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55 lines
2.4 KiB
Markdown
55 lines
2.4 KiB
Markdown
# Supabase / pgvector — Project Memory Setup
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## Enable pgvector
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In the Supabase dashboard: **Database → Extensions →** enable `vector` (pgvector).
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Alternatively, the migration `supabase/migrations/202605010001_v3_project_memory.sql` runs `create extension if not exists vector;` (requires sufficient DB privileges).
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## Run migration
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1. Install [Supabase CLI](https://supabase.com/docs/guides/cli).
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2. Link the project: `supabase link --project-ref <ref>`.
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3. Push SQL: `supabase db push` **or** paste the migration file into the SQL editor and execute.
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## Environment variables
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| Variable | Purpose |
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|----------|---------|
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| `SUPABASE_URL` | Project API URL (server-side only). |
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| `SUPABASE_SERVICE_ROLE_KEY` | **Server only** — bypasses RLS; never expose to browsers or mobile clients. |
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| `SUPABASE_ANON_KEY` | Optional for public features — **not** for project memory tables. |
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Local indexing (no keys required):
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```bash
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python scripts/index_project_memory.py --root . --out .dealix/project_index.json
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python scripts/index_project_memory.py --root . --query "personal operator"
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```
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## Embedding model choices
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- **gte-small** (384 dims) via Edge Function or local worker — low cost, aligns with migration vector(384).
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- **OpenAI `text-embedding-3-small`** — set dimension to match your DB column if you change size.
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- **BGE-small** — similar footprint; validate dimension before altering the column type.
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## Security notes
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- **RLS** is enabled on `project_documents`, `project_chunks`, and `strategic_memory` with **no default policies** — intended for **service role from backend only**.
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- **Never store API keys, tokens, or private keys** in `content` or `metadata` destined for embeddings.
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- Strip or redact secrets **before** chunking; use `should_block_embedding()` in `project_intelligence.py` as a guardrail.
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## RLS policy examples (commented in migration)
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Uncomment and adapt only after security review. Typical pattern: allow `service_role` full access; deny `anon`/`authenticated` direct reads on strategic embeddings.
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## Launch checklist
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- [ ] Extension `vector` active
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- [ ] Migration applied without errors
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- [ ] Indexes created (`project_chunks_embedding_hnsw`, etc.)
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- [ ] Backend uses service role only in trusted runtime
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- [ ] Chunk pipeline redacts secrets
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- [ ] Staging load test on `match_project_chunks`
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- [ ] Retention / deletion policy documented
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