Add KNIEPUNKT Assistant with multi-LLM editorial workflow
Six-step weekly workflow (research → sources → storyline → draft → quality → publication) supporting Claude, ChatGPT, Gemini, and Mistral in parallel for creative steps. Web search via Anthropic tool for news research. Episode index built from 34 existing KNIEPUNKT episodes for redundancy checks. Sessions persisted as JSON for mid-workflow resume. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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#!/usr/bin/env python3
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"""KNIEPUNKT Assistant — weekly editorial workflow for Dr. André Knie."""
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from rich.console import Console
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from rich.panel import Panel
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from rich.prompt import Confirm
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from kniepunkt.llm import get_client
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from kniepunkt.providers import get_configured
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from kniepunkt import episodes as ep_module
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from kniepunkt import session as sess_module
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from kniepunkt import research, storyline, drafting, quality, publication
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console = Console()
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def _header():
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console.print(Panel(
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"[bold cyan]KNIEPUNKT Assistant[/bold cyan]\n"
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"[dim]Redaktioneller Workflow · Dr. André Knie[/dim]",
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border_style="cyan",
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))
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def _build_or_load_index(client) -> list[dict]:
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import json
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from pathlib import Path
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cache = Path("episodes_cache.json")
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if cache.exists():
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rebuild = Confirm.ask("\n[dim]Episode-Index vorhanden. Neu aufbauen?[/dim]", default=False)
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if not rebuild:
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with open(cache) as f:
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index = json.load(f)
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console.print(f"[green]Episode-Index: {len(index)} Episoden geladen[/green]")
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return index
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console.print("\n[yellow]Baue Episode-Index auf (einmalig, danach gecacht)...[/yellow]")
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index = ep_module.build_index(client, force=True)
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console.print(f"[green]Episode-Index erstellt: {len(index)} Episoden[/green]")
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return index
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def _run(client, providers: list, session: dict, index: list):
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episodes_context = ep_module.format_for_context(index)
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# ── 1. Research ──────────────────────────────────────────────────────────
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if session["step"] == "research":
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author_input = research.get_author_input()
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news_digest = research.research_news(client, author_input, episodes_context)
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console.print(Panel(news_digest, title="Nachrichten-Kandidaten", border_style="green"))
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session["research"] = {"author_input": author_input, "news_digest": news_digest}
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session["step"] = "sources"
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sess_module.save(session)
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# ── 2. Source assessment ─────────────────────────────────────────────────
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if session["step"] == "sources":
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source_assessment = research.assess_sources(client, session["research"]["news_digest"])
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console.print(Panel(source_assessment, title="Quellenbewertung", border_style="yellow"))
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if not Confirm.ask("\nWeiter zur Storyline-Entwicklung?", default=True):
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console.print("[dim]Session gespeichert. Neustart setzt hier fort.[/dim]")
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return
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session["sources"] = source_assessment
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session["step"] = "storyline"
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sess_module.save(session)
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# ── 3. Storyline ─────────────────────────────────────────────────────────
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if session["step"] == "storyline":
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results = storyline.generate_storylines(
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providers,
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session["research"]["news_digest"],
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session["sources"],
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session["research"]["author_input"],
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episodes_context,
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)
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provider_name, choice, selected_text, adjustments = storyline.select_storyline(results)
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session["storyline"] = {
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"results": results,
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"selected_provider": provider_name,
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"choice": choice,
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"selected_text": selected_text,
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"adjustments": adjustments,
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}
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session["step"] = "draft"
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sess_module.save(session)
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# ── 4. Draft ─────────────────────────────────────────────────────────────
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if session["step"] == "draft":
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sl = session["storyline"]
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draft_results = drafting.generate_drafts(
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providers,
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sl["selected_text"],
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sl["choice"],
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sl["adjustments"],
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session["research"]["news_digest"],
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session["sources"],
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session["research"]["author_input"],
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)
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provider_name, draft = drafting.select_draft(draft_results)
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console.print("\n[dim]Überarbeitungshinweise? (Enter = Entwurf übernehmen)[/dim]")
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feedback = input().strip()
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if feedback:
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draft = drafting.enrich_draft(client, draft, feedback)
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console.print(Panel(draft, title="Überarbeiteter Entwurf", border_style="green"))
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session["draft_results"] = draft_results
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session["draft"] = draft
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session["step"] = "quality"
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sess_module.save(session)
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# ── 5. Quality review ────────────────────────────────────────────────────
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if session["step"] == "quality":
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quality_report = quality.review(
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client,
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session["draft"],
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session["sources"],
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episodes_context,
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)
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console.print(Panel(quality_report, title="Qualitätsprüfung", border_style="yellow"))
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console.print("\n[dim]Weitere Überarbeitungen? (Enter = weiter zur Publikation)[/dim]")
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feedback = input().strip()
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if feedback:
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draft = drafting.enrich_draft(client, session["draft"], feedback)
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session["draft"] = draft
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console.print(Panel(draft, title="Finalisierter Entwurf", border_style="green"))
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session["quality"] = quality_report
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session["step"] = "publication"
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sess_module.save(session)
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# ── 6. Publication prep ──────────────────────────────────────────────────
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if session["step"] == "publication":
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teasers = publication.generate_teasers(client, session["draft"])
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console.print(Panel(teasers, title="Teaser-Varianten", border_style="cyan"))
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visual_ideas = publication.generate_visual_ideas(client, session["draft"])
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console.print(Panel(visual_ideas, title="Cover-Ideen", border_style="cyan"))
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out_path = publication.save_package(
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session["date"],
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session["draft"],
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teasers,
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session["sources"],
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visual_ideas,
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)
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console.print(Panel(
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f"[green]Publikationspaket gespeichert:[/green] {out_path}\n\n"
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"Enthält: Artikel · Teaser-Varianten · Cover-Ideen · Quellenbewertung",
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title="✓ Fertig",
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border_style="green",
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))
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session["publication"] = {"teasers": teasers, "visual_ideas": visual_ideas}
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session["step"] = "done"
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sess_module.save(session)
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def main():
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_header()
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try:
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client = get_client()
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except RuntimeError as e:
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console.print(f"[red]{e}[/red]\nBitte ANTHROPIC_API_KEY in der .env-Datei eintragen.")
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return
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providers = get_configured()
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if not providers:
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console.print("[red]Keine LLM-API-Keys konfiguriert. Bitte .env-Datei prüfen.[/red]")
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return
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provider_names = ", ".join(p.name for p in providers)
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console.print(f"[green]Aktive Modelle: {provider_names}[/green]")
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index = _build_or_load_index(client)
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latest = sess_module.load_latest()
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session = None
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if latest and latest.get("step") not in ("done",):
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if Confirm.ask(
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f"\nGefundene Session vom [bold]{latest['date']}[/bold] "
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f"(Schritt: [bold]{latest['step']}[/bold]). Fortfahren?",
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default=True,
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):
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session = latest
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if session is None:
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session = sess_module.new_session()
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console.print(f"\n[green]Neue Session: {session['date']}[/green]")
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_run(client, providers, session, index)
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if __name__ == "__main__":
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main()
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