Add scoped Agent-mode pipeline as experimental Classic fork.
Wire specialist waves, Brain consolidation, and Classic-compatible reports so Agent mode can run end-to-end via OpenRouter without changing the default Classic path. Co-authored-by: Cursor <cursoragent@cursor.com>
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Cursor
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"""Bounded semantic linkers that build coordination clusters."""
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import json
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import re
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from collections import defaultdict
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from typing import Dict, Iterable, List, Tuple
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from backend import config
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from backend.agents.base import AgentResult, AgentScope, AgentUsage, failure
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from backend.llm import call_json
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from backend.pipeline.clusterer import cluster_by_location
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from backend.pipeline.llm_clusterer import _location
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from backend.prompts import CLUSTER_SYSTEM_PROMPT, CLUSTER_USER_INSTRUCTION
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def _family(assertion: Dict) -> str:
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location = assertion.get("location_key") or {}
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if location.get("room"):
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return "room"
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if location.get("grid"):
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return "grid"
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if location.get("detail_reference"):
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return "detail"
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tag = str(location.get("tag") or "")
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match = re.match(r"[A-Za-z]+", tag)
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return (
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(match.group(0).lower() if match else "")
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or (assertion.get("object_type") or "").lower()
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or "general"
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)
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def build_link_scopes(sheets: List[Dict]) -> List[AgentScope]:
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"""Partition facts by level and object/tag family, then enforce a hard cap."""
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buckets: Dict[Tuple[str, str], List[Dict]] = defaultdict(list)
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for sheet in sheets:
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for assertion in sheet.get("assertions", []):
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enriched = {
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**assertion,
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"discipline": sheet.get("discipline") or "Unknown",
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"sheet_number": sheet.get("sheet_number"),
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"page_number": sheet.get("page_number"),
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}
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level = str((assertion.get("location_key") or {}).get("level")
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or sheet.get("level") or "unknown").lower()
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buckets[(level, _family(assertion))].append(enriched)
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scopes: List[AgentScope] = []
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cap = max(2, config.AGENT_LINK_MAX_ASSERTIONS)
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for (level, family), assertions in sorted(buckets.items()):
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for offset in range(0, len(assertions), cap):
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chunk = assertions[offset:offset + cap]
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if len(chunk) < 2:
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continue
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scopes.append(AgentScope(
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scope_id=f"{level}:{family}:{offset // cap + 1}",
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payload={"assertions": chunk, "level": level, "family": family},
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))
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return scopes
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def _payload(assertions: Iterable[Dict]) -> List[Dict]:
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return [{
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"assertion_id": item.get("id"),
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"discipline": item.get("discipline"),
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"sheet_number": item.get("sheet_number"),
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"attribute": item.get("attribute"),
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"value": item.get("value"),
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"location_key": item.get("location_key"),
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"source_text": item.get("source_text"),
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} for item in assertions]
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def _fallback(assertions: List[Dict]) -> List[Dict]:
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"""Use the deterministic linker within this scope when semantic linking fails."""
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by_sheet: Dict[Tuple, Dict] = {}
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for item in assertions:
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key = (item.get("sheet_number"), item.get("page_number"))
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sheet = by_sheet.setdefault(key, {
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"sheet_number": item.get("sheet_number"),
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"page_number": item.get("page_number"),
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"discipline": item.get("discipline"),
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"assertions": [],
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})
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sheet["assertions"].append(item)
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return cluster_by_location(list(by_sheet.values()))
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class LinkerAgent:
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name = "linker"
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def __init__(self, usage: AgentUsage) -> None:
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self.usage = usage
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def run(self, scope: AgentScope) -> AgentResult:
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try:
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assertions = scope.payload.get("assertions") or []
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by_id = {item.get("id"): item for item in assertions if item.get("id")}
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instruction = CLUSTER_USER_INSTRUCTION.replace(
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"{normalized_assertions}",
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json.dumps(_payload(assertions), ensure_ascii=True),
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)
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parsed = call_json(
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system_prompt=CLUSTER_SYSTEM_PROMPT,
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user_text=instruction,
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max_tokens=config.CLUSTER_MAX_TOKENS,
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model=config.AGENT_LINKER_MODEL,
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usage_tracker=self.usage,
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usage_stage="agent.link",
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)
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raw = parsed if isinstance(parsed, list) else (
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parsed.get("clusters") if isinstance(parsed, dict) else []
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)
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clusters: List[Dict] = []
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for candidate in raw or []:
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if not isinstance(candidate, dict):
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continue
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members = [
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by_id[item_id]
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for item_id in candidate.get("assertion_ids") or []
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if item_id in by_id
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]
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if len(members) < 2:
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continue
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allowed_sheets = []
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for member in members:
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sheet = member.get("sheet_number")
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if sheet not in allowed_sheets:
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allowed_sheets.append(sheet)
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allowed_sheets = allowed_sheets[:config.AGENT_CONFLICT_MAX_IMAGES]
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members = [
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member for member in members
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if member.get("sheet_number") in allowed_sheets
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][:config.AGENT_CLUSTER_MAX_ASSERTIONS]
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primary = candidate.get("primary_location_key") or {}
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clusters.append({
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"key": f"{scope.scope_id}:{candidate.get('cluster_id') or len(clusters) + 1}",
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"location": _location(primary),
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"disciplines": sorted({
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member.get("discipline") or "Unknown" for member in members
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}),
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"page_numbers": sorted({
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member["page_number"] for member in members
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if member.get("page_number")
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}),
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"sheets": sorted({
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member["sheet_number"] for member in members
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if member.get("sheet_number")
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}),
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"assertions": members,
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"kind": "agent_semantic",
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"scope_id": scope.scope_id,
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})
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if not clusters:
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clusters = _fallback(assertions)
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for cluster in clusters:
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cluster["scope_id"] = scope.scope_id
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cluster["kind"] = "agent_deterministic"
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return AgentResult(scope_id=scope.scope_id, artifacts=clusters)
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except Exception as exc:
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return failure(scope, exc)
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def build_object_graph(clusters: List[Dict]) -> Dict:
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"""Build a deterministic graph view from linker output."""
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nodes = []
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edges = []
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seen = set()
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for cluster in clusters:
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cluster_id = cluster.get("key")
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nodes.append({
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"id": cluster_id,
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"type": "cluster",
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"location": cluster.get("location"),
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"sheets": cluster.get("sheets") or [],
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})
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for assertion in cluster.get("assertions") or []:
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assertion_id = assertion.get("id")
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if not assertion_id:
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continue
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if assertion_id not in seen:
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seen.add(assertion_id)
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nodes.append({
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"id": assertion_id,
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"type": assertion.get("object_type") or "assertion",
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"sheet": assertion.get("sheet_number"),
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})
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edges.append({
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"source": assertion_id,
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"target": cluster_id,
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"relationship": "member_of",
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})
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return {"nodes": nodes, "edges": edges}
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