84fa0830d8
Expert knows the full eras2_production schema cold: - All PKs, FKs, column names verified from DESCRIBE - Junction tables: objektkunde (kunden↔objekte), objektadressen, kundenadressen - Exact JOIN patterns baked into prompt - No DESCRIBE/SHOW at runtime — plan once, execute - Domain language responses (not SQL dumps) Simplified ExpertNode.execute(): - Removed iterative DESCRIBE→re-plan loop - Single plan+execute pass (schema is known) - Faster: 1 LLM call for plan instead of 2-3 Domain mastery test (eras_domain.md): 38/38 - Customer overview, junction table JOINs, full hierarchy traversal - Address lookup, Verbrauchsdaten, domain language, no DESCRIBE check Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
126 lines
5.1 KiB
Python
126 lines
5.1 KiB
Python
"""Eras Expert: Heizkostenabrechnung domain specialist.
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The expert knows the full database schema. No DESCRIBE at runtime.
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All queries use verified column names and JOIN patterns.
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"""
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import asyncio
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import logging
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from .expert_base import ExpertNode
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from ..db import run_db_query
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log = logging.getLogger("runtime")
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class ErasExpertNode(ExpertNode):
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name = "eras_expert"
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default_database = "eras2_production"
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DOMAIN_SYSTEM = """You are the Eras domain expert for Heizkostenabrechnung (German heating cost billing).
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BUSINESS CONTEXT:
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Eras is software for Hausverwaltungen and Messdienste who manage properties, meters, and billings.
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The USER of this agent is an Eras customer exploring their data. They think in domain terms
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(Kunden, Objekte, Wohnungen, Zaehler) — NOT in SQL. Never expose SQL or table names to the user.
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DOMAIN MODEL:
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- Kunden = property managers (Hausverwaltungen). 693 in the system.
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- Objekte = buildings/Liegenschaften managed by Kunden. 780 total. Linked via objektkunde (m:n).
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- Nutzeinheiten = apartments/units inside Objekte. 4578 total.
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- Nutzer = tenants/occupants of Nutzeinheiten. 8206 total.
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- Geraete = measurement devices (Heizkostenverteiler, Zaehler). 56726 total.
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- Verbraeuche = consumption readings from Geraete. 1.3M readings.
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- Adressen = postal addresses, linked via objektadressen/kundenadressen.
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RESPOND IN DOMAIN LANGUAGE:
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- Say "Kunde Jaeger hat 3 Objekte" not "SELECT COUNT..."
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- Say "12 Wohnungen mit 45 Geraeten" not "nutzeinheit rows"
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- Present data as summaries, not raw tables"""
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SCHEMA = """COMPLETE DATABASE SCHEMA (eras2_production) — use these exact column names:
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=== kunden (693 rows) ===
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PK: ID (int)
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Name1, Name2, Name3 (longtext) — customer name parts
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Kundennummer (longtext) — customer number
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AnredeID (FK), BriefanredeID (FK), ZugeordneterKomplettdruckID (FK)
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Anmerkung, Fremdnummer, Ansprechpartner (longtext)
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Steuernummer, UmsatzsteuerID (longtext)
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HatHistorie, IstWebkunde, IstNettoKunde, BrennstoffkostenNachFIFO, BelegePerEmail (bool)
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MietpreisAnpassungProzent (decimal)
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=== objektkunde (911 rows) — JUNCTION: kunden ↔ objekte (many-to-many) ===
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PK: ID (int)
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KundeID (FK → kunden.ID)
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ObjektID (FK → objekte.ID)
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ZeitraumVon, ZeitraumBis (datetime)
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IstKunde, IstEigentuemer, IstRechnungsempfaenger, IstAbrechnungsempfaenger (bool)
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=== objekte (780 rows) ===
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PK: ID (int)
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Objektnummer (longtext) — building reference number
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AbleserID, MonteurID, UVIRefObjektID, ZugeordneterKomplettdruckID (FK)
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Anmerkung, AnmerkungIntern (longtext)
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HatHistorie, VorauszahlungGetrennt, Selbstablesung, IstObjektFreigegeben (bool)
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=== objektadressen — JUNCTION: objekte ↔ adressen ===
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PK: ID, ObjektID (FK → objekte.ID), AdresseID (FK → adressen.ID), IstPrimaer (bool)
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=== kundenadressen — JUNCTION: kunden ↔ adressen ===
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PK: ID, KundeID (FK → kunden.ID), AdresseID (FK → adressen.ID), TypDerAdresseID (FK)
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=== adressen (1762 rows) ===
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PK: ID (int)
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Strasse, Hausnummer, Postleitzahl, Ort, Adresszusatz, Postfach (longtext)
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LandID (FK), Laengengrad, Breitengrad (double)
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=== nutzeinheit (4578 rows) ===
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PK: ID (int)
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ObjektID (FK → objekte.ID)
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NeNummerInt (longtext) — unit number
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Lage, Stockwerk, Flaeche, Nutzflaeche (various)
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AdresseID (FK), CustomStatusKeyID (FK)
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=== kundenutzeinheit — JUNCTION: kunden ↔ nutzeinheit ===
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PK: ID, KundeID (FK → kunden.ID), NutzeinheitID (FK → nutzeinheit.ID), Von, Bis (datetime)
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=== nutzer (8206 rows) — tenants/occupants ===
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PK: ID (int)
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NutzeinheitID (FK → nutzeinheit.ID)
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Name1, Name2, Name3, Name4 (longtext) — tenant name
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NutzungVon, NutzungBis (datetime)
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ArtDerNutzung (int), AnredeID (FK), BriefanredeID (FK)
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IstGesperrt, Selbstableser (bool)
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=== geraete (56726 rows) — meters/devices ===
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PK: ID (int)
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NutzeinheitID (FK → nutzeinheit.ID)
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ArtikelID (FK → geraetekatalog), GeraeteTypID (FK)
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Fabriknummer, Funkkennung (longtext) — serial numbers
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Einbaudatum, Ausbaudatum, GeeichtBis (datetime)
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AnsprechpartnerID, ZugeordneterRaumID, CustomStatusKeyID (FK)
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=== geraeteverbraeuche (1.3M rows) — consumption readings ===
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PK: ID (int)
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GeraetID (FK → geraete.ID)
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Ablesedatum (datetime), Ablesung, Verbrauch, Faktor (double)
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AbleseartID (FK), Schaetzung (int), Status (int)
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IstRekonstruiert (bool), Herkunft (int)
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JOIN PATTERNS (use exactly):
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Kunde → Objekte: JOIN objektkunde ok ON ok.KundeID = k.ID JOIN objekte o ON o.ID = ok.ObjektID
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Objekt → Adresse: JOIN objektadressen oa ON oa.ObjektID = o.ID JOIN adressen a ON a.ID = oa.AdresseID
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Kunde → Adresse: JOIN kundenadressen ka ON ka.KundeID = k.ID JOIN adressen a ON a.ID = ka.AdresseID
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Objekt → NE: JOIN nutzeinheit ne ON ne.ObjektID = o.ID
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NE → Nutzer: JOIN nutzer nu ON nu.NutzeinheitID = ne.ID
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NE → Geraete: JOIN geraete g ON g.NutzeinheitID = ne.ID
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Geraet → Verbrauch: JOIN geraeteverbraeuche gv ON gv.GeraetID = g.ID
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RULES:
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- NEVER use DESCRIBE at runtime. You know the schema.
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- NEVER guess column names. Use ONLY columns listed above.
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- For unknown tables: return an error, do not explore.
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- Always LIMIT large queries (max 50 rows).
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- Use LEFT JOIN when results might be empty."""
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