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https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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bf91167350
1. GTM API Routes: 12 endpoints at /api/v1/gtm/* - company-intelligence, score-target, outreach-pack - compliance-check, classify-reply, next-action - daily-command-pack, targets, approvals - approve-action, log-outcome All registered in router.py 2. Governance Module: 4 files - approval_queue.py: add/approve/reject/get_pending - action_policy.py: policy per action type - audit_log.py: log every proposed action - risk_flags.py: HIGH/LOW risk classification 3. Proof Module: 3 files - evidence.py: VERIFIED/INFERRED/UNVERIFIED/LOW_CONFIDENCE - claim_validator.py: blocks fake claims - source_quality.py: rates source reliability 4. Customer Delivery: 2 files - customer_workspace.py: Pydantic model with onboarding checklist - customer_delivery_pipeline.py: create workspace + weekly report 5. All verified: 9/9 new imports pass, 30/30 evals, dry-run works https://claude.ai/code/session_01W1rJthWDkasijTdXCfxVHs
20 lines
741 B
Python
20 lines
741 B
Python
"""Evidence tracking — marks claims as VERIFIED, INFERRED, or UNVERIFIED."""
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from enum import Enum
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class EvidenceLevel(str, Enum):
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VERIFIED = "verified"
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INFERRED = "inferred"
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UNVERIFIED = "unverified"
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LOW_CONFIDENCE = "low_confidence"
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def assess_evidence(claim: str, sources: list[str], confidence: float) -> dict:
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if sources and confidence >= 0.8:
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level = EvidenceLevel.VERIFIED
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elif sources and confidence >= 0.5:
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level = EvidenceLevel.INFERRED
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elif confidence >= 0.3:
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level = EvidenceLevel.LOW_CONFIDENCE
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else:
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level = EvidenceLevel.UNVERIFIED
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return {"claim": claim, "level": level.value, "sources": sources, "confidence": confidence, "source_count": len(sources)}
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