Boilerplate completo para construir soluciones agénticas sobre IBM watsonx Orchestrate (ADK 2.x) con una capa web encima. Destilado de cotemar-poc-n1 y dun-casos-prueba. Incluye: - 11 docs (best practices, architecture patterns, ADK cheatsheet, observability, tool authoring, deployment, RUNBOOK, DEPLOY_TO_NEW_WOX, known-issues con 16 errores reales y fix, eval strategy, INDEX) - 13 templates WxO (orchestrator/specialist/single-meta agents, 3 connections, KB + runbook, observable_tool decorator, coercion helpers, Python tools, OpenAPI spec, backend filter endpoint, webhook validator HMAC, MCP connection) - 6 scripts (deploy idempotente con fallback ADK, undeploy, reset, check-adk-version, new-specialist scaffold, eval-agents runner) - 4 eval pieces (linter de best practices, runner, smoke-test, direct backend probe) + scenario templates - 8 subagentes Claude (.claude/agents/) — wxo-architect, wxo-agent-author, wxo-tool-author, runbook-author, mock-builder, backend-tool-builder, eval-author, web-layer-builder - Skill bundle fit-wxo-bootstrap/ (SKILL.md + 3 templates) listo para copiar a ~/.claude/skills/ - Web layer default FastAPI+HTMX con vista timeline observable + endpoint receptor de trazas - Docker compose Coolify-ready (healthcheck wget -qO-, sin labels Traefik, network split internal:true) - CI Gitea workflow con lint + smoke Best practices enforced por evals/lint_wxo_yaml.py: - A1: máx 10 tools por agente - A3: orchestrator sin tools de remediación - A6: agente sin propósito (react sin tools ni KB) - T1: @observable_tool obligatorio, no @tool directo - T3: _compat shim inline en tools.py - D1: docker-compose sin wget --spider - I-005: OpenAPI con description per-operation - I-009: sin labels Traefik manuales Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
142 lines
4.3 KiB
Python
142 lines
4.3 KiB
Python
#!/usr/bin/env python3
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"""Eval runner — Capas 2 (behavior) y 3 (final state).
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Lee `evals/scenarios/*.yaml`, ejecuta cada scenario contra el agente
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correspondiente, y verifica las trazas observables + estado final.
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Formato del scenario YAML (ver docs/eval-strategy.md):
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name: reset_password_happy_path
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agent: ad_specialist_cotemar
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input: "Necesito resetear..."
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expect:
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agent_response_contains: ["TKT-"]
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tool_calls_in_order:
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- tool: lookup_user
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- tool: reset_password
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- tool: create_ticket
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no_tool_calls:
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- escalate_to_n2
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final_state:
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# ... asserts contra DB / API
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"""
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from __future__ import annotations
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import json
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import os
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import sys
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import sqlite3
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import time
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from pathlib import Path
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try:
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import yaml
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except ImportError:
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print("✗ pyyaml required: pip install pyyaml", file=sys.stderr)
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sys.exit(2)
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ROOT = Path(__file__).resolve().parent.parent
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SCENARIOS_DIR = ROOT / "evals" / "scenarios"
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TRACES_DB = os.environ.get("TRACES_DB_PATH", "/tmp/traces.db")
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def run_scenario(spec: dict) -> tuple[bool, list[str]]:
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"""Returns (passed, errors)."""
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errors: list[str] = []
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name = spec.get("name", "?")
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agent = spec.get("agent")
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input_text = spec.get("input")
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expect = spec.get("expect", {})
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if not agent or not input_text:
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return False, ["scenario sin 'agent' o 'input'"]
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started = int(time.time() * 1000)
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# 1) Mandar el input al agente (usando orchestrate CLI)
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fixture = {"messages": [{"role": "user", "content": input_text}]}
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fixture_path = Path("/tmp") / f"_eval_{name}.json"
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fixture_path.write_text(json.dumps(fixture))
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import subprocess
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proc = subprocess.run(
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["orchestrate", "agents", "test", agent, "--input-file", str(fixture_path)],
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capture_output=True, text=True, timeout=120,
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)
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output = proc.stdout + "\n" + proc.stderr
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# 2) Verificar response (Capa 2)
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for needle in expect.get("agent_response_contains", []):
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if needle not in output:
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errors.append(f"agent_response_contains: '{needle}' not in output")
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# 3) Verificar tool calls vía trazas (Capa 2)
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traces = _read_traces_since(started)
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tool_names = [t["tool"] for t in traces]
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expected_order = [t.get("tool") for t in expect.get("tool_calls_in_order", [])]
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if expected_order:
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if not _is_subsequence(expected_order, tool_names):
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errors.append(f"tool_calls_in_order: expected {expected_order}, got {tool_names}")
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for bad_tool in expect.get("no_tool_calls", []):
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if bad_tool in tool_names:
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errors.append(f"no_tool_calls: {bad_tool} should NOT have been called")
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# 4) Final state (Capa 3) — placeholder, depende del backend
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# TODO en v2: parametrizable según backend del proyecto
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final_state = spec.get("final_state")
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if final_state:
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# Stub — implementación específica del proyecto
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pass
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return (len(errors) == 0), errors
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def _is_subsequence(needle: list[str], haystack: list[str]) -> bool:
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"""¿`needle` es subsequence de `haystack`? (order preserved, gaps OK)"""
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it = iter(haystack)
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return all(x in it for x in needle)
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def _read_traces_since(ts_ms: int) -> list[dict]:
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if not Path(TRACES_DB).exists():
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return []
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conn = sqlite3.connect(TRACES_DB)
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rows = conn.execute(
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"SELECT payload FROM traces WHERE started_at >= datetime(?, 'unixepoch')",
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(ts_ms / 1000,)
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).fetchall()
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conn.close()
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return [json.loads(r[0]) for r in rows]
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def main() -> int:
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scenarios = sorted(SCENARIOS_DIR.glob("*.yaml"))
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if not scenarios:
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print("(no scenarios in evals/scenarios/*.yaml — skipping)")
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return 0
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pass_count = 0
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fail_count = 0
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for f in scenarios:
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if f.name.startswith("_"):
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continue
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spec = yaml.safe_load(f.read_text())
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name = spec.get("name", f.stem)
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ok, errors = run_scenario(spec)
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if ok:
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print(f" ✓ {name}")
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pass_count += 1
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else:
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print(f" ✗ {name}")
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for e in errors:
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print(f" - {e}")
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fail_count += 1
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print(f"\n Total: {pass_count} pass / {fail_count} fail")
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return 0 if fail_count == 0 else 1
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if __name__ == "__main__":
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sys.exit(main())
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