feat(connectors): add OrchestratorConnector base and stubbed Ansible
Multi-step workflow base class with plan/execute lifecycle and partial-completion reporting. Ansible connector stubbed — ansible-runner integration in future sprint. Credentials resolved per-host at runtime via CredentialResolver, never stored. Signed-off-by: Tyler King <tking@guildhouse.dev>
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137
gsap_broker/connectors/ansible.py
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137
gsap_broker/connectors/ansible.py
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# Copyright 2026 Guildhouse Dev
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# SPDX-License-Identifier: Apache-2.0
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"""Ansible connector — fleet management via Ansible playbooks.
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The Ansible connector is an OrchestratorConnector: it plans a
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sequence of steps (playbook runs, ad-hoc commands, fact collection)
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and executes them via ansible-runner.
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Credential model:
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Ansible does NOT receive credentials from the broker. Instead,
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the connector passes a credential callback that ansible-runner's
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credential plugin calls at runtime. This callback resolves
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credentials via the broker's CredentialResolver for each target
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host at the moment the task runs — not at planning time.
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This means:
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- The Ansible inventory file contains NO passwords or keys.
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- Each host's credentials are resolved just-in-time from the
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secrets backend (Entra, Vault, etc).
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- If a credential expires mid-playbook, the next task for that
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host will resolve a fresh credential.
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Real integration:
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Library: ``ansible-runner`` (execution library)
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Auth: Per-host credential resolution via custom credential plugin
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Inventory: Dynamic inventory from Intune device cache or Bascule
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fleet registry
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Stubbed in this sprint — steps return placeholder results.
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"""
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from __future__ import annotations
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from typing import Any
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from gsap_broker.connectors.base import ConnectorContext
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from gsap_broker.connectors.orchestrator import (
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OrchestratorConnector,
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WorkflowPlan,
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WorkflowStep,
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)
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from gsap_broker.credentials.resolver import CredentialResolver
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class AnsibleConnector(OrchestratorConnector):
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"""Fleet management via Ansible playbooks."""
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connector_id = "ansible"
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corpus_entry_cid = "sha256:ansible-connector-v1"
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capability_mask = 0x7 # READ | PROPOSE | MUTATE
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declared_endpoints = ["ansible://*"]
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accord_template = "fleet-management"
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gsap_required = True
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chronicle_enabled = True
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def __init__(self, credential_resolver: CredentialResolver):
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super().__init__(credential_resolver)
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async def plan(
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self, operation: str, parameters: dict[str, Any], context: ConnectorContext
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) -> WorkflowPlan:
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"""Map operations to workflow plans.
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Operations:
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"playbook" → single step running the named playbook
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"adhoc" → single step running a module on targets
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"collect" → single step gathering facts
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"role" → single step applying a role
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"""
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targets = parameters.get("targets", [])
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if isinstance(targets, str):
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targets = [targets]
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if operation == "playbook":
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return WorkflowPlan(steps=[
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WorkflowStep(
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name=f"playbook:{parameters.get('playbook', 'site.yml')}",
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command=parameters.get("playbook", "site.yml"),
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targets=targets,
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extra_vars=parameters.get("extra_vars", {}),
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)
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])
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if operation == "adhoc":
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return WorkflowPlan(steps=[
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WorkflowStep(
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name=f"adhoc:{parameters.get('module', 'ping')}",
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command=parameters.get("module", "ping"),
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targets=targets,
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extra_vars=parameters.get("args", {}),
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)
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])
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if operation == "collect":
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return WorkflowPlan(steps=[
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WorkflowStep(
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name="collect:facts",
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command="setup",
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targets=targets,
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required=False, # fact collection is best-effort
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)
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])
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if operation == "role":
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return WorkflowPlan(steps=[
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WorkflowStep(
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name=f"role:{parameters.get('role', '')}",
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command=parameters.get("role", ""),
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targets=targets,
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extra_vars=parameters.get("extra_vars", {}),
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)
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])
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return WorkflowPlan(steps=[
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WorkflowStep(name=f"unknown:{operation}", command=operation, targets=targets)
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])
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async def execute_step(
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self, step: WorkflowStep, context: ConnectorContext
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) -> dict[str, Any]:
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"""Execute a single workflow step via ansible-runner.
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Stubbed — actual ansible-runner integration in a future sprint.
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"""
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# TODO: use ansible_runner.run() with:
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# - playbook=step.command (for playbook operation)
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# - module=step.command, module_args=step.extra_vars (for adhoc)
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# - inventory from dynamic source (Intune cache, Bascule fleet)
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# - credential plugin that calls self._resolver.resolve()
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# per-host at runtime
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return {
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"success": True,
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"stub": True,
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"step": step.name,
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"targets": step.targets,
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}
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112
gsap_broker/connectors/orchestrator.py
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112
gsap_broker/connectors/orchestrator.py
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# Copyright 2026 Guildhouse Dev
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# SPDX-License-Identifier: Apache-2.0
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"""Orchestrator connector framework — multi-step workflow execution.
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Orchestrator connectors manage workflows that span multiple steps
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and potentially multiple targets. Each step may acquire its own
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credentials via the CredentialResolver.
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Unlike ``SessionConnector`` (single target, single credential,
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single command), an ``OrchestratorConnector``:
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- Plans a sequence of steps before execution
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- Executes steps in order, stopping on required-step failure
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- Reports partial results (which steps completed before failure)
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- Can target different hosts per step
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Rust port note:
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``WorkflowStep`` and ``WorkflowPlan`` map to plain structs.
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``OrchestratorConnector`` maps to an async trait with
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``plan()`` and ``execute_step()`` methods.
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"""
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from __future__ import annotations
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import logging
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from abc import abstractmethod
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from dataclasses import dataclass, field
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from typing import Any
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from gsap_broker.connectors.base import ConnectorContext, ConnectorPlugin, ConnectorResult
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from gsap_broker.credentials.resolver import CredentialResolver
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logger = logging.getLogger(__name__)
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@dataclass
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class WorkflowStep:
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"""A single step in a workflow plan."""
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name: str
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command: str
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targets: list[str] = field(default_factory=list)
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required: bool = True
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extra_vars: dict[str, Any] = field(default_factory=dict)
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@dataclass
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class WorkflowPlan:
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"""Ordered sequence of steps for a workflow."""
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steps: list[WorkflowStep] = field(default_factory=list)
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class OrchestratorConnector(ConnectorPlugin):
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"""Base for multi-step workflow connectors (Ansible, Terraform, etc).
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Subclasses implement ``plan()`` to convert an operation + parameters
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into a ``WorkflowPlan``, and ``execute_step()`` to run each step.
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The base ``invoke()`` handles:
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- Planning the workflow
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- Executing steps in order
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- Stopping on required-step failure
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- Aggregating results with partial-completion reporting
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"""
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def __init__(self, credential_resolver: CredentialResolver):
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self._resolver = credential_resolver
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async def invoke(
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self, operation: str, parameters: dict[str, Any], context: ConnectorContext
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) -> ConnectorResult:
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try:
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plan = await self.plan(operation, parameters, context)
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except Exception as e:
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return ConnectorResult(success=False, error=f"Planning failed: {e}")
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if not plan.steps:
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return ConnectorResult(success=True, data={"steps": []})
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results: list[dict[str, Any]] = []
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for step in plan.steps:
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result = await self.execute_step(step, context)
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results.append({"step": step.name, **result})
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if not result.get("success") and step.required:
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return ConnectorResult(
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success=False,
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data={"completed": results, "failed_at": step.name},
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)
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return ConnectorResult(success=True, data={"steps": results})
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@abstractmethod
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async def plan(
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self, operation: str, parameters: dict[str, Any], context: ConnectorContext
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) -> WorkflowPlan:
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"""Convert an operation into a step-by-step execution plan."""
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...
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@abstractmethod
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async def execute_step(
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self, step: WorkflowStep, context: ConnectorContext
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) -> dict[str, Any]:
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"""Execute a single workflow step.
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Returns a dict with at minimum a ``success: bool`` key.
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"""
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...
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def health_check(self) -> bool:
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return True
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