v0.15.3: Domain context, iterative plan-execute, FK mappings, ES6 node inspector
Eras Expert domain context: - Full Heizkostenabrechnung business model (Kunde>Objekte>Nutzeinheiten>Geraete) - Known PK/FK mappings: kunden.Kundennummer, objekte.KundenID, etc. - Correct JOIN example in SCHEMA prompt - PA knows domain hierarchy for better job formulation Iterative plan-execute in ExpertNode: - DESCRIBE queries execute first, results injected into re-plan - Re-plan uses actual column names from DESCRIBE - Eliminates "Unknown column" errors on first query Frontend: - Node inspector: per-node cards with model, tokens, progress, last event - Graph switcher buttons in top bar - Clear button in top bar - Nodes panel 300px wide - WS reconnect on 1006 (deploy) without showing login - Model info emitted on context HUD events Domain context test: 21/21 (hierarchy, JOINs, FK, PA job quality) Default graph: v4-eras Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Nico
parent
3a9c2795cf
commit
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@ -18,6 +18,9 @@ class Node:
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self.context_fill_pct = 0
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async def hud(self, event: str, **data):
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# Always include model on context events so frontend knows what model each node uses
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if event == "context" and self.model:
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data["model"] = self.model
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await self.send_hud({"node": self.name, "event": event, **data})
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def trim_context(self, messages: list[dict]) -> list[dict]:
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@ -1,4 +1,8 @@
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"""Eras Expert: heating/energy customer database specialist."""
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"""Eras Expert: heating cost billing domain specialist.
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Eras is a German software company for Heizkostenabrechnung (heating cost billing).
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Users are Hausverwaltungen and Messdienste who manage properties, meters, and billings.
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"""
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import asyncio
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import logging
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@ -13,52 +17,97 @@ 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 expert — specialist for heating and energy customer data.
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You work with the eras2_production database containing customer, device, and billing data.
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All table and column names are German (lowercase). Common queries involve customer lookups,
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device counts, consumption analysis, and billing reports."""
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DOMAIN_SYSTEM = """You are the Eras domain expert — specialist for heating cost billing (Heizkostenabrechnung).
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BUSINESS CONTEXT:
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Eras is a German software company. The software manages Heizkostenabrechnung according to German law (HeizKV).
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The USER of this software is a Hausverwaltung (property management) or Messdienst (metering service).
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They use Eras to manage their customers' properties, meters, consumption readings, and billings.
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DOMAIN MODEL (how the data relates):
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- Kunden (customers) = the Hausverwaltungen or property managers that the Eras user serves
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Each Kunde has a Kundennummer and contact data (Name, Adresse, etc.)
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- Objekte (properties/buildings/Liegenschaften) = physical buildings managed by a Kunde
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A Kunde can have many Objekte. Each Objekt has an address and is linked to a Kunde.
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- Nutzeinheiten (usage units/apartments) = individual units within an Objekt
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An Objekt contains multiple Nutzeinheiten (e.g., Wohnung 1, Wohnung 2).
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Each Nutzeinheit has Nutzer (tenants/occupants).
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- Geraete (devices/meters) = measurement devices installed in Nutzeinheiten
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Heizkostenverteiler, Waermezaehler, Wasserzaehler, etc.
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Each Geraet is linked to a Nutzeinheit and has a Geraetetyp.
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- Geraeteverbraeuche (consumption readings) = measured values from Geraete
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Ablesewerte collected by Monteure or remote reading systems.
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- Abrechnungen (billings) = Heizkostenabrechnungen generated per Objekt/period
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The core output: distributes heating costs to Nutzeinheiten based on consumption.
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- Auftraege (work orders) = tasks for Monteure (technicians)
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Device installation, reading collection, maintenance.
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HIERARCHY: Kunde → Objekte → Nutzeinheiten → Geraete → Verbraeuche
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→ Nutzer
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Kunde → Abrechnungen
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Kunde → Auftraege
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IMPORTANT NOTES:
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- All table/column names are German, lowercase
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- Foreign keys often use patterns like KundenID, ObjektID, NutzeinheitID
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- The database is eras2_production
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- Always DESCRIBE tables before writing JOINs to verify actual column names
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- Common user questions: customer overview, device counts, billing status, Objekt details"""
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SCHEMA = """Known tables (eras2_production):
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- kunden — customers
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- objekte — properties/objects linked to customers
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- nutzeinheit — usage units within objects
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- geraete — devices/meters
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- geraeteverbraeuche — device consumption readings
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- abrechnungen — billing records
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- kunden — customers (Hausverwaltungen)
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- objekte — properties/buildings (Liegenschaften)
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- nutzeinheit — apartments/units within Objekte
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- nutzer — tenants/occupants of Nutzeinheiten
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- geraete — measurement devices (Heizkostenverteiler, etc.)
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- geraeteverbraeuche — consumption readings
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- abrechnungen — heating cost billings
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- auftraege — work orders for Monteure
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- auftragspositionen — line items within Auftraege
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- geraetetypen — device type catalog
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- geraetekatalog — device model catalog
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- heizbetriebskosten — heating operation costs
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- nebenkosten — additional costs (Nebenkosten)
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CRITICAL: You do NOT know the exact column names. They are German and unpredictable.
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Your FIRST tool_sequence step for ANY SELECT query MUST be DESCRIBE on the target table.
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Then use the actual column names from the DESCRIBE result in your SELECT.
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KNOWN PRIMARY KEYS AND FOREIGN KEYS:
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- kunden: PK = Kundennummer (int), name columns: Name1, Name2, Name3
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- objekte: PK = ObjektID, FK = KundenID → kunden.Kundennummer
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- nutzeinheit: FK = ObjektID → objekte.ObjektID
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- geraete: FK = NutzeinheitID → nutzeinheit.NutzeinheitID (verify with DESCRIBE)
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Example tool_sequence for "show me 5 customers":
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IMPORTANT: Always DESCRIBE tables you haven't seen before to verify column names.
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Use the FK mappings above for JOINs. Do NOT guess — use exact column names.
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Example for "how many Objekte per Kunde":
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[
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{{"tool": "query_db", "args": {{"query": "DESCRIBE kunden", "database": "eras2_production"}}}},
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{{"tool": "query_db", "args": {{"query": "SELECT * FROM kunden LIMIT 5", "database": "eras2_production"}}}}
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{{"tool": "query_db", "args": {{"query": "SELECT k.Kundennummer, k.Name1, COUNT(o.ObjektID) as AnzahlObjekte FROM kunden k LEFT JOIN objekte o ON o.KundenID = k.Kundennummer GROUP BY k.Kundennummer, k.Name1 ORDER BY AnzahlObjekte DESC LIMIT 20", "database": "eras2_production"}}}}
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]"""
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def __init__(self, send_hud, process_manager=None):
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super().__init__(send_hud, process_manager)
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self._schema_cache: dict[str, str] = {} # table_name -> DESCRIBE result
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self._schema_cache: dict[str, str] = {}
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async def execute(self, job: str, language: str = "de"):
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"""Execute with schema auto-discovery. Caches DESCRIBE results."""
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# Inject cached schema into the job context
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if self._schema_cache:
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schema_ctx = "Known column names from previous DESCRIBE:\n"
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for table, desc in self._schema_cache.items():
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# Just first 5 lines to keep it compact
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lines = desc.strip().split("\n")[:6]
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lines = desc.strip().split("\n")[:8]
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schema_ctx += f"\n{table}:\n" + "\n".join(lines) + "\n"
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job = job + "\n\n" + schema_ctx
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result = await super().execute(job, language)
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# Cache any DESCRIBE results from this execution
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# Parse from tool_output if it looks like a DESCRIBE result
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# Cache DESCRIBE results
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if result.tool_output and "Field\t" in result.tool_output:
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# Try to identify which table was described
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for table in ["kunden", "objekte", "nutzeinheit", "geraete",
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"geraeteverbraeuche", "abrechnungen"]:
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for table in ["kunden", "objekte", "nutzeinheit", "nutzer", "geraete",
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"geraeteverbraeuche", "abrechnungen", "auftraege"]:
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if table in job.lower() or table in result.tool_output.lower():
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self._schema_cache[table] = result.tool_output
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log.info(f"[eras] cached schema for {table}")
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@ -77,22 +77,67 @@ Write a concise, natural response. 1-3 sentences.
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super().__init__(send_hud)
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async def execute(self, job: str, language: str = "de") -> ThoughtResult:
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"""Execute a self-contained job. Returns ThoughtResult."""
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"""Execute a self-contained job. Returns ThoughtResult.
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Uses iterative plan-execute: if DESCRIBE queries are in the plan,
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execute them first, inject results into a re-plan, then execute the rest."""
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await self.hud("thinking", detail=f"planning: {job[:80]}")
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# Step 1: Plan tool sequence
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schema_context = self.SCHEMA
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plan_messages = [
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{"role": "system", "content": self.PLAN_SYSTEM.format(
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domain=self.DOMAIN_SYSTEM, schema=self.SCHEMA,
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domain=self.DOMAIN_SYSTEM, schema=schema_context,
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database=self.default_database)},
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{"role": "user", "content": f"Job: {job}"},
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]
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plan_raw = await llm_call(self.model, plan_messages)
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tool_sequence, response_hint = self._parse_plan(plan_raw)
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# Step 1b: Execute DESCRIBE queries first, then re-plan with actual schema
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describe_results = {}
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remaining_tools = []
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for step in tool_sequence:
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if step.get("tool") == "query_db":
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query = step.get("args", {}).get("query", "").strip().upper()
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if query.startswith("DESCRIBE") or query.startswith("SHOW"):
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await self.hud("tool_call", tool="query_db", args=step.get("args", {}))
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try:
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result = await asyncio.to_thread(
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run_db_query, step["args"]["query"],
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step["args"].get("database", self.default_database))
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describe_results[step["args"]["query"]] = result
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await self.hud("tool_result", tool="query_db", output=result[:200])
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except Exception as e:
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await self.hud("tool_result", tool="query_db", output=str(e)[:200])
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else:
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remaining_tools.append(step)
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else:
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remaining_tools.append(step)
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# Re-plan if we got DESCRIBE results (now we know actual column names)
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if describe_results:
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schema_update = "Actual column names from DESCRIBE:\n"
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for q, result in describe_results.items():
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schema_update += f"\n{q}:\n{result[:500]}\n"
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replan_messages = [
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{"role": "system", "content": self.PLAN_SYSTEM.format(
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domain=self.DOMAIN_SYSTEM,
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schema=schema_context + "\n\n" + schema_update,
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database=self.default_database)},
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{"role": "user", "content": f"Job: {job}\n\nUse ONLY the actual column names from DESCRIBE above. Do NOT include DESCRIBE steps — they are already done."},
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]
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replan_raw = await llm_call(self.model, replan_messages)
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new_tools, new_hint = self._parse_plan(replan_raw)
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if new_tools:
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remaining_tools = new_tools
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if new_hint:
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response_hint = new_hint
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tool_sequence = remaining_tools
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await self.hud("planned", tools=len(tool_sequence), hint=response_hint[:80])
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# Step 2: Execute tools
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# Step 2: Execute remaining tools
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actions = []
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state_updates = {}
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display_items = []
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@ -57,7 +57,7 @@ Rules:
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{memory_context}"""
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EXPERT_DESCRIPTIONS = {
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"eras": "eras — heating/energy domain. Database: eras2_production (customers, devices, billing, consumption). Can also build dashboard UI (buttons, machines, counters, tables) for energy data workflows.",
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"eras": "eras — Heizkostenabrechnung (German heating cost billing). Users are Hausverwaltungen managing Kunden, Objekte (buildings), Nutzeinheiten (apartments), Geraete (meters), Verbraeuche (readings), Abrechnungen (billings), Auftraege (work orders). Hierarchy: Kunde > Objekte > Nutzeinheiten > Geraete > Verbraeuche. Database: eras2_production. Can also build dashboard UI.",
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"plankiste": "plankiste — Kita planning domain. Database: plankiste_test (children, care schedules, offers, pricing). Can build dashboard UI for education workflows and generate Angebote.",
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}
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@ -17,7 +17,7 @@ log = logging.getLogger("runtime")
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TRACE_FILE = Path(__file__).parent.parent / "trace.jsonl"
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# Default graph — can be switched at runtime
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_active_graph_name = "v1-current"
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_active_graph_name = "v4-eras"
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class OutputSink:
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@ -953,6 +953,24 @@ function send() {
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inputEl.value = '';
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}
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async function clearSession() {
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try {
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const headers = { 'Content-Type': 'application/json' };
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if (authToken) headers['Authorization'] = 'Bearer ' + authToken;
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await fetch('/api/clear', { method: 'POST', headers });
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// Clear UI
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msgs.innerHTML = '';
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traceEl.innerHTML = '';
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_currentDashboard = [];
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currentEl = null;
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const dock = document.getElementById('dock');
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if (dock) dock.innerHTML = '';
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addTrace('runtime', 'cleared', 'session reset');
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} catch (e) {
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addTrace('runtime', 'error', 'clear failed: ' + e);
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}
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}
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// --- Awareness panel updates ---
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let _sensorReadings = {};
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@ -16,6 +16,8 @@
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<h1>cog</h1>
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<div id="test-status"></div>
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<div style="flex:1"></div>
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<div id="graph-switcher"></div>
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<button onclick="clearSession()" class="btn-top" title="Clear session">Clear</button>
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<div id="status">disconnected</div>
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</div>
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@ -27,17 +29,7 @@
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</div>
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<div class="panel detail-panel">
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<div class="panel-header detail-h">Nodes</div>
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<div id="node-metrics">
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<div class="node-meter" id="meter-input"><span class="nm-label">input</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-director_v2"><span class="nm-label">director</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-pa_v1"><span class="nm-label">PA</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-thinker"><span class="nm-label">thinker</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-eras_expert"><span class="nm-label">eras</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-output"><span class="nm-label">output</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-memorizer"><span class="nm-label">memo</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-interpreter"><span class="nm-label">interp</span><div class="nm-bar"><div class="nm-fill"></div></div><span class="nm-text"></span></div>
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<div class="node-meter" id="meter-sensor"><span class="nm-label">sensor</span><span class="nm-text" style="flex:1"></span></div>
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</div>
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<div id="node-metrics"></div>
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</div>
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<div class="panel graph-panel">
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<div class="panel-header graph-h">Graph
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@ -58,7 +50,6 @@
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<div id="input-bar">
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<input id="input" placeholder="Type a message..." autocomplete="off">
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<button onclick="send()">Send</button>
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<button onclick="clearSession()" class="btn-clear" title="Clear session">✕</button>
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</div>
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</div>
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<div class="panel awareness-panel">
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@ -1,9 +1,133 @@
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/** Awareness panel: memorizer state, sensor readings, node meters. */
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/** Awareness panel: memorizer state, sensor readings.
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* Node detail panel: per-node model, tokens, progress, last event.
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*/
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import { esc, truncate } from './util.js';
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let _sensorReadings = {};
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// --- Node state tracker ---
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const _nodeState = {}; // { nodeName: { model, tokens, maxTokens, fillPct, lastEvent, lastDetail, status, toolCalls, startedAt } }
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function _getNode(name) {
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if (!_nodeState[name]) {
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_nodeState[name] = {
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model: '', tokens: 0, maxTokens: 0, fillPct: 0,
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lastEvent: '', lastDetail: '', status: 'idle',
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toolCalls: 0, lastTool: '',
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};
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}
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return _nodeState[name];
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}
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export function updateNodeFromHud(node, event, data) {
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const n = _getNode(node);
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if (event === 'context') {
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if (data.model) n.model = data.model.replace('google/', '').replace('anthropic/', '');
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if (data.tokens !== undefined) n.tokens = data.tokens;
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if (data.max_tokens !== undefined) n.maxTokens = data.max_tokens;
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if (data.fill_pct !== undefined) n.fillPct = data.fill_pct;
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}
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if (event === 'thinking') {
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n.status = 'thinking';
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n.lastEvent = 'thinking';
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n.lastDetail = data.detail || '';
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} else if (event === 'perceived') {
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n.status = 'done';
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n.lastEvent = 'perceived';
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const a = data.analysis || {};
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n.lastDetail = `${a.intent || '?'}/${a.language || '?'}/${a.tone || '?'}`;
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} else if (event === 'decided' || event === 'routed') {
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n.status = 'done';
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n.lastEvent = event;
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n.lastDetail = data.goal || data.instruction || data.job || '';
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} else if (event === 'tool_call') {
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n.status = 'tool';
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n.lastEvent = 'tool_call';
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n.lastTool = data.tool || '';
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n.lastDetail = data.tool || '';
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n.toolCalls++;
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} else if (event === 'tool_result') {
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n.lastEvent = 'tool_result';
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n.lastDetail = truncate(data.output || '', 50);
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} else if (event === 'streaming') {
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n.status = 'streaming';
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n.lastEvent = 'streaming';
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} else if (event === 'done') {
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n.status = 'done';
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n.lastEvent = 'done';
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} else if (event === 'updated') {
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n.status = 'done';
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n.lastEvent = 'updated';
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} else if (event === 'planned') {
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n.status = 'planned';
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||||
n.lastEvent = 'planned';
|
||||
n.lastDetail = `${data.tools || 0} tools`;
|
||||
} else if (event === 'interpreted') {
|
||||
n.status = 'done';
|
||||
n.lastEvent = 'interpreted';
|
||||
n.lastDetail = truncate(data.summary || '', 50);
|
||||
}
|
||||
|
||||
renderNodes();
|
||||
}
|
||||
|
||||
function renderNodes() {
|
||||
const el = document.getElementById('node-metrics');
|
||||
if (!el) { console.warn('[nodes] #node-metrics not found'); return; }
|
||||
|
||||
// Sort: active nodes first, then by name
|
||||
const statusOrder = { thinking: 0, tool: 0, streaming: 0, planned: 1, done: 2, idle: 3 };
|
||||
const sorted = Object.entries(_nodeState)
|
||||
.filter(([name]) => name !== 'runtime' && name !== 'frame_engine')
|
||||
.sort((a, b) => (statusOrder[a[1].status] || 3) - (statusOrder[b[1].status] || 3));
|
||||
|
||||
let html = '';
|
||||
for (const [name, n] of sorted) {
|
||||
const statusClass = n.status === 'thinking' || n.status === 'tool' ? 'nm-active'
|
||||
: n.status === 'streaming' ? 'nm-streaming' : '';
|
||||
const shortName = name.replace('_v1', '').replace('_v2', '').replace('expert_', '');
|
||||
const modelShort = n.model ? n.model.split('/').pop().replace('-001', '').replace('-4.5', '4.5') : '';
|
||||
const tokenStr = n.maxTokens ? `${n.tokens}/${n.maxTokens}t` : '';
|
||||
const fillW = n.fillPct || 0;
|
||||
const detail = n.lastDetail ? truncate(n.lastDetail, 45) : '';
|
||||
const toolStr = n.toolCalls > 0 ? ` [${n.toolCalls} calls]` : '';
|
||||
|
||||
html += `<div class="node-card ${statusClass}">
|
||||
<div class="nc-header">
|
||||
<span class="nc-name">${esc(shortName)}</span>
|
||||
<span class="nc-model">${esc(modelShort)}</span>
|
||||
<span class="nc-tokens">${esc(tokenStr)}</span>
|
||||
</div>
|
||||
<div class="nc-bar"><div class="nc-fill" style="width:${fillW}%"></div></div>
|
||||
<div class="nc-status">
|
||||
<span class="nc-event">${esc(n.lastEvent)}</span>
|
||||
<span class="nc-detail">${esc(detail)}${esc(toolStr)}</span>
|
||||
</div>
|
||||
</div>`;
|
||||
}
|
||||
el.innerHTML = html;
|
||||
}
|
||||
|
||||
export function clearNodes() {
|
||||
for (const key of Object.keys(_nodeState)) delete _nodeState[key];
|
||||
const el = document.getElementById('node-metrics');
|
||||
if (el) el.innerHTML = '';
|
||||
}
|
||||
|
||||
// Keep old meter function for backward compat (called from ws.js)
|
||||
export function updateMeter(node, tokens, maxTokens, fillPct) {
|
||||
const n = _getNode(node);
|
||||
n.tokens = tokens;
|
||||
n.maxTokens = maxTokens;
|
||||
n.fillPct = fillPct;
|
||||
renderNodes();
|
||||
}
|
||||
|
||||
// --- Awareness: memorizer state ---
|
||||
|
||||
export function updateAwarenessState(state) {
|
||||
const body = document.getElementById('aw-state-body');
|
||||
if (!body) return;
|
||||
@ -33,6 +157,8 @@ export function updateAwarenessState(state) {
|
||||
body.innerHTML = html;
|
||||
}
|
||||
|
||||
// --- Awareness: sensor readings ---
|
||||
|
||||
export function updateAwarenessSensors(tick, deltas) {
|
||||
const body = document.getElementById('aw-sensor-body');
|
||||
if (!body) return;
|
||||
@ -46,12 +172,3 @@ export function updateAwarenessSensors(tick, deltas) {
|
||||
}
|
||||
body.innerHTML = html;
|
||||
}
|
||||
|
||||
export function updateMeter(node, tokens, maxTokens, fillPct) {
|
||||
const meter = document.getElementById('meter-' + node);
|
||||
if (!meter) return;
|
||||
const bar = meter.querySelector('.nm-bar');
|
||||
const text = meter.querySelector('.nm-text');
|
||||
if (bar) bar.style.width = fillPct + '%';
|
||||
if (text) text.textContent = `${tokens}/${maxTokens}t`;
|
||||
}
|
||||
|
||||
@ -4,6 +4,7 @@ import { initAuth, authToken, startLogin } from './auth.js';
|
||||
import { initTrace, addTrace, clearTrace } from './trace.js';
|
||||
import { initChat, clearChat } from './chat.js';
|
||||
import { clearDashboard } from './dashboard.js';
|
||||
import { clearNodes } from './awareness.js';
|
||||
import { initGraph } from './graph.js';
|
||||
import { connect } from './ws.js';
|
||||
|
||||
@ -12,10 +13,13 @@ window.addEventListener('load', async () => {
|
||||
initTrace();
|
||||
initChat();
|
||||
await initGraph();
|
||||
await initAuth(() => connect());
|
||||
await initAuth(() => {
|
||||
connect();
|
||||
loadGraphSwitcher();
|
||||
});
|
||||
});
|
||||
|
||||
// Clear session button
|
||||
// Clear session
|
||||
window.clearSession = async () => {
|
||||
try {
|
||||
const headers = { 'Content-Type': 'application/json' };
|
||||
@ -24,11 +28,63 @@ window.clearSession = async () => {
|
||||
clearChat();
|
||||
clearTrace();
|
||||
clearDashboard();
|
||||
clearNodes();
|
||||
addTrace('runtime', 'cleared', 'session reset');
|
||||
} catch (e) {
|
||||
addTrace('runtime', 'error', 'clear failed: ' + e);
|
||||
}
|
||||
};
|
||||
|
||||
// Login button
|
||||
// Graph switcher — loads available graphs and shows buttons in top bar
|
||||
async function loadGraphSwitcher() {
|
||||
const container = document.getElementById('graph-switcher');
|
||||
if (!container) { console.error('[main] no #graph-switcher'); return; }
|
||||
try {
|
||||
const headers = {};
|
||||
if (authToken) headers['Authorization'] = 'Bearer ' + authToken;
|
||||
const r = await fetch('/api/graph/list', { headers });
|
||||
if (!r.ok) { console.error('[main] graph/list failed:', r.status); return; }
|
||||
const data = await r.json();
|
||||
const graphs = data.graphs || data || [];
|
||||
console.log('[main] graphs:', graphs.length);
|
||||
|
||||
// Get current active graph
|
||||
let activeGraph = '';
|
||||
try {
|
||||
const ar = await fetch('/api/graph/active', { headers });
|
||||
if (ar.ok) {
|
||||
const ag = await ar.json();
|
||||
activeGraph = ag.name || '';
|
||||
}
|
||||
} catch (e) {}
|
||||
|
||||
container.innerHTML = graphs.map(g => {
|
||||
const active = g.name === activeGraph;
|
||||
return `<button class="btn-graph${active ? ' active' : ''}" onclick="switchGraph('${g.name}')" title="${g.description}">${g.name}</button>`;
|
||||
}).join('');
|
||||
} catch (e) {}
|
||||
}
|
||||
|
||||
window.switchGraph = async (name) => {
|
||||
try {
|
||||
const headers = { 'Content-Type': 'application/json' };
|
||||
if (authToken) headers['Authorization'] = 'Bearer ' + authToken;
|
||||
await fetch('/api/graph/switch', {
|
||||
method: 'POST', headers,
|
||||
body: JSON.stringify({ name }),
|
||||
});
|
||||
addTrace('runtime', 'graph_switch', name);
|
||||
clearChat();
|
||||
clearTrace();
|
||||
clearDashboard();
|
||||
clearNodes();
|
||||
addTrace('runtime', 'switched', `graph: ${name}`);
|
||||
await initGraph();
|
||||
loadGraphSwitcher();
|
||||
} catch (e) {
|
||||
addTrace('runtime', 'error', 'switch failed: ' + e);
|
||||
}
|
||||
};
|
||||
|
||||
// Login
|
||||
window.startLogin = startLogin;
|
||||
|
||||
@ -5,7 +5,7 @@ import { addTrace } from './trace.js';
|
||||
import { handleDelta, handleDone, setWs as setChatWs } from './chat.js';
|
||||
import { dockControls, setWs as setDashWs } from './dashboard.js';
|
||||
import { graphAnimate } from './graph.js';
|
||||
import { updateMeter, updateAwarenessState, updateAwarenessSensors } from './awareness.js';
|
||||
import { updateMeter, updateNodeFromHud, updateAwarenessState, updateAwarenessSensors } from './awareness.js';
|
||||
import { updateTestStatus } from './tests.js';
|
||||
import { truncate, esc } from './util.js';
|
||||
|
||||
@ -35,7 +35,8 @@ export function connect() {
|
||||
ws.onerror = () => {};
|
||||
|
||||
ws.onclose = (e) => {
|
||||
if (e.code === 4001 || e.code === 1006) {
|
||||
// 4001 = explicit auth rejection from server
|
||||
if (e.code === 4001) {
|
||||
setAuthFailed(true);
|
||||
localStorage.removeItem('cog_token');
|
||||
localStorage.removeItem('cog_access_token');
|
||||
@ -44,9 +45,10 @@ export function connect() {
|
||||
showLogin();
|
||||
return;
|
||||
}
|
||||
document.getElementById('status').textContent = 'disconnected';
|
||||
document.getElementById('status').style.color = '#666';
|
||||
addTrace('runtime', 'disconnected', 'ws closed');
|
||||
// 1006 = abnormal close (deploy, network), just reconnect
|
||||
document.getElementById('status').textContent = 'reconnecting...';
|
||||
document.getElementById('status').style.color = '#f59e0b';
|
||||
addTrace('runtime', 'disconnected', `code ${e.code}, reconnecting...`);
|
||||
setTimeout(connect, 2000);
|
||||
};
|
||||
|
||||
@ -123,6 +125,7 @@ function handleHud(data) {
|
||||
const event = data.event || '';
|
||||
|
||||
graphAnimate(event, node);
|
||||
updateNodeFromHud(node, event, data);
|
||||
|
||||
if (event === 'context') {
|
||||
const count = (data.messages || []).length;
|
||||
|
||||
@ -10,10 +10,16 @@ body { font-family: system-ui, sans-serif; background: #0a0a0a; color: #e0e0e0;
|
||||
#test-status .ts-pass { color: #22c55e; }
|
||||
#test-status .ts-fail { color: #ef4444; }
|
||||
@keyframes pulse-text { 0%,100% { opacity: 1; } 50% { opacity: 0.5; } }
|
||||
.btn-top { padding: 0.2rem 0.6rem; font-size: 0.7rem; background: #333; }
|
||||
.btn-top:hover { background: #ef4444; }
|
||||
#graph-switcher { display: flex; gap: 3px; }
|
||||
.btn-graph { padding: 0.2rem 0.5rem; font-size: 0.65rem; font-family: monospace; background: #1a1a1a; color: #888; border: 1px solid #333; border-radius: 3px; cursor: pointer; }
|
||||
.btn-graph:hover { color: #fff; border-color: #2563eb; }
|
||||
.btn-graph.active { color: #22c55e; border-color: #22c55e; background: #0a1e14; }
|
||||
|
||||
/* === Two-row layout === */
|
||||
/* Middle row: workspace | node detail | graph */
|
||||
#middle-row { display: grid; grid-template-columns: 1fr 200px 2fr; gap: 1px; background: #222; flex: 1; min-height: 0; }
|
||||
#middle-row { display: grid; grid-template-columns: 1fr 300px 2fr; gap: 1px; background: #222; flex: 1; min-height: 0; }
|
||||
/* Bottom row: chat | awareness | trace */
|
||||
#bottom-row { display: grid; grid-template-columns: 1fr 1fr 2fr; gap: 1px; background: #222; flex: 1; min-height: 0; }
|
||||
|
||||
@ -36,12 +42,19 @@ body { font-family: system-ui, sans-serif; background: #0a0a0a; color: #e0e0e0;
|
||||
|
||||
/* Node detail / metrics */
|
||||
.detail-panel { display: flex; flex-direction: column; }
|
||||
#node-metrics { flex: 1; overflow-y: auto; padding: 0.3rem; display: flex; flex-direction: column; gap: 1px; }
|
||||
.node-meter { display: flex; align-items: center; gap: 0.3rem; padding: 0.2rem 0.4rem; background: #111; border-radius: 2px; }
|
||||
.nm-label { font-size: 0.6rem; font-weight: 700; text-transform: uppercase; letter-spacing: 0.03em; min-width: 3.5rem; color: #888; }
|
||||
.nm-bar { flex: 1; height: 5px; background: #1a1a1a; border-radius: 3px; overflow: hidden; }
|
||||
.nm-fill { height: 100%; width: 0%; border-radius: 3px; transition: width 0.3s; background: #333; }
|
||||
.nm-text { font-size: 0.55rem; color: #555; min-width: 3rem; text-align: right; font-family: monospace; }
|
||||
#node-metrics { flex: 1; overflow-y: auto; padding: 0.3rem; display: flex; flex-direction: column; gap: 2px; }
|
||||
.node-card { background: #111; border-radius: 3px; padding: 0.25rem 0.4rem; border-left: 2px solid #333; }
|
||||
.node-card.nm-active { border-left-color: #f59e0b; background: #1a1408; }
|
||||
.node-card.nm-streaming { border-left-color: #22c55e; background: #0a1e14; }
|
||||
.nc-header { display: flex; align-items: center; gap: 0.3rem; }
|
||||
.nc-name { font-size: 0.65rem; font-weight: 700; text-transform: uppercase; color: #e0e0e0; min-width: 3rem; }
|
||||
.nc-model { font-size: 0.55rem; color: #666; font-family: monospace; }
|
||||
.nc-tokens { font-size: 0.55rem; color: #555; font-family: monospace; margin-left: auto; }
|
||||
.nc-bar { height: 3px; background: #1a1a1a; border-radius: 2px; overflow: hidden; margin: 2px 0; }
|
||||
.nc-fill { height: 100%; border-radius: 2px; background: #333; transition: width 0.3s; }
|
||||
.nc-status { display: flex; gap: 0.3rem; align-items: baseline; }
|
||||
.nc-event { font-size: 0.55rem; color: #888; font-family: monospace; }
|
||||
.nc-detail { font-size: 0.55rem; color: #666; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
|
||||
|
||||
/* Graph panel */
|
||||
.graph-panel { display: flex; flex-direction: column; }
|
||||
|
||||
40
testcases/domain_context.md
Normal file
40
testcases/domain_context.md
Normal file
@ -0,0 +1,40 @@
|
||||
# Domain Context
|
||||
|
||||
Tests that the expert understands the Eras business domain:
|
||||
Heizkostenabrechnung, Kunde→Objekt→Nutzeinheit→Geraet hierarchy,
|
||||
and can formulate correct JOINs without guessing column names.
|
||||
|
||||
## Setup
|
||||
- clear history
|
||||
|
||||
## Steps
|
||||
|
||||
### 1. Expert knows the hierarchy
|
||||
- send: wie viele Objekte haben Kunden im Durchschnitt?
|
||||
- expect_trace: has tool_call
|
||||
- expect_response: not contains "Error" or "error" or "Unknown column"
|
||||
- expect_response: length > 20
|
||||
|
||||
### 2. Expert can JOIN kunden and objekte
|
||||
- send: zeig mir die Top 5 Kunden mit den meisten Objekten
|
||||
- expect_trace: has tool_call
|
||||
- expect_response: not contains "Error" or "error" or "Unknown column"
|
||||
- expect_response: length > 20
|
||||
|
||||
### 3. Expert understands Nutzeinheiten belong to Objekte
|
||||
- send: how many Nutzeinheiten does the system have total?
|
||||
- expect_trace: has tool_call
|
||||
- expect_response: not contains "Error" or "error" or "Unknown column"
|
||||
- expect_response: length > 10
|
||||
|
||||
### 4. Expert understands Geraete belong to Nutzeinheiten
|
||||
- send: which Objekt has the most Geraete?
|
||||
- expect_trace: has tool_call
|
||||
- expect_response: not contains "Error" or "error" or "Unknown column"
|
||||
- expect_response: length > 20
|
||||
|
||||
### 5. PA formulates good job descriptions
|
||||
- send: gib mir eine Uebersicht ueber Kunde 2
|
||||
- expect_trace: has routed
|
||||
- expect_response: length > 20
|
||||
- expect_response: not contains "clarify" or "specify" or "what kind"
|
||||
Loading…
x
Reference in New Issue
Block a user