45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
"""
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Citation Expert Agent implementation.
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"""
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from typing import List, Dict, Any, Optional
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from datetime import datetime
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from loguru import logger
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from .base import SIFBaseAgent
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from services.intelligence.agents.core_agent_framework import TaskProposal
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from services.intelligence.txtai_service import TxtaiIntelligenceService
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class CitationExpert(SIFBaseAgent):
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"""Agent for fact-checking and source management."""
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def __init__(self, intelligence_service: TxtaiIntelligenceService, user_id: str, **kwargs):
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super().__init__(intelligence_service, user_id, agent_type="citation_expert", **kwargs)
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async def verify_citations(self, content: str) -> Dict[str, Any]:
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"""Verify citations in content against trusted sources."""
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# Simple extraction for now
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# Could use LLM to extract claims and verify against knowledge base
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return {
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"verified_claims": [],
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"unverified_claims": [],
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"missing_citations": []
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}
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async def propose_daily_tasks(self, context: Dict[str, Any]) -> List[TaskProposal]:
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"""Propose fact-checking tasks."""
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proposals = []
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# 1. Fact Check High-Value Content
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proposals.append(TaskProposal(
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title="Verify Sources for 'AI Trends 2025'",
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description="Double-check statistical claims in your latest draft.",
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pillar_id="create",
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priority="medium",
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estimated_time=20,
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source_agent="CitationExpert",
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reasoning="Ensures credibility and trust.",
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action_type="navigate",
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action_url="/content-planning-dashboard"
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))
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return proposals
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