mcp 2.x already on main. Does not replace the variety chunker (one chunk per variety is the anti-hallucination contract). - Numbered [1] citations on search_docs / search_trials - Eval JSONL sidecar, k-curve, eval.pvalue, eval.trace - Nomic prefixes at embed time only; stored text unprefixed Closes #25
144 lines
4.9 KiB
Python
144 lines
4.9 KiB
Python
"""Build Chroma (and BM25) indexes from the seed corpus on disk.
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Reads ``corpus/<source>/<source_key>.json`` sidecars, chunks each
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variety via ``rag.chunk.chunks_from_variety``, upserts into Chroma.
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With ``--rebuild``, drops + recreates the collection (clean state).
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With ``--bm25-only``, skips Chroma and rebuilds only the FTS5 index
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— useful for fast iteration when the chunker didn't change.
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Collection name is ``<PRODUCT_NAME>_docs`` (default: ``crop_seed_docs``).
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Override via the PRODUCT_NAME env var.
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"""
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from __future__ import annotations
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import argparse
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import json
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import logging
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import os
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import time
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from pathlib import Path
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from typing import Iterator
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import chromadb
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from chromadb.config import Settings
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from .chunk import chunks_from_variety, chunks_from_trial
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from .embeddings import EMBED_DOC_PREFIX, embed_texts, embedding_function
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log = logging.getLogger(__name__)
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logging.basicConfig(level=logging.INFO, format="%(asctime)s %(message)s")
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ROOT = Path(__file__).resolve().parent.parent
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CORPUS = ROOT / "corpus"
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CHROMA_DIR = ROOT / "chroma"
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PRODUCT_NAME = os.environ.get("PRODUCT_NAME", "crop_seed")
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COLLECTION = f"{PRODUCT_NAME}_docs"
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def variety_records() -> Iterator[dict]:
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"""Walk ``corpus/<source>/<source_key>.json``, yield one chunk per
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document.
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Dispatches by the sidecar's ``data_type`` field:
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- ``"trial"`` → chunks_from_trial (gh_plot_reports, agripro_trials)
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- anything else (or absent) → chunks_from_variety (default)
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The output shape (id/text/metadata) is identical for both — only
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the chunk text composition and metadata keys differ. Chroma + BM25
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can index both into the same collection; downstream tools filter
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by the ``data_type`` metadata field.
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"""
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if not CORPUS.exists():
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log.error("corpus/ doesn't exist; run a scraper first")
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return
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for source_dir in sorted(CORPUS.iterdir()):
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if not source_dir.is_dir() or source_dir.name.startswith("."):
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continue
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for sidecar_path in sorted(source_dir.glob("*.json")):
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try:
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head = json.loads(sidecar_path.read_text(encoding="utf-8"))
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except (OSError, json.JSONDecodeError) as exc:
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log.warning("skipping unreadable sidecar %s: %s", sidecar_path, exc)
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continue
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if head.get("data_type") == "trial":
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yield from chunks_from_trial(sidecar_path)
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else:
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yield from chunks_from_variety(sidecar_path)
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def upsert_to_chroma(records: list[dict]) -> int:
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client = chromadb.PersistentClient(
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path=str(CHROMA_DIR),
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settings=Settings(anonymized_telemetry=False),
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)
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# Drop + recreate for --rebuild semantics.
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try:
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client.delete_collection(COLLECTION)
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except Exception:
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pass
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col = client.create_collection(COLLECTION, embedding_function=embedding_function())
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BATCH = 64
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total = 0
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for i in range(0, len(records), BATCH):
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chunk = records[i:i + BATCH]
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texts = [r["text"] for r in chunk]
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vectors = embed_texts(texts, prefix=EMBED_DOC_PREFIX, ef=embedding_function())
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col.upsert(
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ids=[r["id"] for r in chunk],
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documents=texts,
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embeddings=vectors,
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metadatas=[r["metadata"] for r in chunk],
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)
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total += len(chunk)
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log.info("upserted %d / %d chunks", total, len(records))
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return total
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def main() -> int:
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p = argparse.ArgumentParser()
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p.add_argument("--rebuild", action="store_true",
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help="Drop and recreate the Chroma collection.")
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p.add_argument("--bm25-only", action="store_true",
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help="Rebuild only the BM25 index, skip Chroma.")
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p.add_argument("--bm25-db", type=Path,
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default=ROOT / "bm25" / f"{PRODUCT_NAME}_docs.db",
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help="Path to the BM25 sqlite db.")
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args = p.parse_args()
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log.info("reading corpus from %s", CORPUS)
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t0 = time.time()
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records = list(variety_records())
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log.info("loaded %d chunks in %.1fs", len(records), time.time() - t0)
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if not records:
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log.error("no chunks — is corpus/ populated?")
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return 1
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if args.bm25_only:
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from .bm25 import BM25Index
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log.info("--bm25-only: building FTS5 only")
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BM25Index(args.bm25_db).build(records)
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return 0
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if not args.rebuild:
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log.info("no --rebuild; nothing to do. (Use --rebuild to upsert.)")
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return 0
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t_c = time.time()
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n = upsert_to_chroma(records)
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log.info("chroma: %d chunks in %.1fs", n, time.time() - t_c)
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try:
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from .bm25 import BM25Index
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t_b = time.time()
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BM25Index(args.bm25_db).build(records)
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log.info("bm25 done in %.1fs", time.time() - t_b)
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except ImportError:
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log.info("rag.bm25 not available — skipping BM25 build")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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