fix: apply saved todo config on next organize

.gitignore

@@ -1,4 +1,5 @@
 node_modules/
+.agentmemory-python/
 dist/
 artifacts/
 *.tsbuildinfo

README.md

@@ -36,7 +36,7 @@ Then refresh the viewer: the dashboard fills with browsable sessions, memory, an
 
 - **Codex sessions (local):** the daemon scans your Codex session directories (`~/.codex/sessions` and `~/.codex/archived_sessions`) on startup and on an interval. Toggle with `AGENTMEMORY_CODEX_AUTOSCAN=false`; tune the cadence with `AGENTMEMORY_CODEX_SCAN_INTERVAL_MS` (default 5 min). You can also import a transcript on demand from a source checkout with `node dist/cli.mjs import-jsonl <path>` (installed package binary: `agentmemory-lab import-jsonl <path>`).
 - **Browser AI conversations:** load the browser extension under [`browser-extension/`](browser-extension/); it captures supported AI sites and posts them to the local daemon, which extracts todos into the same queue.
-- **LangExtract extraction (optional):** install Python deps with `python3 -m pip install -r requirements-langextract.txt` (includes SOCKS proxy support). Configure it during first-run setup (`node dist/cli.mjs --reset` from source, or `agentmemory-lab --reset` when installed), from the viewer Settings panel, or in `~/.agentmemory/.env`: `AGENTMEMORY_TODO_EXTRACTOR=langextract`, `LANGEXTRACT_PYTHON=/path/to/python`, `LANGEXTRACT_PROVIDER=openai`, `LANGEXTRACT_MODEL=deepseek/deepseek-v4-flash`, `LANGEXTRACT_BASE_URL=https://api.novita.ai/openai/v1`, `LANGEXTRACT_API_KEY=<runtime secret>`, and optionally `AGENTMEMORY_TODO_EXTRACT_TIMEOUT_MS=120000`. Trigger it from the To-Do tab or with `POST /agentmemory/todo-extract/generate`.
+- **LangExtract extraction (optional):** `npm install` creates a project-local `.agentmemory-python` environment and installs the Python deps from `requirements-langextract.txt` (includes SOCKS proxy support). Configure it during first-run setup (`node dist/cli.mjs --reset` from source, or `agentmemory-lab --reset` when installed), from the viewer Settings panel, or in `~/.agentmemory/.env`: `AGENTMEMORY_TODO_EXTRACTOR=langextract`, `LANGEXTRACT_PROVIDER=openai`, `LANGEXTRACT_MODEL=deepseek/deepseek-v4-flash`, `LANGEXTRACT_BASE_URL=https://api.novita.ai/openai/v1`, `LANGEXTRACT_API_KEY=<runtime secret>`, and optionally `AGENTMEMORY_TODO_EXTRACT_TIMEOUT_MS=120000`. Set `LANGEXTRACT_PYTHON=/path/to/python` only when you want to override the managed environment. Trigger it from the To-Do tab or with `POST /agentmemory/todo-extract/generate`.
 - **Isolated data roots:** set `AGENTMEMORY_HOME=/path/to/data` to keep AI Todo runtime files (`.env`, preferences, pidfiles, snapshots) separate from your normal `~/.agentmemory`. This does not change the Codex session source; local Codex history is still read from `~/.codex/sessions` and `~/.codex/archived_sessions`.
 - **First-run setup:** the first-run CLI model choice configures To-Do extraction — it seeds the `LANGEXTRACT_*` settings above for the model you pick (or keeps the rules extractor if you skip). The legacy memory compression/consolidation/embeddings provider is an advanced `.env`-only setting.
 

package.json

@@ -19,6 +19,7 @@
   "scripts": {
     "build": "tsdown && node scripts/build-viewer-html.mjs --check && (cp iii-config.yaml dist/ 2>/dev/null || true) && (cp iii-config.docker.yaml dist/ 2>/dev/null || true) && (cp docker-compose.yml dist/ 2>/dev/null || true) && (cp .env.example dist/ 2>/dev/null || true) && mkdir -p dist/viewer/agent-avatars dist/viewer/demo dist/functions && cp src/viewer/index.html dist/viewer/ && cp src/viewer/favicon.svg dist/viewer/ && cp src/viewer/agent-avatars/* dist/viewer/agent-avatars/ && cp src/viewer/demo/* dist/viewer/demo/ && cp src/functions/todo-extract-langextract.py dist/functions/ && cp src/functions/todo-update-llm.py dist/functions/",
     "dev": "tsx src/index.ts",
+    "postinstall": "node scripts/install-langextract.mjs",
     "viewer:build": "node scripts/build-viewer-html.mjs",
     "viewer:watch": "node scripts/build-viewer-html.mjs --watch",
     "start": "node dist/cli.mjs",
@@ -64,10 +65,12 @@
   "files": [
     "dist/",
     "plugin/",
+    "scripts/install-langextract.mjs",
     "iii-config.yaml",
     "iii-config.docker.yaml",
     "docker-compose.yml",
     ".env.example",
+    "requirements-langextract.txt",
     "LICENSE",
     "README.md",
     "AGENTS.md"

scripts/install-langextract.mjs

@@ -0,0 +1,32 @@
+import { existsSync } from "node:fs";
+import { join } from "node:path";
+import { spawnSync } from "node:child_process";
+
+const root = process.cwd();
+const requirements = join(root, "requirements-langextract.txt");
+const venv = join(root, ".agentmemory-python");
+const python = process.platform === "win32" ? join(venv, "Scripts", "python.exe") : join(venv, "bin", "python");
+
+function run(command, args) {
+  return spawnSync(command, args, { stdio: "inherit" });
+}
+
+if (!existsSync(requirements)) {
+  process.stderr.write("[agentmemory] requirements-langextract.txt not found; skipping LangExtract setup.\n");
+  process.exit(0);
+}
+
+if (!existsSync(python)) {
+  const created = run("python3", ["-m", "venv", venv]);
+  if (created.status !== 0) {
+    process.stderr.write("[agentmemory] Could not create .agentmemory-python venv; set LANGEXTRACT_PYTHON manually.\n");
+    process.exit(0);
+  }
+}
+
+const installed = run(python, ["-m", "pip", "install", "-r", requirements]);
+if (installed.status !== 0) {
+  process.stderr.write("[agentmemory] LangExtract Python deps were not installed; set LANGEXTRACT_PYTHON manually.\n");
+  process.exit(0);
+}
+

src/config.ts

@@ -1,6 +1,8 @@
+import { spawnSync } from "node:child_process";
 import { existsSync, mkdirSync, readFileSync, writeFileSync } from "node:fs";
-import { join } from "node:path";
+import { dirname, join, resolve } from "node:path";
 import { homedir } from "node:os";
+import { fileURLToPath } from "node:url";
 import type {
   AgentMemoryConfig,
   ProviderConfig,
@@ -91,9 +93,10 @@ function maskSecret(value: string | undefined): string {
 
 export function getTodoExtractorUserConfig(): Record<string, string | boolean> {
   const env = getMergedEnv();
+  const runtime = detectLangExtractRuntime(env);
   return {
     AGENTMEMORY_TODO_EXTRACTOR: env["AGENTMEMORY_TODO_EXTRACTOR"] || "auto",
-    LANGEXTRACT_PYTHON: env["LANGEXTRACT_PYTHON"] || "python3",
+    LANGEXTRACT_PYTHON: resolveLangExtractPython(env),
     LANGEXTRACT_MODEL: normalizeTodoExtractorModel(env["LANGEXTRACT_MODEL"]),
     LANGEXTRACT_PROVIDER: normalizeTodoExtractorProvider(env["LANGEXTRACT_PROVIDER"]),
     LANGEXTRACT_BASE_URL: env["LANGEXTRACT_BASE_URL"] || DEFAULT_LANGEXTRACT_BASE_URL,
@@ -106,9 +109,43 @@ export function getTodoExtractorUserConfig(): Record<string, string | boolean> {
       env["AGENTMEMORY_TODO_EXTRACT_MAX_INTERACTIONS_PER_SESSION"] || String(DEFAULT_TODO_EXTRACT_MAX_INTERACTIONS),
     LANGEXTRACT_API_KEY_CONFIGURED: hasRealValue(env["LANGEXTRACT_API_KEY"]),
     LANGEXTRACT_API_KEY_MASKED: maskSecret(env["LANGEXTRACT_API_KEY"]),
+    LANGEXTRACT_RUNTIME_READY: runtime.ready,
+    LANGEXTRACT_RUNTIME_ERROR: runtime.error,
   };
 }
 
+function detectLangExtractRuntime(env: Record<string, string>): { ready: boolean; error: string } {
+  const python = resolveLangExtractPython(env);
+  const result = spawnSync(python, ["-c", detectLangExtractRuntimeProbe()], {
+    encoding: "utf8",
+    timeout: 3000,
+  });
+  if (result.status === 0) return { ready: true, error: "" };
+  return {
+    ready: false,
+    error: String(result.stderr || result.error?.message || "langextract unavailable").replace(/\s+/g, " ").trim(),
+  };
+}
+
+export function detectLangExtractRuntimeProbe(): string {
+  return "import importlib.util; raise SystemExit(0 if importlib.util.find_spec('langextract') else 1)";
+}
+
+export function resolveLangExtractPython(env?: Record<string, string>): string {
+  const source = env ?? getMergedEnv();
+  const configured = source["LANGEXTRACT_PYTHON"]?.trim();
+  if (configured && configured !== "python3") return configured;
+  const moduleRoot = resolve(dirname(fileURLToPath(import.meta.url)), "..");
+  const candidates = [process.cwd(), moduleRoot].map((root) =>
+    process.platform === "win32"
+      ? join(root, ".agentmemory-python", "Scripts", "python.exe")
+      : join(root, ".agentmemory-python", "bin", "python"),
+  );
+  const local = candidates.find((candidate) => existsSync(candidate));
+  if (local) return local;
+  return configured || "python3";
+}
+
 export function normalizeTodoExtractorModel(value: string | undefined): string {
   const model = value?.trim();
   return model && !LEGACY_LANGEXTRACT_MODELS.has(model) ? model : DEFAULT_LANGEXTRACT_MODEL;

src/functions/todo-extract.ts

@@ -15,6 +15,7 @@ import {
   getEnvVar,
   normalizeTodoExtractorModel,
   normalizeTodoExtractorProvider,
+  resolveLangExtractPython,
 } from "../config.js";
 import { scanCodexSource } from "./source-scan-codex.js";
 import {
@@ -821,7 +822,7 @@ export async function runLangExtractSidecar(
 ): Promise<ExtractedTodo[]> {
   const script = sidecarPath();
   if (!script) throw new Error("langextract sidecar not found");
-  const python = getEnvVar("LANGEXTRACT_PYTHON") || "python3";
+  const python = resolveLangExtractPython();
   const env = { ...process.env };
   for (const key of SIDE_CAR_ENV_KEYS) {
     const value = getEnvVar(key);
@@ -947,7 +948,14 @@ function parseCheckpoint(cursor: string | undefined): Record<string, string> {
   if (!cursor) return {};
   try {
     const parsed = JSON.parse(cursor) as unknown;
-    return parsed && typeof parsed === "object" ? parsed as Record<string, string> : {};
+    if (!parsed || typeof parsed !== "object") return {};
+    const raw = parsed as Record<string, unknown>;
+    if (raw.__engine !== "langextract") return {};
+    const out: Record<string, string> = {};
+    for (const [key, value] of Object.entries(raw)) {
+      if (key !== "__engine" && typeof value === "string") out[key] = value;
+    }
+    return out;
   } catch {
     return {};
   }
@@ -1261,7 +1269,7 @@ async function runCleanupSidecar(
 ): Promise<LlmCleanupItem[]> {
   const script = sidecarPath(CLEANUP_SIDE_CAR);
   if (!script) throw new Error("cleanup sidecar not found");
-  const python = getEnvVar("LANGEXTRACT_PYTHON") || "python3";
+  const python = resolveLangExtractPython();
   const env = { ...process.env };
   for (const key of SIDE_CAR_ENV_KEYS) {
     const value = getEnvVar(key);
@@ -2001,14 +2009,16 @@ export async function generateTodosFromSessions(
       existing.add(titleKey);
       seenTitles.push(titleKey);
     }
-    processed[session.id] = key;
+    if (engine === "langextract" && !fallbackReason) processed[session.id] = key;
   }
 
-  await kv.set(KV.scanCheckpoints, checkpointId, {
-    sourceId: checkpointId,
-    cursor: JSON.stringify(processed),
-    lastSuccessAt: now,
-  });
+  if (Object.keys(processed).length) {
+    await kv.set(KV.scanCheckpoints, checkpointId, {
+      sourceId: checkpointId,
+      cursor: JSON.stringify({ __engine: "langextract", ...processed }),
+      lastSuccessAt: now,
+    });
+  }
 
   return {
     success: true,

src/triggers/api.ts

@@ -522,7 +522,7 @@ export function registerApiTriggers(
           success: true,
           envPath: getUserEnvPath(),
           config: getTodoExtractorUserConfig(),
-          restartRequired: true,
+          restartRequired: false,
         },
       };
     },