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Motivation
Description
RetrievalServicefacade atbackend/app/services/retrieval_service.pythat exposesget_persistent_retrieverandget_hybrid_retrieverabstractions.get_hybrid_retriever(...)inbackend/app/agents/legal_research/retrievers.pyto combine aChromadense retriever andBM25Retrieverwith anEnsembleRetrieverfusion.LegalResearchAgent(backend/app/agents/legal_research/agent.py) to acquire its retriever viaRetrievalServiceinstead of importing a module-level function.backend/app/agents/document_generator/prompt_templates.py) to accept and injectretrieved_legal_context(and skip it when rendering facts) into theGrounded Legal Contextblock of the prompt.backend/app/api/v1/endpoints/documents.py) by building a compact retrieval query, fetching grounded legal snippets and source metadata via the new service, and attachingretrieved_legal_contextandretrieved_legal_sourcesintomerged_factsbefore callingassembly_engine.assemble_document.docs/rag_upgrade_proposal.mdanddocs/upgrade_execution_plan.mddescribing the RAG/validation upgrade plan and phase 0 work done.Testing
pytest -qand confirmed no regressions in unrelated modules.RetrievalServicefacade which passed locally.POST /documents/generatethat verifies the retrieval step runs andretrieved_legal_contextis injected into the assembled prompt, and this smoke test passed.Codex Task