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/app/api/conversations/schemas.py

@@ -0,0 +1,55 @@
+"""Request and response shapes for conversations and their turns."""
+
+import uuid
+from datetime import datetime
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from app.models import ConversationMode, MessageRole
+
+
+class ConversationCreate(BaseModel):
+    mode: ConversationMode
+
+
+class ConversationSummary(BaseModel):
+    model_config = ConfigDict(from_attributes=True)
+
+    id: uuid.UUID
+    title: str | None = None
+
+
+class MessageSource(BaseModel):
+    document_id: uuid.UUID
+    title: str
+    heading_path: str
+    excerpt: str = ""
+    # True when the passage was passed to the model; False for passages that
+    # were retrieved but dropped as too weak (a no-answer turn). Old messages
+    # predate the flag, so it defaults to True (they were all cited).
+    used: bool = True
+    # The cited document has an unanswered request to check it. Snapshotted
+    # with the citation, so a reload shows what was true when it was answered.
+    review_pending: bool = False
+
+
+class MessageOut(BaseModel):
+    model_config = ConfigDict(from_attributes=True)
+
+    id: uuid.UUID
+    role: MessageRole
+    content: str
+    created_at: datetime
+    sources: list[MessageSource] = []
+    # Set when no model answered this turn and `sources` is a plain full-text
+    # result list instead: the `llm_*` code that caused it, which the frontend
+    # phrases. Null on every normal turn.
+    fallback: str | None = None
+
+
+class ConversationDetail(ConversationSummary):
+    messages: list[MessageOut] = []
+
+
+class SendMessage(BaseModel):
+    content: str = Field(min_length=1, max_length=8000)