feat(rag): add optional NPU reranker fallback

This commit is contained in:
William Valentin
2026-06-04 14:50:41 -07:00
parent 06f235d26b
commit 71f3c05587
5 changed files with 303 additions and 9 deletions
+142 -1
View File
@@ -21,14 +21,32 @@ import os
import subprocess
import sys
import threading
import time
from pathlib import Path
from urllib.parse import parse_qs, urlparse
from urllib import request, error
PORT = int(os.environ.get("PORT", 18810))
REINDEX_TIMEOUT = int(os.environ.get("REINDEX_TIMEOUT", "1800"))
RAG_COLLECTION = os.environ.get("RAG_COLLECTION", "obsidian").strip() or "obsidian"
RAG_EMBED_MODEL = os.environ.get("RAG_EMBED_MODEL", "nomic-embed-text").strip() or "nomic-embed-text"
OLLAMA_BASE_URL = (os.environ.get("OLLAMA_BASE_URL") or "http://127.0.0.1:18807").rstrip("/")
RAG_RERANK_ENABLED = (os.environ.get("RAG_RERANK_ENABLED") or "false").strip().lower() in {
"1",
"true",
"yes",
"on",
}
RAG_RERANK_URL = (os.environ.get("RAG_RERANK_URL") or "http://127.0.0.1:18818/rerank").strip()
RAG_RERANK_INITIAL_K = max(1, int(os.environ.get("RAG_RERANK_INITIAL_K") or "20"))
RAG_RERANK_TOP_K = max(1, int(os.environ.get("RAG_RERANK_TOP_K") or "5"))
RAG_RERANK_TIMEOUT_MS = max(1, int(os.environ.get("RAG_RERANK_TIMEOUT_MS") or "3000"))
RAG_RERANK_REQUIRE_NPU_PROOF = (os.environ.get("RAG_RERANK_REQUIRE_NPU_PROOF") or "true").strip().lower() in {
"1",
"true",
"yes",
"on",
}
REINDEX_SCRIPT = str(
Path.home()
@@ -102,12 +120,125 @@ def get_status() -> dict:
return {"error": str(e)}
def _result_text(result: dict) -> str:
"""Return the text field sent to the reranker without changing response shape."""
return str(result.get("text") or result.get("content") or "")
def _apply_rerank(query: str, results: list[dict], final_k: int) -> tuple[list[dict], dict]:
"""Optionally rerank semantic results, falling back to vector order on any error."""
metadata = {
"enabled": RAG_RERANK_ENABLED,
"attempted": False,
"ok": False,
"url": RAG_RERANK_URL,
"initial_k": len(results),
"top_k": final_k,
}
if not RAG_RERANK_ENABLED:
metadata["ok"] = True
metadata["reason"] = "disabled"
return results[:final_k], metadata
if not results:
metadata["ok"] = True
metadata["reason"] = "no_results"
return [], metadata
metadata["attempted"] = True
documents = []
for idx, item in enumerate(results):
text = _result_text(item)
if not text:
continue
documents.append(
{
"id": str(item.get("id") or idx),
"text": text,
"metadata": {
"index": idx,
"path": item.get("path"),
"source": item.get("source"),
"chunk": item.get("chunk"),
},
}
)
if not documents:
metadata["ok"] = True
metadata["reason"] = "no_text_documents"
return results[:final_k], metadata
started = time.monotonic()
try:
body = json.dumps(
{
"query": query,
"documents": documents,
"top_k": final_k,
"return_documents": False,
}
).encode("utf-8")
req = request.Request(
RAG_RERANK_URL,
data=body,
headers={"Content-Type": "application/json"},
method="POST",
)
with request.urlopen(req, timeout=RAG_RERANK_TIMEOUT_MS / 1000.0) as resp:
payload = json.loads(resp.read().decode("utf-8"))
except (OSError, TimeoutError, json.JSONDecodeError, error.URLError, error.HTTPError) as exc:
metadata["duration_ms"] = round((time.monotonic() - started) * 1000, 2)
metadata["error"] = f"{type(exc).__name__}: {exc}"
return results[:final_k], metadata
metadata["duration_ms"] = round((time.monotonic() - started) * 1000, 2)
metadata["ok"] = bool(payload.get("ok", True))
metadata["model"] = payload.get("model")
metadata["device"] = payload.get("device")
metadata["npu_busy_delta_us"] = payload.get("npu_busy_delta_us")
metadata["require_npu_proof"] = RAG_RERANK_REQUIRE_NPU_PROOF
metadata["input_count"] = payload.get("input_count")
ranked = payload.get("results") or []
if RAG_RERANK_REQUIRE_NPU_PROOF and int(payload.get("npu_busy_delta_us") or 0) <= 0:
metadata["ok"] = False
metadata["error"] = "reranker response lacked positive npu_busy_delta_us"
return results[:final_k], metadata
if not metadata["ok"] or not ranked:
metadata["error"] = payload.get("error") or "reranker returned no ranked results"
return results[:final_k], metadata
by_id = {str(item.get("id") or idx): item for idx, item in enumerate(results)}
reranked = []
for rank, ranked_item in enumerate(ranked):
source_item = None
if "id" in ranked_item:
source_item = by_id.get(str(ranked_item.get("id")))
if source_item is None and isinstance(ranked_item.get("index"), int):
idx = ranked_item["index"]
if 0 <= idx < len(results):
source_item = results[idx]
if source_item is None:
continue
merged = dict(source_item)
merged["rerank_score"] = ranked_item.get("score")
merged["rerank_rank"] = rank + 1
reranked.append(merged)
if len(reranked) >= final_k:
break
if not reranked:
metadata["ok"] = False
metadata["error"] = "reranker result IDs did not match search results"
return results[:final_k], metadata
return reranked, metadata
def run_semantic_search(query: str, top_k: int = 5) -> dict:
"""Query the local Obsidian Chroma index via the rag-search script."""
query = (query or "").strip()
if not query:
return {"ok": False, "error": "query is required", "results": []}
top_k = max(1, min(int(top_k or 5), 20))
search_k = max(top_k, min(RAG_RERANK_INITIAL_K, 100)) if RAG_RERANK_ENABLED else top_k
final_k = min(top_k, RAG_RERANK_TOP_K) if RAG_RERANK_ENABLED else top_k
env = os.environ.copy()
env.setdefault("RAG_COLLECTION", RAG_COLLECTION)
env.setdefault("RAG_EMBED_MODEL", RAG_EMBED_MODEL)
@@ -119,7 +250,7 @@ def run_semantic_search(query: str, top_k: int = 5) -> dict:
"--index",
RAG_COLLECTION,
"--top-k",
str(top_k),
str(search_k),
"--raw",
query,
],
@@ -133,17 +264,27 @@ def run_semantic_search(query: str, top_k: int = 5) -> dict:
"ok": False,
"query": query,
"top_k": top_k,
"search_k": search_k,
"error": result.stderr.strip()[-2000:] or result.stdout.strip()[-2000:],
"results": [],
"rerank": {
"enabled": RAG_RERANK_ENABLED,
"attempted": False,
"ok": False,
"error": "vector search failed before rerank",
},
}
payload = json.loads(result.stdout)
results = payload.get("results") or []
results, rerank_meta = _apply_rerank(query, results, final_k)
return {
"ok": True,
"query": query,
"index": payload.get("index", RAG_COLLECTION),
"top_k": top_k,
"search_k": search_k,
"result_count": len(results),
"rerank": rerank_meta,
"results": results,
}