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docs/README_rag_samples.md

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+# RAG Sample PDFs for agent_template_backend
+
+These PDF files are synthetic, searchable sample documents created to validate the RAG embedding and retrieval flow of `agent_template_backend`.
+
+## Files
+
+- `01_billing_agent_invoice_policy.pdf` - sample knowledge for `billing_agent`
+- `02_orders_agent_lifecycle_policy.pdf` - sample knowledge for `orders_agent`
+- `03_product_agent_catalog_policy.pdf` - sample knowledge for `product_agent`
+- `04_support_agent_sla_policy.pdf` - sample knowledge for `support_agent`
+- `05_business_context_rag_flow.pdf` - sample knowledge about BusinessContext, identity.yaml and MCP parameter mapping
+
+## How to use
+
+Copy the PDF files to the backend documentation directory:
+
+```bash
+mkdir -p agent_template_backend/docs/rag_samples
+cp *.pdf agent_template_backend/docs/rag_samples/
+```
+
+For a local smoke test, use:
+
+```env
+VECTOR_STORE_PROVIDER=sqlite
+EMBEDDING_PROVIDER=mock
+SQLITE_DB_PATH=./data/agent_framework.db
+RAG_TOP_K=4
+```
+
+Then run:
+
+```bash
+python scripts/generate_rag_embeddings.py \
+  --docs-dir ./agent_template_backend/docs/rag_samples \
+  --namespace default
+```
+
+For production-like semantic embeddings with OCI Generative AI, use:
+
+```env
+VECTOR_STORE_PROVIDER=autonomous
+EMBEDDING_PROVIDER=oci
+OCI_COMPARTMENT_ID=ocid1.compartment.oc1..xxxx
+OCI_REGION=us-chicago-1
+OCI_EMBEDDING_MODEL=cohere.embed-multilingual-v3.0
+```
+
+## Suggested retrieval test questions
+
+- What is a prorated charge?
+- When can the OrdersAgent open an exchange request?
+- Which SKU represents the AI Agents book?
+- What is the target response for a critical support ticket?
+- How does BusinessContext map customer_key to MCP tool parameters?