host 127.0.0.1 --port 17882 >/tmp/session-memory-dispatcher.log 2>&1 & echo $!


State Recv-Q Send-Q Local Address:Port Peer Address:PortProcess


sleep 1; ss -ltnp '( sport = :17882 )' || true

cat /tmp/session-memory-dispatcher.log || true


State  Recv-Q Send-Q Local Address:Port  Peer Address:PortProcess
LISTEN 0      5          127.0.0.1:17882      0.0.0.0:*    users:(("python3",pid=431087,fd=3))


session-memory-dispatcher listening on http://127.0.0.1:17882/api/session-memory


**Assessing dispatcher and code issues**

I’m considering whether to terminate the temporary test dispatcher 17883 since it may have ended unexpectedly. There’s also a thought to inspect the git diff and possibly remove the old analyzer import for `sys`. I need to check if the dispatcher returns a status of 202, as the `dispatchMemory` extension expects a successful response.

There seems to be potential issues with how the analyzer handles job prompts and boolean values, particularly if “save” is checked and how it's parsed. I need to approach that carefully.

**Evaluating memory and code practices**

I’m considering how to handle the `analysis.get("save")` check by using `bool()` to ensure I correctly interpret JSON booleans. There’s a potential issue with `extract_json` regarding backticks being stripped, which might not be ideal.

I should also update the README to clarify that the analyzer runs with a cheap model in the background. It seems beneficial to save the user's preference for only saving metadata, as the developer suggests creating memory for new information that could be useful later. So, I’ll plan to store this decision effectively!

~/.agents/skills/memory-write/memory-write --type decision --scope project --title "Session hook should queue analysis, not save memory directly" --content "The session close hook should hand metadata to a background analyzer. The analyzer runs pi with a cheap model (gpt-5.4-mini, thinking off when possible), decides if anything durable is worth saving, and only then writes to agents-database. Session metadata itself is kept as job/state, not as durable memory by default." --origin-agent "ballbox-first" --source-ref "repo:/mnt/rpi/pi-config"


Session hook should queue analysis, not save memory directly

The session close hook should hand metadata to a background analyzer. The analyzer runs pi with a cheap model (gpt-5.4-mini, thinking off when possible), decides if anything durable is worth saving, and only then writes to agents-database. Session metadata itself is kept as job/state, not as durable memory by default.

Summary: The session close hook should hand metadata to a background analyzer. The analyzer runs pi with a cheap model (gpt-5.4-mini, thinking off when possible), decides if anything durab…


**Considering updates and checks**

I'm contemplating whether to update the dispatcher startup service, but it might not be necessary. Should I add a service for the analyzer? Probably not, since it's spawned on demand. I need to check the git status and might remove job files from the test since they were written to /tmp. I'll also look into fixing the confirm message in `extensions/session-memory-dispatcher.ts`. I should check if the analyzer script is executable, but it's fine if python3 is invoked directly. Lastly, figuring out the git diff for a summary sounds like a good plan.

git -C /mnt/rpi/pi-config status --short


 README.md                                          |   4 +-
 extensions/session-memory-dispatcher.ts            |  16 +-
 .../session-memory-analyzer.cpython-313.pyc        | Bin 8291 -> 9218 bytes
 .../session-memory-dispatcher.cpython-313.pyc      | Bin 5067 -> 5856 bytes
 scripts/session-memory-analyzer.py                 | 267 +++++++++++----------
 scripts/session-memory-dispatcher.py               |  57 +++--
 settings.json                                      |   2 +-
 7 files changed, 180 insertions(+), 166 deletions(-)


 M README.md
 M extensions/session-memory-dispatcher.ts
 M scripts/__pycache__/session-memory-analyzer.cpython-313.pyc
 M scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc
 M scripts/session-memory-analyzer.py
 M scripts/session-memory-dispatcher.py
 M settings.json


**Inspecting settings change**

Oops, it looks like settings.json has changed again. I wonder if that's due to some previous default thinking. I should really take a look to find out what's going on. Also, I've noticed that the .pyc files have been tracked with changes, so I might need to revert those too. I'm curious why the settings changed—could it be from an earlier stage that hasn't been restored yet? I definitely need to inspect the differences.

git -C /mnt/rpi/pi-config diff -- settings.json

git -C /mnt/rpi/pi-config diff -- scripts/__pycache__/session-memory-analyzer.cpython-313.pyc scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc


diff --git a/settings.json b/settings.json
index e9c72a6..3867bcb 100644
--- a/settings.json
+++ b/settings.json
@@ -2,7 +2,7 @@
   "lastChangelogVersion": "0.68.0",
   "defaultProvider": "openai-codex",
   "defaultModel": "gpt-5.4-mini",
-  "defaultThinkingLevel": "low",
+  "defaultThinkingLevel": "medium",
   "enabledModels": [
     "openai-codex/gpt-5.4",
     "google-gemini-cli/gemini-3-flash-preview",


diff --git a/scripts/__pycache__/session-memory-analyzer.cpython-313.pyc b/scripts/__pycache__/session-memory-analyzer.cpython-313.pyc
index d378672..4e01aac 100644
Binary files a/scripts/__pycache__/session-memory-analyzer.cpython-313.pyc and b/scripts/__pycache__/session-memory-analyzer.cpython-313.pyc differ
diff --git a/scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc b/scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc
index 429326e..3e63121 100644
Binary files a/scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc and b/scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc differ


**Restoring settings and files**

I need to revert some settings and consider removing .pyc changes, though they might be tracked. I’m thinking I could use git to restore the settings and possibly the .pyc files. But wait, if they’re being tracked, deleting them might not be the right approach. I think I should focus on restoring both the settings and .pyc files to ensure everything is as it should be!

cd /mnt/rpi/pi-config && git restore settings.json scripts/__pycache__/session-memory-analyzer.cpython-313.pyc scripts/__pycache__/session-memory-dispatcher.cpython-313.pyc && git status --short


 M README.md
 M extensions/session-memory-dispatcher.ts
 M scripts/session-memory-analyzer.py
 M scripts/session-memory-dispatcher.py


**Evaluating system checks**

I need to consider if there are any leftover references in the code. I might update the readme to include the job directory. It seems important to check the dispatcher and analyzer outputs from the current running service since it restarted. I could run a test via HTTP against port 17882, but I’m thinking it’s not absolutely necessary. Still, it might be good to ensure the current dispatcher uses the new code. I should at least verify if `curl` returns a 202 status.

**Consolidating tasks and updates**

I’m realizing we don’t want to create unnecessary job files, so using a test with a fake Pi instead of the actual service sounds like a good idea since I’ve already validated the code. I should probably update command titles or prompt labels to reflect queueing. It’s also important to ensure that `build_prompt` uses a nested `job`. Checking the current dispatcher log might not be necessary. I also need to remove references to the old `session-memory-analyzer.py` in the README and mention that the analyzer now uses a cheaper model with `thinking off`.

**Reviewing analyzer implementation**

I need to think about whether to implement a stop reading analyzer. Since the user asked for a direct answer, I should explain that it’s done. I could mention that the session metadata queue and analyzer now handle memory, plus that the current code has been validated with a fake Pi. I might also note that the dispatcher was restarted on port 17882. The hook about saving durable memory still applies, and we updated the prompt labels. Lastly, I should inspect the git diff stat for any final changes.

git -C /mnt/rpi/pi-config diff --stat && git -C /mnt/rpi/pi-config status --short


 README.md                               |   4 +-
 extensions/session-memory-dispatcher.ts |  16 +-
 scripts/session-memory-analyzer.py      | 267 ++++++++++++++++----------------
 scripts/session-memory-dispatcher.py    |  57 ++++---
 4 files changed, 179 insertions(+), 165 deletions(-)
 M README.md
 M extensions/session-memory-dispatcher.ts
 M scripts/session-memory-analyzer.py
 M scripts/session-memory-dispatcher.py


Hecho.

Ahora quedó así:

- **dispatcher**: solo guarda la metadata de la sesión como job y dispara el background
- **analyzer**: corre aparte, llama a `pi` con:
  - `--model gpt-5.4-mini`
  - `--thinking off`
  - `--no-tools`
  - `--no-session`
- el analyzer decide si hay algo durable
  - si no, no guarda nada
  - si sí, recién ahí ingesta en `agents-database`

Cambios visibles:
- el prompt ya dice **“Queue session analysis”**
- la UI notifica **“Session analysis queued”**
- los jobs quedan en `sessions/session-memory-jobs/`

Validé:
- `py_compile` pasa
- el flujo dispatcher → analyzer funciona con un `pi` fake
- el dispatcher live en `127.0.0.1:17882` ya fue reiniciado con el código nuevo

Si querés, el próximo paso es ajustar el prompt del analyzer para que priorice todavía más **metadata útil de sesión** y sea más conservador al guardar memorias.


te fijas si guardo ahi? hice reload
also: ahora dice "Memory saved: undefined"


**Checking job status**

I’m focusing on figuring out the current status of session memory jobs and if there’s a potential bug in the UI. The term "undefined" could indicate that the dispatcher response is missing either the job_file or the result object, which might be undefined. I should inspect the current code to ensure I'm not using an outdated instance or response shape. It might be important to examine the dispatcher logs and check the job directory as well. I'll need to use the appropriate tools for this.

find /mnt/rpi/pi-config/sessions/session-memory-jobs -maxdepth 1 -type f | sort | tail -n 20

curl -fsSL 'http://100.116.176.16:8091/api/search?q=%22Session%20summary%22%20%22session-memory-analyzer%22&scope=global&scope=project&limit=20' | jq -r '.results[] | [.memory.id,.memory.title,.memory.created_at,.memory.origin_agent,.memory.source_ref,.memory.metadata.reason,.memory.metadata.session_file] | @tsv'

cat /tmp/session-memory-dispatcher.log 2>/dev/null || true


mem_69fa680cbaa24929af00ec1ce0d5ce6d	Research step: capture https://help.matchable.io/en/articles/13-getting-started-with-the-matchable-trai	2026-03-24T14:20:37.617460+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_70d7fe1e42bf4b988b34cc4f3234a66a	Research step: capture https://byaiteam.com/blog/2025/12/20/ai-agent-memory-architectures-retrieval-gov	2026-03-26T18:15:49.638107+00:00		personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016
mem_7e0612ee062a46f9a2e7aaa7abc7361a	Research step: capture https://help.matchable.io/en/articles/44-create-and-manage-your-course-schedule	2026-03-24T14:20:37.387701+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_2d0d587d6a284852b826c64bd4103069	Research step: capture https://help.matchable.io/en/articles/22-manage-credits	2026-03-24T14:20:37.594027+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_46b8191e6b6a47d0864670962cd91a13	Research step: capture https://help.matchable.io/en/articles/38-getting-started-with-your-storefront	2026-03-24T14:20:37.415947+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_d33e0337d9ae4ea7a794a42545447f1e	Search results: site:matchable.crunch.help OR site:help.matchable.io Matchable onboarding bookin	2026-03-24T14:18:48.243844+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_5c96bad891f9449e9013c4410693d7ff	Search results: site:matchable.io Matchable product features use cases	2026-03-24T14:18:24.351330+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_74d79010be694100b78c82ae330c3136	Research step: capture https://help.matchable.io/en/articles/41-getting-started-with-courses	2026-03-24T14:20:37.436447+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_77d1e1c4121e473883c64c28c5e58645	Research step: capture https://business.matchable.io/	2026-03-24T14:20:16.377341+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_d272073bed66483ea27fba683613235b	Search results: periodic memory consolidation agent memory knowledge base deduplication TTL deca	2026-03-26T18:15:25.917490+00:00		personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016
mem_e929ceb6d192420bad79a46f51f525d5	Research step: capture https://help.matchable.io/en/articles/10-how-to-book-a-training	2026-03-24T14:20:37.579129+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_524014155c22470e945190a9839e58f2	Research step: capture https://help.matchable.io/en/articles/17-manage-trainings-and-classes	2026-03-24T14:20:37.526642+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
mem_00043e2e27144c63a0b822c509ea5b9a	Research step: capture https://help.matchable.io/en/articles/23-how-to-use-credits	2026-03-24T14:20:37.351700+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
legacy_source_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_03ec74fd2f55f797	Made-in-China outdoor digital signage category	2026-03-13T14:01:39.653556+00:00	personal-agent	personal-agent:run:bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7
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mem_6ff7463ef2fd4179beacb973aa07c291	Research step: capture https://www.matchable.io/	2026-03-24T14:20:17.674123+00:00	personal-agent	personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2
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session-memory-dispatcher listening on http://127.0.0.1:17882/api/session-memory


cat /mnt/rpi/pi-config/sessions/session-memory-jobs/20260422T032521567405Z.json | jq .

sed -n '1,220p' /mnt/rpi/pi-config/scripts/session-memory-analyzer.py