Benjamin Admin
65de90114a
Der Compliance-Check streamt jetzt progressive Events; der Impressum-Tab
erscheint, sobald das Thema fertig ist, statt am Ende alles auf einmal.
Additiv — das Polling fürs finale Ergebnis bleibt.
- backend: _sse.py (Queue/emit/event_generator) + Endpoint
/compliance-check/{id}/stream; _update emittiert progress,
run_agent_outputs emittiert topic (laeuft jetzt frueh nach Phase B),
Orchestrator emittiert complete/error.
- frontend: SSE-Proxy-Route + EventSource in ComplianceCheckTab merged
topic-Events in agent_outputs -> Tab erscheint progressiv.
- Tests: backend 5 passed (SSE + agent_outputs); tsc 0 neue Fehler,
vitest 2 passed, check-loc 0.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
93 lines
3.4 KiB
Python
93 lines
3.4 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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from ._sse import emit
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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, AgentOutput ablegen + als SSE topic-Event
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emittieren (Tab füllt sich progressiv)."""
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check_id = state.get("check_id", "")
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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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emit(check_id, {"type": "topic", "topic": topic,
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"output": outputs[topic]})
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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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