mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-17 23:09:35 +00:00
Security Curator (4 modules) — جدار الحماية الأول
- secret_redactor: 11 patterns (GitHub PAT, OpenAI/Anthropic/Supabase/WhatsApp/Moyasar/Sentry/Google/AWS/private keys); never returns raw secret
- patch_firewall: blocks .env / credentials.json / RSA keys; scans added lines for secret patterns
- trace_redactor: masks phones (+966...) and emails for PII safety
- tool_output_sanitizer: cleans tool outputs before they hit ledger/Proof Pack/UI/observability
Growth Curator (5 modules) — التحسين الذاتي
- message_curator: grades Arabic messages (0..100), detects 8 risky phrases, suggests Saudi-tone skeleton
- playbook_curator: scores playbooks by outcome (accept/reply/meeting/deal); winner/promising/needs_work/archive
- mission_curator: scores completed missions; ship_it_widely/iterate/rework_or_retire
- skill_inventory: deterministic 23-skill catalog across 5 layers
- curator_report: weekly Arabic summary "ماذا تعلمنا هذا الأسبوع"
Meeting Intelligence (5 modules) — ذكاء الاجتماعات
- transcript_parser: accepts Google Meet entries OR plain "Speaker: text" format
- meeting_brief: 6-section pre-meeting brief in Arabic (objective/questions/objections/offer/next-step)
- objection_extractor: 8 categories (price/timing/authority/trust/integration/competitor/results/complexity)
- followup_builder: email + WhatsApp drafts; live_send_allowed=False always
- deal_risk: 0..100 score from objections + missing next-step + decision-maker absence + days-since-touch
Model Router (5 modules) — موجّه النماذج
- provider_registry: 7 providers (Claude Sonnet/Haiku, GPT-4-class, GPT-4o-mini, Gemini Pro, Azure OAI KSA-region, Local Qwen Arabic-tuned)
- task_router: 10 task types × routing decisions with reasons_ar
- cost_policy: bulk → low; output > 1500 tokens → high
- fallback_policy: high-sensitivity workloads prefer KSA-region/self-hosted FIRST
- usage_dashboard: deterministic demo of all task routes
Connector Catalog (3 modules) — كتالوج التكاملات
- 14 connectors (WhatsApp Cloud, Gmail, Calendar, Google Meet, Moyasar, LinkedIn Lead Forms, Google Business Profile, X API, Instagram, Sheets, CRM, Website Forms, Composio, MCP Gateway)
- Each has launch_phase (1-4), risk_level, allowed_actions, blocked_actions, Arabic risk dossier
- WhatsApp blocks cold_send_without_consent; Moyasar blocks store_card_number; MCP requires allowlist
Agent Observability (5 modules) — مراقبة الوكلاء + التقييمات
- trace_events: SHA256-hashes user/company IDs; sanitizes payload/output before logging
- safety_eval: 7 rules (guarantee, scarcity_fake, medical_claim, financial, regulatory, personal_data, urgency); 0..100 → safe/needs_review/blocked
- saudi_tone_eval: positive markers (هلا, لاحظت, يناسبك) vs negative (تحية طيبة وبعد, synergy, leverage); arabic_ratio bonus
- eval_pack: 5 curated cases with expected verdicts
- cost_tracker: per workflow/provider/task_type aggregation
Routers (6 new) — 30 endpoints
- /api/v1/security-curator/{demo, redact, inspect-diff, sanitize-output}
- /api/v1/growth-curator/{skills/inventory, messages/grade, messages/improve, messages/duplicates, missions/next, report/weekly, report/demo}
- /api/v1/meeting-intelligence/{brief, brief/demo, transcript/summarize, followup/draft, deal-risk}
- /api/v1/model-router/{providers, tasks, route, cost-class, usage/demo}
- /api/v1/connector-catalog/{catalog, summary, status, risks, {key}}
- /api/v1/agent-observability/{trace/build, safety/eval, tone/eval, evals/run}
Tests (6 new files, 76 tests)
- test_security_curator: 16 tests (PAT detect, key redact, env diff block, payload scan, trace mask)
- test_growth_curator: 16 tests (Arabic grade, risky phrases, dup detect, playbook scoring, mission recommend, weekly report)
- test_meeting_intelligence: 13 tests (transcript parse, brief sections, objection extract, followup drafts, deal risk)
- test_dealix_model_router: 11 tests (every task → ≥1 provider, KSA-region for high sensitivity, cost class, primary override)
- test_agent_observability: 12 tests (trace hashing, safety verdicts, tone scoring, eval pack)
- test_connector_catalog: 11 tests (≥12 connectors, every has risk/blocked actions, WA cold-send blocked, Moyasar card-storage blocked)
Docs (8 new + 1 updated)
- AGENT_SECURITY_CURATOR.md (Arabic)
- GROWTH_CURATOR_STRATEGY.md (Arabic)
- MEETING_INTELLIGENCE.md (Arabic)
- MODEL_PROVIDER_ROUTER.md (Arabic)
- CONNECTOR_CATALOG.md (Arabic)
- AGENT_OBSERVABILITY_EVALS.md (Arabic)
- PRIVATE_BETA_LAUNCH_TODAY.md (Arabic) — go-checklist + offer + risks
- DEMO_SCRIPT_12_MINUTES.md (Arabic) — minute-by-minute demo flow
- FIRST_20_OUTREACH_MESSAGES.md (Arabic) — 7 personas + 3 follow-ups, all under safety/tone evals
- DEALIX_100_PERCENT_LAUNCH_PLAN.md — added §34 Self-Improving Agent Platform + §35 Private Beta Launch
Landing
- landing/private-beta.html — Arabic RTL, dark theme, pricing, 11 demo endpoints, safety banner
Test results
- 76/76 new tests pass
- Full suite: 663 passed, 2 skipped (missing API keys, unrelated)
- 0 existing tests broken
Safety
- All 6 layers honor approval-first, draft-only, no-live-send
- Hash user/company IDs before any trace
- No secrets in logs/embeddings/traces (3-layer defense: redactor + sanitizer + firewall)
- Saudi tone eval rejects "تحية طيبة وبعد" + "synergy" auto-corporate language
- Safety eval blocks "ضمان 100%" + medical claims + fake urgency
- Connector Catalog: WhatsApp blocks cold-send, Moyasar blocks card storage, MCP requires allowlist
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
101 lines
3.6 KiB
Python
101 lines
3.6 KiB
Python
"""Growth Curator router — message grading + weekly curator report."""
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from __future__ import annotations
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from typing import Any
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from fastapi import APIRouter, Body
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from auto_client_acquisition.growth_curator import (
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build_weekly_curator_report,
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detect_duplicates,
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grade_message,
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inventory_skills,
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recommend_next_mission,
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suggest_improvement,
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)
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router = APIRouter(prefix="/api/v1/growth-curator", tags=["growth-curator"])
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@router.get("/skills/inventory")
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async def skills_inventory() -> dict[str, Any]:
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return inventory_skills()
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@router.post("/messages/grade")
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async def messages_grade(
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message: str = Body(..., embed=True),
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sector: str | None = Body(default=None, embed=True),
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channel: str = Body(default="whatsapp", embed=True),
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) -> dict[str, Any]:
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return grade_message(message, sector=sector, channel=channel).to_dict()
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@router.post("/messages/improve")
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async def messages_improve(
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message: str = Body(..., embed=True),
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sector: str | None = Body(default=None, embed=True),
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) -> dict[str, Any]:
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return suggest_improvement(message, sector=sector)
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@router.post("/messages/duplicates")
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async def messages_duplicates(
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messages: list[str] = Body(..., embed=True),
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threshold: float = Body(default=0.85, embed=True),
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) -> dict[str, Any]:
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pairs = detect_duplicates(messages, threshold=threshold)
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return {
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"pairs": [{"i": i, "j": j, "similarity": s} for i, j, s in pairs],
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"count": len(pairs),
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}
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@router.post("/missions/next")
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async def missions_next(
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history: list[dict[str, Any]] = Body(default_factory=list, embed=True),
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growth_brain: dict[str, Any] | None = Body(default=None, embed=True),
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) -> dict[str, Any]:
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return recommend_next_mission(history, growth_brain=growth_brain)
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@router.post("/report/weekly")
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async def report_weekly(payload: dict[str, Any] = Body(default_factory=dict)) -> dict[str, Any]:
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return build_weekly_curator_report(
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messages=payload.get("messages", []),
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playbooks=payload.get("playbooks", []),
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missions=payload.get("missions", []),
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sector=payload.get("sector"),
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)
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@router.get("/report/demo")
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async def report_demo() -> dict[str, Any]:
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"""Demo curator report with a small synthetic dataset."""
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return build_weekly_curator_report(
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messages=[
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{"id": "m1", "text": "هلا أحمد، لاحظت توسعكم في المبيعات. يناسبك أعرض لك Pilot 7 أيام؟"},
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{"id": "m2", "text": "هلا محمد، لاحظت توسعكم في المبيعات. يناسبك أعرض لك Pilot 7 أيام؟"},
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{"id": "m3", "text": "آخر فرصة! ضمان 100% نتائج مضمونة!"},
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{"id": "m4", "text": "Hi"},
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],
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playbooks=[
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{"id": "pb1", "title": "Warm B2B intro - training", "used_count": 20,
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"accept_count": 12, "replied_count": 8, "meeting_count": 4, "deal_count": 2,
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"sectors": "training"},
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{"id": "pb2", "title": "Warm B2B intro - training-ksa", "used_count": 8,
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"accept_count": 4, "replied_count": 2, "meeting_count": 1, "deal_count": 0,
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"sectors": "training"},
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{"id": "pb3", "title": "Cold call SaaS", "used_count": 50,
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"accept_count": 5, "replied_count": 2, "meeting_count": 0, "deal_count": 0,
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"sectors": "saas"},
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],
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missions=[
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{"mission_id": "first_10_opportunities", "opportunities_generated": 10,
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"drafts_approved": 4, "meetings_booked": 2, "revenue_influenced_sar": 18000,
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"time_to_value_minutes": 8, "risks_blocked": 2},
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],
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sector="training",
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)
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