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)
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# --- Python ---
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__pycache__/
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*.py[cod]
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*.egg-info/
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.venv/
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.pytest_cache/
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.ruff_cache/
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.pyright/
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.mypy_cache/
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.coverage
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coverage.xml
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htmlcov/
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# --- Environment / secrets ---
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.env
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.env.*
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!.env.example
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# --- Planning / agent pipeline state (committed on demand with `git add -f .agent/...`) ---
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.agent/
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# --- Frontend build artifacts (sources live in frontend/, builds are local-only) ---
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node_modules/
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frontend/dist/
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# --- Logs & misc ---
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*.log
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.DS_Store
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Thumbs.db
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