Graph access via SPARQL

This commit is contained in:
Oxy8
2026-03-02 16:27:28 -03:00
parent bf03d333f9
commit bba0ae887d
8 changed files with 667 additions and 84 deletions

View File

@@ -0,0 +1,94 @@
from __future__ import annotations
from typing import Any
def edge_retrieval_query(*, edge_limit: int, include_bnodes: bool) -> str:
bnode_filter = "" if include_bnodes else "FILTER(!isBlank(?s) && !isBlank(?o))"
return f"""
SELECT ?s ?p ?o
WHERE {{
?s ?p ?o .
FILTER(!isLiteral(?o))
FILTER(?p NOT IN (
<http://www.w3.org/2000/01/rdf-schema#label>,
<http://www.w3.org/2004/02/skos/core#prefLabel>,
<http://www.w3.org/2004/02/skos/core#altLabel>
))
{bnode_filter}
}}
LIMIT {edge_limit}
"""
def graph_from_sparql_bindings(
bindings: list[dict[str, Any]],
*,
node_limit: int,
include_bnodes: bool,
) -> tuple[list[dict[str, object]], list[dict[str, object]]]:
"""
Convert SPARQL JSON results bindings into:
nodes: [{id, termType, iri, label}]
edges: [{source, target, predicate}]
IDs are assigned densely (0..N-1) based on first occurrence in bindings.
"""
node_id_by_key: dict[tuple[str, str], int] = {}
node_meta: list[tuple[str, str]] = [] # (termType, iri)
out_edges: list[dict[str, object]] = []
def term_to_key_and_iri(term: dict[str, Any]) -> tuple[tuple[str, str], tuple[str, str]] | None:
t = term.get("type")
v = term.get("value")
if not t or v is None:
return None
if t == "literal":
return None
if t == "bnode":
if not include_bnodes:
return None
# SPARQL JSON uses bnode identifiers without the "_:" prefix; we normalize to "_:id".
return (("bnode", str(v)), ("bnode", f"_:{v}"))
# Default to "uri".
return (("uri", str(v)), ("uri", str(v)))
def get_or_add(term: dict[str, Any]) -> int | None:
out = term_to_key_and_iri(term)
if out is None:
return None
key, meta = out
existing = node_id_by_key.get(key)
if existing is not None:
return existing
if len(node_meta) >= node_limit:
return None
nid = len(node_meta)
node_id_by_key[key] = nid
node_meta.append(meta)
return nid
for b in bindings:
s_term = b.get("s") or {}
o_term = b.get("o") or {}
p_term = b.get("p") or {}
sid = get_or_add(s_term)
oid = get_or_add(o_term)
if sid is None or oid is None:
continue
pred = p_term.get("value")
if not pred:
continue
out_edges.append({"source": sid, "target": oid, "predicate": str(pred)})
out_nodes = [
{"id": i, "termType": term_type, "iri": iri, "label": None}
for i, (term_type, iri) in enumerate(node_meta)
]
return out_nodes, out_edges

View File

@@ -5,6 +5,7 @@ from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException, Query
from fastapi.middleware.cors import CORSMiddleware
from .graph_export import edge_retrieval_query, graph_from_sparql_bindings
from .models import EdgesResponse, GraphResponse, NodesResponse, SparqlQueryRequest, StatsResponse
from .rdf_store import RDFStore
from .sparql_engine import AnzoGraphEngine, RdflibEngine, SparqlEngine, create_sparql_engine
@@ -161,87 +162,13 @@ async def graph(
) -> GraphResponse:
sparql: SparqlEngine = app.state.sparql
if settings.graph_backend == "rdflib":
store: RDFStore = app.state.store
return GraphResponse(
nodes=store.node_slice(offset=0, limit=node_limit),
edges=store.edge_slice(offset=0, limit=edge_limit),
)
# AnzoGraph mode: return a simple subgraph by pulling the first N triples.
assert isinstance(sparql, AnzoGraphEngine)
edges_bnode_filter = "" if settings.include_bnodes else "FILTER(!isBlank(?s) && !isBlank(?o))"
edges_q = f"""
SELECT ?s ?p ?o
WHERE {{
?s ?p ?o .
FILTER(!isLiteral(?o))
FILTER(?p NOT IN (
<http://www.w3.org/2000/01/rdf-schema#label>,
<http://www.w3.org/2004/02/skos/core#prefLabel>,
<http://www.w3.org/2004/02/skos/core#altLabel>
))
{edges_bnode_filter}
}}
LIMIT {edge_limit}
"""
# Use SPARQL for graph export in BOTH modes so callers don't care which backend is in use.
edges_q = edge_retrieval_query(edge_limit=edge_limit, include_bnodes=settings.include_bnodes)
res = await sparql.query_json(edges_q)
bindings = (((res.get("results") or {}).get("bindings")) or [])
node_id_by_key: dict[tuple[str, str], int] = {}
node_meta: list[tuple[str, str]] = [] # (termType, iri)
out_edges: list[dict[str, object]] = []
def _term_to_key_and_iri(term: dict[str, str]) -> tuple[tuple[str, str], tuple[str, str]] | None:
t = term.get("type")
v = term.get("value")
if not t or v is None:
return None
if t == "literal":
return None
if t == "bnode" and not settings.include_bnodes:
return None
if t == "bnode":
return (("bnode", v), ("bnode", f"_:{v}"))
# Default to "uri".
return (("uri", v), ("uri", v))
def _get_or_add(term: dict[str, str]) -> int | None:
out = _term_to_key_and_iri(term)
if out is None:
return None
key, meta = out
existing = node_id_by_key.get(key)
if existing is not None:
return existing
if len(node_meta) >= node_limit:
return None
nid = len(node_meta)
node_id_by_key[key] = nid
node_meta.append(meta)
return nid
for b in bindings:
s_term = b.get("s") or {}
o_term = b.get("o") or {}
p_term = b.get("p") or {}
sid = _get_or_add(s_term)
oid = _get_or_add(o_term)
if sid is None or oid is None:
continue
pred = p_term.get("value")
if not pred:
continue
out_edges.append({"source": sid, "target": oid, "predicate": pred})
out_nodes = [
{"id": i, "termType": term_type, "iri": iri, "label": None}
for i, (term_type, iri) in enumerate(node_meta)
]
return GraphResponse(nodes=out_nodes, edges=out_edges)
nodes, edges = graph_from_sparql_bindings(
bindings,
node_limit=node_limit,
include_bnodes=settings.include_bnodes,
)
return GraphResponse(nodes=nodes, edges=edges)

View File

@@ -0,0 +1 @@

View File

@@ -0,0 +1,153 @@
from __future__ import annotations
from typing import Any
from ..sparql_engine import SparqlEngine
RDFS_SUBCLASS_OF = "http://www.w3.org/2000/01/rdf-schema#subClassOf"
RDFS_LABEL = "http://www.w3.org/2000/01/rdf-schema#label"
def _bindings(res: dict[str, Any]) -> list[dict[str, Any]]:
return (((res.get("results") or {}).get("bindings")) or [])
def _term_key(term: dict[str, Any]) -> tuple[str, str] | None:
t = term.get("type")
v = term.get("value")
if not t or v is None:
return None
if t == "literal":
return None
if t == "bnode":
return ("bnode", str(v))
return ("uri", str(v))
def _key_to_entity_string(key: tuple[str, str]) -> str:
t, v = key
if t == "bnode":
return f"_:{v}"
return v
def _label_score(binding: dict[str, Any]) -> int:
"""
Higher is better.
Prefer English, then no-language, then anything else.
"""
lang = (binding.get("xml:lang") or "").lower()
if lang == "en":
return 3
if lang == "":
return 2
return 1
async def extract_subclass_entities_and_labels(
sparql: SparqlEngine,
*,
include_bnodes: bool,
label_batch_size: int = 500,
) -> tuple[list[str], list[str | None]]:
"""
Pipeline:
1) Query all rdfs:subClassOf triples.
2) Build a unique set of entity terms from subjects+objects, convert to list.
3) Fetch rdfs:label for those entities and return an aligned labels list.
Returns:
entities: list[str] (IRI or "_:bnodeId")
labels: list[str|None], aligned with entities
"""
subclass_q = f"""
SELECT ?s ?o
WHERE {{
?s <{RDFS_SUBCLASS_OF}> ?o .
FILTER(!isLiteral(?o))
{"FILTER(!isBlank(?s) && !isBlank(?o))" if not include_bnodes else ""}
}}
"""
res = await sparql.query_json(subclass_q)
entity_keys: set[tuple[str, str]] = set()
for b in _bindings(res):
sk = _term_key(b.get("s") or {})
ok = _term_key(b.get("o") or {})
if sk is not None and (include_bnodes or sk[0] != "bnode"):
entity_keys.add(sk)
if ok is not None and (include_bnodes or ok[0] != "bnode"):
entity_keys.add(ok)
# Deterministic ordering.
entity_key_list = sorted(entity_keys, key=lambda k: (k[0], k[1]))
entities = [_key_to_entity_string(k) for k in entity_key_list]
# Build label map keyed by term key.
best_label_by_key: dict[tuple[str, str], tuple[int, str]] = {}
# URIs can be batch-queried via VALUES.
uri_values = [v for (t, v) in entity_key_list if t == "uri"]
for i in range(0, len(uri_values), label_batch_size):
batch = uri_values[i : i + label_batch_size]
values = " ".join(f"<{u}>" for u in batch)
labels_q = f"""
SELECT ?s ?label
WHERE {{
VALUES ?s {{ {values} }}
?s <{RDFS_LABEL}> ?label .
}}
"""
lres = await sparql.query_json(labels_q)
for b in _bindings(lres):
sk = _term_key(b.get("s") or {})
if sk is None or sk[0] != "uri":
continue
label_term = b.get("label") or {}
if label_term.get("type") != "literal":
continue
label_value = label_term.get("value")
if label_value is None:
continue
score = _label_score(label_term)
prev = best_label_by_key.get(sk)
if prev is None or score > prev[0]:
best_label_by_key[sk] = (score, str(label_value))
# Blank nodes can't reliably be addressed by ID across queries, but if enabled we can still
# fetch all bnode labels and filter locally.
if include_bnodes:
bnode_keys = {k for k in entity_key_list if k[0] == "bnode"}
if bnode_keys:
bnode_labels_q = f"""
SELECT ?s ?label
WHERE {{
?s <{RDFS_LABEL}> ?label .
FILTER(isBlank(?s))
}}
"""
blres = await sparql.query_json(bnode_labels_q)
for b in _bindings(blres):
sk = _term_key(b.get("s") or {})
if sk is None or sk not in bnode_keys:
continue
label_term = b.get("label") or {}
if label_term.get("type") != "literal":
continue
label_value = label_term.get("value")
if label_value is None:
continue
score = _label_score(label_term)
prev = best_label_by_key.get(sk)
if prev is None or score > prev[0]:
best_label_by_key[sk] = (score, str(label_value))
labels: list[str | None] = []
for k in entity_key_list:
item = best_label_by_key.get(k)
labels.append(item[1] if item else None)
return entities, labels

View File

@@ -132,3 +132,19 @@ class RDFStore:
}
)
return out
def edges_within_nodes(self, *, max_node_id_exclusive: int, limit: int) -> list[dict[str, Any]]:
out: list[dict[str, Any]] = []
for row in self._edges:
if row.source >= max_node_id_exclusive or row.target >= max_node_id_exclusive:
continue
out.append(
{
"source": row.source,
"target": row.target,
"predicate": row.predicate,
}
)
if len(out) >= limit:
break
return out

View File

@@ -33,6 +33,7 @@ class Settings(BaseSettings):
sparql_timeout_s: float = Field(default=300.0, alias="SPARQL_TIMEOUT_S")
sparql_ready_retries: int = Field(default=30, alias="SPARQL_READY_RETRIES")
sparql_ready_delay_s: float = Field(default=4.0, alias="SPARQL_READY_DELAY_S")
sparql_ready_timeout_s: float = Field(default=10.0, alias="SPARQL_READY_TIMEOUT_S")
# Comma-separated, or "*" (default).
cors_origins: str = Field(default="*", alias="CORS_ORIGINS")

View File

@@ -56,6 +56,7 @@ class AnzoGraphEngine:
self.timeout_s = settings.sparql_timeout_s
self.ready_retries = settings.sparql_ready_retries
self.ready_delay_s = settings.sparql_ready_delay_s
self.ready_timeout_s = settings.sparql_ready_timeout_s
self.user = settings.sparql_user
self.password = settings.sparql_pass
@@ -135,15 +136,34 @@ class AnzoGraphEngine:
resp.raise_for_status()
async def _wait_ready(self) -> None:
if self._client is None:
raise RuntimeError("AnzoGraphEngine not started")
# Match the repo's Julia readiness gate: real SPARQL POST + valid JSON parse.
headers = {
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/sparql-results+json",
}
if self._auth_header:
headers["Authorization"] = self._auth_header
last_err: Exception | None = None
for _ in range(self.ready_retries):
try:
# Keep it cheap and JSON-parseable.
await self.query_json("ASK WHERE { ?s ?p ?o }")
resp = await self._client.post(
self.endpoint,
headers=headers,
data={"query": "ASK WHERE { ?s ?p ?o }"},
timeout=self.ready_timeout_s,
)
resp.raise_for_status()
# Ensure it's JSON, not HTML/text during boot.
resp.json()
return
except Exception as e:
last_err = e
await asyncio.sleep(self.ready_delay_s)
raise RuntimeError(f"AnzoGraph not ready at {self.endpoint}") from last_err