mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-17 23:09:35 +00:00
feat: close 5 truth audit gaps — GTM routes + governance + proof + delivery
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
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salesflow-saas/backend/app/api/v1/gtm.py
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salesflow-saas/backend/app/api/v1/gtm.py
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"""Dealix GTM Intelligence API Routes — all dry-run safe, no real sending."""
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import sys, os
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", ".."))
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from fastapi import APIRouter
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from pydantic import BaseModel
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from typing import Optional
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router = APIRouter(prefix="/gtm", tags=["GTM Intelligence"])
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class CompanyRequest(BaseModel):
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company_name: str
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sector: str = ""
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city: str = ""
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email: str = ""
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website: str = ""
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class ComplianceRequest(BaseModel):
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channel: str
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action: str = "send_message"
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class ReplyRequest(BaseModel):
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reply_text: str
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class ApprovalRequest(BaseModel):
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target_company: str
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action: str
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approved: bool = False
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class OutcomeRequest(BaseModel):
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target_company: str
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outcome: str
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channel: str = ""
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notes: str = ""
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@router.post("/company-intelligence")
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async def company_intelligence(req: CompanyRequest):
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from dealix_gtm_os.agents.supervisor_agent import SupervisorAgent
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s = SupervisorAgent()
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return await s.run({"name": req.company_name, "sector": req.sector, "city": req.city, "email": req.email})
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@router.post("/score-target")
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async def score_target(req: CompanyRequest):
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from dealix_gtm_os.scoring.scoring_engine import score_target
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return score_target(req.company_name, req.sector, bool(req.email)).model_dump()
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@router.post("/generate-outreach-pack")
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async def generate_outreach_pack(req: CompanyRequest):
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from dealix_gtm_os.agents.supervisor_agent import SupervisorAgent
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s = SupervisorAgent()
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result = await s.run({"name": req.company_name, "sector": req.sector, "city": req.city, "email": req.email})
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return {"company": req.company_name, "message": result.get("message"), "channel_plan": result.get("channel_plan"), "compliance": result.get("compliance"), "proof_pack": result.get("proof_pack"), "approval_required": result.get("approval_required", True), "trace_id": result.get("trace_id")}
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@router.post("/compliance-check")
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async def compliance_check(req: ComplianceRequest):
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from dealix_gtm_os.compliance.compliance_engine import check_compliance
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return check_compliance(req.channel, req.action)
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@router.post("/classify-reply")
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async def classify_reply(req: ReplyRequest):
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from dealix_gtm_os.agents.negotiation_agent import NegotiationAgent
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n = NegotiationAgent()
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return await n.run({"objection": req.reply_text})
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@router.post("/next-action")
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async def next_action(req: CompanyRequest):
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from dealix_gtm_os.agents.supervisor_agent import SupervisorAgent
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s = SupervisorAgent()
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result = await s.run({"name": req.company_name, "sector": req.sector, "city": req.city})
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return {"company": req.company_name, "next_action": result.get("next_action"), "approval_required": result.get("approval_required"), "channel": result.get("channel_plan", {}).get("primary_channel")}
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@router.post("/generate-daily-command-pack")
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async def daily_command_pack(req: CompanyRequest):
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from dealix_gtm_os.agents.supervisor_agent import SupervisorAgent
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s = SupervisorAgent()
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result = await s.run({"name": req.company_name or "Daily Pack Target", "sector": req.sector or "agency", "city": req.city or "الرياض"})
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return {"pack_type": "daily", "target": result.get("company"), "score": result.get("score"), "message": result.get("message"), "channel": result.get("channel_plan"), "compliance": result.get("compliance"), "trace_id": result.get("trace_id"), "no_real_send": True}
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@router.get("/targets")
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async def list_targets():
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return {"targets": [], "note": "Connect to database for persistent targets. Currently uses file-based targets in FIRST_20_TARGETS.md"}
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@router.get("/approvals")
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async def list_approvals():
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from dealix_gtm_os.governance.approval_queue import get_pending
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return {"pending": get_pending()}
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@router.post("/approve-action")
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async def approve_action(req: ApprovalRequest):
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from dealix_gtm_os.governance.approval_queue import approve, reject
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if req.approved:
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return approve(req.target_company, req.action)
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return reject(req.target_company, req.action)
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@router.post("/log-outcome")
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async def log_outcome(req: OutcomeRequest):
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from dealix_gtm_os.governance.audit_log import log_entry
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return log_entry(req.target_company, req.outcome, req.channel, req.notes)
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@ -33,6 +33,7 @@ from app.api.v1 import model_routing as model_routing_router
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from app.api.v1 import saudi_compliance as saudi_compliance_router
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from app.api.v1 import saudi_compliance as saudi_compliance_router
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from app.api.v1 import forecast_control as forecast_control_router
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from app.api.v1 import forecast_control as forecast_control_router
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from app.api.v1 import approval_center as approval_center_router
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from app.api.v1 import approval_center as approval_center_router
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from app.api.v1 import gtm as gtm_router
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api_router = APIRouter()
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api_router = APIRouter()
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@ -117,6 +118,9 @@ api_router.include_router(saudi_compliance_router.router)
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api_router.include_router(forecast_control_router.router)
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api_router.include_router(forecast_control_router.router)
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api_router.include_router(approval_center_router.router)
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api_router.include_router(approval_center_router.router)
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# ── GTM Intelligence OS ────────────────────────────────────
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api_router.include_router(gtm_router.router)
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# ── Golden Path — Tier-1 Verification Flow ───────────────────
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# ── Golden Path — Tier-1 Verification Flow ───────────────────
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from app.api.v1 import golden_path as golden_path_router
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from app.api.v1 import golden_path as golden_path_router
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api_router.include_router(golden_path_router.router)
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api_router.include_router(golden_path_router.router)
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"""Action policy — decides what requires approval vs auto-allowed."""
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POLICY = {
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"email_send": "semi_auto",
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"linkedin_dm": "manual_required",
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"linkedin_connect": "manual_required",
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"whatsapp_warm": "manual_required",
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"whatsapp_cold": "prohibited",
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"instagram_dm": "manual_required",
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"x_post": "auto_allowed",
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"x_reply": "manual_required",
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"payment_link": "manual_required",
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"partner_terms": "manual_required",
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"claim_result": "manual_required",
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"use_customer_name": "manual_required",
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}
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def check_action(action: str) -> dict:
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level = POLICY.get(action, "manual_required")
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return {"action": action, "level": level, "requires_approval": level in ("manual_required",), "prohibited": level == "prohibited", "reason": f"Policy: {action} is {level}"}
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"""Approval queue — tracks actions that need Sami's approval before sending."""
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import time
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from typing import Optional
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_queue: list[dict] = []
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def add_to_queue(company: str, action: str, channel: str, message_preview: str = "") -> dict:
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entry = {"id": len(_queue) + 1, "company": company, "action": action, "channel": channel, "preview": message_preview[:100], "status": "pending", "created_at": time.time()}
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_queue.append(entry)
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return entry
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def get_pending() -> list[dict]:
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return [e for e in _queue if e["status"] == "pending"]
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def approve(company: str, action: str) -> dict:
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for e in _queue:
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if e["company"] == company and e["action"] == action and e["status"] == "pending":
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e["status"] = "approved"
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e["approved_at"] = time.time()
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return {"approved": True, "entry": e}
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return {"approved": False, "reason": "Not found in queue"}
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def reject(company: str, action: str) -> dict:
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for e in _queue:
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if e["company"] == company and e["action"] == action and e["status"] == "pending":
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e["status"] = "rejected"
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return {"rejected": True, "entry": e}
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return {"rejected": False, "reason": "Not found in queue"}
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15
salesflow-saas/backend/dealix_gtm_os/governance/audit_log.py
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salesflow-saas/backend/dealix_gtm_os/governance/audit_log.py
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"""Audit log — records every proposed and executed action."""
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import time
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_log: list[dict] = []
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def log_entry(company: str, action: str, channel: str = "", notes: str = "") -> dict:
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entry = {"id": len(_log) + 1, "company": company, "action": action, "channel": channel, "notes": notes, "timestamp": time.time()}
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_log.append(entry)
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return {"logged": True, "entry_id": entry["id"]}
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def get_log(limit: int = 50) -> list[dict]:
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return _log[-limit:]
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def get_log_for_company(company: str) -> list[dict]:
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return [e for e in _log if e["company"] == company]
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"""Risk flags — identifies risky actions before they happen."""
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HIGH_RISK = {"whatsapp_cold", "linkedin_scraping", "linkedin_auto_dm", "instagram_mass_dm", "fake_claim", "guaranteed_revenue", "send_without_approval"}
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def check_risk(action: str) -> dict:
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is_high = action in HIGH_RISK
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return {"action": action, "risk": "HIGH" if is_high else "LOW", "blocked": is_high, "reason": f"{action} is {'HIGH RISK — blocked' if is_high else 'acceptable'}"}
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from pydantic import BaseModel, Field
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from typing import Optional
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from datetime import datetime
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class CustomerWorkspace(BaseModel):
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company_name: str
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sector: str
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plan: str = "pilot"
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status: str = "onboarding"
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lead_sources: list[str] = Field(default_factory=list)
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qualification_questions: list[str] = Field(default_factory=list)
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channels: list[str] = Field(default_factory=list)
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onboarding_checklist: list[dict] = Field(default_factory=lambda: [
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{"task": "استلام الدفع", "done": False},
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{"task": "استلام رقم واتساب/إيميل", "done": False},
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{"task": "استلام 3 أسئلة تأهيل", "done": False},
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{"task": "تفعيل النظام", "done": False},
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{"task": "إرسال تأكيد للعميل", "done": False},
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])
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created_at: str = Field(default_factory=lambda: datetime.now().isoformat())
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"""Customer Delivery Pipeline — creates workspace and manages onboarding."""
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from dealix_gtm_os.models.customer_workspace import CustomerWorkspace
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def create_workspace(company_name: str, sector: str, plan: str = "pilot", whatsapp: str = "", email: str = "", questions: list[str] = None) -> dict:
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ws = CustomerWorkspace(
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company_name=company_name,
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sector=sector,
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plan=plan,
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lead_sources=[s for s in [whatsapp, email] if s],
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qualification_questions=questions or [],
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channels=["whatsapp" if whatsapp else "email"],
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)
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return ws.model_dump()
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def get_onboarding_status(workspace: dict) -> dict:
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checklist = workspace.get("onboarding_checklist", [])
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done = sum(1 for t in checklist if t.get("done"))
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return {"total": len(checklist), "done": done, "remaining": len(checklist) - done, "complete": done == len(checklist)}
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def generate_weekly_report(workspace: dict) -> dict:
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return {
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"company": workspace.get("company_name"),
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"plan": workspace.get("plan"),
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"channels_active": workspace.get("channels", []),
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"recommendations": [
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"راجع سرعة الرد — هل تحت 45 ثانية؟",
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"شيك الردود وصنّفها",
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"تابع الاستفسارات اللي ما انحلت",
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],
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}
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"""Claim validator — blocks fake or overclaimed statements."""
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FORBIDDEN = ["مضمون", "guaranteed", "100%", "أفضل في السوق", "بدون منافس", "SOC 2", "ISO 27001", "bank-grade", "military-grade", "zero risk", "ربح مضمون", "دخل مضمون", "نتائج مضمونة"]
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def validate_claim(text: str) -> dict:
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violations = [f for f in FORBIDDEN if f.lower() in text.lower()]
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return {"valid": len(violations) == 0, "violations": violations, "severity": "critical" if violations else "none"}
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salesflow-saas/backend/dealix_gtm_os/proof/evidence.py
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salesflow-saas/backend/dealix_gtm_os/proof/evidence.py
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"""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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salesflow-saas/backend/dealix_gtm_os/proof/source_quality.py
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salesflow-saas/backend/dealix_gtm_os/proof/source_quality.py
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"""Source quality — rates the reliability of evidence sources."""
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SOURCE_RATINGS = {
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"company_website": 0.8,
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"uploaded_file": 0.9,
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"google_search": 0.6,
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"tavily": 0.7,
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"manual_input": 1.0,
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"llm_inference": 0.4,
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"mock": 0.3,
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"unknown": 0.1,
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}
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def rate_source(source_type: str) -> float:
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return SOURCE_RATINGS.get(source_type, 0.2)
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def rate_sources(sources: list[str]) -> dict:
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if not sources:
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return {"average_quality": 0.0, "best_source": None, "count": 0}
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ratings = [rate_source(s) for s in sources]
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return {"average_quality": round(sum(ratings) / len(ratings), 2), "best_source": sources[ratings.index(max(ratings))], "count": len(sources)}
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