trustgraph/trustgraph-flow/trustgraph/tables/knowledge.py
cybermaggedon 286f762369
The id field in pipeline Metadata was being overwritten at each processing (#686)
The id field in pipeline Metadata was being overwritten at each processing
stage (document → page → chunk), causing knowledge storage to create
separate cores per chunk instead of grouping by document.

Add a root field that:
- Is set by librarian to the original document ID
- Is copied unchanged through PDF decoder, chunkers, and extractors
- Is used by knowledge storage for document_id grouping (with fallback to id)

Changes:
- Add root field to Metadata schema with empty string default
- Set root=document.id in librarian when initiating document processing
- Copy root through PDF decoder, recursive chunker, and all extractors
- Update knowledge storage to use root (or id as fallback) for grouping
- Add root handling to translators and gateway serialization
- Update test mock Metadata class to include root parameter
2026-03-11 12:16:39 +00:00

465 lines
12 KiB
Python

from .. schema import KnowledgeResponse, Triple, Triples, EntityEmbeddings
from .. schema import Metadata, Term, IRI, LITERAL, GraphEmbeddings
from cassandra.cluster import Cluster
def term_to_tuple(term):
"""Convert Term to (value, is_uri) tuple for database storage."""
if term.type == IRI:
return (term.iri, True)
else: # LITERAL
return (term.value, False)
def tuple_to_term(value, is_uri):
"""Convert (value, is_uri) tuple from database to Term."""
if is_uri:
return Term(type=IRI, iri=value)
else:
return Term(type=LITERAL, value=value)
from cassandra.auth import PlainTextAuthProvider
from ssl import SSLContext, PROTOCOL_TLSv1_2
import uuid
import time
import asyncio
import logging
logger = logging.getLogger(__name__)
class KnowledgeTableStore:
def __init__(
self,
cassandra_host, cassandra_username, cassandra_password, keyspace,
):
self.keyspace = keyspace
logger.info("Connecting to Cassandra...")
# Ensure cassandra_host is a list
if isinstance(cassandra_host, str):
cassandra_host = [h.strip() for h in cassandra_host.split(',')]
if cassandra_username and cassandra_password:
ssl_context = SSLContext(PROTOCOL_TLSv1_2)
auth_provider = PlainTextAuthProvider(
username=cassandra_username, password=cassandra_password
)
self.cluster = Cluster(
cassandra_host,
auth_provider=auth_provider,
ssl_context=ssl_context
)
else:
self.cluster = Cluster(cassandra_host)
self.cassandra = self.cluster.connect()
logger.info("Connected.")
self.ensure_cassandra_schema()
self.prepare_statements()
def ensure_cassandra_schema(self):
logger.debug("Ensure Cassandra schema...")
logger.debug("Keyspace...")
# FIXME: Replication factor should be configurable
self.cassandra.execute(f"""
create keyspace if not exists {self.keyspace}
with replication = {{
'class' : 'SimpleStrategy',
'replication_factor' : 1
}};
""");
self.cassandra.set_keyspace(self.keyspace)
logger.debug("triples table...")
self.cassandra.execute("""
CREATE TABLE IF NOT EXISTS triples (
user text,
document_id text,
id uuid,
time timestamp,
metadata list<tuple<
text, boolean, text, boolean, text, boolean
>>,
triples list<tuple<
text, boolean, text, boolean, text, boolean
>>,
PRIMARY KEY ((user, document_id), id)
);
""");
logger.debug("graph_embeddings table...")
self.cassandra.execute("""
create table if not exists graph_embeddings (
user text,
document_id text,
id uuid,
time timestamp,
metadata list<tuple<
text, boolean, text, boolean, text, boolean
>>,
entity_embeddings list<
tuple<
tuple<text, boolean>,
list<double>
>
>,
PRIMARY KEY ((user, document_id), id)
);
""");
self.cassandra.execute("""
CREATE INDEX IF NOT EXISTS graph_embeddings_user ON
graph_embeddings ( user );
""");
logger.debug("document_embeddings table...")
self.cassandra.execute("""
create table if not exists document_embeddings (
user text,
document_id text,
id uuid,
time timestamp,
metadata list<tuple<
text, boolean, text, boolean, text, boolean
>>,
chunks list<
tuple<
blob,
list<double>
>
>,
PRIMARY KEY ((user, document_id), id)
);
""");
self.cassandra.execute("""
CREATE INDEX IF NOT EXISTS document_embeddings_user ON
document_embeddings ( user );
""");
logger.info("Cassandra schema OK.")
def prepare_statements(self):
self.insert_triples_stmt = self.cassandra.prepare("""
INSERT INTO triples
(
id, user, document_id,
time, metadata, triples
)
VALUES (?, ?, ?, ?, ?, ?)
""")
self.insert_graph_embeddings_stmt = self.cassandra.prepare("""
INSERT INTO graph_embeddings
(
id, user, document_id, time, metadata, entity_embeddings
)
VALUES (?, ?, ?, ?, ?, ?)
""")
self.insert_document_embeddings_stmt = self.cassandra.prepare("""
INSERT INTO document_embeddings
(
id, user, document_id, time, metadata, chunks
)
VALUES (?, ?, ?, ?, ?, ?)
""")
self.list_cores_stmt = self.cassandra.prepare("""
SELECT DISTINCT user, document_id FROM graph_embeddings
WHERE user = ?
""")
self.get_triples_stmt = self.cassandra.prepare("""
SELECT id, time, metadata, triples
FROM triples
WHERE user = ? AND document_id = ?
""")
self.get_graph_embeddings_stmt = self.cassandra.prepare("""
SELECT id, time, metadata, entity_embeddings
FROM graph_embeddings
WHERE user = ? AND document_id = ?
""")
self.get_document_embeddings_stmt = self.cassandra.prepare("""
SELECT id, time, metadata, chunks
FROM document_embeddings
WHERE user = ? AND document_id = ?
""")
self.delete_triples_stmt = self.cassandra.prepare("""
DELETE FROM triples
WHERE user = ? AND document_id = ?
""")
self.delete_graph_embeddings_stmt = self.cassandra.prepare("""
DELETE FROM graph_embeddings
WHERE user = ? AND document_id = ?
""")
async def add_triples(self, m):
when = int(time.time() * 1000)
triples = [
(
*term_to_tuple(v.s), *term_to_tuple(v.p), *term_to_tuple(v.o)
)
for v in m.triples
]
while True:
try:
resp = self.cassandra.execute(
self.insert_triples_stmt,
(
uuid.uuid4(), m.metadata.user,
m.metadata.root or m.metadata.id, when,
[], triples,
)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
async def add_graph_embeddings(self, m):
when = int(time.time() * 1000)
entities = [
(
term_to_tuple(v.entity),
v.vector
)
for v in m.entities
]
while True:
try:
resp = self.cassandra.execute(
self.insert_graph_embeddings_stmt,
(
uuid.uuid4(), m.metadata.user,
m.metadata.root or m.metadata.id, when,
[], entities,
)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
async def add_document_embeddings(self, m):
when = int(time.time() * 1000)
chunks = [
(
v.chunk_id,
v.vector,
)
for v in m.chunks
]
while True:
try:
resp = self.cassandra.execute(
self.insert_document_embeddings_stmt,
(
uuid.uuid4(), m.metadata.user,
m.metadata.root or m.metadata.id, when,
[], chunks,
)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
async def list_kg_cores(self, user):
logger.debug("List kg cores...")
while True:
try:
resp = self.cassandra.execute(
self.list_cores_stmt,
(user,)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
lst = [
row[1]
for row in resp
]
logger.debug("Done")
return lst
async def delete_kg_core(self, user, document_id):
logger.debug("Delete kg cores...")
while True:
try:
resp = self.cassandra.execute(
self.delete_triples_stmt,
(user, document_id)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
while True:
try:
resp = self.cassandra.execute(
self.delete_graph_embeddings_stmt,
(user, document_id)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
async def get_triples(self, user, document_id, receiver):
logger.debug("Get triples...")
while True:
try:
resp = self.cassandra.execute(
self.get_triples_stmt,
(user, document_id)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
for row in resp:
if row[3]:
triples = [
Triple(
s = tuple_to_term(elt[0], elt[1]),
p = tuple_to_term(elt[2], elt[3]),
o = tuple_to_term(elt[4], elt[5]),
)
for elt in row[3]
]
else:
triples = []
await receiver(
Triples(
metadata = Metadata(
id = document_id,
user = user,
collection = "default", # FIXME: What to put here?
),
triples = triples
)
)
logger.debug("Done")
async def get_graph_embeddings(self, user, document_id, receiver):
logger.debug("Get GE...")
while True:
try:
resp = self.cassandra.execute(
self.get_graph_embeddings_stmt,
(user, document_id)
)
break
except Exception as e:
logger.error("Exception occurred", exc_info=True)
raise e
for row in resp:
if row[3]:
entities = [
EntityEmbeddings(
entity = tuple_to_term(ent[0][0], ent[0][1]),
vectors = ent[1]
)
for ent in row[3]
]
else:
entities = []
await receiver(
GraphEmbeddings(
metadata = Metadata(
id = document_id,
user = user,
collection = "default", # FIXME: What to put here?
),
entities = entities
)
)
logger.debug("Done")