mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 15:29:36 +00:00
d8bb836614
Add revenue discovery APIs/services, launch verification gates, CI quality checks, and frontend E2E/docs updates to prepare the branch for production go-live. Made-with: Cursor
438 lines
18 KiB
Python
438 lines
18 KiB
Python
"""
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Dealix Master API — Full Power Endpoints
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أقوى وأشمل API في مجال المبيعات السعودية
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"""
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from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query, Request
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from pydantic import BaseModel, Field
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from sqlalchemy.ext.asyncio import AsyncSession
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from typing import Any, Optional, List
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import hashlib
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import json
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import logging
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import os
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from pathlib import Path
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from app.api.deps import get_optional_user
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from app.database import async_session, get_db
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from app.models.user import User
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from app.schemas.dealix_master import EnrichExplorationBody
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logger = logging.getLogger("dealix.api.master")
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router = APIRouter(prefix="/dealix", tags=["🏰 Dealix Master API"])
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def _key():
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return os.getenv("GROQ_API_KEY", "")
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# ── Lead Generation ───────────────────────────────────────────
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@router.post("/generate-leads")
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async def generate_leads(
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request: Request,
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sector: str = Query(default="تقنية المعلومات", description="القطاع"),
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city: str = Query(default="الرياض", description="المدينة"),
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count: int = Query(default=10, le=50),
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user: Optional[User] = Depends(get_optional_user),
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):
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"""🎯 توليد leads مؤهلة تلقائياً لأي قطاع وأي مدينة سعودية."""
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from app.services.intelligence_plane_control import audit_ai_decision, check_rate_limit, cache_get, cache_set
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from app.services.lead_generation import GoogleMapsLeadScraper
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from app.services.revenue_discovery_service import attach_generation_provenance
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client = request.client.host if request.client else "unknown"
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xf = request.headers.get("x-forwarded-for")
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tenant_id = str(user.tenant_id) if user else None
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ok, reason = check_rate_limit(client_ip=client, x_forwarded_for=xf, tenant_id=tenant_id)
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if not ok:
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raise HTTPException(status_code=429, detail=reason)
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cache_key = f"genleads:{sector}:{city}:{count}"
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cached = cache_get(cache_key)
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if cached is not None:
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return cached
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scraper = GoogleMapsLeadScraper()
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leads, sector_insights = await scraper.generate_leads_for_sector(sector, city, count)
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manifest = attach_generation_provenance(leads, sector, city)
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out = {
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"sector": sector,
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"city": city,
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"count": len(leads),
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"leads": leads,
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"sector_insights": sector_insights,
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"discovery_manifest": manifest,
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}
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cache_set(cache_key, out)
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audit_ai_decision(
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operation="generate_leads",
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tenant_id=tenant_id,
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user_id=str(user.id) if user else None,
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model_id="llama-3.3-70b-versatile",
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extra={"count": len(leads), "sector": sector},
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)
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return out
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async def _run_enrich_job(
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job_id: str,
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body_dict: dict[str, Any],
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tenant_id: str | None,
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tid_for_tavily: str | None,
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) -> None:
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from app.services.dealix_enrichment_runner import compute_enrich_exploration
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from app.services.intel_async_jobs import mark_done, mark_error, mark_running
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from app.services.intelligence_plane_control import audit_ai_decision
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mark_running(job_id)
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try:
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body = EnrichExplorationBody(**body_dict)
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async with async_session() as db:
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out = await compute_enrich_exploration(
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db, body, tenant_id=tenant_id, tid_for_tavily=tid_for_tavily
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)
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mark_done(job_id, out)
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audit_ai_decision(
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operation="enrich_exploration_async",
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tenant_id=tenant_id,
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user_id=None,
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model_id=out.get("model_id"),
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extra={"job_id": job_id, "playbook": out.get("vertical_playbook_id")},
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)
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except Exception:
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logger.exception("enrich job failed job_id=%s", job_id)
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mark_error(job_id, "enrichment_failed")
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@router.post("/enrich-exploration")
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async def enrich_exploration(
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request: Request,
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body: EnrichExplorationBody,
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db: AsyncSession = Depends(get_db),
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user: Optional[User] = Depends(get_optional_user),
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):
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"""Structured enrichment + provenance + vertical playbook linkage (optional Tavily)."""
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from app.services.dealix_enrichment_runner import compute_enrich_exploration
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from app.services.intelligence_plane_control import audit_ai_decision, check_rate_limit
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client = request.client.host if request.client else "unknown"
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xf = request.headers.get("x-forwarded-for")
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tenant_id = str(user.tenant_id) if user else None
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ok, reason = check_rate_limit(client_ip=client, x_forwarded_for=xf, tenant_id=tenant_id)
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if not ok:
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raise HTTPException(status_code=429, detail=reason)
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tid_for_tavily = tenant_id or request.headers.get("x-tenant-id")
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out = await compute_enrich_exploration(db, body, tenant_id=tenant_id, tid_for_tavily=tid_for_tavily)
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audit_ai_decision(
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operation="enrich_exploration",
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tenant_id=tenant_id,
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user_id=str(user.id) if user else None,
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model_id=out.get("model_id"),
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extra={"sector": body.sector, "playbook": out.get("vertical_playbook_id")},
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)
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return out
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@router.post("/enrich-exploration/async")
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async def enrich_exploration_async(
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request: Request,
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background_tasks: BackgroundTasks,
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body: EnrichExplorationBody,
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user: Optional[User] = Depends(get_optional_user),
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):
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"""Queue enrichment after HTTP response; poll GET .../jobs/{job_id}."""
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if os.getenv("DEALIX_ASYNC_ENRICH_JOBS", "true").lower() in ("0", "false", "no"):
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raise HTTPException(status_code=404, detail="async enrich jobs disabled")
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from app.services.intel_async_jobs import create_job
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from app.services.intelligence_plane_control import check_rate_limit
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client = request.client.host if request.client else "unknown"
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xf = request.headers.get("x-forwarded-for")
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tenant_id = str(user.tenant_id) if user else None
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ok, reason = check_rate_limit(client_ip=client, x_forwarded_for=xf, tenant_id=tenant_id)
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if not ok:
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raise HTTPException(status_code=429, detail=reason)
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tid_for_tavily = tenant_id or request.headers.get("x-tenant-id")
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job_id = create_job()
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background_tasks.add_task(
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_run_enrich_job,
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job_id,
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body.model_dump(),
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tenant_id,
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tid_for_tavily,
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)
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return {
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"job_id": job_id,
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"status": "pending",
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"poll": f"/api/v1/dealix/enrich-exploration/jobs/{job_id}",
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}
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@router.get("/enrich-exploration/jobs/{job_id}")
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async def enrich_exploration_job_status(job_id: str):
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from app.services.intel_async_jobs import get_job
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row = get_job(job_id)
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if not row:
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raise HTTPException(status_code=404, detail="job not found")
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return {"job_id": job_id, **row}
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@router.get("/intelligence-flags")
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async def intelligence_flags(request: Request, user: Optional[User] = Depends(get_optional_user)):
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"""Feature flags + intel config for workspace (no secrets)."""
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from app.services.intelligence_plane_control import intelligence_feature_snapshot
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tid = str(user.tenant_id) if user else request.headers.get("x-tenant-id")
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return intelligence_feature_snapshot(tenant_id=tid)
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_GOLDEN_PATH = Path(__file__).resolve().parents[2] / "data" / "ai_eval_golden.json"
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@router.get("/ai-eval/golden")
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async def ai_eval_golden():
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"""Golden / rubric JSON for regression & human-in-the-loop QA (no execution)."""
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if not _GOLDEN_PATH.is_file():
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return {"version": 0, "note": "ai_eval_golden.json missing"}
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return json.loads(_GOLDEN_PATH.read_text(encoding="utf-8"))
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class ChannelDraftRequest(BaseModel):
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company_name: str
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partnership_angle_ar: str = ""
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contact_name: str = "فريق العمليات"
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@router.post("/channel-drafts")
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async def governed_channel_drafts(body: ChannelDraftRequest):
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"""
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مسودات قنوات للمراجعة البشرية — واتساب/إيميل قابلة للتعديل؛ لينكدإن: موافقة بشرية إلزامية.
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"""
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cn = body.company_name.strip() or "الفريق"
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angle = (body.partnership_angle_ar or "استكشاف فرص تعاون في مجال عملكم").strip()
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return {
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"whatsapp_draft_ar": (
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f"السلام عليكم، معكم {body.contact_name} من Dealix. "
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f"نودّ استكشاف تعاون مع {cn} بخصوص: {angle}. هل يُناسبكم موعد قصير الأسبوع القادم؟"
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),
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"email_subject_ar": f"Dealix — استكشاف شراكة محتملة مع {cn}",
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"email_body_ar": (
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f"السلام عليكم،\n\nنتواصل من Dealix لاستكشاف {angle} مع {cn}. "
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f"نرحّب بمشاركة المسؤول المناسب لديكم.\n\nمع الشكر،\n{body.contact_name}"
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),
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"linkedin": {
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"human_in_loop_required": True,
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"policy_note_ar": (
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"لا يُرسل هذا النص تلقائياً عبر LinkedIn — يتطلب موافقة بشرية واستخدام واجهات رسمية أو استيراد يدوي وفق سياسة المنصة."
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),
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"draft_ar": (
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f"تحية طيبة، أتابع عمل {cn} وأودّ ربط نقاش مختصر حول {angle}. "
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f"هل يمكن توجيهي للمسؤول المناسب؟"
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),
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},
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"governance": {
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"pdpl_note_ar": "تأكد من وجود أساس قانوني للتواصل والموافقة حيث تنطبق PDPL.",
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"approval_recommended": True,
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},
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}
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@router.post("/daily-leads")
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async def get_daily_leads(target_count: int = Query(default=50, le=100)):
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"""📋 الحصة اليومية من الـ leads — يولّدها النظام تلقائياً."""
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from app.services.lead_generation import DealixLeadGenerationHub
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hub = DealixLeadGenerationHub()
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return await hub.generate_daily_leads(target_count)
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@router.get("/bulk-generate")
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async def bulk_generate(background_tasks: BackgroundTasks):
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"""⚡ توليد leads من جميع القطاعات والمدن السعودية في الخلفية."""
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from app.services.lead_generation import DealixLeadGenerationHub
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hub = DealixLeadGenerationHub()
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background_tasks.add_task(hub.generate_daily_leads, 100)
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return {"status": "generating", "message": "جاري توليد 100 lead من 5 قطاعات..."}
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# ── Company Research ──────────────────────────────────────────
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class CompanyInput(BaseModel):
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company_name: str
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website: Optional[str] = None
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extra_info: Optional[str] = ""
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@router.post("/research-company")
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async def research_company(company: CompanyInput):
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"""🔍 تحليل عميق لأي شركة — SWOT + درجة ملاءمة + استراتيجية البيع."""
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from app.services.company_research import DeepCompanyAnalyzer
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analyzer = DeepCompanyAnalyzer(_key())
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return await analyzer.analyze(company.company_name, company.website, company.extra_info)
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@router.post("/research-person")
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async def research_decision_maker(name: str, company: str):
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"""👤 تحليل شخصية المقرر ونفسيته وأفضل أسلوب للتعامل معه."""
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from app.services.lead_generation import LinkedInIntelligence
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li = LinkedInIntelligence()
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return await li.research_decision_maker(name, company)
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@router.post("/compare-companies")
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async def compare_companies(company_a: str, company_b: str):
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"""⚖️ مقارنة شركتين وتحديد الأفضل للاستهداف."""
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from app.services.company_research import DeepCompanyAnalyzer
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analyzer = DeepCompanyAnalyzer(_key())
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return await analyzer.compare_companies(company_a, company_b)
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# ── WhatsApp ──────────────────────────────────────────────────
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class OutreachCampaign(BaseModel):
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leads: List[dict]
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message_template: str = "أهلاً {name}، أنا من ديليكس وأتمنى التحدث معك عن تطوير مبيعات {company}"
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@router.post("/whatsapp/campaign")
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async def run_whatsapp_campaign(campaign: OutreachCampaign, background_tasks: BackgroundTasks):
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"""📱 حملة واتساب تلقائية لقائمة leads."""
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from app.services.whatsapp_service import WhatsAppService
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wa = WhatsAppService()
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background_tasks.add_task(wa.run_outreach_campaign, campaign.leads, campaign.message_template)
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return {"status": "campaign_started", "leads_count": len(campaign.leads)}
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@router.post("/whatsapp/reply")
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async def generate_whatsapp_reply(phone: str, message: str, customer_name: str = ""):
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"""💬 رد واتساب ذكي ومخصص باللهجة السعودية."""
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from app.services.whatsapp_service import WhatsAppService
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wa = WhatsAppService()
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reply = await wa._generate_intelligent_reply(phone, message)
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return {"reply": reply, "phone": phone}
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# ── Meeting Intelligence ──────────────────────────────────────
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class MeetingPrepInput(BaseModel):
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company_name: str
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contact_name: str
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contact_title: Optional[str] = ""
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meeting_time: Optional[str] = ""
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company_website: Optional[str] = None
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@router.post("/meeting/prepare")
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async def prepare_meeting(meeting: MeetingPrepInput):
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"""📊 حقيبة تحضير الاجتماع الكاملة — نقاط الحوار + الشرائح + الاستراتيجية."""
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from app.services.meeting_intelligence import MeetingPreparationService
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from app.services.company_research import DeepCompanyAnalyzer
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analyzer = DeepCompanyAnalyzer(_key())
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research = await analyzer.analyze(meeting.company_name, meeting.company_website)
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prep_service = MeetingPreparationService()
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return await prep_service.prepare_meeting_package({
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"company_name": meeting.company_name,
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"contact_name": meeting.contact_name,
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"contact_title": meeting.contact_title,
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"meeting_time": meeting.meeting_time,
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"company_research": research
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})
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@router.get("/meeting/slots")
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async def get_meeting_slots():
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"""📅 المواعيد المتاحة للاجتماعات (Cal.com)."""
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from app.services.meeting_intelligence import CalComService
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cal = CalComService()
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return {"slots": await cal.get_available_slots()}
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# ── ZATCA Compliance ──────────────────────────────────────────
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class DealForCompliance(BaseModel):
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id: Optional[str] = None
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amount: float
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company_name: str
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service_description: str = "خدمات ذكاء اصطناعي للمبيعات"
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buyer_vat: Optional[str] = ""
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buyer_cr: Optional[str] = ""
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city: Optional[str] = "الرياض"
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generate_invoice: bool = True
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@router.post("/compliance/check")
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async def check_compliance(deal: DealForCompliance):
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"""⚖️ فحص امتثال كامل (ZATCA + عقاري + AML) لأي صفقة."""
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from app.services.zatca_compliance import DealixComplianceOrchestrator
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import asyncio
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orchestrator = DealixComplianceOrchestrator()
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return await orchestrator.full_compliance_check(deal.model_dump())
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@router.post("/compliance/invoice")
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async def generate_zatca_invoice(deal: DealForCompliance):
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"""🧾 فاتورة ZATCA Phase 2 متوافقة — جاهزة للتقديم."""
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from app.services.zatca_compliance import ZATCAInvoiceEngine
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engine = ZATCAInvoiceEngine()
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return engine.generate_invoice(deal.model_dump())
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@router.get("/compliance/validate-vat/{vat_number}")
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async def validate_vat(vat_number: str):
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"""✅ التحقق من صحة الرقم الضريبي السعودي."""
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from app.services.zatca_compliance import ZATCAInvoiceEngine
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engine = ZATCAInvoiceEngine()
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return engine.validate_vat_number(vat_number)
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# ── Full Power Endpoint ───────────────────────────────────────
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class MegaRequest(BaseModel):
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company_name: str
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contact_name: str
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contact_phone: str
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contact_title: Optional[str] = ""
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website: Optional[str] = None
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@router.post("/full-power")
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async def full_power_pipeline(req: MegaRequest):
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"""
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🏰 FULL POWER — كل شيء في طلب واحد:
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Company Research + Qualification + WhatsApp Message
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+ Meeting Prep + Compliance Check + Executive Strategy
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"""
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from app.services.company_research import DeepCompanyAnalyzer
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from app.services.lead_pipeline import DealixLeadPipeline, Lead, Company
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from app.services.meeting_intelligence import MeetingPreparationService
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import asyncio
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# 1. Deep research
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analyzer = DeepCompanyAnalyzer(_key())
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research = await analyzer.analyze(req.company_name, req.website)
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# 2. Full pipeline
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pipeline = DealixLeadPipeline(_key())
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from app.services.lead_pipeline import Lead, Company
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lead = Lead(
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id=f"fp_{req.contact_phone}",
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contact_name=req.contact_name,
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contact_phone=req.contact_phone,
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contact_title=req.contact_title,
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company=Company(name=req.company_name, website=req.website)
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)
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pipeline_result = await pipeline.run_full_pipeline(lead)
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# 3. Meeting prep
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prep = MeetingPreparationService()
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|
meeting_prep = await prep.prepare_meeting_package({
|
|
"company_name": req.company_name,
|
|
"contact_name": req.contact_name,
|
|
"contact_title": req.contact_title,
|
|
"company_research": research
|
|
})
|
|
|
|
return {
|
|
"status": "FULL_POWER_COMPLETE",
|
|
"company": req.company_name,
|
|
"research": research,
|
|
"pipeline": pipeline_result,
|
|
"meeting_preparation": meeting_prep,
|
|
"generated_at": __import__('datetime').datetime.utcnow().isoformat()
|
|
}
|