The openclaw user owns and operates the OpenClaw agent service on the agent server to enforce least privilege security and service isolation.

Streaming event generated by OpenClaw Gateway, streamed via openclaw_http_client.py.

Generate a strong 32-byte hex secret key for system security. DataLens Platform deployment requires using openssl rand -hex 32 to generate a session signing key (SECRET_KEY).

DataLens depends on the Ops Engineer to review and approve deployment requests. Ops Engineer approves deployments listed in DEPLOYMENT_QUEUE.md and authorizes execution. Ops Engineer controls deployment execution of DataLens and is responsible for safe deployment procedures.

The ops user owns and runs the Skill API on the agent server, handling ringfenced SQL execution isolated from the OpenClaw agent service.

The decision is to implement Option A which involves reverting to the last known good commit and deploying it to resolve current issues with DataLens OpenClaw Integration.

The Phase 2 MVP includes Partial Extraction of 44 files (Excel and PDF) into DuckDB. Partial Extraction stores extracted data in DuckDB file for Project 4.

Payment & Commitment Cluster requires the Consolidation Mechanism to join payments and commitments data tables appropriately.

PDF extractor component implements the PDF Extraction requirement, but large file support is partially untested.

The Cleveland Clinic E2E use case utilizes the PDF Infrastructure to handle extraction of PDF files. DataLens Development requires PDF Infrastructure capability to support lazy loading and on-demand table extraction from large PDFs. Lazy Loading Implementation is part of the PDF Infrastructure feature set to enhance user experience during large PDF uploads.

DataLens needs to integrate PermissionFilter mechanisms to enforce row-level security and user permission filtering in SQL. DataLens requires adding PermissionFilter for query filtering based on user access. DataLens requires PermissionFilter to enforce per-user query filtering like Vanna

The new pg_data_service.py file provides PostgreSQL data management functionality replacing DuckDBService. The extract.py worker is modified to write extracted data using pg_data_service.py instead of DuckDBService. question_router.py is updated to use pg_data_service.py for reading extracted data in place of DuckDBService.

Phase 1 Implementation includes reducing the maximum number of tables passed to SQL generator via Schema Limiting to avoid Arctic context overflow. The Phase 2 Strategy Research & Decision Point depends on the status of Phase 1, which is currently frozen with partial Excel file processing completed.

Phase 2 GPU-First Document Extraction involves GPU-first document extraction as its core capability.

PHASE2_SCOPE_DECISION.md contains research outputs related to Phase 2. Phase 2 research outputs include LOAD_STRATEGY.md as a component of research. Phase 2 research outputs include IMPLEMENTATION_PLAN.md as a component of research. Phase 2 research outputs include the Memory research document as part of the documentation. Phase 2 research outputs include the Memory decision point document as part of the documentation. Phase 2 research outputs include PHASE2_IMPLEMENTATION_PLAN.md as part of the documentation. Phase 2 research outputs include PHASE2_LOAD_STRATEGY.md as part of the documentation. Phase 2 research outputs contain PHASE2_SCOPE_DECISION.md. Phase 2 research outputs include SOUL.md in the research documents.