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)

alembic/env.py

@@ -0,0 +1,50 @@
+"""Alembic migration environment (sync engine, URL from app settings)."""
+from __future__ import annotations
+
+import os
+from logging.config import fileConfig
+
+from sqlalchemy import engine_from_config, pool
+
+import app.models  # noqa: F401  (registers all models on Base.metadata)
+from alembic import context
+from app.config import get_settings
+from app.db import Base
+
+config = context.config
+
+if config.config_file_name is not None and os.path.exists(config.config_file_name):
+    fileConfig(config.config_file_name)
+
+config.set_main_option("sqlalchemy.url", get_settings().database_url)
+target_metadata = Base.metadata
+
+
+def run_migrations_offline() -> None:
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        dialect_opts={"paramstyle": "named"},
+    )
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def run_migrations_online() -> None:
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section, {}),
+        prefix="sqlalchemy.",
+        poolclass=pool.NullPool,
+    )
+    with connectable.connect() as connection:
+        context.configure(connection=connection, target_metadata=target_metadata)
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()

alembic/script.py.mako

@@ -0,0 +1,25 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from __future__ import annotations
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+revision = ${repr(up_revision)}
+down_revision = ${repr(down_revision)}
+branch_labels = ${repr(branch_labels)}
+depends_on = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    ${downgrades if downgrades else "pass"}

alembic/versions/0001_initial_schema.py

@@ -0,0 +1,86 @@
+"""initial schema: documents, chunks (pgvector), query_log
+
+Revision ID: 0001
+Revises:
+Create Date: 2026-08-21
+
+"""
+from __future__ import annotations
+
+import sqlalchemy as sa
+from pgvector.sqlalchemy import Vector
+from sqlalchemy.dialects import postgresql
+
+from alembic import op
+
+EMBEDDING_DIM = 768  # keep in sync with app/models.py (PLAN anchor A6)
+
+revision = "0001"
+down_revision = None
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.execute("CREATE EXTENSION IF NOT EXISTS vector")
+
+    op.create_table(
+        "documents",
+        sa.Column("id", postgresql.UUID(as_uuid=True), primary_key=True),
+        sa.Column("source", sa.String(120), nullable=False),
+        sa.Column("path", sa.String(1000), nullable=False),
+        sa.Column("full_path", sa.String(2000), nullable=False),
+        sa.Column("title", sa.String(500), nullable=False),
+        sa.Column("content", sa.Text(), nullable=False),
+        sa.Column("content_hash", sa.String(64), nullable=False),
+        sa.Column(
+            "indexed_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.func.now(),
+            nullable=False,
+        ),
+        sa.UniqueConstraint("source", "path", name="uq_documents_source_path"),
+    )
+    op.create_index("ix_documents_source", "documents", ["source"])
+    op.create_index("ix_documents_path", "documents", ["path"])
+    op.create_index("ix_documents_content_hash", "documents", ["content_hash"])
+
+    op.create_table(
+        "chunks",
+        sa.Column("id", postgresql.UUID(as_uuid=True), primary_key=True),
+        sa.Column(
+            "document_id",
+            postgresql.UUID(as_uuid=True),
+            sa.ForeignKey("documents.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column("position", sa.Integer(), nullable=False),
+        sa.Column("content", sa.Text(), nullable=False),
+        sa.Column("embedding", Vector(EMBEDDING_DIM), nullable=True),
+    )
+    op.create_index("ix_chunks_document_id", "chunks", ["document_id"])
+
+    op.create_table(
+        "query_log",
+        sa.Column("id", postgresql.UUID(as_uuid=True), primary_key=True),
+        sa.Column("question", sa.Text(), nullable=False),
+        sa.Column("top_score", sa.Float(), nullable=False, server_default="0"),
+        sa.Column("chunk_hits", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column("deflected", sa.Boolean(), nullable=False, server_default=sa.false()),
+        sa.Column("sources", sa.Text(), nullable=False, server_default=""),
+        sa.Column("latency_ms", sa.Integer(), nullable=False, server_default="0"),
+        sa.Column(
+            "created_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.func.now(),
+            nullable=False,
+        ),
+    )
+    op.create_index("ix_query_log_created_at", "query_log", ["created_at"])
+
+
+def downgrade() -> None:
+    op.drop_table("query_log")
+    op.drop_table("chunks")
+    op.drop_table("documents")
+    op.execute("DROP EXTENSION IF EXISTS vector")