Rewrite stretched interjections so narration reads them correctly

app.py

@@ -17,6 +17,8 @@ from zoneinfo import ZoneInfo
 import requests
 from fastapi import FastAPI, Request
 from fastapi.responses import FileResponse, JSONResponse, RedirectResponse
+from starlette.concurrency import run_in_threadpool
+from google.auth.exceptions import RefreshError
 from google.auth.transport.requests import Request as GoogleRequest
 from google.oauth2.credentials import Credentials
 from google_auth_oauthlib.flow import Flow
@@ -79,6 +81,10 @@ GLOBAL_DEFAULTS = {
     "aspect_ratio": "9:16",
     "target_seconds": 60,
     "clip_seconds": 8,
+    "scene_timing": "narration",
+    "low_memory": True,
+    "free_models_between_stages": True,
+    "cpu_threads": 0,
     "error_cooldown_minutes": 5,
     "work_hours_enabled": False,
     "work_days": "mon,tue,wed,thu,fri,sat,sun",
@@ -298,7 +304,19 @@ def published_root(s):
     return resolve_storage(s["storage_dir"]) / "published"
 
 
+def volume_ready(path):
+    parts = Path(path).resolve().parts
+    if len(parts) >= 3 and parts[1] == "Volumes":
+        mount = Path("/Volumes") / parts[2]
+        if not os.path.ismount(str(mount)):
+            return False, str(mount)
+    return True, ""
+
+
 def writable(root):
+    ok, mount = volume_ready(root)
+    if not ok:
+        raise ValueError(f"The volume {mount} is not mounted. Connect the disk, or pick a different folder in Settings")
     try:
         root.mkdir(parents=True, exist_ok=True)
         probe = root / ".write_test"
@@ -485,6 +503,15 @@ def sweep_temp(temp, max_age_hours=1):
         logger.info("Cleaned %d old items from the temp folder", removed)
 
 
+def check_storage_alive(s):
+    root = resolve_storage(s["storage_dir"])
+    ok, mount = volume_ready(root)
+    if not ok:
+        raise RuntimeError(f"The volume {mount} is no longer mounted, the disk may have unmounted. Nothing more was written")
+    if not root.is_dir():
+        raise RuntimeError(f"The storage folder {root} disappeared, the disk may have unmounted")
+
+
 def prepare_storage(s):
     root = validate_storage(s["storage_dir"])
     free = free_gb(root)
@@ -683,6 +710,49 @@ def record_slot(pid, iso):
         save_state(st)
 
 
+def recent_stories(pid):
+    return load_state().get("stories", {}).get(pid, [])
+
+
+def remember_story(pid, script):
+    names = re.findall(r"\b([A-Z][a-z]{2,})\b", script.get("characters", ""))
+    stop = {"The", "His", "Her", "Their", "With", "And", "Who", "She", "They", "This", "That", "Mr", "Mrs", "Miss"}
+    names = [n for n in dict.fromkeys(names) if n not in stop][:6]
+    with state_lock:
+        st = load_state()
+        lst = st.setdefault("stories", {}).setdefault(pid, [])
+        lst.append({"title": script["title"], "names": names})
+        st["stories"][pid] = lst[-50:]
+        save_state(st)
+
+
+def channel_titles(s):
+    try:
+        yt = youtube_client(s["profile_id"])
+        ch = yt.channels().list(part="contentDetails", mine=True).execute().get("items", [])
+        if not ch:
+            return []
+        uploads = ch[0]["contentDetails"]["relatedPlaylists"]["uploads"]
+        items = yt.playlistItems().list(part="snippet", playlistId=uploads, maxResults=50).execute().get("items", [])
+        titles = [re.sub(r"\s*#shorts\b", "", i["snippet"]["title"], flags=re.I).strip() for i in items]
+        return [x for x in titles if x]
+    except Exception as e:
+        logger.warning("Could not read existing channel titles: %s", e)
+        return []
+
+
+def past_stories(s):
+    past = list(recent_stories(s["profile_id"]))
+    for title in s.get("_channel_titles", []):
+        names = re.findall(r"\b([A-Z][a-z]{2,})'s\b", title)
+        past.append({"title": title, "names": names})
+    return past
+
+
+def norm_title(t):
+    return re.sub(r"[^a-z0-9 ]", "", str(t).lower()).strip()
+
+
 def load_state():
     with state_lock:
         st = read_json(STATE_FILE, {})
@@ -716,7 +786,14 @@ def load_creds(pid):
         return None
     creds = Credentials.from_authorized_user_file(str(tf), SCOPES)
     if creds.expired and creds.refresh_token:
-        creds.refresh(GoogleRequest())
+        try:
+            creds.refresh(GoogleRequest())
+        except RefreshError:
+            raise RuntimeError(
+                f"The YouTube sign in for profile '{load_profile(pid)['name']}' has expired. "
+                "Unlink and link the channel again in Settings. "
+                "Publishing the app in Google Cloud stops this happening every week"
+            ) from None
         tf.write_text(creds.to_json(), encoding="utf-8")
     return creds
 
@@ -819,14 +896,22 @@ def fetch_trending(s, query=None):
     return kept
 
 
-def ollama_tags(s):
+_tags_cache = {"at": 0.0, "models": []}
+
+
+def ollama_tags(s, max_age=60):
+    now = datetime.now().timestamp()
+    if _tags_cache["models"] and now - _tags_cache["at"] < max_age:
+        return _tags_cache["models"]
     try:
-        r = requests.get(f"{s['ollama_url'].rstrip('/')}/api/tags", timeout=10)
+        r = requests.get(f"{s['ollama_url'].rstrip('/')}/api/tags", timeout=5)
         r.raise_for_status()
-        return sorted(m["name"] for m in r.json().get("models", []) if m.get("name"))
+        models = sorted(m["name"] for m in r.json().get("models", []) if m.get("name"))
+        _tags_cache.update({"at": now, "models": models})
+        return models
     except Exception as e:
         logger.debug("Could not list Ollama models: %s", e)
-        return []
+        return _tags_cache["models"]
 
 
 _caps_cache = {}
@@ -836,7 +921,7 @@ def ollama_caps(s, model):
     if model in _caps_cache:
         return _caps_cache[model]
     try:
-        r = requests.post(f"{s['ollama_url'].rstrip('/')}/api/show", json={"model": model}, timeout=10)
+        r = requests.post(f"{s['ollama_url'].rstrip('/')}/api/show", json={"model": model}, timeout=5)
         if r.status_code != 200:
             return None
         caps = set(r.json().get("capabilities") or [])
@@ -895,6 +980,21 @@ def ollama_pull(s, model):
     return True
 
 
+def unload_ollama(s, model):
+    model = (model or "").strip()
+    if not model or not s.get("free_models_between_stages", True):
+        return
+    try:
+        requests.post(
+            f"{s['ollama_url'].rstrip('/')}/api/generate",
+            json={"model": model, "prompt": "", "keep_alive": 0, "stream": False},
+            timeout=20,
+        )
+        logger.debug("Asked Ollama to release %s", model)
+    except Exception as e:
+        logger.debug("Could not release %s: %s", model, e)
+
+
 def ensure_local_deps(s):
     if not ensure_module(s, "torch", "torch") or not ensure_module(s, "diffusers", "diffusers accelerate safetensors transformers".split()[0]):
         raise RuntimeError("Could not install the image packages. Run ./install-local.sh")
@@ -930,7 +1030,7 @@ def ensure_models(s, engine):
             raise RuntimeError(f"'{vm}' is a text model and cannot check images. Pick a vision model such as qwen2.5vl:7b in Settings")
 
 
-def ollama_call(s, prompt, temperature=0.9, model=None, images=None, num_predict=2048, as_json=True):
+def ollama_call(s, prompt, temperature=0.9, model=None, images=None, num_predict=2048, as_json=True, keep_alive="5m"):
     url = f"{s['ollama_url'].rstrip('/')}/api/generate"
     model = model or s["ollama_model"]
     timeout = max(30, int(s["ollama_timeout"]))
@@ -938,7 +1038,7 @@ def ollama_call(s, prompt, temperature=0.9, model=None, images=None, num_predict
         "model": model,
         "prompt": prompt,
         "stream": False,
-        "keep_alive": "5m",
+        "keep_alive": keep_alive,
         "options": {"temperature": temperature, "num_predict": num_predict, "num_ctx": 8192},
     }
     if as_json:
@@ -982,13 +1082,23 @@ def write_script(s, src, feedback=None):
         "A previous draft was rejected for these problems. Do not repeat them:\n" + "\n".join(f"- {f}" for f in feedback) + "\n"
         if feedback else ""
     )
+    past = past_stories(s)
+    used_titles = list(dict.fromkeys(x["title"] for x in past))[-40:]
+    used_names = sorted({n for x in past for n in x.get("names", [])})
+    avoid_block = ""
+    if used_titles or used_names:
+        avoid_block = "This channel has already published stories. Make this one feel new.\n"
+        if used_titles:
+            avoid_block += "Do not reuse or closely copy any of these titles: " + "; ".join(used_titles) + "\n"
+        if used_names:
+            avoid_block += "Do not use any of these character names: " + ", ".join(used_names) + ". Invent fresh names.\n"
     prompt = f"""You are a short-form video writer. This video is currently popular on YouTube:
 Title: {src['title']}
 Channel: {src['channel']}
 Description: {src['description']}
 Tags: {', '.join(src['tags'])}
 
-{niche_block}{kids_block}{feedback_block}
+{niche_block}{kids_block}{feedback_block}{avoid_block}
 Identify the underlying topic and why it appeals to viewers. Then write a completely ORIGINAL {n * clip}-second YouTube Short in English.
 Do not reuse the source's title, script, characters, jokes, branding, or channel identity.
 Do not depict real people, celebrities, brands, logos, or copyrighted characters. Invent new characters.
@@ -998,7 +1108,7 @@ Every character is a cartoon: a cartoon animal, a cartoon creature, or a simple
 
 The Short has exactly {n} scenes of {clip} seconds each. Each scene has:
 "visual": a detailed, self-contained shot description of one still image (setting, action, mood, lighting). Name the characters but do not re-describe their appearance, that comes from "characters". Never mention on-screen text or words.
-"narration": one spoken line of at most {words} words.
+"narration": one spoken line of {max(4, words - 5)} to {words} words, so it fills most of the scene. Write real words only, never stretched sounds like Mmm, Ahhh, Ooooh, or Shhh, because the narrator reads those letter by letter.
 
 Scene 1 must hook the viewer in the first 2 seconds. The final scene must deliver a payoff.
 
@@ -1017,6 +1127,8 @@ Return JSON only in this shape:
                 raise ValueError(f"expected {n} scenes, got {len(scenes)}")
             if not str(data.get("title", "")).strip():
                 raise ValueError("missing title")
+            if norm_title(data["title"]) in {norm_title(x["title"]) for x in past_stories(s)}:
+                raise ValueError(f"title '{data['title']}' was already used on this channel")
             data["scenes"] = [{"visual": str(sc.get("visual", "")), "narration": str(sc.get("narration", ""))} for sc in scenes[:n]]
             data["title"] = str(data["title"])
             data["style"] = str(data.get("style", ""))
@@ -1346,10 +1458,10 @@ def kids_vision_check(s, clip_path):
     problems = []
     unclear = []
     try:
-        desc = ollama_call(s, "Describe this image in one short sentence.", temperature=0.1, model=model, images=images, num_predict=80, as_json=False).strip()
+        desc = ollama_call(s, "Describe this image in one short sentence.", temperature=0.1, model=model, images=images, num_predict=80, as_json=False, keep_alive="30s").strip()
         def ask(q):
             for _ in range(2):
-                a = yes_no(ollama_call(s, q, temperature=0.0, model=model, images=images, num_predict=10, as_json=False))
+                a = yes_no(ollama_call(s, q, temperature=0.0, model=model, images=images, num_predict=10, as_json=False, keep_alive="30s"))
                 if a is not None:
                     return a
             return None
@@ -1397,10 +1509,21 @@ def load_pipeline(s):
             device, dtype = "cuda", torch.float16
         else:
             device, dtype = "cpu", torch.float32
+        threads = int(s.get("cpu_threads", 0) or 0)
+        if threads > 0:
+            torch.set_num_threads(threads)
+            logger.info("Limiting image generation to %d CPU threads", threads)
         logger.info("Loading image model %s on %s (first run downloads several GB)", model, device)
         pipe = AutoPipelineForText2Image.from_pretrained(model, torch_dtype=dtype, variant="fp16" if dtype == torch.float16 else None)
         pipe = pipe.to(device)
         pipe.set_progress_bar_config(disable=True)
+        if s.get("low_memory", True):
+            for enable in ("enable_attention_slicing", "enable_vae_slicing", "enable_vae_tiling"):
+                try:
+                    getattr(pipe, enable)()
+                except Exception:
+                    pass
+            logger.info("Low memory mode is on for image generation")
         pipeline["id"] = model
         pipeline["obj"] = pipe
         logger.info("Image model ready")
@@ -1425,6 +1548,40 @@ def generate_image(s, prompt, path):
     logger.info("Generated %s in %.1fs", path.name, (datetime.now() - started).total_seconds())
 
 
+SPEECH_FIXES = [
+    (r"\bm{2,}\b", "Yum"),
+    (r"\bmhm+\b", "Mm hmm"),
+    (r"\bhm{2,}\b", "Hmm"),
+    (r"\bo{2,}h*\b", "Ooh"),
+    (r"\ba{2,}h+\b", "Ah"),
+    (r"\bah{2,}\b", "Ah"),
+    (r"\bsh{2,}\b", "Shh"),
+    (r"\bw+o{2,}h*\b", "Whoa"),
+    (r"\bwh?e{2,}\b", "Whee"),
+    (r"\byay+\b", "Yay"),
+    (r"\bya{2,}y*\b", "Yay"),
+    (r"\bye{2,}h*\b", "Yeah"),
+    (r"\bhur+a+h*\b", "Hooray"),
+    (r"\bz{2,}\b", "Zzz"),
+    (r"\bbr{2,}\b", "Brr"),
+    (r"\bgr{2,}\b", "Grr"),
+    (r"\bha{2,}\b", "Ha ha"),
+    (r"\bhe{2,}\b", "Hee hee"),
+    (r"\bwo{2,}w+\b", "Wow"),
+]
+
+
+def speakable(text):
+    out = text
+    for pattern, replacement in SPEECH_FIXES:
+        out = re.sub(pattern, replacement, out, flags=re.I)
+    out = re.sub(r"([!?.,])\1{1,}", r"\1", out)
+    out = re.sub(r"\s{2,}", " ", out).strip()
+    if out != text:
+        logger.debug("Narration adjusted for speech: %r to %r", text, out)
+    return out
+
+
 def pick_tts(s):
     engine = s["tts_engine"] if s["tts_engine"] in TTS_ENGINES else "auto"
     if engine != "auto":
@@ -1454,7 +1611,7 @@ def system_speak(s, text, out_wav):
 
 
 def tts_speak(s, text, out_wav):
-    text = text.strip() or "..."
+    text = speakable(text.strip()) or "..."
     engine = pick_tts(s)
     try:
         if engine == "kokoro":
@@ -1494,7 +1651,11 @@ def media_duration(path):
 
 def render_scene(s, image, audio, out, aspect):
     w, h = (1080, 1920) if aspect == "9:16" else (1920, 1080)
-    dur = max(float(s["clip_seconds"]), media_duration(audio) + 0.6)
+    spoken = media_duration(audio)
+    if s.get("scene_timing", "narration") == "fixed":
+        dur = max(float(s["clip_seconds"]), spoken + 0.6)
+    else:
+        dur = max(2.5, spoken + 0.8)
     frames = int(dur * 30)
     vf = (
         f"[0:v]scale={w * 2}:{h * 2}:force_original_aspect_ratio=increase,crop={w * 2}:{h * 2},"
@@ -1718,7 +1879,13 @@ def run_job(s):
     compliance = {}
     finalized = False
     try:
+        s["_channel_titles"] = channel_titles(s)
+        if s["_channel_titles"]:
+            logger.info("Loaded %d existing channel titles to avoid repeats", len(s["_channel_titles"]))
         script, tags, compliance = produce_script(s, src)
+        remember_story(s["profile_id"], script)
+        if engine == "local":
+            unload_ollama(s, s["ollama_model"])
         compliance["engine"] = engine
         update_history(job_id, title=script["title"], notes="; ".join(compliance.get("reviewer_notes", []))[:400])
         write_json(job_dir / "script.json", {"profile": s["name"], "source": src, "script": script, "tags": tags})
@@ -1747,62 +1914,98 @@ def run_job(s):
                         raise
                     stop_event.wait(10)
 
-        for i, scene in enumerate(script["scenes"], 1):
-            set_stage(f"generating scene {i}/{n}", step=2 + i)
-            path = job_dir / f"clip_{i:02d}.mp4"
-            build_scene(i, scene, path)
-            clips.append(path)
+        anatomy_flags = []
+        batch_pending = []
+        inline = kids
 
-        anatomy_note = ""
-        safety_hits = set()
-        if kids:
-            pending = list(range(1, n + 1))
+        def judge(i, rnd):
+            try:
+                kids_vision_check(s, clips[i - 1])
+                vision_log.append({"clip": i, "round": rnd, "result": "passed"})
+                return "pass"
+            except Cancelled:
+                raise
+            except VisionUnavailable as e:
+                if s["kids_manual_review"]:
+                    logger.warning("Scene %d: %s. Continuing, check this video manually before publishing", i, e)
+                    vision_log.append({"clip": i, "round": rnd, "result": f"skipped: {e}"[:300]})
+                    return "pass"
+                raise
+            except VisionReject as e:
+                logger.warning("Scene %d attempt %d rejected: %s", i, rnd, e)
+                vision_log.append({"clip": i, "round": rnd, "result": str(e)[:300]})
+                return "unsafe" if e.safety else "anatomy"
+
+        def settle(i, verdict):
+            if verdict == "unsafe":
+                raise RuntimeError(f"Scene {i} still failed the safety check after 3 attempts")
+            if verdict == "anatomy":
+                logger.warning("Scene %d may still have an anatomy glitch after 3 attempts, keeping it. Check it before publishing", i)
+                anatomy_flags.append(i)
+
+        for i, scene in enumerate(script["scenes"], 1):
+            check_storage_alive(s)
+            path = job_dir / f"clip_{i:02d}.mp4"
+            clips.append(path)
+            verdict = "pass"
+            for attempt in range(1, 4):
+                set_stage(f"generating scene {i}/{n}" + (f" (attempt {attempt})" if attempt > 1 else ""), step=(1 + 2 * i) if inline else (2 + i))
+                path.unlink(missing_ok=True)
+                build_scene(i, scene, path)
+                if not inline:
+                    if kids:
+                        batch_pending.append(i)
+                    verdict = "pass"
+                    break
+                set_stage(f"checking scene {i}/{n}" + (f" (attempt {attempt})" if attempt > 1 else ""), step=2 + 2 * i)
+                try:
+                    verdict = judge(i, attempt)
+                except VisionUnavailable as e:
+                    logger.warning("Checking scenes right after drawing failed (%s). Switching to checking after all scenes are drawn", e)
+                    inline = False
+                    batch_pending.append(i)
+                    verdict = "pass"
+                    break
+                if verdict == "pass":
+                    break
+            if inline:
+                settle(i, verdict)
+
+        if batch_pending:
+            pending = batch_pending
             for rnd in range(1, 4):
                 unload_pipeline()
-                rejected = []
+                results = {}
                 for i in pending:
                     check()
-                    set_stage(f"vision check scene {i}/{n}", step=2 + n + i)
+                    set_stage(f"checking scene {i}/{n}", step=2 + n + i)
                     try:
-                        kids_vision_check(s, clips[i - 1])
-                        vision_log.append({"clip": i, "round": rnd, "result": "passed"})
-                    except Cancelled:
-                        raise
+                        results[i] = judge(i, rnd)
                     except VisionUnavailable as e:
-                        if s["kids_manual_review"]:
-                            logger.warning("Scene %d: %s. Continuing, check this video manually before publishing", i, e)
-                            vision_log.append({"clip": i, "round": rnd, "result": f"skipped: {e}"[:300]})
-                        else:
-                            raise RuntimeError(f"{e}. Frames were not verified, so nothing was uploaded")
-                    except Exception as e:
-                        logger.warning("Scene %d rejected (round %d): %s", i, rnd, e)
-                        vision_log.append({"clip": i, "round": rnd, "result": str(e)[:300]})
-                        rejected.append(i)
-                        if getattr(e, "safety", True):
-                            safety_hits.add(i)
-                        else:
-                            safety_hits.discard(i)
-                if not rejected:
+                        raise RuntimeError(f"{e}. Frames were not verified, so nothing was uploaded")
+                failed = [i for i, v in results.items() if v != "pass"]
+                if not failed:
                     break
                 if rnd == 3:
-                    unsafe = [i for i in rejected if i in safety_hits]
-                    if unsafe:
-                        raise RuntimeError(f"Scenes {unsafe} still failed the safety check after 3 rounds")
-                    flagged = ", ".join(str(i) for i in rejected)
-                    logger.warning("Scenes %s may still have anatomy glitches after 3 redraws, keeping them. Check them before publishing", flagged)
-                    anatomy_note = f"Possible anatomy glitches kept in scenes {flagged}"
+                    for i in failed:
+                        settle(i, results[i])
                     break
-                for i in rejected:
+                for i in failed:
                     set_stage(f"regenerating scene {i}/{n}", step=2 + i)
                     clips[i - 1].unlink(missing_ok=True)
                     build_scene(i, script["scenes"][i - 1], clips[i - 1])
-                pending = rejected
+                pending = failed
+
+        if kids:
+            unload_ollama(s, s["vision_model"])
+        anatomy_note = f"Possible anatomy glitches kept in scenes {', '.join(str(i) for i in anatomy_flags)}" if anatomy_flags else ""
         if kids:
             compliance["vision_checks"] = vision_log
             if anatomy_note:
                 compliance["anatomy_note"] = anatomy_note
                 prior = "; ".join(compliance.get("reviewer_notes", []))
                 update_history(job_id, notes=(prior + "; " if prior else "") + anatomy_note)
+        check_storage_alive(s)
         set_stage("stitching video", step=3 + n * 2)
         final = job_dir / "final.mp4"
         concat_clips(clips, final, s["aspect_ratio"])
@@ -1860,6 +2063,7 @@ def run_loop():
             if limit > 0 and published_today(s["profile_id"]) >= limit:
                 if status["stage"] != "daily limit reached":
                     logger.info("Profile '%s' reached its daily limit of %d, waiting for tomorrow", s["name"], limit)
+                    reset_progress()
                 set_stage("daily limit reached", log=False)
                 stop_event.wait(60)
                 continue
@@ -1868,11 +2072,15 @@ def run_loop():
             except Cancelled:
                 break
             except Exception as e:
-                logger.exception("Job failed: %s", e)
+                if "has expired" in str(e) or "not mounted" in str(e) or "unmounted" in str(e):
+                    logger.error("%s", e)
+                else:
+                    logger.exception("Job failed: %s", e)
                 mins = max(1, int(s["error_cooldown_minutes"]))
                 set_stage(f"cooling down {mins} min after error")
                 stop_event.wait(mins * 60)
                 continue
+            reset_progress()
             gap = int(s["minutes_between_videos"])
             if gap > 0 and not stop_event.is_set():
                 set_stage(f"waiting {gap} min before next video")
@@ -1884,7 +2092,23 @@ def run_loop():
         logger.info("Autopilot stopped")
 
 
+def reset_stale_jobs():
+    with state_lock:
+        st = load_state()
+        stale = [h for h in st["history"] if h.get("status") == "running"]
+        if not stale:
+            return
+        now = int(datetime.now().timestamp())
+        for h in stale:
+            h["status"] = "interrupted"
+            h["error"] = "The app stopped before this job finished"
+            h.setdefault("finished_ts", h.get("started_ts", now))
+        save_state(st)
+        logger.info("Marked %d unfinished job(s) from a previous run as interrupted", len(stale))
+
+
 migrate()
+reset_stale_jobs()
 app = FastAPI()
 
 
@@ -1920,8 +2144,7 @@ def api_status():
     }
 
 
-@app.get("/api/settings")
-def get_settings():
+def build_settings():
     g = load_global()
     if g["gemini_api_key"]:
         g["gemini_api_key"] = MASK
@@ -1940,9 +2163,18 @@ def get_settings():
     }
 
 
+@app.get("/api/settings")
+async def get_settings():
+    return await run_in_threadpool(build_settings)
+
+
 @app.post("/api/settings")
 async def post_settings(request: Request):
     body = await request.json()
+    return await run_in_threadpool(apply_settings, body)
+
+
+def apply_settings(body):
     with settings_lock:
         g = load_global()
         old_storage = g["storage_dir"]

static/index.html

@@ -116,7 +116,7 @@ td.title{font-weight:700}
 td .sub{font-size:12.5px;color:var(--muted);margin-top:6px;overflow-wrap:anywhere}
 td .sub.notes{color:var(--amber)}
 td .sub.err{color:var(--coral)}
-.st-published{--c:var(--sage)}.st-failed{--c:var(--coral)}.st-running{--c:var(--gold-text)}.st-review{--c:var(--violet)}.st-scheduled{--c:var(--sky)}.st-cancelled{--c:var(--muted)}
+.st-published{--c:var(--sage)}.st-failed{--c:var(--coral)}.st-running{--c:var(--gold-text)}.st-review{--c:var(--violet)}.st-scheduled{--c:var(--sky)}.st-cancelled{--c:var(--muted)}.st-interrupted{--c:var(--muted)}
 .links{display:flex;gap:6px}
 .empty{padding:36px 16px;text-align:center;color:var(--muted)}
 .source a{color:var(--text);text-decoration-color:var(--line)}
@@ -319,6 +319,10 @@ const FIELDS=[
 ["piper_model","Piper voice file","wide","Blank uses the first voice found in the voices folder under Models","g"],
 ["gemini_api_key","Gemini API key (Veo)","password","Only needed for the Veo engine. Billing must be enabled","g"],
 ["veo_model","Veo model","text","e.g. veo-3.1-fast-generate-preview","g"],
+["","Performance","header","Shared by all profiles. Lower settings here if the Mac becomes slow or unstable",""],
+["low_memory","Low memory mode","checkbox","Generates images in smaller pieces. A little slower, much less memory. Leave on for Macs with 16 GB or less","g"],
+["free_models_between_stages","Free models between stages","checkbox","Unloads the writing model before images are drawn and the vision model after checks","g"],
+["cpu_threads","CPU threads","select:0=Automatic|2|4|6|8|10","Caps how many cores image generation uses so the rest of the Mac stays responsive","g"],
 ["","Writing and timing","header","Shared by all profiles",""],
 ["ollama_url","Ollama URL","text","","g"],
 ["ollama_model","Ollama model","model:text","Writes scripts and tags. Models not installed yet are downloaded automatically","g"],
@@ -326,12 +330,13 @@ const FIELDS=[
 ["ollama_timeout","Ollama timeout (seconds)","select:120|300|600|900","Max wait per Ollama request before retrying","g"],
 ["aspect_ratio","Aspect ratio","select:9:16|16:9","","g"],
 ["target_seconds","Target length (seconds)","select:30|45|60|90|120|180","Split into scenes of the length below","g"],
-["clip_seconds","Seconds per scene","select:5|6|8|10|12","8 gives 7 scenes in a 60 second Short","g"],
+["clip_seconds","Seconds per scene","select:5|6|8|10|12","Sets how many scenes the story has and how long each narration line is. 8 gives 7 scenes","g"],
+["scene_timing","Scene timing","select:narration=Match the narration|fixed=Fixed length per scene","Match the narration moves to the next scene shortly after the voice finishes","g"],
 ["error_cooldown_minutes","Wait after error (minutes)","select:1|5|10|15|30|60","","g"]
 ];
 const DAYS=[["mon","Mon"],["tue","Tue"],["wed","Wed"],["thu","Thu"],["fri","Fri"],["sat","Sat"],["sun","Sun"]];
 const TIMES=[];for(let h=0;h<24;h++)for(const m of [0,30]){const v=String(h).padStart(2,"0")+":"+String(m).padStart(2,"0");const hr=h%12||12;TIMES.push([v,hr+":"+String(m).padStart(2,"0")+(h<12?" AM":" PM")])}
-const NUMERIC=new Set(["sd_steps","sd_guidance","sd_width","sd_height","trending_days","trending_count","videos_per_day","minutes_between_videos","target_seconds","clip_seconds","ollama_timeout","error_cooldown_minutes","tts_rate"]);
+const NUMERIC=new Set(["sd_steps","sd_guidance","sd_width","sd_height","trending_days","trending_count","videos_per_day","minutes_between_videos","target_seconds","clip_seconds","ollama_timeout","error_cooldown_minutes","tts_rate","cpu_threads"]);
 const $=s=>document.querySelector(s);
 const esc=s=>String(s??"").replace(/[&<>"]/g,c=>({"&":"&amp;","<":"&lt;",">":"&gt;",'"':"&quot;"}[c]));
 async function api(path,opts={}){const r=await fetch(path,{headers:{"Content-Type":"application/json"},...opts});const j=await r.json().catch(()=>({}));if(!r.ok)throw new Error(j.detail||r.statusText);return j}
@@ -429,7 +434,7 @@ btn.disabled=false}
 
 async function activate(id){try{await api("/api/profiles/activate",{method:"POST",body:JSON.stringify({id})})}catch(e){alert(e.message)}await loadSettings();refresh()}
 
-const STATUS_TEXT={review:"Private, needs review",published:"Published",failed:"Failed",running:"Running",cancelled:"Cancelled",scheduled:"Scheduled"};
+const STATUS_TEXT={review:"Private, needs review",published:"Published",failed:"Failed",running:"Running",cancelled:"Cancelled",scheduled:"Scheduled",interrupted:"Interrupted"};
 function fmtDur(d){d=Math.max(0,d|0);const h=Math.floor(d/3600),m=Math.floor(d%3600/60),s=d%60;return h?`${h}h ${m}m`:m?`${m}m ${s}s`:`${s}s`}
 function fmtStart(t){if(!t)return"";const d=new Date(t.replace(" ","T"));if(isNaN(d))return t;return d.toLocaleString([], {month:"short",day:"numeric",hour:"numeric",minute:"2-digit"})}
 
@@ -451,7 +456,7 @@ const segs=$("#pg-segs");if(segs.childElementCount!==s.steps){segs.innerHTML="<i
 [...segs.children].forEach((el,i)=>{el.className=i<s.step-1?"on":i===s.step-1?"now":""});
 const pct=Math.min(100,Math.round(s.step*100/s.steps));
 $("#pg-meta").textContent=`Step ${s.step} of ${s.steps}, ${pct}% done`+(s.elapsed?`, running for ${fmtDur(s.elapsed)}`:"");
-}else{pg.classList.remove("show");note.hidden=false;note.textContent=s.running?"Waiting for the next video to start.":"Press GO to start making videos for the active profile."}
+}else{pg.classList.remove("show");note.hidden=false;note.textContent=s.running?(s.stage&&s.stage!=="idle"?"":"Waiting for the next video to start."):"Press GO to start making videos for the active profile."}
 lastChannel=s.channel||"";const lb=$("#link");if(lb){lb.textContent=s.channel?"Unlink YouTube channel":"Link YouTube channel"}const ls=$("#link-status");if(ls){ls.textContent=s.channel?"Linked to "+s.channel:"No channel linked yet"}
 setButton(s.running);
 const dur=h=>{if(!h.started_ts)return"";const end=h.finished_ts||(h.status==="running"?s.now:0);return end?fmtDur(end-h.started_ts):""};