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8058e7e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 | import json
from dataclasses import dataclass
from app.db.sqlite import db
from app.rag.text import hamming_distance, normalize_text, sha256_text, simhash
@dataclass
class DocumentCacheDecision:
should_embed: bool
status: str
matched_doc_id: str | None = None
reason: str = ""
class DocumentCache:
near_duplicate_hamming_threshold = 4
def inspect(self, raw_text: str) -> DocumentCacheDecision:
normalized = normalize_text(raw_text)
file_hash = sha256_text(raw_text)
normalized_hash = sha256_text(normalized)
signature = simhash(normalized)
with db() as conn:
exact = conn.execute(
"SELECT doc_id FROM documents WHERE file_hash = ? OR normalized_hash = ?",
(file_hash, normalized_hash),
).fetchone()
if exact:
return DocumentCacheDecision(
should_embed=False,
status="skipped_exact_duplicate",
matched_doc_id=exact["doc_id"],
reason="Document hash already exists.",
)
rows = conn.execute("SELECT doc_id, simhash FROM documents").fetchall()
for row in rows:
distance = hamming_distance(signature, int(row["simhash"]))
if distance <= self.near_duplicate_hamming_threshold:
return DocumentCacheDecision(
should_embed=False,
status="skipped_near_duplicate",
matched_doc_id=row["doc_id"],
reason=f"Near-duplicate SimHash distance {distance}.",
)
return DocumentCacheDecision(should_embed=True, status="new_document")
def chunk_exists(self, text_hash: str) -> bool:
with db() as conn:
row = conn.execute("SELECT chunk_id FROM chunks WHERE text_hash = ?", (text_hash,)).fetchone()
return row is not None
def save_document(
self,
doc_id: str,
source_name: str,
raw_text: str,
status: str,
) -> None:
normalized = normalize_text(raw_text)
with db() as conn:
conn.execute(
"""
INSERT INTO documents(doc_id, source_name, file_hash, normalized_hash, simhash, status)
VALUES (?, ?, ?, ?, ?, ?)
""",
(
doc_id,
source_name,
sha256_text(raw_text),
sha256_text(normalized),
str(simhash(normalized)),
status,
),
)
def save_chunk(
self,
chunk_id: str,
doc_id: str,
chunk_index: int,
text: str,
text_hash: str,
metadata: dict,
embedded: bool,
) -> None:
with db() as conn:
conn.execute(
"""
INSERT OR IGNORE INTO chunks(chunk_id, doc_id, chunk_index, text, text_hash, metadata_json, embedded_at)
VALUES (?, ?, ?, ?, ?, ?, CASE WHEN ? THEN CURRENT_TIMESTAMP ELSE NULL END)
""",
(chunk_id, doc_id, chunk_index, text, text_hash, json.dumps(metadata), int(embedded)),
)
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