Benjamin Admin
e21984e0ad
Der Compliance-Check legt zusätzlich einen strukturierten v3-AgentOutput pro Thema in result.agent_outputs ab (additiv; B18-HTML + Firehose-Mail bleiben unangetastet). Frontend: standardisiertes Ergebnis-Tab statt Firehose — Impressum-Tab (AgentResultTab) + "Alle Checks (roh)" (ChecklistView). - backend: _agent_outputs.py ruft den registrierten v3-ImpressumAgent, gewired in _orchestrator nach B18, surfaced via _phase_f_persist. - frontend: AgentResultView (aus AgentSlotCard extrahiert, DRY), AgentResultTab, ComplianceResultTabs; ComplianceCheckTab 490->391 Zeilen. - Tests: backend 2 passed, frontend 2 passed; tsc 0 neue Fehler; check-loc 0. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
87 lines
3.2 KiB
Python
87 lines
3.2 KiB
Python
"""Run registered v3 specialist agents and surface their structured
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AgentOutput per topic for the standardized result tabs.
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Additive to the legacy B-wiring HTML (`_b18_wiring`): this does NOT
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replace it — it puts a clean, typed `AgentOutput` into
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`state["agent_outputs"][topic]`, which `_phase_f_persist` forwards into
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the API result so the frontend can render a per-topic tab.
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Phase 1 ships only impressum; the topic map extends to cookie / vendor /
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… as those agents get wired (same contract, no code change here beyond
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the map). Once the tabs are the source of truth, B18's v1 path retires.
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"""
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from __future__ import annotations
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import logging
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from compliance.services.specialist_agents import REGISTRY, AgentInput
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logger = logging.getLogger(__name__)
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# topic key (matches state["doc_texts"]) -> registered agent_id
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_TOPIC_AGENTS: dict[str, str] = {
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"impressum": "impressum",
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}
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_MIN_TEXT = 100
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def _derive_scope(profile_dict: dict) -> list[str]:
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"""Business-scope aus dem erkannten Profil — identisch zu B18, damit
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der Tab denselben Scope sieht wie die bestehende Auswertung. Das
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Rechtsform-Gate kommt in einer späteren Phase (eigene Klassifizierung)."""
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scope: set[str] = set()
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if profile_dict.get("has_online_shop"):
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scope.add("ecommerce")
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if profile_dict.get("is_regulated_profession"):
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scope.add("regulated_profession")
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if profile_dict.get("industry") in ("insurance", "Finance", "finance"):
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scope.add("insurance")
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return sorted(scope)
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async def run_agent_outputs(state: dict) -> None:
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"""Für jedes Topic mit registriertem v3-Agent + ausreichend Text:
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Agent laufen lassen und den strukturierten AgentOutput ablegen."""
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doc_texts = state.get("doc_texts") or {}
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profile_dict = state.get("profile_dict") or {}
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req = state.get("req")
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company_name = (
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(getattr(req, "company_name", None) or "")
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or (state.get("extracted_profile") or {}).get("company_name", "")
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or state.get("site_name", "")
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)
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origin_domain = (
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getattr(req, "origin_domain", None) or ""
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) or state.get("domain", "")
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scope = _derive_scope(profile_dict)
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outputs: dict[str, dict] = state.get("agent_outputs") or {}
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for topic, agent_id in _TOPIC_AGENTS.items():
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text = (doc_texts.get(topic) or "").strip()
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if len(text) < _MIN_TEXT:
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continue
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agent = REGISTRY.get(agent_id)
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if agent is None:
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logger.warning("agent_outputs: agent '%s' not registered", agent_id)
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continue
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try:
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out = await agent.evaluate(AgentInput(
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doc_type=topic,
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text=text,
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business_scope=scope,
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company_name=company_name,
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origin_domain=origin_domain,
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))
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outputs[topic] = out.model_dump(mode="json")
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logger.info(
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"agent_outputs[%s]: %d findings, confidence %.2f",
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topic, len(out.findings), out.confidence,
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)
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except Exception as e: # noqa: BLE001 — best-effort, never break the run
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logger.warning("agent_outputs[%s] failed: %s", topic, e)
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if outputs:
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state["agent_outputs"] = outputs
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