Prepare publishable Tauri app

2026-05-04 10:13:03 +02:00
parent dd135a6089
commit ff66d0aea3
20 changed files with 6386 additions and 159 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1,44 @@
+venv
+.venv
+sync.sh
+summaries.db
+.env
+node_modules
+data
+package-lock.json
+dump_summaries.sql
+.DS_Store
+.git
+__pycache__
+.mypy_cache
+.pytest_cache
+dist
+build
+out
+.next
+.nuxt
+.turbo
+.parcel-cache
+.cache
+target
+src-tauri/target
+src-tauri/gen
+coverage
+logs
+tmp
+temp
+output
+tmp*
+*.log
+*.tmp
+*.swp
+*.lock
+*.exe
+
+Cargo.lock
+!src-tauri/Cargo.lock
+
+src-tauri/resources/backend/*
+!src-tauri/resources/backend/.gitkeep
+src-tauri/resources/ffmpeg/*
+!src-tauri/resources/ffmpeg/.gitkeep
--- a/MIGRATION_NOTES.md
+++ b/MIGRATION_NOTES.md
@@ -0,0 +1,26 @@
+# Migration Notes
+
+## What Was Preserved
+
+- Static frontend design from `ui/index.html`, including the rose color palette, compact header form, list layout, collapsed summary previews and pagination.
+- Frontend behavior from `ui/renderer.js`: model loading, local UI preferences, Whisper toggle, auto-translation toggle, per-entry language tabs, delete confirmation, progress updates, expandable summaries and thumbnail external links.
+- Tauri command surface: `get_models`, `get_summaries`, `summarize_video`, `delete_summary`, `translate_summary`, `open_external` and `open_file`.
+- Local runtime model: SQLite history in the OS app local data directory, media under that data directory, Ollama on `localhost:11434`, and Python helpers for YouTube metadata, transcripts, Whisper, summaries and translation.
+- Release bundling path: a PyInstaller-built backend sidecar plus copied `ffmpeg` and `ffprobe` resources under `src-tauri/resources`.
+
+## Electron Reality Check
+
+No active Electron app was present in the source snapshot used for this migration. There was no Electron main process, preload script, `ipcMain`/`ipcRenderer` bridge, `BrowserWindow` setup, `package.json` or Electron build configuration. The working desktop shell was already Tauri 2, so this folder packages that actual implementation as a standalone Tauri project rather than inventing behavior from missing Electron files.
+
+## Important Runtime Details
+
+- The Tauri identifier remains `com.victorgiers.youtube-summarizer` so OS-level app data and history stay aligned with the existing app identity.
+- `run.sh` and `run.bat` now change into this folder before creating the Python environment or launching Cargo.
+- The frontend still uses `window.__TAURI__` because `withGlobalTauri` is enabled in `src-tauri/tauri.conf.json`.
+- Development falls back to local Python scripts when no bundled backend sidecar exists.
+
+## Imported Legacy Data
+
+- The old Electron database from `/Users/giers/Tools/victors-tools/youtube_summarizer/summaries.db` was copied into the Tauri runtime data directory at `/Users/giers/Library/Application Support/com.victorgiers.youtube-summarizer/summaries.db`.
+- A copy also exists at `summaries.db` in this folder for local migration reference.
+- Thumbnail files from the old `data/` folder were copied so historical entries keep their images. Audio and transcript files were not copied because the Tauri runtime clears those artifact references on startup.
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-# YouTube Summarizer
+# YouTube Summarizer Tauri

 This is a local-first desktop app for summarizing YouTube videos with Ollama.

@@ -9,6 +9,10 @@ It uses:
 - Ollama on `localhost` for summarization and translation
 - SQLite for local history

+## Migration State
+
+This folder is the standalone Tauri version of the app. The repository snapshot this was created from did not contain an active Electron runtime, `package.json`, preload script or Electron main process; the actual app behavior was already represented by a static HTML/CSS/JS frontend, a Tauri 2 Rust shell and Python backend helpers. The migration work here keeps that behavior and design intact inside `ytsummarizer_tauri` so it can be built and run without depending on files outside this folder.
+
 ## What It Does

 Given a YouTube URL, the app can:
@@ -48,7 +52,7 @@ For development in this repo you still need:
 - FFmpeg in `PATH`
 - Ollama running locally on `http://localhost:11434`

-Python dependencies are listed in [requirements.txt](/Users/giers/youtube_summarizer/requirements.txt).
+Python dependencies are listed in [requirements.txt](requirements.txt).

 ## Run In Development

@@ -73,7 +77,7 @@ pip install -r requirements.txt
 cargo run --manifest-path src-tauri/Cargo.toml
 ```

-The app prefers a bundled backend executable when one is present under [src-tauri/resources/backend](/Users/giers/youtube_summarizer/src-tauri/resources/backend), and otherwise falls back to the local Python environment for development.
+The app prefers a bundled backend executable when one is present under [src-tauri/resources/backend](src-tauri/resources/backend), and otherwise falls back to the local Python environment for development.

 ## Build A Shippable Bundle

@@ -93,21 +97,21 @@ cargo tauri build
 What `tools/prepare_bundle.py` does:

 - installs PyInstaller into the current Python environment
- builds a single-file backend executable from [backend_cli.py](/Users/giers/youtube_summarizer/backend_cli.py)
- copies that executable into [src-tauri/resources/backend](/Users/giers/youtube_summarizer/src-tauri/resources/backend)
- copies `ffmpeg` and `ffprobe` from the build machine into [src-tauri/resources/ffmpeg](/Users/giers/youtube_summarizer/src-tauri/resources/ffmpeg)
+- builds a single-file backend executable from [backend_cli.py](backend_cli.py)
+- copies that executable into [src-tauri/resources/backend](src-tauri/resources/backend)
+- copies `ffmpeg` and `ffprobe` from the build machine into [src-tauri/resources/ffmpeg](src-tauri/resources/ffmpeg)

 Build once on each target OS you want to ship. For Windows 10, build on Windows.

 ## Build On GitHub Actions

-A Windows build workflow is included at [.github/workflows/windows-installer.yml](/Users/giers/youtube_summarizer/.github/workflows/windows-installer.yml).
+A Windows build workflow from the original repository can be pointed at this folder by running the same commands from `ytsummarizer_tauri`.

-It runs on `windows-latest`, installs `ffmpeg` and NSIS, prepares the bundled Python backend with [tools/prepare_bundle.py](/Users/giers/youtube_summarizer/tools/prepare_bundle.py), builds an NSIS installer, and uploads the result as a workflow artifact named `windows-installer`.
+It should run on `windows-latest`, install `ffmpeg` and NSIS, prepare the bundled Python backend with [tools/prepare_bundle.py](tools/prepare_bundle.py), build an NSIS installer, and upload the result as a workflow artifact named `windows-installer`.

 ## Notes

 - If Python is not on your `PATH` for development, set `YTS_PYTHON` to the interpreter you want the Tauri backend to use.
 - If you want to test a prebuilt backend executable during development, set `YTS_BACKEND_BIN` to its full path.
- If `ffmpeg` or `ffprobe` are not on `PATH` during bundle prep, set `YTS_FFMPEG` and `YTS_FFPROBE` to their full paths before running [tools/prepare_bundle.py](/Users/giers/youtube_summarizer/tools/prepare_bundle.py).
+- If `ffmpeg` or `ffprobe` are not on `PATH` during bundle prep, set `YTS_FFMPEG` and `YTS_FFPROBE` to their full paths before running [tools/prepare_bundle.py](tools/prepare_bundle.py).
 - Generated thumbnails and the SQLite database are created on first run in the app's local data directory.
--- a/backend_cli.py
+++ b/backend_cli.py
@@ -8,6 +8,7 @@ while still supporting direct Python execution during development.

 import argparse
 import json
+import multiprocessing
 import sys
 from pathlib import Path

@@ -18,19 +19,38 @@ from youtube_summarizer import process_video
 DEFAULT_MODEL = "mistral:latest"


+def compact_error_message(exc: BaseException) -> str:
+    """Build a short error string without dumping a traceback into the GUI."""
+    parts = []
+    current = exc
+    while current:
+        text = " ".join(str(current).split())
+        if text and text not in parts:
+            parts.append(text)
+        current = current.__cause__ or current.__context__
+    return ": ".join(parts) or exc.__class__.__name__
+
+
 def configure_stdio() -> None:
    """Keep progress output line-buffered for the desktop app."""
    if hasattr(sys.stdout, "reconfigure"):
-        sys.stdout.reconfigure(line_buffering=True)
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace", line_buffering=True)
    if hasattr(sys.stderr, "reconfigure"):
-        sys.stderr.reconfigure(line_buffering=True)
+        sys.stderr.reconfigure(encoding="utf-8", errors="replace", line_buffering=True)


 def summarize(args: argparse.Namespace) -> int:
+    prompt_template = None
+    if args.prompt_template_file:
+        prompt_template = Path(args.prompt_template_file).read_text(encoding="utf-8")
+    elif args.prompt_template:
+        prompt_template = args.prompt_template
+
    meta = process_video(
        args.url,
        use_whisper=args.use_whisper,
        model=args.model,
+        prompt_template=prompt_template,
        output_json=args.output_json,
    )
    if not args.output_json:
@@ -44,7 +64,13 @@ def translate(args: argparse.Namespace) -> int:
    if not summary_text:
        raise SystemExit("Empty summary text!")

-    translation = translate_summary_text(summary_text, args.lang, args.model)
+    prompt_template = None
+    if args.prompt_template_file:
+        prompt_template = Path(args.prompt_template_file).read_text(encoding="utf-8")
+    elif args.prompt_template:
+        prompt_template = args.prompt_template
+
+    translation = translate_summary_text(summary_text, args.lang, args.model, prompt_template)

    if args.output_file:
        Path(args.output_file).write_text(translation, encoding="utf-8")
@@ -60,6 +86,8 @@ def build_parser() -> argparse.ArgumentParser:
    summarize_parser = subparsers.add_parser("summarize", help="Summarize a YouTube video")
    summarize_parser.add_argument("--url", required=True, help="YouTube video URL")
    summarize_parser.add_argument("--model", default=DEFAULT_MODEL, help="Ollama model to use")
+    summarize_parser.add_argument("--prompt-template", help="Prompt template for the summary LLM call")
+    summarize_parser.add_argument("--prompt-template-file", help="Path to a prompt template file")
    summarize_parser.add_argument(
        "--no-whisper",
        dest="use_whisper",
@@ -76,6 +104,8 @@ def build_parser() -> argparse.ArgumentParser:
    translate_parser.add_argument("--summary-file", required=True, help="Path to the English summary text")
    translate_parser.add_argument("--lang", required=True, choices=["de", "jp"], help="Target language")
    translate_parser.add_argument("--model", default=DEFAULT_MODEL, help="Ollama model to use")
+    translate_parser.add_argument("--prompt-template", help="Prompt template for the translation LLM call")
+    translate_parser.add_argument("--prompt-template-file", help="Path to a translation prompt template file")
    translate_parser.add_argument("--output-file", help="Optional path to write the translated text")
    translate_parser.set_defaults(handler=translate)

@@ -83,10 +113,18 @@ def build_parser() -> argparse.ArgumentParser:


 def main() -> int:
+    multiprocessing.freeze_support()
    configure_stdio()
    parser = build_parser()
    args = parser.parse_args()
-    return args.handler(args)
+    try:
+        return args.handler(args)
+    except KeyboardInterrupt:
+        print("[error] Cancelled.", file=sys.stderr, flush=True)
+        return 130
+    except Exception as exc:
+        print(f"[error] {compact_error_message(exc)}", file=sys.stderr, flush=True)
+        return 1


 if __name__ == "__main__":
--- a/run.bat
+++ b/run.bat
@@ -1,5 +1,6 @@
@echo off
 setlocal
+cd /d "%~dp0"

 REM 1. Prüfen, ob venv existiert, sonst erstellen
 if not exist venv (
--- a/run.sh
+++ b/run.sh
@@ -1,6 +1,8 @@
 #!/usr/bin/env bash
 set -e

+cd "$(dirname "$0")"
+
 # 1. Python venv einrichten
 GREEN="\033[0;32m"
 CYAN="\033[0;36m"
--- a/src-tauri/Cargo.lock
+++ b/src-tauri/Cargo.lock
--- a/src-tauri/icons/128x128.png
+++ b/src-tauri/icons/128x128.png
--- a/src-tauri/icons/128x128@2x.png
+++ b/src-tauri/icons/128x128@2x.png
--- a/src-tauri/icons/32x32.png
+++ b/src-tauri/icons/32x32.png
--- a/src-tauri/icons/icon.icns
+++ b/src-tauri/icons/icon.icns
--- a/src-tauri/icons/icon.ico
+++ b/src-tauri/icons/icon.ico
--- a/src-tauri/icons/icon.png
+++ b/src-tauri/icons/icon.png
--- a/src-tauri/src/main.rs
+++ b/src-tauri/src/main.rs
@@ -1,8 +1,9 @@
 #![cfg_attr(not(debug_assertions), windows_subsystem = "windows")]

 use std::{
-    env, fs,
-    io::{BufRead, BufReader, ErrorKind},
+    env,
+    fs::{self, OpenOptions},
+    io::{BufRead, BufReader, ErrorKind, Write},
    path::{Path, PathBuf},
    process::{Command, Stdio},
    sync::{Arc, Mutex},
@@ -10,16 +11,22 @@ use std::{
    time::{SystemTime, UNIX_EPOCH},
 };

+#[cfg(target_os = "windows")]
+use std::os::windows::process::CommandExt;
+
 use open::that;
 use reqwest::blocking::Client;
 use rusqlite::{params, Connection, OptionalExtension};
 use serde::{Deserialize, Serialize};
-use tauri::{AppHandle, Emitter, Manager, State, WebviewWindow};
+use tauri::menu::{MenuBuilder, SubmenuBuilder};
+use tauri::{path::BaseDirectory, AppHandle, Emitter, Manager, State, WebviewWindow};

 const DEFAULT_MODEL: &str = "mistral:latest";
 const OLLAMA_TAGS_URL: &str = "http://localhost:11434/api/tags";
 const BACKEND_EXECUTABLE_NAME: &str = "yts-backend";
 const TARGET_TRIPLE: &str = env!("TAURI_BUILD_TARGET");
+#[cfg(target_os = "windows")]
+const CREATE_NO_WINDOW: u32 = 0x0800_0000;

 #[derive(Clone)]
 enum BackendRuntime {
@@ -37,6 +44,7 @@ struct AppState {
    app_dir: PathBuf,
    media_dir: PathBuf,
    db_path: PathBuf,
+    backend_log_path: PathBuf,
    backend: BackendRuntime,
    ffmpeg_path: Option<PathBuf>,
    ffprobe_path: Option<PathBuf>,
@@ -49,6 +57,7 @@ struct SummarizeVideoRequest {
    url: String,
    use_whisper: bool,
    model: Option<String>,
+    master_prompt: Option<String>,
 }

 #[derive(Debug, Deserialize)]
@@ -57,10 +66,12 @@ struct DeleteSummaryRequest {
 }

 #[derive(Debug, Deserialize)]
+#[serde(rename_all = "camelCase")]
 struct TranslateSummaryRequest {
    id: i64,
    lang: String,
    model: Option<String>,
+    prompt_template: Option<String>,
 }

 #[derive(Debug, Deserialize)]
@@ -165,6 +176,12 @@ fn normalize_model(model: Option<String>) -> String {
        .unwrap_or_else(|| DEFAULT_MODEL.to_string())
 }

+fn normalize_prompt_template(prompt: Option<String>) -> Option<String> {
+    prompt
+        .map(|value| value.trim().to_string())
+        .filter(|value| !value.is_empty())
+}
+
 fn now_millis() -> u128 {
    SystemTime::now()
        .duration_since(UNIX_EPOCH)
@@ -190,15 +207,16 @@ fn platform_executable_name(base_name: &str) -> String {
 fn resolve_resource_file(app: &AppHandle, relative_path: &Path) -> Option<PathBuf> {
    let mut candidates = Vec::new();

-    if let Ok(resource_dir) = app.path().resource_dir() {
-        candidates.push(resource_dir.join(relative_path));
+    if let Ok(resource_path) = app.path().resolve(relative_path, BaseDirectory::Resource) {
+        candidates.push(resource_path);
    }

-    candidates.push(
-        PathBuf::from(env!("CARGO_MANIFEST_DIR"))
-            .join("resources")
-            .join(relative_path),
-    );
+    let manifest_dir = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
+    candidates.push(manifest_dir.join(relative_path));
+    candidates.push(manifest_dir.join("resources").join(relative_path));
+    if let Ok(project_root) = resolve_project_root() {
+        candidates.push(project_root.join(relative_path));
+    }

    candidates.into_iter().find(|path| path.exists())
 }
@@ -218,9 +236,9 @@ fn resolve_backend_binary(app: &AppHandle) -> Option<PathBuf> {
 }

 fn resolve_script_dir(app: &AppHandle) -> Result<PathBuf, String> {
-    if let Ok(resource_dir) = app.path().resource_dir() {
-        if resource_dir.join("backend_cli.py").exists() {
-            return Ok(resource_dir);
+    if let Some(resource_file) = resolve_resource_file(app, Path::new("backend_cli.py")) {
+        if let Some(parent) = resource_file.parent() {
+            return Ok(parent.to_path_buf());
        }
    }

@@ -292,6 +310,21 @@ fn resolve_whisper_cache_dir(app: &AppHandle) -> Result<PathBuf, String> {
    Ok(whisper_cache_dir)
 }

+fn resolve_log_dir(app: &AppHandle) -> Result<PathBuf, String> {
+    let log_dir = app
+        .path()
+        .app_log_dir()
+        .or_else(|_| {
+            app.path()
+                .app_local_data_dir()
+                .map(|path| path.join("logs"))
+        })
+        .map_err(|err| format!("Failed to resolve application log directory: {err}"))?;
+    fs::create_dir_all(&log_dir)
+        .map_err(|err| format!("Failed to create application log directory: {err}"))?;
+    Ok(log_dir)
+}
+
 fn open_connection(state: &AppState) -> Result<Connection, String> {
    Connection::open(&state.db_path).map_err(|err| format!("Failed to open SQLite database: {err}"))
 }
@@ -341,8 +374,10 @@ fn cleanup_artifacts(state: &AppState, audio: Option<&str>, transcript: Option<&
 fn purge_existing_artifacts(state: &AppState) -> Result<(), String> {
    let db = open_connection(state)?;
    let mut stmt = db
-    .prepare("SELECT id, audio, transcript FROM summaries WHERE audio IS NOT NULL OR transcript IS NOT NULL")
-    .map_err(|err| format!("Failed to prepare artifact cleanup query: {err}"))?;
+        .prepare(
+            "SELECT id, audio, transcript FROM summaries WHERE audio IS NOT NULL OR transcript IS NOT NULL",
+        )
+        .map_err(|err| format!("Failed to prepare artifact cleanup query: {err}"))?;

    let rows = stmt
        .query_map([], |row| {
@@ -372,6 +407,30 @@ fn purge_existing_artifacts(state: &AppState) -> Result<(), String> {
    Ok(())
 }

+fn write_startup_error_log(app: &AppHandle, message: &str) {
+    let mut candidates = Vec::new();
+
+    if let Ok(path) = app.path().app_log_dir() {
+        candidates.push(path);
+    }
+    if let Ok(path) = app.path().app_local_data_dir() {
+        candidates.push(path);
+    }
+    candidates.push(env::temp_dir().join("youtube-summarizer"));
+
+    for directory in candidates {
+        if fs::create_dir_all(&directory).is_ok() {
+            let log_path = directory.join("startup-error.log");
+            if fs::write(&log_path, message).is_ok() {
+                eprintln!("Startup failure written to {}", log_path.display());
+                return;
+            }
+        }
+    }
+
+    eprintln!("{message}");
+}
+
 fn ensure_app_state(app: &AppHandle) -> Result<AppState, String> {
    let app_dir = app
        .path()
@@ -386,6 +445,7 @@ fn ensure_app_state(app: &AppHandle) -> Result<AppState, String> {
        ffmpeg_path: resolve_optional_tool_path(app, "YTS_FFMPEG", "ffmpeg"),
        ffprobe_path: resolve_optional_tool_path(app, "YTS_FFPROBE", "ffprobe"),
        whisper_cache_dir: resolve_whisper_cache_dir(app)?,
+        backend_log_path: resolve_log_dir(app)?.join("backend.log"),
        app_dir: app_dir.clone(),
        media_dir,
        db_path: app_dir.join("summaries.db"),
@@ -403,8 +463,47 @@ fn emit_progress(app: &AppHandle, window_label: &str, line: &str) {
    }
 }

+fn append_backend_log(log_path: &Path, line: &str) {
+    if let Ok(mut file) = OpenOptions::new().create(true).append(true).open(log_path) {
+        let _ = writeln!(file, "{line}");
+    }
+}
+
+fn backend_failure_message(stderr_output: &str, fallback: String) -> String {
+    for line in stderr_output.lines().rev() {
+        let trimmed = line.trim();
+        if let Some(message) = trimmed.strip_prefix("[error]") {
+            let message = message.trim();
+            if !message.is_empty() {
+                return message.to_string();
+            }
+        }
+    }
+
+    for line in stderr_output.lines().rev() {
+        let trimmed = line.trim();
+        if trimmed.is_empty()
+            || trimmed.starts_with("WARNING:")
+            || trimmed.starts_with("Traceback")
+            || trimmed.starts_with("File ")
+            || trimmed.starts_with("During handling")
+        {
+            continue;
+        }
+        if trimmed.starts_with("ERROR:")
+            || trimmed.contains("RuntimeError:")
+            || trimmed.contains("SystemExit:")
+        {
+            return trimmed.to_string();
+        }
+    }
+
+    fallback
+}
+
 fn apply_backend_env(command: &mut Command, state: &AppState) {
    command.env("PYTHONUNBUFFERED", "1");
+    command.env("PYTHONIOENCODING", "utf-8");
    command.env("YTS_WHISPER_CACHE_DIR", &state.whisper_cache_dir);

    if let Some(ffmpeg_path) = &state.ffmpeg_path {
@@ -427,6 +526,8 @@ fn build_backend_command(state: &AppState, args: &[String]) -> Command {

    command.args(args).current_dir(&state.media_dir);
    apply_backend_env(&mut command, state);
+    #[cfg(target_os = "windows")]
+    command.creation_flags(CREATE_NO_WINDOW);
    command
 }

@@ -440,12 +541,20 @@ fn run_backend_json_command(
    let mut command_args = args.to_vec();
    command_args.push("--output-json".to_string());
    command_args.push(output_path.to_string_lossy().into_owned());
+    append_backend_log(
+        &state.backend_log_path,
+        &format!("=== summarize {} ===", command_args.join(" ")),
+    );

    let mut child = build_backend_command(state, &command_args)
        .stdout(Stdio::piped())
        .stderr(Stdio::piped())
        .spawn()
-        .map_err(|err| format!("Failed to start bundled backend: {err}"))?;
+        .map_err(|err| {
+            let message = format!("Failed to start bundled backend: {err}");
+            append_backend_log(&state.backend_log_path, &message);
+            message
+        })?;

    let stdout = child
        .stdout
@@ -456,26 +565,29 @@ fn run_backend_json_command(
        .take()
        .ok_or_else(|| "Backend stderr was not captured.".to_string())?;
    let stderr_buffer = Arc::new(Mutex::new(String::new()));
+    let stdout_log_path = state.backend_log_path.clone();
+    let stderr_log_path = state.backend_log_path.clone();

    let stdout_app = app.clone();
    let stdout_label = window_label.to_string();
    let stdout_handle = thread::spawn(move || {
        for line in BufReader::new(stdout).lines() {
            match line {
-                Ok(line) => emit_progress(&stdout_app, &stdout_label, &line),
+                Ok(line) => {
+                    append_backend_log(&stdout_log_path, &format!("[stdout] {line}"));
+                    emit_progress(&stdout_app, &stdout_label, &line);
+                }
                Err(_) => break,
            }
        }
    });

-    let stderr_app = app.clone();
-    let stderr_label = window_label.to_string();
    let stderr_buffer_clone = Arc::clone(&stderr_buffer);
    let stderr_handle = thread::spawn(move || {
        for line in BufReader::new(stderr).lines() {
            match line {
                Ok(line) => {
-                    emit_progress(&stderr_app, &stderr_label, &line);
+                    append_backend_log(&stderr_log_path, &format!("[stderr] {line}"));
                    if let Ok(mut buffer) = stderr_buffer_clone.lock() {
                        buffer.push_str(&line);
                        buffer.push('\n');
@@ -486,9 +598,15 @@ fn run_backend_json_command(
        }
    });

-    let status = child
-        .wait()
-        .map_err(|err| format!("Failed to wait for bundled backend: {err}"))?;
+    let status = child.wait().map_err(|err| {
+        let message = format!("Failed to wait for bundled backend: {err}");
+        append_backend_log(&state.backend_log_path, &message);
+        message
+    })?;
+    append_backend_log(
+        &state.backend_log_path,
+        &format!("Bundled backend exit status: {status}"),
+    );

    let _ = stdout_handle.join();
    let _ = stderr_handle.join();
@@ -498,34 +616,66 @@ fn run_backend_json_command(
            .lock()
            .map(|buffer| buffer.trim().to_string())
            .unwrap_or_else(|_| String::new());
-        let message = if stderr_output.is_empty() {
-            format!("Bundled backend exited with status {status}.")
-        } else {
-            stderr_output
-        };
+        let message = backend_failure_message(
+            &stderr_output,
+            format!("Bundled backend exited with status {status}."),
+        );
+        append_backend_log(
+            &state.backend_log_path,
+            &format!("Backend failure: {message}"),
+        );
        let _ = fs::remove_file(&output_path);
        return Err(message);
    }

-    let raw_json = fs::read_to_string(&output_path)
-        .map_err(|err| format!("Failed to read backend output JSON: {err}"))?;
+    let raw_json = fs::read_to_string(&output_path).map_err(|err| {
+        let message = format!("Failed to read backend output JSON: {err}");
+        append_backend_log(&state.backend_log_path, &message);
+        message
+    })?;
    let _ = fs::remove_file(&output_path);

-    serde_json::from_str(&raw_json).map_err(|err| format!("Invalid backend output JSON: {err}"))
+    serde_json::from_str(&raw_json).map_err(|err| {
+        let message = format!("Invalid backend output JSON: {err}");
+        append_backend_log(&state.backend_log_path, &message);
+        message
+    })
 }

 fn run_backend_text_command(state: &AppState, args: &[String]) -> Result<String, String> {
-    let output = build_backend_command(state, args)
-        .output()
-        .map_err(|err| format!("Failed to start translation backend: {err}"))?;
+    append_backend_log(
+        &state.backend_log_path,
+        &format!("=== translate {} ===", args.join(" ")),
+    );
+    let output = build_backend_command(state, args).output().map_err(|err| {
+        let message = format!("Failed to start translation backend: {err}");
+        append_backend_log(&state.backend_log_path, &message);
+        message
+    })?;
+
+    for line in String::from_utf8_lossy(&output.stdout).lines() {
+        append_backend_log(&state.backend_log_path, &format!("[stdout] {line}"));
+    }
+    for line in String::from_utf8_lossy(&output.stderr).lines() {
+        append_backend_log(&state.backend_log_path, &format!("[stderr] {line}"));
+    }
+    append_backend_log(
+        &state.backend_log_path,
+        &format!("Translation backend exit status: {}", output.status),
+    );

    if !output.status.success() {
        let stderr = String::from_utf8_lossy(&output.stderr).trim().to_string();
-        return Err(if stderr.is_empty() {
+        let message = if stderr.is_empty() {
            format!("Translation backend exited with status {}.", output.status)
        } else {
            stderr
-        });
+        };
+        append_backend_log(
+            &state.backend_log_path,
+            &format!("Translation failure: {message}"),
+        );
+        return Err(message);
    }

    let translation = String::from_utf8(output.stdout)
@@ -533,7 +683,9 @@ fn run_backend_text_command(state: &AppState, args: &[String]) -> Result<String,
        .trim()
        .to_string();
    if translation.is_empty() {
-        return Err("Translation backend returned an empty result.".to_string());
+        let message = "Translation backend returned an empty result.".to_string();
+        append_backend_log(&state.backend_log_path, &message);
+        return Err(message);
    }

    Ok(translation)
@@ -559,19 +711,42 @@ fn summarize_video_inner(
    window_label: &str,
    request: SummarizeVideoRequest,
 ) -> Result<SummaryEntry, String> {
-    let model = normalize_model(request.model);
+    let SummarizeVideoRequest {
+        url,
+        use_whisper,
+        model,
+        master_prompt,
+    } = request;
+    let model = normalize_model(model);
    let mut args = vec![
        "summarize".to_string(),
        "--url".to_string(),
-        request.url,
+        url,
        "--model".to_string(),
        model,
    ];
-    if !request.use_whisper {
+    if !use_whisper {
        args.push("--no-whisper".to_string());
    }

-    let info = run_backend_json_command(state, app, window_label, &args)?;
+    let prompt_path = if let Some(prompt) = normalize_prompt_template(master_prompt) {
+        let path = state
+            .app_dir
+            .join(format!("tmp_prompt_{}.txt", now_millis()));
+        fs::write(&path, prompt)
+            .map_err(|err| format!("Failed to write temporary prompt file: {err}"))?;
+        args.push("--prompt-template-file".to_string());
+        args.push(path.to_string_lossy().into_owned());
+        Some(path)
+    } else {
+        None
+    };
+
+    let result = run_backend_json_command(state, app, window_label, &args);
+    if let Some(path) = prompt_path {
+        let _ = fs::remove_file(path);
+    }
+    let info = result?;
    cleanup_artifacts(state, info.audio.as_deref(), info.transcript.as_deref());

    let db = open_connection(state)?;
@@ -601,11 +776,17 @@ fn translate_summary_inner(
    state: &AppState,
    request: TranslateSummaryRequest,
 ) -> Result<SummaryEntry, String> {
+    let TranslateSummaryRequest {
+        id,
+        lang,
+        model,
+        prompt_template,
+    } = request;
    let db = open_connection(state)?;
    let summary_text = db
        .query_row(
            "SELECT summary_en FROM summaries WHERE id = ?",
-            [request.id],
+            [id],
            |row| row.get::<_, Option<String>>(0),
        )
        .optional()
@@ -613,29 +794,49 @@ fn translate_summary_inner(
        .flatten()
        .ok_or_else(|| "No English summary found for translation.".to_string())?;

-    let tmp_summary_path =
-        state
-            .app_dir
-            .join(format!("tmp_summary_{}_{}.txt", request.id, now_millis()));
+    let tmp_summary_path = state
+        .app_dir
+        .join(format!("tmp_summary_{}_{}.txt", id, now_millis()));
    fs::write(&tmp_summary_path, summary_text)
        .map_err(|err| format!("Failed to write temporary summary file: {err}"))?;

-    let model = normalize_model(request.model);
-    let args = vec![
+    let model = normalize_model(model);
+    let mut args = vec![
        "translate".to_string(),
        "--summary-file".to_string(),
        tmp_summary_path.to_string_lossy().into_owned(),
        "--lang".to_string(),
-        request.lang.clone(),
+        lang.clone(),
        "--model".to_string(),
        model,
    ];
+    let tmp_prompt_path = if let Some(prompt) = normalize_prompt_template(prompt_template) {
+        let path = state.app_dir.join(format!(
+            "tmp_translation_prompt_{}_{}.txt",
+            id,
+            now_millis()
+        ));
+        if let Err(err) = fs::write(&path, prompt) {
+            let _ = fs::remove_file(&tmp_summary_path);
+            return Err(format!(
+                "Failed to write temporary translation prompt file: {err}"
+            ));
+        }
+        args.push("--prompt-template-file".to_string());
+        args.push(path.to_string_lossy().into_owned());
+        Some(path)
+    } else {
+        None
+    };
    let result = run_backend_text_command(state, &args);

    let _ = fs::remove_file(&tmp_summary_path);
+    if let Some(path) = tmp_prompt_path {
+        let _ = fs::remove_file(path);
+    }
    let translation = result?;

-    let column = match request.lang.as_str() {
+    let column = match lang.as_str() {
        "de" => "summary_de",
        "jp" => "summary_jp",
        _ => return Err("Unsupported language code.".to_string()),
@@ -643,11 +844,11 @@ fn translate_summary_inner(

    db.execute(
        &format!("UPDATE summaries SET {column} = ? WHERE id = ?"),
-        params![translation, request.id],
+        params![translation, id],
    )
    .map_err(|err| format!("Failed to save translated summary: {err}"))?;

-    get_entry_by_id(state, request.id)
+    get_entry_by_id(state, id)
 }

 #[tauri::command]
@@ -733,13 +934,57 @@ fn open_file(file_path: String) -> Result<(), String> {
    that(path).map_err(|err| format!("Failed to open file: {err}"))
 }

+fn install_app_menu(app: &mut tauri::App) -> tauri::Result<()> {
+    let handle = app.handle();
+    let menu_builder = MenuBuilder::new(handle);
+    #[cfg(target_os = "macos")]
+    let menu_builder = {
+        let app_menu = SubmenuBuilder::new(handle, "YouTube Summarizer")
+            .hide()
+            .hide_others()
+            .show_all()
+            .separator()
+            .quit()
+            .build()?;
+        menu_builder.item(&app_menu)
+    };
+    let settings_menu = SubmenuBuilder::new(handle, "Settings")
+        .text("open_settings", "Settings...")
+        .build()?;
+    let edit_menu = SubmenuBuilder::new(handle, "Edit")
+        .undo()
+        .redo()
+        .separator()
+        .cut()
+        .copy()
+        .paste()
+        .select_all()
+        .build()?;
+    let menu = menu_builder.item(&settings_menu).item(&edit_menu).build()?;
+    app.set_menu(menu)?;
+    Ok(())
+}
+
 fn main() {
    tauri::Builder::default()
        .plugin(tauri_plugin_dialog::init())
+        .on_menu_event(|app, event| {
+            if event.id() == "open_settings" {
+                let _ = app.emit_to("main", "open-settings", ());
+            }
+        })
        .setup(|app| {
-            let state = ensure_app_state(app.handle())?;
-            app.manage(state);
-            Ok(())
+            install_app_menu(app)?;
+            match ensure_app_state(app.handle()) {
+                Ok(state) => {
+                    app.manage(state);
+                    Ok(())
+                }
+                Err(err) => {
+                    write_startup_error_log(app.handle(), &err);
+                    Err(err.into())
+                }
+            }
        })
        .invoke_handler(tauri::generate_handler![
            get_models,
--- a/src-tauri/tauri.conf.json
+++ b/src-tauri/tauri.conf.json
@@ -27,13 +27,20 @@
  },
  "bundle": {
    "active": true,
-    "resources": [
-      "../backend_cli.py",
-      "../youtube_summarizer.py",
-      "../translate_summary.py",
-      "../requirements.txt",
-      "resources/backend",
-      "resources/ffmpeg"
-    ]
+    "icon": [
+      "icons/32x32.png",
+      "icons/128x128.png",
+      "icons/128x128@2x.png",
+      "icons/icon.icns",
+      "icons/icon.ico"
+    ],
+    "resources": {
+      "../backend_cli.py": "backend_cli.py",
+      "../youtube_summarizer.py": "youtube_summarizer.py",
+      "../translate_summary.py": "translate_summary.py",
+      "../requirements.txt": "requirements.txt",
+      "resources/backend": "backend",
+      "resources/ffmpeg": "ffmpeg"
+    }
  }
 }
--- a/tools/autofill_translations.py
+++ b/tools/autofill_translations.py
@@ -4,9 +4,11 @@ import os
 import sqlite3
 import subprocess
 import sys
+from pathlib import Path

-DB_FILE = os.path.join(os.path.dirname(__file__), 'summaries.db')
-TRANSLATE_SCRIPT = os.path.join(os.path.dirname(__file__), 'translate_summary.py')
+ROOT = Path(__file__).resolve().parents[1]
+DB_FILE = os.environ.get("YTS_DB_FILE", str(ROOT / "summaries.db"))
+TRANSLATE_SCRIPT = ROOT / "translate_summary.py"
 MODEL = "mistral-small3.1:24b"

 def get_entries_needing_translation(conn):
@@ -30,7 +32,7 @@ def translate(summary_text, lang):
        # Führe das Übersetzungsskript aus
        cmd = [
            sys.executable,  # benutzt aktuelles Python
-            TRANSLATE_SCRIPT,
+            str(TRANSLATE_SCRIPT),
            "--summary-file", tmp_summary_path,
            "--lang", lang,
            "--model", MODEL,
--- a/translate_summary.py
+++ b/translate_summary.py
@@ -18,20 +18,54 @@ Example:
 import sys
 import argparse
 import json
+import math
 import requests

 LANG_MAP = {
    "de": "German",
    "jp": "Japanese"
 }
+OLLAMA_CHARS_PER_TOKEN = 3.5
+OLLAMA_OUTPUT_TOKEN_BUDGET = 2048
+OLLAMA_CONTEXT_BUCKETS = (4096, 8192, 16384, 32768, 65536)

-def translate_summary_text(summary_text, target_language, model="mistral:latest"):
+
+def default_translation_prompt_template(target_language):
+    if target_language not in LANG_MAP:
+        raise ValueError("Supported languages: de (German), jp (Japanese)")
+    return (
+        f"Translate the following summary into {LANG_MAP[target_language]}. Only output the translated summary, "
+        "no explanation or intro. If it's already in the target language, do nothing but repeat it.\n\n"
+        "Summary:\n{summary}\n\nTranslation:"
+    )
+
+
+def render_translation_prompt(summary_text, target_language, prompt_template=None):
+    template = (prompt_template or default_translation_prompt_template(target_language)).strip()
+    prompt = (
+        template
+        .replace("{language}", LANG_MAP[target_language])
+        .replace("{summary}", summary_text)
+    )
+    if "{summary}" not in template:
+        prompt = f"{prompt}\n\nSummary:\n{summary_text}\n\nTranslation:"
+    return prompt
+
+
+def choose_ollama_num_ctx(prompt, output_budget=OLLAMA_OUTPUT_TOKEN_BUDGET):
+    estimated_input_tokens = math.ceil(len(prompt) / OLLAMA_CHARS_PER_TOKEN)
+    needed_tokens = estimated_input_tokens + output_budget
+    for bucket in OLLAMA_CONTEXT_BUCKETS:
+        if needed_tokens <= bucket:
+            return bucket
+    return OLLAMA_CONTEXT_BUCKETS[-1]
+
+
+def translate_summary_text(summary_text, target_language, model="mistral:latest", prompt_template=None):
    if target_language not in LANG_MAP:
        raise ValueError("Supported languages: de (German), jp (Japanese)")
    prompt = (
-        f"Translate the following summary into {LANG_MAP[target_language]}. Only output the translated summary, "
-        "no explanation or intro. If it's already in the target language, do nothing but repeat it.\n\n"
-        f"Summary:\n{summary_text}\n\nTranslation:"
+        render_translation_prompt(summary_text, target_language, prompt_template)
    )
    payload = {
        "model": model,
@@ -39,6 +73,9 @@ def translate_summary_text(summary_text, target_language, model="mistral:latest"
            {"role": "system", "content": f"You are an expert translator proficient in {LANG_MAP[target_language]} and English."},
            {"role": "user", "content": prompt}
        ],
+        "options": {
+            "num_ctx": choose_ollama_num_ctx(prompt)
+        },
        "stream": False
    }
    resp = requests.post("http://localhost:11434/api/chat", json=payload)
@@ -47,24 +84,31 @@ def translate_summary_text(summary_text, target_language, model="mistral:latest"
    return data.get("message", {}).get("content", "").strip()


-def translate_summary_file(summary_file, target_language, model="mistral:latest"):
+def translate_summary_file(summary_file, target_language, model="mistral:latest", prompt_template=None):
    with open(summary_file, "r", encoding="utf-8") as f:
        summary_text = f.read().strip()
    if not summary_text:
        raise ValueError("Empty summary text!")
-    return translate_summary_text(summary_text, target_language, model)
+    return translate_summary_text(summary_text, target_language, model, prompt_template)

 def main():
    parser = argparse.ArgumentParser(description="Translate summary using Ollama")
    parser.add_argument("--summary-file", required=True, help="Path to file with English summary text")
    parser.add_argument("--lang", required=True, choices=["de", "jp"], help="Target language: 'de' or 'jp'")
    parser.add_argument("--model", default="mistral:latest", help="Ollama model to use")
+    parser.add_argument("--prompt-template", help="Prompt template for the translation LLM call")
+    parser.add_argument("--prompt-template-file", help="Path to a text file containing the translation prompt template")
    parser.add_argument("--output-file", help="Output file for translated summary")
    args = parser.parse_args()

+    prompt_template = args.prompt_template
+    if args.prompt_template_file:
+        with open(args.prompt_template_file, "r", encoding="utf-8") as f:
+            prompt_template = f.read()
+
    # Read summary
    try:
-        translation = translate_summary_file(args.summary_file, args.lang, args.model)
+        translation = translate_summary_file(args.summary_file, args.lang, args.model, prompt_template)
    except Exception as e:
        print(f"Translation failed: {e}", file=sys.stderr)
        sys.exit(2)
--- a/ui/index.html
+++ b/ui/index.html
@@ -98,6 +98,12 @@
    .entry .summary {
      transition: max-height 0.2s;
    }
+    .entry .summary hr {
+      border: 0;
+      border-top: 1px solid currentColor;
+      color: inherit;
+      margin: 0.7em 0;
+    }
    .entry.collapsed .summary {
      display: -webkit-box !important;
      -webkit-line-clamp: 2;
@@ -130,36 +136,160 @@
      color: white;
      font-weight: bold;
    }
-    header button:disabled {
-      background-color: #ffe4e6;
-      color: #9f1239;
-      opacity: 0.7;
-      cursor: default;
-      border: 1px solid #fbb6ce;
-    }
-  </style>
-</head>
-<body>
-  <header style="display:flex; flex-direction:column; gap:5px;">
-    <form id="summarize-form" style="display:flex; width:100%; gap:10px; align-items:center; flex-wrap: wrap;">
-      <input type="text" id="url-input" placeholder="Enter YouTube URL" />
-      <button type="submit">Summarize!</button>
-      <div style="display: flex; flex-direction: column; gap: 2px; min-width:120px;">
-        <label style="font-size:14px; color:#9f1239; display: flex; align-items: center; gap: 5px;">
-          <input type="checkbox" id="whisper-checkbox" checked />Use Whisper
-        </label>
-        <label style="font-size:14px; color:#9f1239; display: flex; align-items: center; gap: 5px;">
-          <input type="checkbox" id="autotranslate-checkbox" checked />Auto Translate
-        </label>
-      </div>
-      <select id="model-select" style="padding:6px; font-size:14px;">
-        <option disabled selected>Loading models…</option>
-      </select>
-    </form>
-    <div id="loading" class="loading" style="display:none;">Loading…</div>
-  </header>
-  <div id="pagination-top" class="pagination" style="display:none;"></div>
-  <div id="summaries-container"></div>
+	    header button:disabled {
+	      background-color: #ffe4e6;
+	      color: #9f1239;
+	      opacity: 0.7;
+	      cursor: default;
+	      border: 1px solid #fbb6ce;
+	    }
+	    .settings-dialog[hidden] {
+	      display: none;
+	    }
+	    .settings-dialog {
+	      position: fixed;
+	      inset: 0;
+	      z-index: 1000;
+	      display: flex;
+	      align-items: center;
+	      justify-content: center;
+	      padding: 24px;
+	      background: rgba(69, 10, 10, 0.28);
+	    }
+	    .settings-panel {
+	      width: min(720px, 100%);
+	      max-height: min(760px, calc(100vh - 48px));
+	      overflow: auto;
+	      padding: 18px;
+	      border: 1px solid #fecdd3;
+	      border-radius: 6px;
+	      background: #fff1f2;
+	      box-shadow: 0 16px 40px rgba(159, 18, 57, 0.18);
+	    }
+	    .settings-panel-header {
+	      display: flex;
+	      align-items: center;
+	      justify-content: space-between;
+	      gap: 16px;
+	      margin-bottom: 14px;
+	    }
+	    .settings-panel-header h2 {
+	      margin: 0;
+	      font-size: 20px;
+	    }
+	    .settings-close-button {
+	      width: 30px;
+	      height: 30px;
+	      display: flex;
+	      align-items: center;
+	      justify-content: center;
+	      padding: 0;
+	      border: none;
+	      border-radius: 4px;
+	      background: transparent;
+	      color: #9f1239;
+	      font-size: 24px;
+	      line-height: 1;
+	      cursor: pointer;
+	    }
+	    .settings-close-button:hover {
+	      background: #ffe4e6;
+	    }
+	    .settings-row {
+	      display: flex;
+	      align-items: center;
+	      gap: 8px;
+	      margin: 10px 0;
+	      font-size: 15px;
+	    }
+	    .settings-row input[type="checkbox"] {
+	      accent-color: #9f1239;
+	    }
+	    .settings-field-label {
+	      display: block;
+	      margin: 16px 0 6px;
+	      font-size: 14px;
+	      font-weight: bold;
+	    }
+	    .settings-prompt-textarea {
+	      width: 100%;
+	      min-height: 260px;
+	      box-sizing: border-box;
+	      padding: 10px;
+	      border: 1px solid #fda4af;
+	      border-radius: 4px;
+	      background: #fff;
+	      color: #7f1d1d;
+	      font: 13px/1.45 ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", monospace;
+	      resize: vertical;
+	    }
+	    .settings-prompt-textarea.compact {
+	      min-height: 150px;
+	    }
+	    .settings-actions {
+	      display: flex;
+	      justify-content: flex-end;
+	      gap: 10px;
+	      margin-top: 12px;
+	    }
+	    .settings-actions button {
+	      padding: 8px 12px;
+	      border: 1px solid #9f1239;
+	      border-radius: 4px;
+	      background: #fff1f2;
+	      color: #9f1239;
+	      cursor: pointer;
+	    }
+	    .settings-actions button:hover {
+	      background: #9f1239;
+	      color: #fff;
+	    }
+	  </style>
+	</head>
+	<body>
+	  <header style="display:flex; flex-direction:column; gap:5px;">
+	    <form id="summarize-form" style="display:flex; width:100%; gap:10px; align-items:center; flex-wrap: wrap;">
+	      <input type="text" id="url-input" placeholder="Enter YouTube URL" />
+	      <button type="submit">Summarize!</button>
+	      <select id="model-select" style="padding:6px; font-size:14px;">
+	        <option disabled selected>Loading models…</option>
+	      </select>
+	    </form>
+	    <div id="loading" class="loading" style="display:none;">Loading…</div>
+	  </header>
+	  <div id="settings-dialog" class="settings-dialog" hidden role="dialog" aria-modal="true" aria-labelledby="settings-title">
+	    <section class="settings-panel">
+	      <div class="settings-panel-header">
+	        <h2 id="settings-title">Settings</h2>
+	        <button type="button" id="settings-close-button" class="settings-close-button" aria-label="Close settings">&times;</button>
+	      </div>
+	      <label class="settings-row">
+	        <input type="checkbox" id="whisper-checkbox" checked />
+	        <span>Use Whisper</span>
+	      </label>
+	      <label class="settings-row">
+	        <input type="checkbox" id="autotranslate-checkbox" checked />
+	        <span>Auto Translate</span>
+	      </label>
+	      <label for="master-prompt-textarea" class="settings-field-label">Master Prompt</label>
+	      <textarea id="master-prompt-textarea" class="settings-prompt-textarea" spellcheck="false"></textarea>
+	      <div class="settings-actions">
+	        <button type="button" id="reset-master-prompt-button">Reset to default</button>
+	      </div>
+	      <label for="translation-prompt-de-textarea" class="settings-field-label">German Translation Prompt</label>
+	      <textarea id="translation-prompt-de-textarea" class="settings-prompt-textarea compact" spellcheck="false"></textarea>
+	      <div class="settings-actions">
+	        <button type="button" id="reset-translation-prompt-de-button">Reset to default</button>
+	      </div>
+	      <label for="translation-prompt-jp-textarea" class="settings-field-label">Japanese Translation Prompt</label>
+	      <textarea id="translation-prompt-jp-textarea" class="settings-prompt-textarea compact" spellcheck="false"></textarea>
+	      <div class="settings-actions">
+	        <button type="button" id="reset-translation-prompt-jp-button">Reset to default</button>
+	      </div>
+	    </section>
+	  </div>
+	  <div id="pagination-top" class="pagination" style="display:none;"></div>
+	  <div id="summaries-container"></div>
  <div id="pagination-bottom" class="pagination" style="display:none;"></div>
  <script src="renderer.js"></script>
 </body>
--- a/ui/renderer.js
+++ b/ui/renderer.js
@@ -3,6 +3,28 @@ const invoke = tauriApi?.core?.invoke;
 const listen = tauriApi?.event?.listen;
 const convertFileSrc = tauriApi?.core?.convertFileSrc;
 const confirmDialog = tauriApi?.dialog?.confirm;
+const DEFAULT_MASTER_PROMPT = `You are an expert summarizer. Summarize the following video concisely:
+
+Title: {title}
+
+Transcript:
+{transcript}
+
+Summary:`;
+const DEFAULT_TRANSLATION_PROMPTS = {
+  de: `Translate the following summary into German. Only output the translated summary, no explanation or intro. If it's already in the target language, do nothing but repeat it.
+
+Summary:
+{summary}
+
+Translation:`,
+  jp: `Translate the following summary into Japanese. Only output the translated summary, no explanation or intro. If it's already in the target language, do nothing but repeat it.
+
+Summary:
+{summary}
+
+Translation:`
+};

 if (!invoke || !listen) {
  throw new Error('Tauri runtime API is unavailable.');
@@ -21,11 +43,12 @@ function toWebviewFileUrl(filePath) {
 window.api = {
  getModels: () => invoke('get_models'),
  getSummaries: () => invoke('get_summaries'),
-  summarizeVideo: (url, useWhisper, model) => invoke('summarize_video', {
+  summarizeVideo: (url, useWhisper, model, masterPrompt) => invoke('summarize_video', {
    request: {
      url,
      useWhisper,
-      model: model || null
+      model: model || null,
+      masterPrompt: masterPrompt || null
    }
  }),
  openExternal: (url) => invoke('open_external', { url }),
@@ -33,16 +56,18 @@ window.api = {
  deleteSummary: (id) => invoke('delete_summary', {
    request: { id }
  }),
-  translateSummary: (id, lang, model) => invoke('translate_summary', {
+  translateSummary: (id, lang, model, promptTemplate) => invoke('translate_summary', {
    request: {
      id,
      lang,
-      model: model || null
+      model: model || null,
+      promptTemplate: promptTemplate || null
    }
  }),
  onSummarizeProgress: (callback) => listen('summarize-progress', (event) => {
    callback(String(event.payload || ''));
-  })
+  }),
+  onOpenSettings: (callback) => listen('open-settings', callback)
 };

 window.addEventListener('DOMContentLoaded', async () => {
@@ -56,6 +81,15 @@ window.addEventListener('DOMContentLoaded', async () => {
  const paginationBottom = document.getElementById('pagination-bottom');
  const summarizeButton = form.querySelector('button[type="submit"]');
  const autoTranslateCheckbox = document.getElementById('autotranslate-checkbox');
+  const settingsDialog = document.getElementById('settings-dialog');
+  const settingsPanel = settingsDialog.querySelector('.settings-panel');
+  const settingsCloseButton = document.getElementById('settings-close-button');
+  const masterPromptTextarea = document.getElementById('master-prompt-textarea');
+  const resetMasterPromptButton = document.getElementById('reset-master-prompt-button');
+  const translationPromptDeTextarea = document.getElementById('translation-prompt-de-textarea');
+  const translationPromptJpTextarea = document.getElementById('translation-prompt-jp-textarea');
+  const resetTranslationPromptDeButton = document.getElementById('reset-translation-prompt-de-button');
+  const resetTranslationPromptJpButton = document.getElementById('reset-translation-prompt-jp-button');

  let fullSummaries = [];
  let currentPage = 1;
@@ -71,8 +105,45 @@ window.addEventListener('DOMContentLoaded', async () => {
    loadingIndicator.textContent = message;
  }

+  function getMasterPrompt() {
+    const savedPrompt = localStorage.getItem('masterPrompt');
+    if (savedPrompt && savedPrompt.trim()) {
+      return savedPrompt;
+    }
+    return DEFAULT_MASTER_PROMPT;
+  }
+
+  function getTranslationPrompt(lang) {
+    const savedPrompt = localStorage.getItem(`translationPrompt.${lang}`);
+    if (savedPrompt && savedPrompt.trim()) {
+      return savedPrompt;
+    }
+    return DEFAULT_TRANSLATION_PROMPTS[lang];
+  }
+
+  function syncSettingsFields() {
+    whisperCheckbox.checked = localStorage.getItem('useWhisper') === '0' ? false : true;
+    autoTranslateCheckbox.checked = localStorage.getItem('autoTranslate') === '1' ? true : false;
+    masterPromptTextarea.value = getMasterPrompt();
+    translationPromptDeTextarea.value = getTranslationPrompt('de');
+    translationPromptJpTextarea.value = getTranslationPrompt('jp');
+  }
+
+  function openSettings() {
+    syncSettingsFields();
+    settingsDialog.hidden = false;
+    masterPromptTextarea.focus();
+  }
+
+  function closeSettings() {
+    settingsDialog.hidden = true;
+  }
+
  whisperCheckbox.checked = localStorage.getItem('useWhisper') === '0' ? false : true;
  autoTranslateCheckbox.checked = localStorage.getItem('autoTranslate') === '1' ? true : false;
+  masterPromptTextarea.value = getMasterPrompt();
+  translationPromptDeTextarea.value = getTranslationPrompt('de');
+  translationPromptJpTextarea.value = getTranslationPrompt('jp');

  whisperCheckbox.addEventListener('change', () => {
    localStorage.setItem('useWhisper', whisperCheckbox.checked ? '1' : '0');
@@ -80,6 +151,41 @@ window.addEventListener('DOMContentLoaded', async () => {
  autoTranslateCheckbox.addEventListener('change', () => {
    localStorage.setItem('autoTranslate', autoTranslateCheckbox.checked ? '1' : '0');
  });
+  masterPromptTextarea.addEventListener('input', () => {
+    localStorage.setItem('masterPrompt', masterPromptTextarea.value);
+  });
+  translationPromptDeTextarea.addEventListener('input', () => {
+    localStorage.setItem('translationPrompt.de', translationPromptDeTextarea.value);
+  });
+  translationPromptJpTextarea.addEventListener('input', () => {
+    localStorage.setItem('translationPrompt.jp', translationPromptJpTextarea.value);
+  });
+  resetMasterPromptButton.addEventListener('click', () => {
+    masterPromptTextarea.value = DEFAULT_MASTER_PROMPT;
+    localStorage.setItem('masterPrompt', DEFAULT_MASTER_PROMPT);
+    masterPromptTextarea.focus();
+  });
+  resetTranslationPromptDeButton.addEventListener('click', () => {
+    translationPromptDeTextarea.value = DEFAULT_TRANSLATION_PROMPTS.de;
+    localStorage.setItem('translationPrompt.de', DEFAULT_TRANSLATION_PROMPTS.de);
+    translationPromptDeTextarea.focus();
+  });
+  resetTranslationPromptJpButton.addEventListener('click', () => {
+    translationPromptJpTextarea.value = DEFAULT_TRANSLATION_PROMPTS.jp;
+    localStorage.setItem('translationPrompt.jp', DEFAULT_TRANSLATION_PROMPTS.jp);
+    translationPromptJpTextarea.focus();
+  });
+  settingsCloseButton.addEventListener('click', closeSettings);
+  settingsDialog.addEventListener('click', (event) => {
+    if (!settingsPanel.contains(event.target)) {
+      closeSettings();
+    }
+  });
+  window.addEventListener('keydown', (event) => {
+    if (event.key === 'Escape' && !settingsDialog.hidden) {
+      closeSettings();
+    }
+  });

  function renderSummaries(list) {
    summariesContainer.innerHTML = '';
@@ -345,6 +451,8 @@ window.addEventListener('DOMContentLoaded', async () => {
      .replace(/^## (.+)$/gm, '<h2>$1</h2>')
      .replace(/^# (.+)$/gm, '<h1>$1</h1>');

+    escaped = escaped.replace(/^---$/gm, '<hr>');
+
    escaped = escaped.replace(
      /(^|\n)([ \t]*\* .+(?:\n[ \t]*\* .+)*)/g,
      (_, lead, listBlock) => {
@@ -525,7 +633,7 @@ window.addEventListener('DOMContentLoaded', async () => {
    setActionLinksDisabled(true);

    const selectedModel = modelSelect.value;
-    window.api.summarizeVideo(url, useWhisper, selectedModel)
+    window.api.summarizeVideo(url, useWhisper, selectedModel, getMasterPrompt())
      .then((newEntry) => {
        if (!newEntry || !newEntry.id) {
          return window.api.getSummaries().then(setSummaries);
@@ -539,10 +647,10 @@ window.addEventListener('DOMContentLoaded', async () => {

        let translationsOk = true;
        setLoadingMessage('Translating to German (DE)…');
-        return window.api.translateSummary(newEntry.id, 'de', selectedModel)
+        return window.api.translateSummary(newEntry.id, 'de', selectedModel, getTranslationPrompt('de'))
          .then(() => {
            setLoadingMessage('Translating to Japanese (JP)…');
-            return window.api.translateSummary(newEntry.id, 'jp', selectedModel);
+            return window.api.translateSummary(newEntry.id, 'jp', selectedModel, getTranslationPrompt('jp'));
          })
          .catch(err => {
            translationsOk = false;
@@ -575,4 +683,5 @@ window.addEventListener('DOMContentLoaded', async () => {
    }
    setLoadingMessage(line);
  });
+  window.api.onOpenSettings(openSettings);
 });
--- a/youtube_summarizer.py
+++ b/youtube_summarizer.py
@@ -35,8 +35,10 @@ import re
 import time
 import json
 import glob
+import math
 import subprocess
 import multiprocessing
+import threading
 import requests
 import yt_dlp
 import webvtt
@@ -62,6 +64,17 @@ NUM_SLICES = 8
 OVERLAP_SEC = 1
 MAX_OVERLAP_WORDS = 7
 WHISPER_MODEL = "small"  # e.g. "small", "medium", "large-v3" …
+OLLAMA_CHARS_PER_TOKEN = 3.5
+OLLAMA_OUTPUT_TOKEN_BUDGET = 2048
+OLLAMA_CONTEXT_BUCKETS = (4096, 8192, 16384, 32768, 65536)
+DEFAULT_SUMMARY_PROMPT_TEMPLATE = """You are an expert summarizer. Summarize the following video concisely:
+
+Title: {title}
+
+Transcript:
+{transcript}
+
+Summary:"""


 def debug_print(*args, **kwargs):
@@ -70,6 +83,30 @@ def debug_print(*args, **kwargs):
        print("[DEBUG]", *args, **kwargs, file=sys.stderr)


+class ProgressHeartbeat:
+    """Emit periodic progress while a blocking backend operation is active."""
+
+    def __init__(self, message_fn, interval: float = 15.0):
+        self.message_fn = message_fn
+        self.interval = interval
+        self._stop = threading.Event()
+        self._thread = threading.Thread(target=self._run, daemon=True)
+
+    def __enter__(self):
+        self._thread.start()
+        return self
+
+    def __exit__(self, exc_type, exc, tb):
+        self._stop.set()
+        self._thread.join(timeout=1.0)
+
+    def _run(self):
+        while not self._stop.wait(self.interval):
+            message = self.message_fn()
+            if message:
+                print(message, flush=True)
+
+
 def get_ffmpeg_binary() -> str:
    """Return the ffmpeg executable path, preferring a bundled override."""
    value = os.environ.get("YTS_FFMPEG", "").strip()
@@ -82,6 +119,31 @@ def get_ffprobe_binary() -> str:
    return value or "ffprobe"


+def get_ffmpeg_directory() -> Optional[str]:
+    """Return the directory containing the configured ffmpeg binary."""
+    value = os.environ.get("YTS_FFMPEG", "").strip()
+    if not value:
+        return None
+    if os.path.isfile(value):
+        return os.path.dirname(value)
+    return value
+
+
+def get_yt_dlp_ffmpeg_location() -> Optional[str]:
+    """Return an ffmpeg location suitable for yt_dlp postprocessors."""
+    return get_ffmpeg_directory()
+
+
+def ensure_ffmpeg_on_path() -> None:
+    """Expose bundled ffmpeg to libraries that shell out to plain `ffmpeg`."""
+    ffmpeg_dir = get_ffmpeg_directory()
+    if not ffmpeg_dir:
+        return
+    path_entries = [entry for entry in os.environ.get("PATH", "").split(os.pathsep) if entry]
+    if ffmpeg_dir not in path_entries:
+        os.environ["PATH"] = os.pathsep.join([ffmpeg_dir, *path_entries])
+
+
 def get_whisper_download_root() -> Optional[str]:
    """Return a stable Whisper cache directory when one is configured."""
    value = os.environ.get("YTS_WHISPER_CACHE_DIR", "").strip()
@@ -286,6 +348,9 @@ def _download_audio_with_yt_dlp(url: str, vid: str, extractor_args: Optional[dic
    }
    if extractor_args:
        opts["extractor_args"] = extractor_args
+    ffmpeg_location = get_yt_dlp_ffmpeg_location()
+    if ffmpeg_location:
+        opts["ffmpeg_location"] = ffmpeg_location
    with yt_dlp.YoutubeDL(opts) as ydl:
        ydl.download([url])
    if not os.path.exists(audio_fn):
@@ -295,7 +360,8 @@ def _download_audio_with_yt_dlp(url: str, vid: str, extractor_args: Optional[dic

 def download_video_audio(url: str, vid: str) -> str:
    """Download the best available audio for a YouTube video."""
-    print(f"📥 Downloading audio from {url} …")
+    ensure_ffmpeg_on_path()
+    print(f"Downloading audio from {url} ...")

    # Clean up any stale partials that can trigger HTTP 416 resume errors.
    _cleanup_audio_artifacts(vid)
@@ -322,16 +388,63 @@ def download_video_audio(url: str, vid: str) -> str:

 def get_audio_duration(path: str) -> float:
    """Return the duration of an audio file using ffprobe."""
-    res = subprocess.run([
+    try:
+        file_size = os.path.getsize(path)
+    except OSError:
+        file_size = None
+
+    ffprobe_args = [
        get_ffprobe_binary(), "-v", "error", "-show_entries", "format=duration",
        "-of", "default=noprint_wrappers=1:nokey=1", path
-    ], capture_output=True, text=True)
-    return float(res.stdout.strip())
+    ]
+    res = subprocess.run(
+        ffprobe_args,
+        capture_output=True,
+        text=True,
+        encoding="utf-8",
+        errors="replace",
+    )
+
+    print(f"[ffprobe] command: {ffprobe_args}", file=sys.stderr, flush=True)
+    print(f"[ffprobe] target: {path}", file=sys.stderr, flush=True)
+    print(f"[ffprobe] target size bytes: {file_size}", file=sys.stderr, flush=True)
+    print(f"[ffprobe] returncode: {res.returncode}", file=sys.stderr, flush=True)
+    print("[ffprobe] stdout raw begin", file=sys.stderr, flush=True)
+    if res.stdout:
+        sys.stderr.write(res.stdout)
+        if not res.stdout.endswith("\n"):
+            sys.stderr.write("\n")
+        sys.stderr.flush()
+    else:
+        print("<empty>", file=sys.stderr, flush=True)
+    print("[ffprobe] stdout raw end", file=sys.stderr, flush=True)
+    print("[ffprobe] stderr raw begin", file=sys.stderr, flush=True)
+    if res.stderr:
+        sys.stderr.write(res.stderr)
+        if not res.stderr.endswith("\n"):
+            sys.stderr.write("\n")
+        sys.stderr.flush()
+    else:
+        print("<empty>", file=sys.stderr, flush=True)
+    print("[ffprobe] stderr raw end", file=sys.stderr, flush=True)
+
+    stdout_value = res.stdout.strip()
+    try:
+        return float(stdout_value)
+    except ValueError:
+        match = re.search(r"[-+]?\d+(?:[.,]\d+)?", stdout_value or res.stderr)
+        if match:
+            return float(match.group(0).replace(",", "."))
+
+    raise RuntimeError(
+        "ffprobe did not return a parseable duration "
+        f"(returncode={res.returncode}, stdout={stdout_value!r}, stderr={res.stderr.strip()!r})"
+    )


 def slice_audio(audio_path: str, vid: str) -> List[Tuple[str, float, float]]:
    """Slice a long audio file into overlapping chunks for Whisper."""
-    print("Slicing audio …")
+    print("Slicing audio ...")
    duration = get_audio_duration(audio_path)
    length = duration / NUM_SLICES
    slices = []
@@ -351,6 +464,7 @@ def slice_audio(audio_path: str, vid: str) -> List[Tuple[str, float, float]]:

 def transcribe_slice(args: Tuple[str, int, str, str]) -> str:
    """Transcribe a single audio slice using Whisper and save to a text file."""
+    ensure_ffmpeg_on_path()
    slice_path, idx, model_name, vid = args
    if whisper is None:
        raise RuntimeError("Whisper package is required but not installed")
@@ -398,9 +512,10 @@ def clean_temp(pattern: str) -> None:

 def whisper_transcript(url: str, vid: str) -> str:
    """Run the Whisper pipeline and return the final transcript text."""
+    ensure_ffmpeg_on_path()
    audio = download_video_audio(url, vid)
    slices = slice_audio(audio, vid)
-    print("✍️  Transcribing using Whisper...", flush=True)
+    print("Transcribing using Whisper...", flush=True)
    args = [(p, i, WHISPER_MODEL, vid) for i, (p, _, _) in enumerate(slices)]
    with multiprocessing.Pool(len(slices)) as pool:
        t_files = pool.map(transcribe_slice, args)
@@ -415,17 +530,36 @@ def whisper_transcript(url: str, vid: str) -> str:
 # Ollama‑Summarizer
 # -----------------------

-def summarize_with_ollama(title: str, transcript: str, model: str = "mistral:latest") -> str:
+def render_summary_prompt(title: str, transcript: str, prompt_template: Optional[str] = None) -> str:
+    template = (prompt_template or DEFAULT_SUMMARY_PROMPT_TEMPLATE).strip()
+    prompt = template.replace("{title}", title).replace("{transcript}", transcript)
+    if "{title}" not in template:
+        prompt = f"{prompt}\n\nTitle: {title}"
+    if "{transcript}" not in template:
+        prompt = f"{prompt}\n\nTranscript:\n{transcript}"
+    return prompt
+
+
+def choose_ollama_num_ctx(prompt: str, output_budget: int = OLLAMA_OUTPUT_TOKEN_BUDGET) -> int:
+    estimated_input_tokens = math.ceil(len(prompt) / OLLAMA_CHARS_PER_TOKEN)
+    needed_tokens = estimated_input_tokens + output_budget
+    for bucket in OLLAMA_CONTEXT_BUCKETS:
+        if needed_tokens <= bucket:
+            return bucket
+    return OLLAMA_CONTEXT_BUCKETS[-1]
+
+
+def summarize_with_ollama(
+    title: str,
+    transcript: str,
+    model: str = "mistral:latest",
+    prompt_template: Optional[str] = None,
+) -> str:
    """
    Send video title and transcript text to Ollama and return the summary string.
    """
    debug_print(f"Preparing summary with model {model}, transcript length={len(transcript)}")
-    prompt = (
-        "You are an expert summarizer. Summarize the following video concisely:\n\n"
-        f"Title: {title}\n\n"
-        f"Transcript:\n{transcript}\n\n"
-        "Summary:"
-    )
+    prompt = render_summary_prompt(title, transcript, prompt_template)
    debug_print(prompt)
    payload = {
        "model": model,
@@ -433,21 +567,50 @@ def summarize_with_ollama(title: str, transcript: str, model: str = "mistral:lat
            {"role": "system", "content": "You are an intelligent summarizer."},
            {"role": "user", "content": prompt}
        ],
+        "options": {
+            "num_ctx": choose_ollama_num_ctx(prompt)
+        },
        "stream": True
    }
-    debug_print("Sending request to Ollama …")
-    resp = requests.post("http://localhost:11434/api/chat", json=payload, stream=True)
-    debug_print(f"Ollama status: {resp.status_code}")
+    debug_print("Sending request to Ollama ...")
    summary = ""
-    for line in resp.iter_lines(decode_unicode=True):
-        if not line:
-            continue
-        try:
-            msg = json.loads(line).get("message", {}).get("content", "")
-            summary += msg
-        except Exception:
-            continue
+    last_progress_chars = 0
+
+    def heartbeat_message() -> str:
+        if summary:
+            return f"Ollama is generating summary... {len(summary)} characters received."
+        return "Waiting for Ollama to start responding..."
+
+    try:
+        with ProgressHeartbeat(heartbeat_message):
+            resp = requests.post(
+                "http://localhost:11434/api/chat",
+                json=payload,
+                stream=True,
+                timeout=(10, 1800),
+            )
+            debug_print(f"Ollama status: {resp.status_code}")
+            resp.raise_for_status()
+            for line in resp.iter_lines(decode_unicode=True):
+                if not line:
+                    continue
+                try:
+                    msg = json.loads(line).get("message", {}).get("content", "")
+                    summary += msg
+                    if len(summary) - last_progress_chars >= 1000:
+                        last_progress_chars = len(summary)
+                        print(
+                            f"Ollama is generating summary... {last_progress_chars} characters received.",
+                            flush=True,
+                        )
+                except Exception:
+                    continue
+    except requests.RequestException as exc:
+        raise RuntimeError(f"Ollama request failed: {exc}") from exc
+    if not summary.strip():
+        raise RuntimeError("Ollama returned an empty summary.")
    debug_print(f"Summary generated, length={len(summary)}")
+    print("Summary generated.", flush=True)
    return summary


@@ -517,7 +680,13 @@ def download_thumbnail(vid: str, thumbnail_url: str) -> Optional[str]:
 # Main
 # -----------------------

-def process_video(url: str, use_whisper: bool, model: str = "mistral:latest", output_json: Optional[str] = None) -> dict:
+def process_video(
+    url: str,
+    use_whisper: bool,
+    model: str = "mistral:latest",
+    output_json: Optional[str] = None,
+    prompt_template: Optional[str] = None,
+) -> dict:
    """
    Core processing routine.  Retrieves metadata, obtains transcript via the
    selected workflow, generates a summary using Ollama and writes the
@@ -552,17 +721,17 @@ def process_video(url: str, use_whisper: bool, model: str = "mistral:latest", ou

    # Fetch transcript
    if use_whisper:
-        print("🤖  Using Whisper parallel transcription…")
+        print("Using Whisper parallel transcription...")
        transcript_text = whisper_transcript(url, vid)
        if not transcript_text.strip():
            raise SystemExit("Whisper transcription failed or empty.")
    else:
-        print("▶️  Using classic API/subtitle workflow…")
+        print("Using classic API/subtitle workflow...")
        # Try API first
        try:
            transcript_text = get_transcript_api(vid)
        except Exception:
-            print("API failed, falling back to subtitles…")
+            print("API failed, falling back to subtitles...")
            transcript_text = get_subtitles_via_yt_dlp(url)
        if not transcript_text:
            raise SystemExit("No transcript/subtitles available.")
@@ -601,8 +770,8 @@ def process_video(url: str, use_whisper: bool, model: str = "mistral:latest", ou
            audio_filename = None

    # Generate summary
-    print("✍️  Generating summary with Ollama…", flush=True)
-    summary_text = summarize_with_ollama(title, transcript_text, model)
+    print("Generating summary with Ollama...", flush=True)
+    summary_text = summarize_with_ollama(title, transcript_text, model, prompt_template)

    # Create metadata dictionary
    meta = {
@@ -625,7 +794,13 @@ def process_video(url: str, use_whisper: bool, model: str = "mistral:latest", ou
    return meta


-def rewrite_summary(title: str, transcript_file: str, model: str = "mistral:latest", output_json: Optional[str] = None) -> dict:
+def rewrite_summary(
+    title: str,
+    transcript_file: str,
+    model: str = "mistral:latest",
+    output_json: Optional[str] = None,
+    prompt_template: Optional[str] = None,
+) -> dict:
    """
    Regenerate a summary from an existing transcript file using the specified model.

@@ -648,7 +823,7 @@ def rewrite_summary(title: str, transcript_file: str, model: str = "mistral:late
    with open(transcript_file, 'r', encoding='utf-8') as f:
        transcript_text = f.read()
    debug_print(f"Rewriting summary using model {model} for {transcript_file}")
-    summary_text = summarize_with_ollama(title, transcript_text, model)
+    summary_text = summarize_with_ollama(title, transcript_text, model, prompt_template)
    meta = {'summary': summary_text}
    if output_json:
        with open(output_json, 'w', encoding='utf-8') as f:
@@ -669,17 +844,25 @@ def main():
                        help="Ollama model to use for summarization (default: mistral:latest)")
    parser.add_argument('--transcript-file', type=str, default=None,
                        help="Path to an existing transcript file; when provided the script will skip transcription and only generate a summary.")
+    parser.add_argument('--prompt-template', type=str, default=None,
+                        help="Prompt template for the summary LLM call.")
+    parser.add_argument('--prompt-template-file', type=str, default=None,
+                        help="Path to a text file containing the prompt template.")
    args = parser.parse_args()

    use_whisper = not args.no_ai
+    prompt_template = args.prompt_template
+    if args.prompt_template_file:
+        with open(args.prompt_template_file, 'r', encoding='utf-8') as f:
+            prompt_template = f.read()

    try:
        # If a transcript file is provided, skip the normal processing and only rewrite summary
        if args.transcript_file:
            vid, title, _ = fetch_video_metadata(args.url)
-            meta = rewrite_summary(title, args.transcript_file, args.model, args.output_json)
+            meta = rewrite_summary(title, args.transcript_file, args.model, args.output_json, prompt_template)
        else:
-            meta = process_video(args.url, use_whisper, args.model, args.output_json)
+            meta = process_video(args.url, use_whisper, args.model, args.output_json, prompt_template)
        # If no JSON output specified, print metadata as JSON to stdout
        if not args.output_json:
            print(json.dumps(meta, ensure_ascii=False, indent=2))