File size: 11,507 Bytes
fcacf10 bab270b fcacf10 302a2fd ca2b2b6 fcacf10 ca2b2b6 302a2fd fcacf10 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 31cf797 ca2b2b6 fcacf10 bab270b fcacf10 5c6742c fcacf10 5c6742c fcacf10 bab270b fcacf10 5c6742c fcacf10 5c6742c bab270b 5c6742c fcacf10 b8bddd1 fcacf10 b8bddd1 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 | from __future__ import annotations
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy.orm import Session, joinedload, subqueryload
from app.core.dependencies import get_current_user
from app.database.session import get_db
from app.models.knowledge_item import KnowledgeItem, KnowledgeStatus, KnowledgeType
from app.models.user import User
from app.models.workspace import Workspace
router = APIRouter(
prefix="/knowledge",
tags=["Knowledge"],
)
def _knowledge_response(item: KnowledgeItem) -> dict:
dv = item.document_version
evidence_list = []
for ev in (item.evidence or []):
evidence_list.append({
"quote": ev.quote,
"page_number": ev.page_number,
"section": ev.section,
"confidence": ev.confidence,
"source_type": ev.source_type,
})
# Include the most recent proposal info for governance context
proposal_info = None
if item.proposals:
# Get the most recent proposal (by created_at or just first)
latest_proposal = sorted(
item.proposals,
key=lambda p: p.created_at or "",
reverse=True,
)[0]
proposal_info = {
"id": str(latest_proposal.id),
"status": latest_proposal.status.value,
"proposal_type": latest_proposal.proposal_type.value,
}
return {
"id": str(item.id),
"workspace_id": str(item.workspace_id),
"document_version_id": str(item.document_version_id),
"filename": dv.filename if dv else None,
"type": item.type.value,
"title": item.title,
"value": item.value,
"summary": item.summary,
"attributes": item.attributes,
"confidence": item.confidence,
"status": item.status.value,
"proposal": proposal_info,
"evidence": evidence_list,
"created_at": item.created_at,
"updated_at": item.updated_at,
}
@router.get("")
def list_knowledge(
workspace_id: UUID,
status: str | None = None,
type: str | None = None,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db),
):
workspace = (
db.query(Workspace)
.filter(
Workspace.id == workspace_id,
Workspace.created_by == current_user.id,
)
.first()
)
if workspace is None:
raise HTTPException(
status_code=403,
detail="You do not have access to this workspace.",
)
query = db.query(KnowledgeItem).filter(
KnowledgeItem.workspace_id == workspace_id,
)
if status:
status_upper = status.upper()
# Special case: "ARCHIVED" means knowledge items whose proposal
# has been archived or the knowledge item itself is marked ARCHIVED.
if status_upper == "ARCHIVED":
from app.models.proposal import Proposal, ProposalStatus
from sqlalchemy import select
archived_ki_ids = (
select(Proposal.knowledge_item_id)
.filter(
Proposal.knowledge_item_id.isnot(None),
Proposal.status == ProposalStatus.ARCHIVED,
)
)
query = query.filter(
(KnowledgeItem.status == KnowledgeStatus.ARCHIVED)
| KnowledgeItem.id.in_(archived_ki_ids)
)
elif status_upper == "PENDING":
# PENDING means genuinely untouched — PENDING knowledge with
# a PENDING proposal (not archived, not decided).
from app.models.proposal import Proposal, ProposalStatus
from sqlalchemy import select
archived_or_rejected_ki_ids = (
select(Proposal.knowledge_item_id)
.filter(
Proposal.knowledge_item_id.isnot(None),
Proposal.status.in_([ProposalStatus.ARCHIVED, ProposalStatus.REJECTED]),
)
)
query = query.filter(
KnowledgeItem.status == KnowledgeStatus.PENDING,
~KnowledgeItem.id.in_(archived_or_rejected_ki_ids),
)
else:
try:
ks = KnowledgeStatus(status_upper)
query = query.filter(KnowledgeItem.status == ks)
except ValueError:
pass
if type:
try:
kt = KnowledgeType(type.upper())
query = query.filter(KnowledgeItem.type == kt)
except ValueError:
pass
items = (
query
.options(
joinedload(KnowledgeItem.document_version), # 1 JOIN — gets filename
subqueryload(KnowledgeItem.evidence), # 1 extra query for all evidence
subqueryload(KnowledgeItem.proposals), # 1 extra query for all proposals
)
.order_by(KnowledgeItem.created_at.desc())
.limit(200)
.all()
)
return [_knowledge_response(i) for i in items]
@router.get("/search")
def search_knowledge(
workspace_id: UUID,
q: str,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db),
):
"""
Hybrid search: lexical (ILIKE) + vector (pgvector cosine similarity),
merged with Reciprocal Rank Fusion (RRF).
"""
workspace = (
db.query(Workspace)
.filter(
Workspace.id == workspace_id,
Workspace.created_by == current_user.id,
)
.first()
)
if workspace is None:
raise HTTPException(
status_code=403,
detail="You do not have access to this workspace.",
)
# --- Lexical search (substring match on title/value/summary) ---
lexical_items = (
db.query(KnowledgeItem)
.options(
joinedload(KnowledgeItem.document_version),
subqueryload(KnowledgeItem.evidence),
subqueryload(KnowledgeItem.proposals),
)
.filter(
KnowledgeItem.workspace_id == workspace_id,
(
KnowledgeItem.title.ilike(f"%{q}%")
| KnowledgeItem.value.ilike(f"%{q}%")
| KnowledgeItem.summary.ilike(f"%{q}%")
),
)
.order_by(KnowledgeItem.created_at.desc())
.limit(30)
.all()
)
# --- Vector search (embed query, find nearest chunks, map to knowledge items) ---
vector_items = []
try:
from app.services.embedding_service import EmbeddingService
from app.models.document_chunk import DocumentChunk
from app.models.document_version import DocumentVersion
embedding_service = EmbeddingService()
query_embedding = embedding_service.embed(q)
if query_embedding:
# Find nearest chunks in this workspace's documents
nearest_chunks = (
db.query(DocumentChunk)
.join(DocumentVersion, DocumentChunk.document_version_id == DocumentVersion.id)
.filter(
DocumentVersion.document.has(workspace_id=workspace_id),
DocumentChunk.embedding.isnot(None),
)
.order_by(DocumentChunk.embedding.cosine_distance(query_embedding))
.limit(20)
.all()
)
# Map chunks to knowledge items via document_version_id
if nearest_chunks:
version_ids = list({c.document_version_id for c in nearest_chunks})
vector_items = (
db.query(KnowledgeItem)
.options(
joinedload(KnowledgeItem.document_version),
subqueryload(KnowledgeItem.evidence),
subqueryload(KnowledgeItem.proposals),
)
.filter(
KnowledgeItem.workspace_id == workspace_id,
KnowledgeItem.document_version_id.in_(version_ids),
)
.limit(30)
.all()
)
except Exception:
# If vector search fails (model not loaded, etc.), fall back to lexical only
pass
# --- RRF merge (Reciprocal Rank Fusion, k=60) ---
k = 60
scores: dict[str, float] = {}
item_map: dict[str, KnowledgeItem] = {}
# Score lexical results
for rank, item in enumerate(lexical_items):
item_id = str(item.id)
scores[item_id] = scores.get(item_id, 0) + 1.0 / (k + rank + 1)
item_map[item_id] = item
# Score vector results
for rank, item in enumerate(vector_items):
item_id = str(item.id)
scores[item_id] = scores.get(item_id, 0) + 1.0 / (k + rank + 1)
item_map[item_id] = item
# Sort by RRF score descending
ranked_ids = sorted(scores.keys(), key=lambda x: scores[x], reverse=True)
results = [item_map[item_id] for item_id in ranked_ids[:30]]
return [_knowledge_response(i) for i in results]
@router.get("/{item_id}")
def get_knowledge_item(
item_id: UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db),
):
from app.models.proposal import Proposal
from app.models.review import Review
from app.models.commit import Commit
item = db.query(KnowledgeItem).filter(KnowledgeItem.id == item_id).first()
if item is None:
raise HTTPException(status_code=404, detail="Knowledge item not found.")
workspace = (
db.query(Workspace)
.filter(
Workspace.id == item.workspace_id,
Workspace.created_by == current_user.id,
)
.first()
)
if workspace is None:
raise HTTPException(status_code=403, detail="You do not have access to this item.")
# Get proposals related to this knowledge item
proposals = (
db.query(Proposal)
.filter(Proposal.knowledge_item_id == item_id)
.order_by(Proposal.created_at.desc())
.all()
)
history = []
for p in proposals:
entry = {
"type": "proposal",
"proposal_id": str(p.id),
"proposal_type": p.proposal_type.value,
"status": p.status.value,
"summary": p.summary,
"timestamp": p.created_at.isoformat() if p.created_at else None,
}
history.append(entry)
# If proposal was reviewed, add the review event
if p.reviewed_at:
history.append({
"type": "decision",
"proposal_id": str(p.id),
"status": p.status.value,
"timestamp": p.reviewed_at.isoformat(),
})
# If approved, find the commit
if p.status.value == "APPROVED":
commit = (
db.query(Commit)
.filter(Commit.proposal_id == p.id)
.first()
)
if commit:
history.append({
"type": "commit",
"commit_id": str(commit.id),
"message": commit.message,
"timestamp": commit.committed_at.isoformat() if commit.committed_at else None,
})
# Sort history by timestamp
history.sort(key=lambda h: h.get("timestamp") or "", reverse=True)
resp = _knowledge_response(item)
resp["history"] = history
return resp
|