Files
AI/crawler_platform/app/api/routes.py
lasta 39097d0240 Phase 1.5: 엔티티/클레임 직접 입력 — OntologyEditorPage + 3탭 (엔티티/클레임/JSON 일괄)
백엔드 (crawler_platform/app/api/routes.py):
- POST /projects/{n}/entities: 단일 엔티티 직접 생성 (upsert)
  - CreateEntityRequest (entity_type, name, metadata)
- POST /projects/{n}/entities/bulk: 다수 엔티티 일괄 생성
  - BulkCreateEntitiesRequest, 응답 created 수 + entities
- DELETE /projects/{n}/entities/{id}: 단일 엔티티 삭제
- POST /projects/{n}/claims: 단일 클레임 직접 생성
  - CreateClaimRequest (source_name, subject_entity_id, predicate,
    object_entity_id|object_value, confidence, confidence_reason, evidence_text)
  - claim_hash로 중복 검출 → 있으면 confidence/메타 갱신
  - status="validated_claim", extraction_method="manual"
  - evidence_text 있으면 Evidence 자동 생성
- DELETE /projects/{n}/claims/{id}: 단일 클레임 삭제

프론트엔드 API (src/lib/api/):
- entities.ts: list/create/bulkCreate/delete + Zod 스키마
- claims.ts: list/create/delete + Zod 스키마 (passthrough)

TanStack Query 훅 (src/hooks/):
- useEntities.ts: useEntities, useCreateEntity, useBulkCreateEntities, useDeleteEntity
- useClaims.ts: useClaims, useCreateClaim, useDeleteClaim
- queryKeys에 entities.list, claims.list 키 팩토리

UI 프리미티브 (src/components/ui/):
- tabs.tsx: Tabs, TabsList, TabsTrigger, TabsContent (Context API 기반)

OntologyEditorPage 신규 (src/pages/):
- 3개 탭 구조:
  * 엔티티 탭: 도메인의 entity_types에서 타입 선택 + 이름 입력 → 추가
    + 엔티티 목록 (max-h scroll, 타입 배지, 삭제 버튼)
  * 클레임 탭: 소스/주어/술어/목적어(엔티티 or 리터럴)/신뢰도 입력
    + 클레임 목록 (S-P-O 시각화, 신뢰도, status 배지)
  * JSON 일괄 탭: textarea에 { entities: [...] } 붙여넣기 → 파싱 → bulkCreate
- react-hook-form + zod 검증
- useOntology(domain)으로 entity_types/predicates 자동 로드
- 삭제 confirm 대화상자, sonner 토스트

라우팅 & Sidebar:
- App.tsx: /editor/:projectId 라우트 추가
- AppShell: 사이드바에 "온톨로지 편집" 메뉴 (Network 아이콘)

i18n: editor.*, nav.editor 키 (한/영)

UI_REBUILD_PLAN.md 업데이트:
- Phase 1.4 `00786a4` 커밋 기록
- Phase 1.5 완료 표시 + 대기 보드 Phase 2/3 재정렬

다음 단계: Phase 2 — 그래프 시각화/편집 (Cytoscape React 래퍼)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-14 19:10:37 +09:00

1504 lines
64 KiB
Python

from __future__ import annotations
from dataclasses import asdict
from typing import Any
from fastapi import BackgroundTasks, HTTPException
from pydantic import BaseModel, Field
from sqlalchemy import select
from crawler_platform.app.config.loader import (
ProjectConfig,
SourceConfig,
load_project_config,
project_config_from_dict,
)
from crawler_platform.app.core.crawler.discovery import discover_links
from crawler_platform.app.core.crawler.fetchers import RobotsPolicy, make_fetcher
from crawler_platform.app.core.crawler.pipeline import CrawlPipeline
from crawler_platform.app.core.crawler.site_crawler import SiteCrawler
from crawler_platform.app.core.database import models
from crawler_platform.app.core.database.repository import (
KnowledgeRepository,
make_claim_hash,
)
from crawler_platform.app.core.database.session import session_scope
from crawler_platform.app.core.extractor.ai_provider import list_openai_compatible_models
from crawler_platform.app.core.extractor.factory import extractor_for_domain
from crawler_platform.app.core.ontology.definitions import DOMAIN_ONTOLOGIES, ontology_for_domain
from crawler_platform.app.core.ontology.gap_detector import KnowledgeGapDetector
from crawler_platform.app.core.ontology.mapper import ontology_to_dict
from crawler_platform.app.core.ontology.registry import OntologyRegistry
from crawler_platform.app.core.recommendation.scorer import PreferenceInput, RuleBasedRecommender
from crawler_platform.app.core.research.graph_query import SemanticGraphQuery
from crawler_platform.app.core.research.graph_research_loop import GraphResearchLoop
from crawler_platform.app.core.research.memory_store import ResearchMemoryStore, research_session_payload
class CrawlRequest(BaseModel):
config_path: str
source_name: str
url: str
extractor_provider: str = "lm_studio"
extractor_model: str | None = None
extractor_base_url: str | None = "http://localhost:1234/v1"
check_robots_txt: bool = False
respect_robots_txt: bool | None = None
class SiteCrawlRequest(CrawlRequest):
max_depth: int = 2
max_pages: int = 50
same_domain_only: bool = True
analyze_page_types: list[str] = Field(default_factory=lambda: ["ProductPage", "BrandStoryPage", "ReviewPage"])
class SiteCrawlByProjectRequest(BaseModel):
"""Site crawl invoked against an existing project (no filesystem config_path)."""
project_name: str
source_name: str
url: str
extractor_provider: str = "lm_studio"
extractor_model: str | None = None
extractor_base_url: str | None = "http://localhost:1234/v1"
check_robots_txt: bool = False
respect_robots_txt: bool | None = None
max_depth: int = 2
max_pages: int = 50
same_domain_only: bool = True
analyze_page_types: list[str] = Field(
default_factory=lambda: ["ProductPage", "BrandStoryPage", "ReviewPage"]
)
def to_site_crawl_request(self, config_path_placeholder: str = "") -> "SiteCrawlRequest":
"""For internal handoff to existing crawl pipeline (config_path is not used)."""
return SiteCrawlRequest(
config_path=config_path_placeholder,
source_name=self.source_name,
url=self.url,
extractor_provider=self.extractor_provider,
extractor_model=self.extractor_model,
extractor_base_url=self.extractor_base_url,
check_robots_txt=self.check_robots_txt,
respect_robots_txt=self.respect_robots_txt,
max_depth=self.max_depth,
max_pages=self.max_pages,
same_domain_only=self.same_domain_only,
analyze_page_types=list(self.analyze_page_types),
)
class DiscoverRequest(BaseModel):
config_path: str
source_name: str
url: str
limit: int = 30
check_robots_txt: bool = False
respect_robots_txt: bool | None = None
class RecommendRequest(BaseModel):
project_name: str
target_entity_type: str = "Perfume"
preferences: dict = Field(default_factory=dict)
limit: int = 10
class CreateProjectRequest(BaseModel):
config_path: str
class InlineSourceConfig(BaseModel):
name: str
type: str = "unknown"
trust_level: float = 0.5
base_url: str | None = None
allowed_paths: list[str] = Field(default_factory=list)
parser: str = "generic"
fetcher: str = "requests"
rate_limit_per_minute: int = 30
respect_robots_txt: bool = False
class CreateProjectInlineRequest(BaseModel):
"""Create a project from inline JSON config (no filesystem dependency)."""
project_name: str
domain: str
target_entities: list[str] = Field(default_factory=list)
fields: list[str] = Field(default_factory=list)
sources: list[InlineSourceConfig] = Field(default_factory=list)
ontology: dict[str, Any] = Field(default_factory=dict)
recommendation: dict[str, Any] = Field(default_factory=dict)
update_policy: dict[str, Any] = Field(default_factory=dict)
def to_project_config(self) -> ProjectConfig:
return ProjectConfig(
project_name=self.project_name,
domain=self.domain,
target_entities=list(self.target_entities),
fields=list(self.fields),
sources=[SourceConfig(**s.model_dump()) for s in self.sources],
ontology=dict(self.ontology),
recommendation=dict(self.recommendation),
update_policy=dict(self.update_policy),
)
class ResetProjectRequest(BaseModel):
config_path: str
project_name: str | None = None
class CreateEntityRequest(BaseModel):
entity_type: str
name: str
metadata: dict[str, Any] = Field(default_factory=dict)
class BulkCreateEntitiesRequest(BaseModel):
entities: list[CreateEntityRequest]
class CreateClaimRequest(BaseModel):
source_name: str
subject_entity_id: int
predicate: str
object_entity_id: int | None = None
object_value: Any = None
confidence: float = 1.0
confidence_reason: str | None = None
evidence_text: str | None = None
metadata: dict[str, Any] = Field(default_factory=dict)
class ResearchRunByProjectRequest(BaseModel):
"""Run autonomous research against an existing DB project (no config_path)."""
project_name: str
source_name: str
url: str | None = None
seed_entity_id: int | None = None
goal: str = "Semantic ontology exploration"
extractor_provider: str = "lm_studio"
extractor_model: str | None = None
extractor_base_url: str | None = "http://localhost:1234/v1"
check_robots_txt: bool = False
respect_robots_txt: bool | None = None
max_depth: int = 2
max_steps: int = 12
max_branch: int = 8
min_relevance: float = 0.35
same_domain_only: bool = True
analyze_page_types: list[str] = Field(
default_factory=lambda: ["ProductPage", "BrandStoryPage", "ReviewPage"]
)
class UpdateClaimConfidenceRequest(BaseModel):
confidence: float
reason: str | None = None
class UpdateClaimStatusRequest(BaseModel):
status: str
reason: str | None = None
class BulkClaimStatusRequest(BaseModel):
claim_ids: list[int]
status: str
reason: str | None = None
class MergeEntitiesRequest(BaseModel):
project_name: str
source_entity_id: int
target_entity_id: int
class ExtractorModelsRequest(BaseModel):
provider: str
base_url: str | None = None
class ResearchRunRequest(CrawlRequest):
project_name: str | None = None
seed_entity_id: int | None = None
goal: str = "Semantic ontology exploration"
max_depth: int = 2
max_steps: int = 12
max_branch: int = 8
min_relevance: float = 0.35
same_domain_only: bool = True
analyze_page_types: list[str] = Field(default_factory=lambda: ["ProductPage", "BrandStoryPage", "ReviewPage"])
def site_crawl_progress_payload(result, latest_page=None) -> dict[str, Any]:
payload = asdict(result)
if latest_page is not None:
payload["latest_page"] = asdict(latest_page)
return payload
_CLAIM_STATUS_ALIASES = {
"accept": "validated_claim",
"accepted": "validated_claim",
"validated": "validated_claim",
"validated_claim": "validated_claim",
"reject": "rejected",
"rejected": "rejected",
"active": "active",
"candidate": "active",
"pending": "active",
}
def _normalize_claim_status(value: str | None) -> str | None:
if not value:
return None
return _CLAIM_STATUS_ALIASES.get(value.strip().lower())
def _apply_claim_review(claim: models.Claim, status: str, reason: str | None) -> None:
claim.status = status
if reason:
claim.confidence_reason = reason
metadata = dict(claim.metadata_json or {})
review = dict(metadata.get("review") or {})
review["status"] = status
review["reason"] = reason or review.get("reason")
review["reviewed_at"] = models.utcnow().isoformat()
metadata["review"] = review
claim.metadata_json = metadata
claim.last_seen_at = models.utcnow()
def apply_crawl_request_overrides(config, request: CrawlRequest | DiscoverRequest) -> None:
check_robots_txt = request.respect_robots_txt
if check_robots_txt is None:
check_robots_txt = request.check_robots_txt
config.source_by_name(request.source_name).respect_robots_txt = check_robots_txt
def crawl_job_response(job: models.CrawlJob) -> dict[str, Any]:
metadata = job.metadata_json or {}
return {
"job_id": job.id,
"status": job.status,
"url": job.url,
"error": job.error,
"scheduled_at": job.scheduled_at.isoformat() if job.scheduled_at else None,
"started_at": job.started_at.isoformat() if job.started_at else None,
"finished_at": job.finished_at.isoformat() if job.finished_at else None,
"progress": metadata.get("progress", {}),
"request": metadata.get("request", {}),
}
def update_site_crawl_job_metadata(job: models.CrawlJob, **updates: Any) -> None:
metadata = dict(job.metadata_json or {})
metadata.update(updates)
job.metadata_json = metadata
def is_site_crawl_cancel_requested(session, job_id: int) -> bool:
session.expire_all()
job = session.get(models.CrawlJob, job_id)
return job is None or job.status == "cancel_requested"
def run_site_crawl_job(database_url: str, job_id: int, request_data: dict[str, Any]) -> None:
inline_config = request_data.pop("__config_dict", None)
request = SiteCrawlRequest(**request_data)
try:
if inline_config is not None:
config = project_config_from_dict(inline_config)
else:
config = load_project_config(request.config_path)
apply_crawl_request_overrides(config, request)
with session_scope(database_url) as session:
job = session.get(models.CrawlJob, job_id)
if job is None:
return
if job.status == "cancel_requested":
job.status = "canceled"
job.finished_at = models.utcnow()
return
job.status = "running"
job.started_at = models.utcnow()
update_site_crawl_job_metadata(
job,
progress={
"seed_url": request.url,
"visited_count": 0,
"analyzed_count": 0,
"queued_count": 1,
"skipped_count": 0,
"errors": [],
"pages": [],
},
)
session.commit()
repo = KnowledgeRepository(session)
crawler = SiteCrawler(
repo,
extractor_for_domain(
config.domain,
provider=request.extractor_provider,
model=request.extractor_model,
base_url=request.extractor_base_url,
),
)
def save_progress(result, latest_page) -> None:
current_job = session.get(models.CrawlJob, job_id)
if current_job is None:
return
update_site_crawl_job_metadata(
current_job,
progress=site_crawl_progress_payload(result, latest_page),
)
session.commit()
def should_stop() -> bool:
return is_site_crawl_cancel_requested(session, job_id)
result = crawler.crawl_site(
config,
request.source_name,
request.url,
max_depth=max(request.max_depth, 0),
max_pages=max(min(request.max_pages, 500), 1),
same_domain_only=request.same_domain_only,
analyze_page_types=set(request.analyze_page_types),
progress_callback=save_progress,
should_stop=should_stop,
parent_job_id=job_id,
)
finished_job = session.get(models.CrawlJob, job_id)
if finished_job is not None:
finished_job.status = "canceled" if finished_job.status == "cancel_requested" else "completed"
finished_job.finished_at = models.utcnow()
update_site_crawl_job_metadata(
finished_job,
progress=site_crawl_progress_payload(result),
)
except Exception as exc:
with session_scope(database_url) as session:
job = session.get(models.CrawlJob, job_id)
if job is not None:
job.status = "failed"
job.error = str(exc)
job.finished_at = models.utcnow()
metadata = dict(job.metadata_json or {})
progress = dict(metadata.get("progress") or {})
progress["errors"] = [*progress.get("errors", []), str(exc)]
update_site_crawl_job_metadata(job, progress=progress)
def register_routes(app, database_url: str) -> None:
@app.get("/health")
def health():
return {"ok": True}
@app.get("/projects")
def projects():
with session_scope(database_url) as session:
rows = session.scalars(select(models.Project).order_by(models.Project.created_at.desc())).all()
return [
{
"id": project.id,
"name": project.name,
"domain": project.domain,
"created_at": project.created_at.isoformat(),
"updated_at": project.updated_at.isoformat(),
}
for project in rows
]
@app.post("/projects")
def create_project(request: CreateProjectRequest):
config = load_project_config(request.config_path)
with session_scope(database_url) as session:
project = KnowledgeRepository(session).upsert_project(config)
return {"id": project.id, "name": project.name, "domain": project.domain}
@app.post("/projects/inline")
def create_project_inline(request: CreateProjectInlineRequest):
config = request.to_project_config()
with session_scope(database_url) as session:
project = KnowledgeRepository(session).upsert_project(config)
return {"id": project.id, "name": project.name, "domain": project.domain}
@app.get("/domains")
def list_domains():
"""Available pre-defined ontology domains for project creation."""
return [
{
"domain": ont.domain,
"entity_types": list(ont.entity_types),
"predicates": list(ont.predicates),
"attribute_count": len(ont.attributes),
}
for ont in DOMAIN_ONTOLOGIES.values()
]
@app.post("/projects/reset")
def reset_project(request: ResetProjectRequest):
config = load_project_config(request.config_path)
if request.project_name and request.project_name != config.project_name:
raise HTTPException(
status_code=400,
detail=(
f"Selected project '{request.project_name}' does not match "
f"config project '{config.project_name}'."
),
)
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = session.scalar(select(models.Project).where(models.Project.name == config.project_name))
if project is None:
project = repo.upsert_project(config)
return {
"ok": True,
"name": project.name,
"domain": project.domain,
"created": True,
"reset": False,
"deleted": {},
}
deleted = repo.reset_project_runtime_data(project.id)
project = repo.upsert_project(config)
return {
"ok": True,
"name": project.name,
"domain": project.domain,
"created": False,
"reset": True,
"deleted": deleted,
}
@app.get("/projects/{project_name}")
def project_detail(project_name: str):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
sources = session.scalars(select(models.Source).where(models.Source.project_id == project.id)).all()
return {
"id": project.id,
"name": project.name,
"domain": project.domain,
"config": project.config,
"sources": [
{
"id": source.id,
"name": source.name,
"type": source.type,
"base_url": source.base_url,
"trust_level": source.trust_level,
"respect_robots_txt": source.respect_robots_txt,
"rate_limit_per_minute": source.rate_limit_per_minute,
}
for source in sources
],
}
@app.post("/projects/{project_name}/sources")
def add_project_source(project_name: str, request: InlineSourceConfig):
"""Add or update a source on an existing project."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
source = repo.upsert_source(project, SourceConfig(**request.model_dump()))
return {
"id": source.id,
"name": source.name,
"type": source.type,
"base_url": source.base_url,
"trust_level": source.trust_level,
"respect_robots_txt": source.respect_robots_txt,
"rate_limit_per_minute": source.rate_limit_per_minute,
}
@app.delete("/projects/{project_name}/sources/{source_name}")
def delete_project_source(project_name: str, source_name: str):
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
source = session.scalar(
select(models.Source).where(
models.Source.project_id == project.id,
models.Source.name == source_name,
)
)
if source is None:
raise HTTPException(
status_code=404,
detail=f"Source '{source_name}' not found in project '{project_name}'",
)
session.delete(source)
return {"ok": True, "deleted": source_name}
@app.get("/ontology/{domain}")
def ontology(domain: str):
return ontology_to_dict(ontology_for_domain(domain))
@app.get("/projects/{project_name}/ontology/registry")
def ontology_registry(project_name: str):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
return OntologyRegistry(session).registry_payload(project.id)
@app.get("/projects/{project_name}/ontology/proposals")
def ontology_proposals(project_name: str, limit: int = 100):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
rows = session.scalars(
select(models.OntologyProposal)
.where(models.OntologyProposal.project_id == project.id)
.order_by(models.OntologyProposal.updated_at.desc())
.limit(max(min(limit, 300), 1))
).all()
return [
{
"id": row.id,
"proposal_type": row.proposal_type,
"name": row.name,
"reason": row.reason,
"evidence": row.evidence,
"status": row.status,
"confidence": row.confidence,
"metadata": row.metadata_json or {},
"updated_at": row.updated_at.isoformat() if row.updated_at else None,
}
for row in rows
]
@app.get("/projects/{project_name}/ontology/triples")
def ontology_triples(project_name: str, status: str | None = None, limit: int = 100):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
query = select(models.OntologyTriple).where(models.OntologyTriple.project_id == project.id)
if status:
query = query.where(models.OntologyTriple.status == status)
rows = session.scalars(
query.order_by(models.OntologyTriple.last_seen_at.desc()).limit(max(min(limit, 300), 1))
).all()
results = []
for row in rows:
subject = session.get(models.Entity, row.subject_entity_id)
object_entity = session.get(models.Entity, row.object_entity_id) if row.object_entity_id else None
results.append(
{
"id": row.id,
"claim_id": row.claim_id,
"subject": subject.name if subject else None,
"subject_type": row.subject_type,
"predicate": row.predicate,
"object": object_entity.name if object_entity else None,
"object_type": row.object_type,
"object_value": row.object_value,
"value_type": row.value_type,
"status": row.status,
"confidence": row.confidence,
"support_count": row.support_count,
"metadata": row.metadata_json or {},
"last_seen_at": row.last_seen_at.isoformat() if row.last_seen_at else None,
}
)
return results
@app.get("/projects/{project_name}/knowledge-gaps")
def knowledge_gaps(project_name: str, limit: int = 100):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
return KnowledgeGapDetector(session).list_open(project.id, max(min(limit, 300), 1))
@app.post("/extractors/models")
def extractor_models(request: ExtractorModelsRequest):
try:
if request.provider == "lm_studio":
models = list_openai_compatible_models(request.base_url or "http://localhost:1234/v1")
return {"ok": True, "models": models}
if request.provider == "openai":
import os
models = list_openai_compatible_models(
request.base_url or "https://api.openai.com/v1",
os.getenv("OPENAI_API_KEY"),
)
return {"ok": True, "models": models}
if request.provider == "ollama":
return {"ok": False, "error": "Ollama model listing is not implemented yet. Enter the model manually."}
return {"ok": True, "models": [{"id": "rule_based", "owned_by": "local"}]}
except Exception as exc:
return {"ok": False, "error": str(exc), "models": []}
@app.post("/crawl")
def crawl(request: CrawlRequest):
config = load_project_config(request.config_path)
apply_crawl_request_overrides(config, request)
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
pipeline = CrawlPipeline(
repo,
extractor_for_domain(
config.domain,
provider=request.extractor_provider,
model=request.extractor_model,
base_url=request.extractor_base_url,
),
)
try:
result = pipeline.crawl_url(config, request.source_name, request.url)
except Exception as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
return {
"page_id": result.page_id,
"claim_count": result.claim_count,
"entity_count": result.entity_count,
"crawl_status": result.crawl_status,
"extraction_status": result.extraction_status,
"page_type": result.page_type,
"raw_text_length": result.raw_text_length,
"clean_text_length": result.clean_text_length,
"warnings": result.warnings or [],
}
@app.post("/crawl-site")
def crawl_site(request: SiteCrawlRequest, background_tasks: BackgroundTasks):
config = load_project_config(request.config_path)
apply_crawl_request_overrides(config, request)
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.upsert_project(config)
source = repo.get_source(project.id, request.source_name)
job = models.CrawlJob(
project_id=project.id,
source_id=source.id,
url=request.url,
status="pending",
metadata_json={
"kind": "site_crawl",
"request": request.model_dump(),
"progress": {
"seed_url": request.url,
"visited_count": 0,
"analyzed_count": 0,
"queued_count": 1,
"skipped_count": 0,
"errors": [],
"pages": [],
},
},
)
session.add(job)
session.flush()
response = crawl_job_response(job)
background_tasks.add_task(run_site_crawl_job, database_url, response["job_id"], request.model_dump())
return response
@app.post("/crawl-site/by-project")
def crawl_site_by_project(
request: SiteCrawlByProjectRequest, background_tasks: BackgroundTasks
):
"""Start a site crawl against an existing DB project (no config_path)."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(request.project_name)
config_dict = project.config or {}
if not config_dict:
raise HTTPException(
status_code=400,
detail=f"Project '{request.project_name}' has no stored config",
)
config = project_config_from_dict(config_dict)
try:
source = repo.get_source(project.id, request.source_name)
except KeyError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
inner_request = request.to_site_crawl_request()
apply_crawl_request_overrides(config, inner_request)
job = models.CrawlJob(
project_id=project.id,
source_id=source.id,
url=request.url,
status="pending",
metadata_json={
"kind": "site_crawl",
"request": inner_request.model_dump(),
"project_name": request.project_name,
"progress": {
"seed_url": request.url,
"visited_count": 0,
"analyzed_count": 0,
"queued_count": 1,
"skipped_count": 0,
"errors": [],
"pages": [],
},
},
)
session.add(job)
session.flush()
response = crawl_job_response(job)
task_payload = {**inner_request.model_dump(), "__config_dict": config_dict}
background_tasks.add_task(
run_site_crawl_job, database_url, response["job_id"], task_payload
)
return response
@app.get("/crawl-site/jobs/{job_id}")
def crawl_site_job(job_id: int):
with session_scope(database_url) as session:
job = session.get(models.CrawlJob, job_id)
if job is None or (job.metadata_json or {}).get("kind") != "site_crawl":
raise HTTPException(status_code=404, detail="site crawl job not found")
return crawl_job_response(job)
@app.post("/crawl-site/jobs/{job_id}/cancel")
def cancel_crawl_site_job(job_id: int):
with session_scope(database_url) as session:
job = session.get(models.CrawlJob, job_id)
if job is None or (job.metadata_json or {}).get("kind") != "site_crawl":
raise HTTPException(status_code=404, detail="site crawl job not found")
if job.status in {"completed", "failed", "canceled"}:
return crawl_job_response(job)
job.status = "cancel_requested"
job.error = "cancel requested by user"
return crawl_job_response(job)
@app.post("/discover")
def discover(request: DiscoverRequest):
config = load_project_config(request.config_path)
apply_crawl_request_overrides(config, request)
source_config = config.source_by_name(request.source_name)
robots = RobotsPolicy()
robots_decision = robots.check(request.url, source_config.respect_robots_txt)
if not robots_decision.allowed:
return {
"ok": False,
"error": f"{robots_decision.reason}: {request.url}",
"robots_status": robots_decision.status,
"robots_reason": robots_decision.reason,
"links": [],
}
fetcher = make_fetcher(source_config.fetcher, source_config.rate_limit_per_minute)
result = fetcher.fetch(request.url)
links = discover_links(result.analysis_html, result.final_url or request.url, request.limit)
return {
"ok": True,
"status_code": result.status_code,
"final_url": result.final_url,
"crawl_status": result.crawl_status,
"robots_status": robots_decision.status,
"robots_reason": robots_decision.reason,
"warnings": result.warnings,
"links": [asdict(link) for link in links],
}
@app.post("/research/run")
def run_research(request: ResearchRunRequest):
config = load_project_config(request.config_path)
apply_crawl_request_overrides(config, request)
if request.project_name and request.project_name != config.project_name:
raise HTTPException(
status_code=400,
detail=f"Selected project '{request.project_name}' does not match config project '{config.project_name}'.",
)
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
loop = GraphResearchLoop(
repo,
extractor_for_domain(
config.domain,
provider=request.extractor_provider,
model=request.extractor_model,
base_url=request.extractor_base_url,
),
)
try:
result = loop.run(
project_config=config,
source_name=request.source_name,
seed_url=request.url or None,
seed_entity_id=request.seed_entity_id,
goal=request.goal,
max_depth=max(request.max_depth, 0),
max_steps=max(min(request.max_steps, 50), 1),
max_branch=max(min(request.max_branch, 30), 1),
min_relevance=min(max(request.min_relevance, 0.0), 1.0),
same_domain_only=request.same_domain_only,
analyze_page_types=set(request.analyze_page_types),
)
except Exception as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
return asdict(result)
@app.post("/research/run/by-project")
def run_research_by_project(request: ResearchRunByProjectRequest):
"""Run research against an existing DB project (no config_path)."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(request.project_name)
config_dict = project.config or {}
if not config_dict:
raise HTTPException(
status_code=400,
detail=f"Project '{request.project_name}' has no stored config",
)
config = project_config_from_dict(config_dict)
try:
source_config = config.source_by_name(request.source_name)
except KeyError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
check_robots = request.respect_robots_txt
if check_robots is None:
check_robots = request.check_robots_txt
source_config.respect_robots_txt = check_robots
loop = GraphResearchLoop(
repo,
extractor_for_domain(
config.domain,
provider=request.extractor_provider,
model=request.extractor_model,
base_url=request.extractor_base_url,
),
)
try:
result = loop.run(
project_config=config,
source_name=request.source_name,
seed_url=request.url or None,
seed_entity_id=request.seed_entity_id,
goal=request.goal,
max_depth=max(request.max_depth, 0),
max_steps=max(min(request.max_steps, 50), 1),
max_branch=max(min(request.max_branch, 30), 1),
min_relevance=min(max(request.min_relevance, 0.0), 1.0),
same_domain_only=request.same_domain_only,
analyze_page_types=set(request.analyze_page_types),
)
except Exception as exc:
raise HTTPException(status_code=400, detail=str(exc)) from exc
return asdict(result)
@app.get("/projects/{project_name}/research/sessions")
def research_sessions(project_name: str, limit: int = 25):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
return ResearchMemoryStore(session).list_sessions(project.id, limit)
@app.get("/research/sessions/{job_id}")
def research_session(job_id: int):
with session_scope(database_url) as session:
job = session.get(models.CrawlJob, job_id)
if job is None or (job.metadata_json or {}).get("kind") != "research_session":
raise HTTPException(status_code=404, detail="research session not found")
return research_session_payload(job)
@app.get("/projects/{project_name}/graph/neighborhood")
def graph_neighborhood(project_name: str, entity_id: int | None = None, limit: int = 120):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
return SemanticGraphQuery(session).neighborhood(project.id, entity_id, max(min(limit, 300), 1))
@app.get("/projects/{project_name}/graph/query")
def graph_query(
project_name: str,
kind: str = "trend_summary",
predicate: str = "hasAccord",
tag: str | None = None,
brand: str | None = None,
limit: int = 100,
):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
graph = SemanticGraphQuery(session)
bounded_limit = max(min(limit, 300), 1)
if kind == "brand_products":
return graph.brand_products(project.id, brand, bounded_limit)
if kind == "products_by_tag":
return graph.products_by_tag(project.id, predicate, tag, bounded_limit)
if kind == "relation_summary":
return graph.relation_summary(project.id, bounded_limit)
if kind == "entity_type_summary":
return graph.entity_type_summary(project.id, bounded_limit)
if kind == "trend_summary":
return graph.trend_summary(project.id, bounded_limit)
raise HTTPException(status_code=400, detail=f"unknown graph query kind: {kind}")
@app.get("/projects/{project_name}/entities")
def project_entities(project_name: str, entity_type: str | None = None, limit: int = 50):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
query = select(models.Entity).where(models.Entity.project_id == project.id)
if entity_type:
query = query.where(models.Entity.entity_type == entity_type)
entities = session.scalars(query.limit(limit)).all()
return [
{
"id": entity.id,
"type": entity.entity_type,
"name": entity.name,
"metadata": entity.metadata_json,
}
for entity in entities
]
@app.post("/projects/{project_name}/entities")
def create_entity(project_name: str, request: CreateEntityRequest):
"""Create or update a single entity directly (no extraction)."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
entity = repo.upsert_entity(
project_id=project.id,
entity_type=request.entity_type,
name=request.name,
metadata={
**request.metadata,
"input_method": request.metadata.get("input_method", "manual"),
},
)
return {
"id": entity.id,
"type": entity.entity_type,
"name": entity.name,
"metadata": entity.metadata_json,
}
@app.post("/projects/{project_name}/entities/bulk")
def bulk_create_entities(project_name: str, request: BulkCreateEntitiesRequest):
"""Create multiple entities in one call."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
created: list[dict[str, Any]] = []
for item in request.entities:
entity = repo.upsert_entity(
project_id=project.id,
entity_type=item.entity_type,
name=item.name,
metadata={
**item.metadata,
"input_method": item.metadata.get("input_method", "manual"),
},
)
created.append(
{
"id": entity.id,
"type": entity.entity_type,
"name": entity.name,
}
)
return {"created": len(created), "entities": created}
@app.delete("/projects/{project_name}/entities/{entity_id}")
def delete_entity(project_name: str, entity_id: int):
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
entity = session.get(models.Entity, entity_id)
if entity is None or entity.project_id != project.id:
raise HTTPException(
status_code=404,
detail=f"Entity {entity_id} not found in project '{project_name}'",
)
session.delete(entity)
return {"ok": True, "deleted": entity_id}
@app.post("/projects/{project_name}/claims")
def create_claim(project_name: str, request: CreateClaimRequest):
"""Create a single claim directly (manual input)."""
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
try:
source = repo.get_source(project.id, request.source_name)
except KeyError as exc:
raise HTTPException(status_code=404, detail=str(exc)) from exc
subject = session.get(models.Entity, request.subject_entity_id)
if subject is None or subject.project_id != project.id:
raise HTTPException(
status_code=404,
detail=f"Subject entity {request.subject_entity_id} not found",
)
object_entity: models.Entity | None = None
if request.object_entity_id is not None:
object_entity = session.get(models.Entity, request.object_entity_id)
if object_entity is None or object_entity.project_id != project.id:
raise HTTPException(
status_code=404,
detail=f"Object entity {request.object_entity_id} not found",
)
claim_hash = make_claim_hash(
project_id=project.id,
source_id=source.id,
subject_entity_id=subject.id,
predicate=request.predicate,
object_entity_id=object_entity.id if object_entity else None,
object_value=request.object_value,
)
existing = session.scalar(
select(models.Claim).where(
models.Claim.project_id == project.id,
models.Claim.claim_hash == claim_hash,
)
)
if existing is not None:
existing.confidence = max(existing.confidence, request.confidence)
existing.last_seen_at = models.utcnow()
if request.confidence_reason:
existing.confidence_reason = request.confidence_reason
existing.metadata_json = {
**(existing.metadata_json or {}),
**request.metadata,
"input_method": "manual",
}
claim = existing
else:
claim = models.Claim(
project_id=project.id,
source_id=source.id,
page_id=None,
subject_entity_id=subject.id,
predicate=request.predicate,
object_entity_id=object_entity.id if object_entity else None,
object_value=request.object_value,
value_type="entity" if object_entity else "literal",
claim_hash=claim_hash,
confidence=max(0.0, min(1.0, request.confidence)),
confidence_reason=request.confidence_reason,
extraction_method="manual",
status="validated_claim",
metadata_json={**request.metadata, "input_method": "manual"},
)
session.add(claim)
session.flush()
if request.evidence_text:
session.add(
models.Evidence(
project_id=project.id,
claim_id=claim.id,
page_id=None,
evidence_text=request.evidence_text,
)
)
return {
"id": claim.id,
"subject_entity_id": claim.subject_entity_id,
"predicate": claim.predicate,
"object_entity_id": claim.object_entity_id,
"object_value": claim.object_value,
"confidence": claim.confidence,
"status": claim.status,
}
@app.delete("/projects/{project_name}/claims/{claim_id}")
def delete_claim(project_name: str, claim_id: int):
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(project_name)
claim = session.get(models.Claim, claim_id)
if claim is None or claim.project_id != project.id:
raise HTTPException(
status_code=404,
detail=f"Claim {claim_id} not found in project '{project_name}'",
)
session.delete(claim)
return {"ok": True, "deleted": claim_id}
@app.get("/projects/{project_name}/claims")
def project_claims(
project_name: str,
limit: int = 100,
include_candidates: bool = False,
status: str | None = None,
):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
query = (
select(models.Claim, models.Source, models.Page, models.Entity)
.join(models.Source, models.Claim.source_id == models.Source.id)
.join(models.Page, models.Claim.page_id == models.Page.id, isouter=True)
.join(models.Entity, models.Claim.subject_entity_id == models.Entity.id)
.where(models.Claim.project_id == project.id)
)
if status:
normalized = _normalize_claim_status(status)
if normalized is None:
raise HTTPException(status_code=400, detail=f"unknown claim status: {status}")
query = query.where(models.Claim.status == normalized)
elif not include_candidates:
query = query.where(models.Claim.status == "validated_claim")
rows = session.execute(query.order_by(models.Claim.last_seen_at.desc()).limit(limit)).all()
results: list[dict[str, Any]] = []
for claim, source, page, subject in rows:
object_name = None
if claim.object_entity_id:
object_entity = session.get(models.Entity, claim.object_entity_id)
object_name = object_entity.name if object_entity else None
evidence = session.scalar(
select(models.Evidence)
.where(models.Evidence.claim_id == claim.id)
.order_by(models.Evidence.created_at.desc())
)
results.append(
{
"id": claim.id,
"subject": subject.name,
"subject_type": subject.entity_type,
"predicate": claim.predicate,
"object": object_name,
"object_value": claim.object_value,
"source": source.name,
"page_url": page.url if page else None,
"confidence": claim.confidence,
"confidence_reason": claim.confidence_reason,
"status": claim.status,
"evidence_text": evidence.evidence_text if evidence else None,
"evidence_summary": evidence.evidence_summary if evidence else None,
"page_type": (claim.metadata_json or {}).get("page_type")
or ((page.metadata_json or {}).get("page_type") if page else None),
"source_zone": (claim.metadata_json or {}).get("source_zone"),
"source_selector": (claim.metadata_json or {}).get("source_selector"),
"evidence_found": (claim.metadata_json or {}).get("evidence_found"),
"validation_status": (claim.metadata_json or {}).get("validation_status"),
"graph_merge_status": (claim.metadata_json or {}).get("graph_merge_status"),
"graph_merge_reason": (claim.metadata_json or {}).get("graph_merge_reason"),
"confidence_breakdown": (claim.metadata_json or {}).get("confidence_breakdown"),
"review_required": (claim.metadata_json or {}).get("review_required"),
"review_reason": (claim.metadata_json or {}).get("review_reason"),
"conflict_status": (claim.metadata_json or {}).get("conflict_status"),
"source_history": (claim.metadata_json or {}).get("source_history") or [],
"last_seen_at": claim.last_seen_at.isoformat(),
}
)
return results
@app.get("/projects/{project_name}/pipeline")
def project_pipeline(project_name: str):
from sqlalchemy import func as sa_func, distinct
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
pid = project.id
pages_total = session.scalar(
select(sa_func.count(models.Page.id)).where(models.Page.project_id == pid)
) or 0
ext_total = session.scalar(
select(sa_func.count(models.ExtractionLog.id)).where(models.ExtractionLog.project_id == pid)
) or 0
ext_pages = session.scalar(
select(sa_func.count(distinct(models.ExtractionLog.page_id)))
.where(models.ExtractionLog.project_id == pid, models.ExtractionLog.page_id.isnot(None))
) or 0
ext_errors = session.scalar(
select(sa_func.count(models.ExtractionLog.id))
.where(models.ExtractionLog.project_id == pid, models.ExtractionLog.error.isnot(None))
) or 0
status_rows = session.execute(
select(models.Claim.status, sa_func.count(models.Claim.id))
.where(models.Claim.project_id == pid)
.group_by(models.Claim.status)
).all()
claim_statuses = {row[0]: int(row[1]) for row in status_rows}
claim_total = sum(claim_statuses.values())
entity_count = session.scalar(
select(sa_func.count(models.Entity.id)).where(models.Entity.project_id == pid)
) or 0
triple_count = session.scalar(
select(sa_func.count(models.OntologyTriple.id))
.where(models.OntologyTriple.project_id == pid, models.OntologyTriple.status == "active")
) or 0
entity_type_rows = session.execute(
select(models.Entity.entity_type, sa_func.count(models.Entity.id))
.where(models.Entity.project_id == pid)
.group_by(models.Entity.entity_type)
.order_by(sa_func.count(models.Entity.id).desc())
.limit(10)
).all()
recent_pages = session.scalars(
select(models.Page).where(models.Page.project_id == pid)
.order_by(models.Page.fetched_at.desc()).limit(5)
).all()
recent_claims_rows = session.execute(
select(models.Claim, models.Entity)
.join(models.Entity, models.Claim.subject_entity_id == models.Entity.id)
.where(models.Claim.project_id == pid)
.order_by(models.Claim.last_seen_at.desc()).limit(5)
).all()
return {
"stages": [
{"key": "crawled", "count": pages_total},
{"key": "extracted", "count": ext_pages, "extra": {"events": ext_total, "errors": ext_errors}},
{"key": "claims", "count": claim_total, "extra": claim_statuses},
{"key": "validated", "count": claim_statuses.get("validated_claim", 0)},
{"key": "graph", "count": triple_count, "extra": {"entities": entity_count}},
],
"entity_types": [{"type": row[0], "count": int(row[1])} for row in entity_type_rows],
"recent_pages": [
{
"id": p.id,
"url": p.url,
"title": p.title,
"status_code": p.status_code,
"page_type": (p.metadata_json or {}).get("page_type"),
"fetched_at": p.fetched_at.isoformat() if p.fetched_at else None,
}
for p in recent_pages
],
"recent_claims": [
{
"id": claim.id,
"subject": subject.name,
"predicate": claim.predicate,
"confidence": claim.confidence,
"status": claim.status,
"last_seen_at": claim.last_seen_at.isoformat() if claim.last_seen_at else None,
}
for claim, subject in recent_claims_rows
],
}
@app.get("/projects/{project_name}/search")
def project_search(project_name: str, q: str = "", limit: int = 10):
q = (q or "").strip()
if len(q) < 1:
return {"entities": [], "claims": [], "pages": [], "predicates": []}
like = f"%{q.lower()}%"
bounded = max(min(limit, 50), 1)
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
pid = project.id
from sqlalchemy import func as sa_func, or_
entity_rows = session.scalars(
select(models.Entity)
.where(
models.Entity.project_id == pid,
or_(
sa_func.lower(models.Entity.name).like(like),
sa_func.lower(models.Entity.canonical_name).like(like),
),
)
.limit(bounded)
).all()
claim_rows = session.execute(
select(models.Claim, models.Entity)
.join(models.Entity, models.Claim.subject_entity_id == models.Entity.id)
.where(
models.Claim.project_id == pid,
or_(
sa_func.lower(models.Entity.name).like(like),
sa_func.lower(models.Claim.predicate).like(like),
),
)
.order_by(models.Claim.last_seen_at.desc())
.limit(bounded)
).all()
page_rows = session.scalars(
select(models.Page)
.where(
models.Page.project_id == pid,
or_(
sa_func.lower(models.Page.url).like(like),
sa_func.lower(models.Page.title).like(like),
),
)
.order_by(models.Page.fetched_at.desc())
.limit(bounded)
).all()
predicate_rows = session.scalars(
select(models.OntologyRelationType.name)
.where(
models.OntologyRelationType.project_id == pid,
sa_func.lower(models.OntologyRelationType.name).like(like),
)
.limit(bounded)
).all()
return {
"entities": [
{"id": e.id, "name": e.name, "type": e.entity_type, "canonical_name": e.canonical_name}
for e in entity_rows
],
"claims": [
{
"id": claim.id,
"subject": subject.name,
"predicate": claim.predicate,
"object_value": claim.object_value,
"confidence": claim.confidence,
"status": claim.status,
}
for claim, subject in claim_rows
],
"pages": [
{"id": p.id, "url": p.url, "title": p.title}
for p in page_rows
],
"predicates": list(predicate_rows),
}
@app.get("/projects/{project_name}/extraction-logs")
def project_extraction_logs(project_name: str, limit: int = 50):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
rows = session.execute(
select(models.ExtractionLog, models.Page)
.join(models.Page, models.ExtractionLog.page_id == models.Page.id, isouter=True)
.where(models.ExtractionLog.project_id == project.id)
.order_by(models.ExtractionLog.created_at.desc())
.limit(limit)
).all()
return [
{
"id": log.id,
"page_url": page.url if page else None,
"extractor_name": log.extractor_name,
"provider": log.provider,
"error": log.error,
"created_at": log.created_at.isoformat(),
"validation": (log.raw_output or {}).get("validation"),
"page_context": (log.raw_output or {}).get("page_context"),
"candidate_count": len((log.raw_output or {}).get("candidate_claims") or []),
"raw_output": log.raw_output,
}
for log, page in rows
]
@app.patch("/claims/{claim_id}/confidence")
def update_claim_confidence(claim_id: int, request: UpdateClaimConfidenceRequest):
confidence = min(max(request.confidence, 0.0), 1.0)
with session_scope(database_url) as session:
claim = session.get(models.Claim, claim_id)
if claim is None:
return {"ok": False, "error": "claim not found"}
claim.confidence = confidence
claim.confidence_reason = request.reason or "manual admin update"
claim.last_seen_at = models.utcnow()
return {"ok": True, "claim_id": claim.id, "confidence": claim.confidence}
@app.patch("/claims/{claim_id}/status")
def update_claim_status(claim_id: int, request: UpdateClaimStatusRequest):
status = _normalize_claim_status(request.status)
if status is None:
raise HTTPException(status_code=400, detail=f"unknown claim status: {request.status}")
with session_scope(database_url) as session:
claim = session.get(models.Claim, claim_id)
if claim is None:
raise HTTPException(status_code=404, detail="claim not found")
_apply_claim_review(claim, status, request.reason)
return {"ok": True, "claim_id": claim.id, "status": claim.status}
@app.post("/claims/bulk-status")
def bulk_update_claim_status(request: BulkClaimStatusRequest):
status = _normalize_claim_status(request.status)
if status is None:
raise HTTPException(status_code=400, detail=f"unknown claim status: {request.status}")
if not request.claim_ids:
return {"ok": True, "updated": 0}
with session_scope(database_url) as session:
rows = session.execute(
select(models.Claim).where(models.Claim.id.in_(request.claim_ids))
).scalars().all()
for claim in rows:
_apply_claim_review(claim, status, request.reason)
return {"ok": True, "updated": len(rows), "status": status}
@app.post("/entities/merge")
def merge_entities(request: MergeEntitiesRequest):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(request.project_name)
source = session.get(models.Entity, request.source_entity_id)
target = session.get(models.Entity, request.target_entity_id)
if source is None or target is None or source.project_id != project.id or target.project_id != project.id:
return {"ok": False, "error": "entity not found in project"}
session.query(models.Claim).filter(models.Claim.subject_entity_id == source.id).update(
{models.Claim.subject_entity_id: target.id}
)
session.query(models.Claim).filter(models.Claim.object_entity_id == source.id).update(
{models.Claim.object_entity_id: target.id}
)
session.query(models.Relation).filter(models.Relation.subject_entity_id == source.id).update(
{models.Relation.subject_entity_id: target.id}
)
session.query(models.Relation).filter(models.Relation.object_entity_id == source.id).update(
{models.Relation.object_entity_id: target.id}
)
source.metadata_json = {**(source.metadata_json or {}), "merged_into": target.id}
source.updated_at = models.utcnow()
return {"ok": True, "source_entity_id": source.id, "target_entity_id": target.id}
@app.get("/projects/{project_name}/recommendation-tags")
def recommendation_tags(project_name: str):
with session_scope(database_url) as session:
project = KnowledgeRepository(session).get_project(project_name)
tag_predicates = {
"hasTopNote",
"hasMiddleNote",
"hasBaseNote",
"hasScentNote",
"hasFlavorNote",
"evokesMood",
"suitableForSeason",
"suitableForOccasion",
"hasReviewKeyword",
}
rows = session.execute(
select(models.Claim, models.Entity)
.join(models.Entity, models.Claim.object_entity_id == models.Entity.id)
.where(
models.Claim.project_id == project.id,
models.Claim.status == "validated_claim",
models.Claim.predicate.in_(tag_predicates),
)
).all()
grouped: dict[str, dict[str, Any]] = {}
for claim, entity in rows:
key = f"{claim.predicate}:{entity.canonical_name}"
if key not in grouped:
grouped[key] = {
"predicate": claim.predicate,
"name": entity.name,
"type": entity.entity_type,
"support_count": 0,
"max_confidence": 0.0,
}
grouped[key]["support_count"] += 1
grouped[key]["max_confidence"] = max(grouped[key]["max_confidence"], claim.confidence)
return sorted(grouped.values(), key=lambda item: (item["predicate"], -item["support_count"], item["name"]))
@app.post("/recommend")
def recommend(request: RecommendRequest):
with session_scope(database_url) as session:
repo = KnowledgeRepository(session)
project = repo.get_project(request.project_name)
recommender = RuleBasedRecommender(session)
pref = PreferenceInput(**request.preferences)
items = recommender.recommend(project.id, request.target_entity_type, pref, request.limit)
return [asdict(item) for item in items]