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## Summary
- Remove explicit schema qualification (`{schema}.vector` and
`OPERATOR({schema}.<=>)`) from pgvector queries in `embeddings.py` and
`hybrid_search.py`
- Use unqualified `::vector` type cast and `<=>` operator which work
because pgvector is in the search_path on all environments
## Problem
The previous approach tried to explicitly qualify the vector type with
schema names, but this failed because:
- **CI environment**: pgvector is in `public` schema → `platform.vector`
doesn't exist
- **Dev (Supabase)**: pgvector is in `platform` schema → `public.vector`
doesn't exist
## Solution
Use unqualified `::vector` and `<=>` operator. PostgreSQL resolves these
via `search_path`, which includes the schema where pgvector is installed
on all environments.
Tested on both local and dev environments with a test script that
verified:
- ✅ Unqualified `::vector` type cast
- ✅ Unqualified `<=>` operator in ORDER BY
- ✅ Unqualified `<=>` in SELECT (similarity calculation)
- ✅ Combined query patterns matching actual usage
## Test plan
- [ ] CI tests pass
- [ ] Marketplace approval works on dev after deployment
Fixes: AUTOGPT-SERVER-763, AUTOGPT-SERVER-764, AUTOGPT-SERVER-76B