mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-17 23:09:35 +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
83 lines
3.0 KiB
Python
83 lines
3.0 KiB
Python
"""Shared enrichment pipeline for sync HTTP and background jobs."""
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from __future__ import annotations
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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 datetime import datetime, timezone
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.schemas.dealix_master import EnrichExplorationBody
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from app.services.intelligence_plane_control import cache_get, cache_set, tenant_may_use_licensed_search
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from app.services.revenue_discovery_service import build_enrichment_for_lead, resolve_playbook_id
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logger = logging.getLogger("dealix.enrichment_runner")
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async def compute_enrich_exploration(
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db: AsyncSession,
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body: EnrichExplorationBody,
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*,
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tenant_id: str | None,
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tid_for_tavily: str | None,
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) -> dict:
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"""
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Cache-aware enrichment (payload hash + daily idempotency). Returns model_dump dict.
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"""
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payload_hash = hashlib.sha256(
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json.dumps(body.model_dump(), ensure_ascii=False, sort_keys=True).encode("utf-8")
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).hexdigest()[:32]
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cache_key = f"enrich:{payload_hash}"
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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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company_key = str(body.lead.get("company_name") or "").strip().lower()[:160]
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day = datetime.now(timezone.utc).strftime("%Y-%m-%d")
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idem_key = (
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f"enrich:idemp:{day}:{body.sector}:{body.city}:"
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f"{hashlib.sha256(company_key.encode('utf-8')).hexdigest()[:24]}"
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)
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if os.getenv("DEALIX_ENRICH_IDEMPOTENT_DAILY", "true").lower() not in ("0", "false", "no"):
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idem_hit = cache_get(idem_key)
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if idem_hit is not None:
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return idem_hit
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allow_search = (os.getenv("TAVILY_API_KEY") or "").strip() != ""
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if os.getenv("DEALIX_ALLOW_LICENSED_SEARCH", "true").lower() in ("0", "false", "no"):
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allow_search = False
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if tid_for_tavily and not tenant_may_use_licensed_search(tid_for_tavily):
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allow_search = False
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knowledge_chunks: list[dict] = []
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if os.getenv("DEALIX_KNOWLEDGE_RAG_ENRICH", "true").lower() not in ("0", "false", "no"):
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try:
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from app.services.knowledge_service import KnowledgeService
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ks = KnowledgeService(db)
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q = f"{company_key} {body.sector} {body.city} sales partnership B2B"
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pb = resolve_playbook_id(body.sector)
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knowledge_chunks = await ks.search_sector_knowledge(q, sector=pb, limit=3)
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if not knowledge_chunks:
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knowledge_chunks = await ks.search_sector_knowledge(q, sector=None, limit=3)
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except Exception as e:
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logger.debug("knowledge RAG skipped: %s", e)
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enrichment = await build_enrichment_for_lead(
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sector=body.sector,
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city=body.city,
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lead=body.lead,
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icp_notes_ar=body.icp_notes_ar,
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icp_notes_en=body.icp_notes_en,
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use_licensed_search=allow_search,
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knowledge_chunks=knowledge_chunks or None,
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)
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out = enrichment.model_dump()
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cache_set(cache_key, out)
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if os.getenv("DEALIX_ENRICH_IDEMPOTENT_DAILY", "true").lower() not in ("0", "false", "no"):
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cache_set(idem_key, out, ttl_sec=86400)
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return out
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