fix: Resolve conflicts in PR #386 for per-agent timeouts and partial committee handling
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@@ -54,6 +54,14 @@ def _proposal_priority_rank(priority: str) -> int:
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def _proposal_order_key(proposal: Any) -> tuple:
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# Handle both object and dict access for compatibility
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if isinstance(proposal, dict):
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return (
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str(proposal.get("source_agent") or "").lower(),
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str(proposal.get("title") or "").lower(),
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str(proposal.get("description") or "").lower(),
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str(proposal.get("action_url") or "").lower(),
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)
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return (
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str(getattr(proposal, "source_agent", "") or "").lower(),
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str(getattr(proposal, "title", "") or "").lower(),
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@@ -62,6 +70,19 @@ def _proposal_order_key(proposal: Any) -> tuple:
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)
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def _get_agent_proposal_timeout_seconds(grounding: Dict[str, Any]) -> float:
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workflow_config = grounding.get("workflow_config", {}) if isinstance(grounding, dict) else {}
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if not isinstance(workflow_config, dict):
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return 4.0
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raw_timeout = workflow_config.get("agent_proposal_timeout_seconds", 4.0)
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try:
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timeout_seconds = float(raw_timeout)
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except (TypeError, ValueError):
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return 4.0
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return max(1.0, timeout_seconds)
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def _fallback_tasks(date: str) -> List[Dict[str, Any]]:
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return [
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{
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@@ -308,39 +329,82 @@ async def generate_agent_enhanced_plan(db: Session, user_id: str, date: str) ->
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logger.info(f"Gathering daily task proposals from agent committee for user {user_id}")
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agent_tasks = []
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committee_total_failure = False
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try:
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# Define agents to poll
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agents_to_poll = [
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orchestrator.agents.get('content'), # ContentStrategyAgent
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orchestrator.agents.get('strategy'), # StrategyArchitectAgent
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orchestrator.agents.get('seo'), # SEOOptimizationAgent
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orchestrator.agents.get('social'), # SocialAmplificationAgent
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orchestrator.agents.get('competitor'), # CompetitorResponseAgent
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]
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agent_timeout_seconds = _get_agent_proposal_timeout_seconds(grounding)
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# Define agents to poll (keyed for logging/metrics)
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agents_to_poll = {
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"content": orchestrator.agents.get('content'),
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"strategy": orchestrator.agents.get('strategy'),
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"seo": orchestrator.agents.get('seo'),
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"social": orchestrator.agents.get('social'),
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"competitor": orchestrator.agents.get('competitor'),
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}
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# Filter out None agents (disabled/failed init)
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active_agents = [a for a in agents_to_poll if a]
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# Execute propose_daily_tasks in parallel
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results = await asyncio.gather(
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*[a.propose_daily_tasks(grounding) for a in active_agents],
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return_exceptions=True
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active_agents = {key: agent for key, agent in agents_to_poll.items() if agent}
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async def _collect_agent_proposals(agent_key: str, agent: Any) -> Dict[str, Any]:
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started_at = datetime.now(timezone.utc)
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try:
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proposals = await asyncio.wait_for(agent.propose_daily_tasks(grounding), timeout=agent_timeout_seconds)
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elapsed_ms = (datetime.now(timezone.utc) - started_at).total_seconds() * 1000
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return {
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"agent_key": agent_key,
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"status": "ok",
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"elapsed_ms": elapsed_ms,
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"proposals": proposals if isinstance(proposals, list) else [],
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}
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except asyncio.TimeoutError:
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elapsed_ms = (datetime.now(timezone.utc) - started_at).total_seconds() * 1000
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return {
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"agent_key": agent_key,
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"status": "timeout",
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"elapsed_ms": elapsed_ms,
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"proposals": [],
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"error": f"Timed out after {agent_timeout_seconds:.2f}s",
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}
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except Exception as agent_error:
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elapsed_ms = (datetime.now(timezone.utc) - started_at).total_seconds() * 1000
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return {
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"agent_key": agent_key,
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"status": "error",
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"elapsed_ms": elapsed_ms,
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"proposals": [],
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"error": str(agent_error),
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}
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# Execute propose_daily_tasks in parallel with per-agent timeout
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committee_results = await asyncio.gather(
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*[_collect_agent_proposals(agent_key, agent) for agent_key, agent in active_agents.items()]
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)
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# Collect successful proposals
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successful_agent_count = 0
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raw_proposals = []
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for res in results:
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if isinstance(res, list):
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# Normalize pillar IDs and filter invalid proposals
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for proposal in res:
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pillar_id = str(proposal.get("pillarId") or "").lower().strip()
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if pillar_id not in PILLAR_IDS:
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logger.warning(f"Skipping proposal with invalid pillarId: {pillar_id}. Proposal: {proposal}")
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continue
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proposal["pillarId"] = pillar_id
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raw_proposals.append(proposal)
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elif isinstance(res, Exception):
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logger.warning(f"Agent proposal failed: {res}")
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for res in committee_results:
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agent_key = res.get("agent_key")
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status = res.get("status")
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elapsed_ms = res.get("elapsed_ms")
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logger.info(
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"Agent committee proposal metric | agent={} status={} elapsed_ms={:.2f} timeout_s={:.2f} proposal_count={}",
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agent_key,
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status,
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elapsed_ms,
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agent_timeout_seconds,
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len(res.get("proposals") or []),
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)
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if status == "ok":
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successful_agent_count += 1
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raw_proposals.extend(res.get("proposals") or [])
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elif status == "timeout":
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logger.warning(f"Agent proposal timed out for {agent_key}: {res.get('error')}")
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else:
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logger.warning(f"Agent proposal failed for {agent_key}: {res.get('error')}")
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committee_total_failure = successful_agent_count == 0
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# 3. Filter Redundant Proposals (Self-Learning)
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# Note: We need to ensure we don't filter out essential recurring tasks if they were completed long ago
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@@ -350,19 +414,26 @@ async def generate_agent_enhanced_plan(db: Session, user_id: str, date: str) ->
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# Simple deduplication based on title+pillar
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unique_map = {}
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for p in raw_proposals:
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key = f"{p.pillar_id}:{p.title}"
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# Normalize pillar IDs and filter invalid proposals (re-apply from PR #383)
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pillar_id = str(p.get("pillarId") or "").lower().strip()
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if pillar_id not in PILLAR_IDS:
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logger.warning(f"Skipping proposal with invalid pillarId: {pillar_id}. Proposal: {p}")
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continue
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p["pillarId"] = pillar_id
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key = f"{p.get('pillarId')}:{p.get('title')}"
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if key not in unique_map:
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unique_map[key] = p
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continue
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existing = unique_map[key]
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if _proposal_priority_rank(p.priority) > _proposal_priority_rank(existing.priority):
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if _proposal_priority_rank(p.get('priority')) > _proposal_priority_rank(existing.get('priority')):
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unique_map[key] = p
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continue
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# Deterministic tie-breaker for equal priority proposals.
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if (
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_proposal_priority_rank(p.priority) == _proposal_priority_rank(existing.priority)
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_proposal_priority_rank(p.get('priority')) == _proposal_priority_rank(existing.get('priority'))
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and _proposal_order_key(p) < _proposal_order_key(existing)
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):
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unique_map[key] = p
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@@ -374,32 +445,51 @@ async def generate_agent_enhanced_plan(db: Session, user_id: str, date: str) ->
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except Exception as e:
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logger.error(f"Committee proposal phase failed: {e}")
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committee_total_failure = True
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# Continue to fallback or LLM generation if committee fails
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# 4. Final Selection
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# If we have agent tasks, use them. Otherwise fall back to LLM generation.
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if agent_tasks:
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# Use committee outcomes whenever committee partially succeeds, even with sparse proposals.
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if not committee_total_failure:
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logger.info(f"Generated {len(agent_tasks)} tasks via Agent Committee")
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# Convert TaskProposal objects to dicts for frontend
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final_tasks = []
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for prop in agent_tasks:
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final_tasks.append({
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"pillarId": prop.pillar_id,
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"title": prop.title,
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"description": prop.description,
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"priority": prop.priority,
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"estimatedTime": prop.estimated_time,
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"actionType": prop.action_type,
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"actionUrl": prop.action_url,
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"enabled": True,
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"metadata": {
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"source_agent": prop.source_agent,
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"reasoning": prop.reasoning,
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"context_data": prop.context_data
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}
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})
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# Handle both object and dict types
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if isinstance(prop, dict):
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final_tasks.append({
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"pillarId": prop.get("pillarId"),
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"title": prop.get("title"),
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"description": prop.get("description"),
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"priority": prop.get("priority"),
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"estimatedTime": prop.get("estimatedTime"),
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"actionType": prop.get("actionType"),
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"actionUrl": prop.get("actionUrl"),
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"enabled": True,
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"metadata": {
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"source_agent": prop.get("source_agent"),
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"reasoning": prop.get("reasoning"),
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"context_data": prop.get("context_data")
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}
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})
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else:
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final_tasks.append({
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"pillarId": prop.pillar_id,
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"title": prop.title,
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"description": prop.description,
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"priority": prop.priority,
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"estimatedTime": prop.estimated_time,
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"actionType": prop.action_type,
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"actionUrl": prop.action_url,
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"enabled": True,
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"metadata": {
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"source_agent": prop.source_agent,
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"reasoning": prop.reasoning,
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"context_data": prop.context_data
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}
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})
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final_tasks = _ensure_pillar_coverage(final_tasks, user_id, date, grounding)
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return {
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"date": date,
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