Add rag module: Spring AI 2.0 RAG with pgvector, chunking, reranking and a faithfulness check

Co-Authored-By: Claude Sonnet 5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01B38FGKKam5SCGgwgduVAh3

rag/docs/output/09-faithfulness-check.txt

@@ -0,0 +1,32 @@
+# Generation and the faithfulness check
+
+
+--- 1. the answer is in the chunks ---
+status=answered grounded=true sources=4
+answer: Full-time employees are entitled to 20 working days
+of annual leave per calendar year.
+
+--- 2. the model answers with something the chunks do not say ---
+status=ungrounded grounded=false sources=4
+answer: Employees get 30 days of annual leave.
+the check the judge model was given:
+	Evaluate whether or not the following claim is supported by the provided document.
+	Respond with "yes" if the claim is supported, or "no" if it is not.
+
+
+--- 3. the judge says "Yes." instead of "yes" ---
+status=ungrounded grounded=false sources=4
+answer: Full-time employees are entitled to 20 working days
+of annual leave per calendar year.
+with the reply "YES": grounded=true
+
+--- 4. the judge call itself fails ---
+status=ungrounded grounded=false sources=4
+answer: Full-time employees are entitled to 20 working days
+of annual leave per calendar year.
+rag.faithfulness.judge_failures = 1
+
+--- 5. nothing is retrieved (threshold 0.3, off-topic question) ---
+status=no_context grounded=false sources=0
+answer: I don't have enough information in the provided documents.
+fact-check calls made: 0