feat(backend): add hybrid search for store listings, docs and blocks (#11721)

This PR adds hybrid search functionality combining semantic embeddings
with traditional text search for improved store listing discovery.

### Changes 🏗️

- Add `embeddings.py` - OpenAI-based embedding generation and similarity
search
- Add `hybrid_search.py` - Combines vector similarity with text matching
for better search results
- Add `backfill_embeddings.py` - Script to generate embeddings for
existing store listings
- Update `db.py` - Integrate hybrid search into store database queries
- Update `schema.prisma` - Add embedding storage fields and indexes
- Add migrations for embedding columns and HNSW index for vector search

### Architecture Decisions 🏛️

**Fail-Fast Approach (No Silent Fallbacks)**

We explicitly chose NOT to implement graceful degradation when hybrid
search fails. Here's why:

✅ **Benefits:**
- Errors surface immediately → faster fixes
- Tests verify hybrid search actually works (not just fallback)
- Consistent search quality for all users
- Forces proper infrastructure setup (API keys, database)

❌ **Why Not Fallback:**
- Silent degradation hides production issues
- Users get inconsistent results without knowing why
- Tests can pass even when hybrid search is broken
- Reduces operational visibility

**How We Prevent Failures:**
1. Embedding generation in approval flow (db.py:1545)
2. Error logging with `logger.error` (not warning)
3. Clear error messages (ValueError explains what's wrong)
4. Comprehensive test coverage (9/9 tests passing)

If embeddings fail, it indicates a real infrastructure issue (missing
API key, OpenAI down, database issues) that needs immediate attention,
not silent degradation.

### Test Coverage ✅

**All tests passing (1625 total):**
- 9/9 hybrid_search tests (including fail-fast validation)
- 3/3 db search integration tests
- Full schema compatibility (public/platform schemas)
- Error handling verification

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Test hybrid search returns relevant results
  - [x] Test embedding generation for new listings
  - [x] Test backfill script on existing data
  - [x] Verify search performance with embeddings
  - [x] Test fail-fast behavior when embeddings unavailable

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] Configuration: Requires `openai_internal_api_key` in secrets

---------

Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>

.github/workflows/platform-backend-ci.yml

@@ -176,7 +176,7 @@ jobs:
           }
 
       - name: Run Database Migrations
-        run: poetry run prisma migrate dev --name updates
+        run: poetry run prisma migrate deploy
         env:
           DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
           DIRECT_URL: ${{ steps.supabase.outputs.DB_URL }}

.github/workflows/platform-frontend-ci.yml

@@ -11,6 +11,7 @@ on:
       - ".github/workflows/platform-frontend-ci.yml"
       - "autogpt_platform/frontend/**"
   merge_group:
+  workflow_dispatch:
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event_name == 'merge_group' && format('merge-queue-{0}', github.ref) || format('{0}-{1}', github.ref, github.event.pull_request.number || github.sha) }}
@@ -151,6 +152,14 @@ jobs:
         run: |
           cp ../.env.default ../.env
 
+      - name: Copy backend .env and set OpenAI API key
+        run: |
+          cp ../backend/.env.default ../backend/.env
+          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
+        env:
+          # Used by E2E test data script to generate embeddings for approved store agents
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3