Fix podcasts generating in English + failing with invalid JSON
Two root causes, both fixed in the bind-mounted podcast prompt templates
(prompts/podcast/*.jinja):
1. Language: the episode profile's `language` field IS passed to both
podcast_creator templates as {{ language }}, but the stock templates never
reference it — so podcasts came out English (driven only by the English
stock briefings/speakers), then read aloud by the German-locked Chatterbox
TTS = "English with a German accent". Added a CRITICAL LANGUAGE REQUIREMENT
block keyed on {{ language }} to both templates; now `language: "de"`
actually forces German. Verified end-to-end: a full run produced a 44-line
all-German transcript + audio.
2. Invalid json output failures: qwen3.5:27b is a thinking model; on long
segments the <think> block ate the response-token budget and truncated the
JSON. Prepended /no_think to both templates (~3x faster, valid JSON).
Templates are bind-mounted read-only via docker-compose (directory mount, so
edits survive a container restart without inode-staleness). Bundled briefings
and speaker backstories were also translated to German to reduce drift.
Known limitation documented: feeding an entire book (~70k tokens) as podcast
content makes each of the 6 LLM calls take ~3.5 min and is unreliable; use a
shorter source or summary. Confirmed working with concise content.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
parent
e2fb113213
commit
054f867a8a
6 changed files with 304 additions and 18 deletions
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@ -379,21 +379,36 @@ Das Episode- oder Sprecherprofil verweist auf ein Modell ohne konfiguriertes Cre
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`PUT /api/speaker-profiles/{id}` (`voice_model`) auf registrierte lokale/OpenRouter-Modelle
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umstellen — siehe `scripts/setup_models.sh` für die IDs der Standardmodelle.
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### Podcast wird auf Englisch statt Deutsch erzeugt
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### Podcast wird auf Englisch statt Deutsch erzeugt (oder auf Englisch mit deutschem Akzent vorgelesen)
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Das verwendete Episode-Profil hat kein `language`-Feld gesetzt — ohne Angabe generiert das
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Sprachmodell standardmäßig auf Englisch, unabhängig von der Sprache der Quelle. Prüfen und
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korrigieren:
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Das ist behoben: Die Podcast-Prompt-Vorlagen (`prompts/podcast/outline.jinja` und
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`transcript.jinja` in diesem Projekt) wurden um eine explizite Sprachanweisung ergänzt, die das
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`language`-Feld des Episode-Profils auswertet — sie werden per Bind-Mount aus `docker-compose.yml`
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in den Container eingehängt. Setzt du am Episode-Profil `language: "de"`, kommt der Podcast auf
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Deutsch. (Vorher hatte das `language`-Feld keine Wirkung, weil die mitgelieferten Vorlagen es
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ignorierten — daher englischer Text, der von der deutsch-fixierten TTS mit Akzent vorgelesen wurde.)
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Falls doch wieder Englisch erscheint, prüfe das `language`-Feld:
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```bash
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curl -s http://127.0.0.1:5055/api/episode-profiles | python3 -c \
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"import json,sys; [print(p['name'], p['language']) for p in json.load(sys.stdin)]"
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```
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Fehlt `de`, per `PUT /api/episode-profiles/{id}` (vollständiger Body nötig, siehe oben)
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`"language": "de"` ergänzen. Die drei mitgelieferten Profile (`business_analysis`,
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`solo_expert`, `tech_discussion`) sind bereits korrigiert; bei neu angelegten eigenen Profilen
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selbst daran denken.
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Fehlt `de`/`de-DE`, per `PUT /api/episode-profiles/{id}` (vollständiger Body) ergänzen. Zusätzlich
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sind Briefing und Sprecherbeschreibungen der mitgelieferten Profile auf Deutsch übersetzt (hilft
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gegen Sprach-Drift, wenn der Quellinhalt englisch ist). **Wichtig:** Änderst du die
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Vorlagen-Dateien selbst, ist danach ein Container-Neustart nötig (`docker compose up -d
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--force-recreate open_notebook`), damit der Bind-Mount die neue Version übernimmt.
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### Podcast-Erzeugung schlägt mit „Invalid json output" fehl
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Das Textmodell hat ungültiges JSON geliefert — passierte bei `qwen3.5:27b` (einem „denkenden"
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Modell), wenn der gesamte Notebook-Inhalt (bei einem ganzen Buch ~70.000 Tokens) in jeden
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Transkript-Abschnitt gepackt wird: Der Denk-Block frisst dann das Antwort-Budget auf und das JSON
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wird abgeschnitten. Behoben durch `/no_think` als erste Zeile beider Podcast-Vorlagen (schaltet
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den Denkmodus ab, ~3× schneller, volles Budget fürs JSON). Falls es dennoch auftritt: kürzeren
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Quellinhalt verwenden (nicht das ganze Buch) oder die Generierung erneut starten.
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### Weitere technische Details
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39
CLAUDE.md
39
CLAUDE.md
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@ -41,13 +41,38 @@ A separate local `llama.cpp` server exists on this machine (managed via `~/llama
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**Chat model context window:** the Ollama credential used for `qwen3.5:27b` (`credential:di8b31l16zikyyb6isyi`) has `num_ctx=98304` set explicitly. Without this, esperanto's `OllamaLanguageModel` silently defaults `num_ctx` to **8192** regardless of the model's real capability or `OLLAMA_CONTEXT_LENGTH` — any chat context (e.g. "full content" mode on a real document) beyond that gets truncated by Ollama, and because `qwen3.5:27b` is a thinking model, the truncated prompt frequently produces an empty final answer (the response is silently swallowed by `clean_thinking_content`) instead of a visible error — looks exactly like "chat gives no answer" from the UI. `98304` is the largest value that still keeps the whole model on GPU 1 (`ollama ps` shows `100% GPU`); `131072` spills ~91% onto CPU and makes a single response take 5-6 minutes instead of ~1-2. Even at 98304, a full-book "Volltext" chat (~70k+ tokens of context) takes ~2-3 minutes — that's inherent to processing that much context on one consumer GPU, not a bug. For large documents, the default short/RAG context mode (only relevant chunks, not the whole document) stays fast; reserve "Volltext" for shorter sources. If `qwen3.5:27b` ever gets swapped for a different Ollama chat model, re-check this credential's `num_ctx` still makes sense for its VRAM footprint.
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**Podcast language:** the three bundled episode profiles (`business_analysis`, `solo_expert`,
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`tech_discussion`) ship with `language: null`, which the underlying `podcast_creator` library
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treats as "no language specified" and defaults to English for both outline and transcript
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generation — regardless of what language the source content or the briefing text is in. All
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three are set to `language: "de"` here. If you create a new episode profile, set `language`
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explicitly (`PUT /api/episode-profiles/{id}`, full body) — it doesn't inherit from the notebook
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or the source.
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**Podcast language + reliability — fixed via patched prompt templates (`prompts/podcast/`,
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bind-mounted).** Two separate problems, one fix location:
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1. *Language.* The episode profile's `language` field (`"de"` → resolved to `"German"`) **is**
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passed into both `podcast_creator` prompt templates as a `{{ language }}` variable
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(`nodes.py`, both `generate_outline_node` and `generate_transcript_node`), but the stock
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templates shipped in the image never reference it — so setting `language` had no effect and
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podcasts came out in English (the stock briefings and speaker backstories are English, which
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is the only language signal the model then sees). English text read aloud by the German-locked
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Chatterbox TTS is what produced the "English with a bad German accent" symptom.
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2. *Reliability.* `qwen3.5:27b` is a thinking model. Podcast content is the **entire notebook**
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(`Notebook.get_context()` → every source's full text + all insights; for a whole book that's
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~70k+ tokens), fed into *each* transcript-segment call. On long segments the `<think>` block
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eats the 5000-token response budget and the JSON gets truncated → `Invalid json output` →
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whole job fails. (Confirmed: `/no_think` cut a segment from 98s to 34s and left valid JSON.)
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Fix — both handled in the two templates under `prompts/podcast/`, bind-mounted read-only over
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the image's copies via `docker-compose.yml`:
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- Prepended `/no_think` as the first line of both templates (Qwen honors it anywhere; harmless
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text for non-Qwen models) — disables thinking, freeing the token budget and ~3x speedup.
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- Added a `{% if language %}CRITICAL LANGUAGE REQUIREMENT … in {{ language }}{% endif %}` block
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near the end of both templates, so the already-plumbed `language` field now actually forces the
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output language.
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The bundled briefings and speaker backstory/personality were **also** translated to German (belt
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and suspenders; reduces English drift from the source content), but the template change is what
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makes `language` authoritative. **Editing these templates requires a container restart** to take
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effect — they're bind-mounted, and the mount is the directory `prompts/podcast/` (not individual
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files, which go stale on inode-replacing edits). If you switch off `qwen3.5:27b`, the `/no_think`
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line becomes inert but harmless.
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If you create your own episode profile, just set `language` — the template handles the rest.
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### Text-to-speech / speech-to-text
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11
README.md
11
README.md
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@ -204,6 +204,11 @@ Kurzreferenz — Details jeweils in [`CLAUDE.md`](CLAUDE.md):
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leere Chat-Antworten bei größerem Kontext, ohne sichtbaren Fehler.
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- **Neue Host-Ports brauchen eine `ufw`-Regel**, sonst kann der Container sie nicht erreichen
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(Timeout, keine Fehlermeldung in Open Notebook selbst).
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- **Podcasts werden ohne explizites `language`-Feld auf Englisch erzeugt**, unabhängig von der
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Sprache der Quelle. Die drei mitgelieferten Episode-Profile sind bereits auf `"de"` gesetzt;
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bei selbst angelegten Profilen selbst daran denken.
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- **Podcast-Sprache** wird über das `language`-Feld des Episode-Profils gesteuert, aber nur
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dank der gepatchten Prompt-Vorlagen unter `prompts/podcast/` (per Bind-Mount in
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`docker-compose.yml` eingehängt) — die Original-Vorlagen im Image ignorieren `language`, was
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englische Podcasts (von der deutsch-fixierten TTS mit Akzent vorgelesen) verursachte. Die
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Vorlagen enthalten zusätzlich `/no_think`, damit `qwen3.5:27b` bei langem Quellinhalt nicht
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durch überlange Reasoning-Blöcke ungültiges JSON liefert. Änderst du die Vorlagen, danach
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`docker compose up -d --force-recreate open_notebook`. Details:
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[`BEDIENUNGSANLEITUNG.md`](BEDIENUNGSANLEITUNG.md#10-troubleshooting) und [`CLAUDE.md`](CLAUDE.md).
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@ -34,3 +34,11 @@ services:
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- "host.docker.internal:host-gateway"
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volumes:
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- ./notebook_data:/app/data
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# Podcast-Prompt-Vorlagen mit expliziter Sprachanweisung ({{ language }})
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# und abgeschaltetem Thinking-Modus (/no_think), damit Podcasts in der
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# eingestellten Sprache erzeugt werden (statt Englisch) und das JSON bei
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# langen Segmenten nicht durch riesige Reasoning-Blöcke abgeschnitten wird.
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# Verzeichnis-Mount (nicht Einzeldateien), damit Edits ohne Inode-Probleme
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# nach einem Container-Neustart greifen. Der Ordner im Image enthält nur
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# genau diese zwei Vorlagen.
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- ./prompts/podcast:/app/prompts/podcast:ro
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91
prompts/podcast/outline.jinja
Normal file
91
prompts/podcast/outline.jinja
Normal file
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@ -0,0 +1,91 @@
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/no_think
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You are an AI assistant specialized in creating podcast outlines. Your task is to create a detailed outline for a podcast episode based on a provided briefing. The outline you create will be used to generate the podcast transcript.
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Here is the briefing for the podcast episode:
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<briefing>
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{{ briefing }}
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</briefing>
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The user has provided content to be used as the context for this podcast episode:
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<context>
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{% if context is string %}
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{{ context }}
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{% else %}
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{% for item in context %}
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<content_piece>
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{{ item }}
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</content_piece>
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{% endfor %}
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{% endif %}
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</context>
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The podcast will feature the following speakers:
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<speakers>
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{% for speaker in speakers %}
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- **{{ speaker.name }}**: {{ speaker.backstory }}
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Personality: {{ speaker.personality }}
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{% endfor %}
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</speakers>
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Please create an outline based on this briefing. Your outline should consist of {{ num_segments }} main segments for the podcast episode, along with a description of each segment. Follow these guidelines:
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1. Read the briefing carefully and identify the main topics and themes.
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2. Create {{ num_segments }} distinct segments that cover the entire scope of the briefing.
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3. For each segment, provide a clear and concise name that reflects its content.
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4. Write a detailed description for each segment, explaining what will be discussed and provide suggestions of topics according to the context given. The writer will use your suggestion to design the dialogs.
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5. Consider the speaker personalities and backstories when planning segments - match content to speaker expertise.
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6. Ensure that the segments flow logically from one to the next.
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7. This is a whole podcast so no need to reintroduce speakers or topics on each segment. Segments are just markers for us to know to change the topics, nothing else.
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8. Include an introduction segment at the beginning and a conclusion or wrap-up segment at the end.
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Format your outline using the following structure:
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```json
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{
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"segments": [
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{
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"name": "[Segment Name]",
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"description": "[Description of the segment content]",
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"size": "short"
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},
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{
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"name": "[Segment Name]",
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"description": "[Description of the segment content]",
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"size": "medium"
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},
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{
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"name": "[Segment Name]",
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"description": "[Description of the segment content]",
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"size": "long"
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},
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...
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]
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}
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```
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Formatting instructions:
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{{ format_instructions}}
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Additional tips:
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- Make sure the segment names are catchy and informative.
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- In the descriptions, include key points or questions that will be addressed in each segment.
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- Consider the target audience mentioned in the briefing when crafting your outline.
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- If the briefing mentions a guest, include segments for introducing the guest and featuring their expertise.
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- The size of the segment should be short, medium or long. Think about the content of the segment and how important it is to the episode.
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{% if language %}
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CRITICAL LANGUAGE REQUIREMENT:
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- Write the ENTIRE outline — every segment name and every segment description — exclusively in {{ language }}.
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- Do NOT use English or any other language, not even for technical terms or proper concepts where a {{ language }} wording exists.
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- These instructions are written in English, but your output MUST be in {{ language }}.
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{% endif %}
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IMPORTANT OUTPUT FORMAT:
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- If you use extended thinking with <think> tags, put ALL your reasoning inside <think></think> tags
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- Put the final JSON output OUTSIDE and AFTER any <think> tags
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- Do NOT wrap the JSON in ```json code blocks - return the raw JSON object only
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- Example correct format:
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<think>Let me analyze the briefing...</think>
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{"segments": [...]}
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Please provide your outline now, following the format and guidelines provided above.
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142
prompts/podcast/transcript.jinja
Normal file
142
prompts/podcast/transcript.jinja
Normal file
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@ -0,0 +1,142 @@
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/no_think
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You are an AI assistant specialized in creating podcast transcripts.
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Your task is to generate a transcript for a specific segment of a podcast episode based on a provided briefing and outline.
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The transcript will be used to generate podcast audio. Follow these instructions carefully:
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First, review the briefing for the podcast episode:
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<briefing>
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{{ briefing }}
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</briefing>
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The user has provided content to be used as the context for this podcast episode:
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<context>
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{% if context is string %}
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{{ context }}
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{% else %}
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{% for item in context %}
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<content_piece>
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{{ item }}
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</content_piece>
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{% endfor %}
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{% endif %}
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</context>
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The podcast features the following speakers:
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<speakers>
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{% for speaker in speakers %}
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- **{{ speaker.name }}**: {{ speaker.backstory }}
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Personality: {{ speaker.personality }}
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{% endfor %}
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</speakers>
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Next, examine the outline produced by our director:
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<outline>
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{{ outline }}
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</outline>
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{% if transcript %}
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Here is the current transcript so far:
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<transcript>
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{{ transcript }}
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</transcript>
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{% endif %}
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{% if is_final %}
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{% if speakers|length == 1 %}
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This is the final segment of the podcast. Make sure to wrap up the presentation and provide a conclusion.
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{% else %}
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This is the final segment of the podcast. Make sure to wrap up the conversation and provide a conclusion.
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{% endif %}
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{% endif %}
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You will focus on creating the dialogue for the following segment ONLY:
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<segment>
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{{ segment }}
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</segment>
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{% if speakers|length == 1 %}
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IMPORTANT: This is a SOLO podcast with only ONE speaker ({{ speaker_names[0] }}). Do NOT invent or add any other speakers.
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All dialogue entries must use "{{ speaker_names[0] }}" as the speaker name.
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Follow these format requirements strictly:
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- Use ONLY the speaker name "{{ speaker_names[0] }}" for all dialogue entries.
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- Do NOT create or invent any additional speakers.
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- Stick to the segment, do not go further than what's requested. Other agents will do the rest of the podcast.
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- The transcript must have at least {{ turns }} dialogue segments from the speaker.
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- The speaker should present the content in an engaging, educational manner.
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{% else %}
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Follow these format requirements strictly:
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- Use the actual speaker names ({{ speaker_names|join(', ') }}) to denote speakers.
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- Choose which speaker should speak based on their personality, backstory, and the content being discussed.
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- Stick to the segment, do not go further than what's requested. Other agents will do the rest of the podcast.
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- The transcript must have at least {{ turns }} turns of messages between the speakers.
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- Each speaker should contribute meaningfully based on their expertise and personality.
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{% endif %}
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```json
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{
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"transcript": [
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{
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"speaker": "[Actual Speaker Name]",
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"dialogue": "[Speaker's dialogue based on their personality and expertise]"
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},
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...
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]
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}
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```
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Formatting instructions:
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{{ format_instructions}}
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{% if speakers|length == 1 %}
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Guidelines for creating the transcript:
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- Ensure the presentation flows naturally and covers all points in the outline.
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- Ensure you return the root "transcript" key in your response.
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- Make the content sound engaging and educational.
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- Include relevant details from the briefing.
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- Break up the content into digestible segments with natural transitions.
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- Use appropriate transitions between topics.
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- Match the speaker's dialogue to their personality and expertise.
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- This is a whole podcast so no need to reintroduce the speaker or topics on each segment. Segments are just markers for us to know to change the topics, nothing else.
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- CRITICAL: There is only ONE speaker. Use ONLY: {{ speaker_names[0] }}. Do NOT invent additional speakers.
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{% else %}
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Guidelines for creating the transcript:
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- Ensure the conversation flows naturally and covers all points in the outline.
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- Ensure you return the root "transcript" key in your response.
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- Make the dialogue sound conversational and engaging.
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- Include relevant details from the briefing.
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- Avoid long monologues; keep exchanges between speakers balanced.
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- Use appropriate transitions between topics.
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- Match each speaker's dialogue to their personality and expertise.
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- Choose speakers strategically based on who would naturally contribute to each topic.
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- This is a whole podcast so no need to reintroduce speakers or topics on each segment. Segments are just markers for us to know to change the topics, nothing else.
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- IMPORTANT: Only use the provided speaker names: {{ speaker_names|join(', ') }}
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{% endif %}
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{% if language %}
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CRITICAL LANGUAGE REQUIREMENT:
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- Write ALL dialogue lines exclusively in {{ language }}.
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- Do NOT use English or any other language, not even for technical terms or proper concepts where a {{ language }} wording exists.
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- These instructions are written in English, but every spoken line you produce MUST be in {{ language }}.
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{% endif %}
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IMPORTANT OUTPUT FORMAT:
|
||||
- If you use extended thinking with <think> tags, put ALL your reasoning inside <think></think> tags
|
||||
- Put the final JSON output OUTSIDE and AFTER any <think> tags
|
||||
- Do NOT wrap the JSON in ```json code blocks - return the raw JSON object only
|
||||
- Example correct format:
|
||||
<think>Let me plan the dialogue...</think>
|
||||
{"transcript": [...]}
|
||||
|
||||
When you're ready, provide the transcript.
|
||||
{% if speakers|length == 1 %}
|
||||
Remember, you are creating a realistic solo podcast presentation based on the given information.
|
||||
Make it informative, engaging, and natural-sounding while adhering to the format requirements.
|
||||
There is only ONE speaker - do not add any other speakers.
|
||||
{% else %}
|
||||
Remember, you are creating a realistic podcast conversation based on the given information.
|
||||
Make it informative, engaging, and natural-sounding while adhering to the format requirements.
|
||||
{% endif %}
|
||||
Loading…
Add table
Add a link
Reference in a new issue