Phase 02 Plan 02: Google and Jina Embeddings Summary

Google text-multilingual-embedding-002 (768d) and Jina embeddings-v3 (1024d) generated for all 6078 line items with batch processing and rate limit handling

Performance

• Duration: 13 min
• Started: 2026-02-20T11:32:21Z
• Completed: 2026-02-20T11:46:07Z
• Tasks: 3
• Files created: 5

Accomplishments

• Created embedding text preparation utility combining supplier and description consistently
• Implemented Google Vertex AI embedding module using text-multilingual-embedding-002 model
• Implemented Jina API embedding module using jina-embeddings-v3 with rate limit handling
• All 6078 line items now have both embedding_google (768 dimensions) and embedding_jina (1024 dimensions) populated

Task Commits

Each task was committed atomically:

1. Task 1: Create embedding infrastructure (text prep + batch processor) - e5700632 (feat)
2. Task 2: Create Google Vertex AI embedding module and generate embeddings - 07b5650c (feat)
3. Task 3: Create Jina API embedding module and generate embeddings - 5f05b26d (feat)

Files Created/Modified

• src/embeddings/__init__.py - Package exports for embedding utilities
• src/embeddings/text_prep.py - Consistent text preparation (supplier | description)
• src/embeddings/batch_processor.py - Generic batch embedding with tqdm progress
• src/embeddings/google_embed.py - Google Vertex AI embedding functions
• src/embeddings/jina_embed.py - Jina API embedding functions with rate limit handling

Decisions Made

• Used getorcha-dev GCP project instead of orcha-labs (orcha-labs had billing disabled)
• Combined supplier and description with pipe separator for embedding text
• Used conservative batch sizes (100 for Google, 50 for Jina) to avoid rate limits
• Added dotenv loading in embedding modules for credential configuration

Deviations from Plan

Auto-fixed Issues

1. [Rule 3 - Blocking] Fixed GCP project configuration for Vertex AI

• Found during: Task 2 (Google embedding generation)
• Issue: Plan specified orcha-labs project but it had billing disabled; getorcha-prod had Vertex AI not enabled
• Fix: Enabled Vertex AI API on getorcha-dev project, updated .env to use getorcha-dev
• Files modified: src/embeddings/google_embed.py (added dotenv loading and explicit client config), .env
• Verification: Google embeddings generated successfully for all 6078 items
• Committed in: 07b5650c

Total deviations: 1 auto-fixed (1 blocking) Impact on plan: GCP project switch was necessary for API access. No scope creep.

Issues Encountered

None beyond the auto-fixed GCP project issue above.

User Setup Required

None - API credentials already configured in .env file. Vertex AI enabled on getorcha-dev project during execution.

Next Phase Readiness

• Google embeddings complete: 6078 items with 768-dimension vectors
• Jina embeddings complete: 6078 items with 1024-dimension vectors
• Ready for Plan 02-03: Local MiniLM embedding generation
• All embedding infrastructure in place for comparison evaluation

Phase: 02-embedding-generation Completed: 2026-02-20

Self-Check: PASSED

• src/embeddings/init.py exists
• src/embeddings/text_prep.py exists
• src/embeddings/batch_processor.py exists
• src/embeddings/google_embed.py exists
• src/embeddings/jina_embed.py exists
• Commit e5700632 exists (Task 1)
• Commit 07b5650c exists (Task 2)
• Commit 5f05b26d exists (Task 3)
• Database has 6078 items with embedding_google populated
• Database has 6078 items with embedding_jina populated