feat: RAG answers with sutta citations (M1)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

scripts/ask.py

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+import sys
+from pathlib import Path
+from buddhagpt.rag import answer
+
+r = answer(sys.argv[1], "mlx-community/Qwen2.5-7B-Instruct-4bit", Path("data/lancedb"))
+print(r["answer"])
+print("\nSources:", ", ".join(c["uid"] for c in r["citations"]))

src/buddhagpt/rag.py

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+from pathlib import Path
+from buddhagpt.index import search
+
+SYSTEM = (
+    "You are a thoughtful guide grounded in the Pali Canon. Answer with warmth and "
+    "precision. Base doctrinal claims on the provided passages and cite them by uid "
+    "(e.g. [mn21]). If the passages do not cover the question, say so plainly."
+)
+
+def build_prompt(question: str, passages: list[dict]) -> list[dict]:
+    ctx = "\n\n".join(f"[{p['uid']}] {p['title']}:\n{p['chunk']}" for p in passages)
+    return [
+        {"role": "system", "content": SYSTEM},
+        {"role": "user", "content": f"Passages:\n{ctx}\n\nQuestion: {question}"},
+    ]
+
+def answer(question: str, model_path: str, db_path: Path) -> dict:
+    from mlx_lm import load, generate
+    passages = search(db_path, question, k=4)
+    model, tokenizer = load(model_path)
+    prompt = tokenizer.apply_chat_template(
+        build_prompt(question, passages), tokenize=False, add_generation_prompt=True
+    )
+    text = generate(model, tokenizer, prompt=prompt, max_tokens=500)
+    return {"answer": text, "citations": [{"uid": p["uid"], "title": p["title"]} for p in passages]}

tests/test_rag.py

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+from buddhagpt.rag import build_prompt
+
+def test_build_prompt_includes_passages_and_citation_instruction():
+    msgs = build_prompt("What causes suffering?", [
+        {"uid": "sn56.11", "title": "Setting the Wheel in Motion", "chunk": "Craving leads to suffering."}
+    ])
+    system = msgs[0]["content"]
+    assert "sn56.11" in msgs[1]["content"]
+    assert "cite" in system.lower()
+    assert msgs[1]["content"].endswith("What causes suffering?")