fa448f94e1
Initial scaffold: the docs-mcp-template clone with all the
HVM-validated stack ported across, customized for Morpheus
Enterprise (PRODUCT_NAME=morpheus, server name morpheus-docs).
Bundles (live-discovered 2026-05-22; 1710 cataloged pages total):
* morpheus_user_manual_8_1_0 sd00007510en_us 568 pages (Feb 2026)
* morpheus_user_manual_8_1_1 sd00007621en_us 569 pages (Mar 2026)
* morpheus_user_manual_8_1_2 sd00007732en_us 569 pages (Apr 2026)
* morpheus_release_notes_8_1_0 sd00007496en_us single-doc
* morpheus_release_notes_8_1_1 sd00007610en_us single-doc
* morpheus_release_notes_8_1_2 sd00007733en_us single-doc
* morpheus_quickspecs a50009231enw html-file (live
curl_cffi against www.hpe.com; all 12+ Enterprise SKUs captured —
S6E64..S6E73AAE for new/renewal/upgrade × 1/3/5-yr terms, plus
services SKUs HA124A1#V38/V39 and H46SBA1).
No Deployment Guide or Qualification Matrix on HPE Support for
Morpheus Enterprise specifically — the only QM (sd00006551en_us)
covers HVM clusters managed by Morpheus and lives in hvm-docs.
Stack carried forward from hvm-docs:
* rag/{index,chunk,embeddings,bm25}.py — including the
MAX_CHARS=4000 chunk-cap fix for table-dense content
* docs_mcp/{server,usage}.py — 11 MCP tools, BM25-default search,
cross-encoder rerank, hybrid behind HYBRID_SEARCH=true,
morpheus_api_lessons (renamed from hvm_api_lessons), env-gated
submit_doc_bug
* docs_mcp/api_lessons.md — Morpheus-specific scaffold covering
licensing model, HVM elevation path, REST vs Plugin API, with
TODO markers for sections to flesh out from real ops experience
* scrape/{runner,quickspecs,changelog,bundles}.py — TOC + single-doc
+ html-file modes, curl_cffi Chrome120 for www.hpe.com edge bypass
* eval/{retrievers,run_eval}.py + queries.jsonl scaffold (4 placeholder
queries; populate after first scrape)
* scripts/{rerank_server,usage_report,registry_gc}.py
* .gitea/workflows/{refresh,image-only}.yml — same Gitea Actions
setup zerto-docs uses (push LAN, pull public-URL, GPU Ollama pool)
* deploy/docker-compose.yml — morpheus-docs-mcp service definition,
shared jina-rerank sidecar, Watchtower-labeled
* Dockerfile, requirements.txt, requirements-rerank.txt
Verified locally: scrape produced 1599 .md pages (some TOC entries
are parent-only and yield no body), 6353 chunks all under the 4 KB
cap, MCP server boots and lists 11 tools cleanly.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
153 lines
5.4 KiB
Python
153 lines
5.4 KiB
Python
"""Retriever protocol + concrete implementations.
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A single matrix dimension per knob (dense / reranked / bm25 / hybrid)
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so the eval harness can compare them apples-to-apples. Implement these
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once at Phase 7 and reuse them across every retrieval change.
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Each retriever returns a ranked list of (bundle_id, page_id) tuples
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deduplicated to the page level (chunks within the same page collapse
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to one entry; the highest-ranked chunk's position wins).
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"""
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from __future__ import annotations
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from typing import Iterable, Protocol
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class Retriever(Protocol):
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name: str
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def retrieve(self, query: str, k: int = 10) -> list[tuple[str, str]]:
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"""Return up to k (bundle_id, page_id) tuples in rank order."""
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...
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def _split_chunk_id(chunk_id: str) -> tuple[str, str, int]:
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"""`bundle::page::ordinal` -> (bundle, page, int(ordinal))."""
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bid, pid, ordinal = chunk_id.split("::")
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return bid, pid, int(ordinal)
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def _collapse_to_pages(chunk_ids: Iterable[str], k: int) -> list[tuple[str, str]]:
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seen: set[tuple[str, str]] = set()
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out: list[tuple[str, str]] = []
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for cid in chunk_ids:
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bid, pid, _ord = _split_chunk_id(cid)
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key = (bid, pid)
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if key in seen:
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continue
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seen.add(key)
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out.append(key)
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if len(out) >= k:
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break
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return out
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class DenseRetriever:
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"""Chroma cosine search via the live embedding function."""
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name = "dense"
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def __init__(self, collection, pool: int = 50):
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self.col = collection
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self.pool = pool
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def retrieve(self, query: str, k: int = 10) -> list[tuple[str, str]]:
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res = self.col.query(query_texts=[query], n_results=self.pool)
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ids = (res.get("ids") or [[]])[0]
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return _collapse_to_pages(ids, k)
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class BM25Retriever:
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"""SQLite FTS5 lexical search."""
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name = "bm25"
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def __init__(self, bm25_index, pool: int = 200):
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self.bm = bm25_index
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self.pool = pool
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def retrieve(self, query: str, k: int = 10) -> list[tuple[str, str]]:
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hits = self.bm.query(query, n=self.pool)
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return _collapse_to_pages((cid for cid, _score in hits), k)
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class HybridRetriever:
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"""Reciprocal Rank Fusion of dense + BM25 rankings."""
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name = "hybrid_rrf"
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def __init__(self, dense: DenseRetriever, bm25: BM25Retriever, k_rrf: int = 60, pool: int = 100):
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self.dense = dense
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self.bm25 = bm25
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self.k_rrf = k_rrf
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self.pool = pool
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def retrieve(self, query: str, k: int = 10) -> list[tuple[str, str]]:
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dense_pages = self.dense.retrieve(query, k=self.pool)
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bm25_pages = self.bm25.retrieve(query, k=self.pool)
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scores: dict[tuple[str, str], float] = {}
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for rank, page in enumerate(dense_pages, start=1):
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scores[page] = scores.get(page, 0.0) + 1.0 / (self.k_rrf + rank)
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for rank, page in enumerate(bm25_pages, start=1):
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scores[page] = scores.get(page, 0.0) + 1.0 / (self.k_rrf + rank)
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ranked = sorted(scores.items(), key=lambda kv: -kv[1])
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return [page for page, _s in ranked[:k]]
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def _rerank_pool(rerank_url: str, query: str, ids_and_texts: list[tuple[str, str]],
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timeout: float = 30.0) -> list[str] | None:
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"""POST to /v1/rerank, return ids in reranked order. None on failure."""
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if not ids_and_texts:
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return []
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import httpx
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try:
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with httpx.Client(timeout=timeout) as c:
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r = c.post(f"{rerank_url}/v1/rerank", json={
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"query": query,
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"documents": [(t or "")[:2000] for _i, t in ids_and_texts],
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"top_n": len(ids_and_texts),
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})
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r.raise_for_status()
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results = r.json().get("results") or []
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return [ids_and_texts[item["index"]][0] for item in results
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if isinstance(item.get("index"), int)
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and 0 <= item["index"] < len(ids_and_texts)]
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except Exception:
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return None
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class RerankedRetriever:
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"""Pull a candidate pool via a base retriever, then cross-encoder re-rank."""
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def __init__(self, base: Retriever, collection, rerank_url: str, name_suffix: str = "rerank",
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pool: int = 50, timeout: float = 30.0):
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self.base = base
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self.col = collection
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self.url = rerank_url
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self.name = f"{base.name}+{name_suffix}"
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self.pool = pool
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self.timeout = timeout
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def retrieve(self, query: str, k: int = 10) -> list[tuple[str, str]]:
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# Base returns deduplicated page-level tuples; rerank needs CHUNK-level
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# texts to be informative. Pull each page's chunk 0 text from Chroma.
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pages = self.base.retrieve(query, k=self.pool)
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if not pages:
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return []
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chunk_ids = [f"{bid}::{pid}::0" for bid, pid in pages]
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g = self.col.get(ids=chunk_ids, include=["documents"])
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by_id = dict(zip(g["ids"], g["documents"]))
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ids_and_texts = [(cid, by_id.get(cid, "")) for cid in chunk_ids]
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order = _rerank_pool(self.url, query, ids_and_texts, timeout=self.timeout)
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if order is None:
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return pages[:k]
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out: list[tuple[str, str]] = []
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seen: set[tuple[str, str]] = set()
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for cid in order:
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bid, pid, _ = cid.split("::")
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key = (bid, pid)
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if key in seen:
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continue
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seen.add(key)
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out.append(key)
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if len(out) >= k:
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break
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return out
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