feat: scaffold Brain of Reese — FastAPI RAG chat over Postgres 17 + pgvector

Foundation (phase 01, verified):
- FastAPI app: /api/health, /api/suggestions, /api/chat (placeholder),
  static frontend served locally (no CDN)
- Postgres 17 + pgvector via db/Containerfile + compose.yaml
  (podman compose up -d db), Alembic initial migration (documents,
  chunks with vector(768), query_log)
- LLM client targeting https://aipi.reeseapps.com/v1 (turbo/embed);
  scripts/llm_probe.py verified models + 768-dim embeddings live
- Conditional debugpy: imported only when DEBUGPY=1 (attach on demand,
  :5678); logging config for clean single-line logs
- Frontend shell: mobile-first chat + Sources pages, tokens, a11y baselines
- Tests: 24 unit+integration (99% coverage on app/), ruff + pyright clean,
  Playwright smoke E2E (3 tests) against a deterministic mock LLM
- Planning: .agent/PLAN.md (architecture + LOCKED decisions), AGENTS.md,
  6 user stories, 7 phase files (one story / one phase / one Playwright
  suite each)

app/schemas.py

@@ -0,0 +1,45 @@
+"""Pydantic request/response schemas (API contract)."""
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class HealthResponse(BaseModel):
+    status: str
+    db: str
+    version: str
+    environment: str
+
+
+class SuggestionList(BaseModel):
+    suggestions: list[str]
+
+
+class ChatRequest(BaseModel):
+    message: str = Field(min_length=1, max_length=4000)
+
+
+class SourceRef(BaseModel):
+    source: str
+    path: str
+    title: str
+
+
+class ChatDoneEvent(BaseModel):
+    """Final SSE event of a chat turn: metadata for the finished answer."""
+
+    type: str = "done"
+    deflected: bool
+    sources: list[SourceRef]
+    suggestions: list[str] = []
+
+
+class DocSummary(BaseModel):
+    """One indexed document as shown on the Sources page / API."""
+
+    id: str
+    source: str
+    path: str
+    title: str
+    chunks: int
+    indexed_at: str