Pablan, as it stands

Self-hosted knowledge management for SMEs: a split-screen Markdown editor
whose sections an LLM refines while you write, and RAG question answering
over the documents that result. FastAPI + Postgres/pgvector on the back,
SvelteKit on the front, everything OpenAI-compatible and self-hostable.

Squashed into a single commit; the development history stays local.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CA43ZJda8Rbp2hKXNy8f6b

backend/tests/fixtures/loader.py

@@ -0,0 +1,58 @@
+"""Loader for the shared fixture corpus — seeds and tests draw from it.
+
+The corpus is product content (German knowledge documents of the fictional
+SME "Nordwind Maschinenbau GmbH"). PyYAML is available through
+uvicorn[standard]; it becomes a declared dependency with the template
+import in M6.
+"""
+
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+FIXTURES_DIR = Path(__file__).resolve().parent
+CORPUS_DIR = FIXTURES_DIR / "corpus"
+
+
+@dataclass
+class CorpusDoc:
+    slug: str
+    title: str
+    department: str
+    visibility: str
+    content_md: str
+    grants: list[str] = field(default_factory=list)
+
+
+def load_corpus() -> list[CorpusDoc]:
+    docs: list[CorpusDoc] = []
+    for path in sorted(CORPUS_DIR.glob("*.md")):
+        text = path.read_text()
+        if not text.startswith("---\n"):
+            raise ValueError(f"corpus file without frontmatter: {path.name}")
+        _, frontmatter, body = text.split("---\n", 2)
+        meta = yaml.safe_load(frontmatter)
+        docs.append(
+            CorpusDoc(
+                slug=meta["id"],
+                title=meta["title"],
+                department=meta["department"],
+                visibility=meta["visibility"],
+                grants=list(meta.get("grants", [])),
+                content_md=body.strip() + "\n",
+            )
+        )
+    return docs
+
+
+def load_golden_queries() -> list[dict[str, Any]]:
+    return yaml.safe_load((FIXTURES_DIR / "golden_queries.yaml").read_text())
+
+
+def load_conversation_snippets() -> list[dict[str, Any]]:
+    """Short chats whose LAST message is a topic-losing follow-up, with the
+    corpus slug the conversation is really about — for comparing topic-summary
+    retrieval against retrieval over the raw last message."""
+    return yaml.safe_load((FIXTURES_DIR / "conversation_snippets.yaml").read_text())