295d43b3ab
The split between ``strix/sandbox/`` and ``strix/runtime/`` was artificial — both were managing the same backend. ``strix/sandbox/`` also collided uncomfortably with the SDK's ``agents.sandbox.*`` namespace. ``runtime/`` (which matches ``STRIX_RUNTIME_BACKEND``) is the canonical home for everything Docker / Daytona / K8s lifecycle. While merging, also rip out two pieces of Docker-specific coupling: - ``caido_bootstrap`` was POSTing ``loginAsGuest`` from the host via ``aiohttp`` to ``http://127.0.0.1:{forwarded_port}``. That assumed Docker port forwarding; Daytona / K8s expose ports differently. Now we ``session.exec`` curl from *inside* the container — the SDK's runtime-agnostic exec primitive — so any backend works as long as it implements ``exec``. The host-side Caido ``Client`` still uses the runtime's exposed-port URL for post-bootstrap calls, but that goes through the SDK's own ``resolve_exposed_port`` abstraction (also runtime-agnostic). - The bootstrap retry loop now doubles as the readiness probe, so ``healthcheck.wait_for_tcp_ready`` (and the entire ``healthcheck.py`` module) goes away. Drive-by simplification: drop ``caido_host_port`` plumbing entirely. It was only piped through ``make_agent_context`` → child contexts without ever being read; only ``caido_client`` is consumed. Drops ``aiohttp`` runtime dep (it stays only as a transitive of the Caido SDK). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
157 lines
5.2 KiB
Python
157 lines
5.2 KiB
Python
"""``make_run_config`` — assemble a Strix-flavored ``RunConfig`` for ``Runner.run``.
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Every scan goes through here so defaults apply uniformly. Per-call
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overrides land via ``model_settings_override``.
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"""
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from __future__ import annotations
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from typing import TYPE_CHECKING, Any, Literal
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from agents import RunConfig
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from agents.model_settings import ModelSettings
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from agents.retry import (
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ModelRetryBackoffSettings,
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ModelRetrySettings,
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retry_policies,
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)
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from agents.sandbox import SandboxRunConfig
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from openai.types.shared import Reasoning
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from strix.llm.multi_provider_setup import build_multi_provider
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from strix.orchestration.filter import inject_messages_filter
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if TYPE_CHECKING:
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from agents.sandbox.session.base_sandbox_session import BaseSandboxSession
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from strix.orchestration.bus import AgentMessageBus
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#: Default ``max_turns`` callers should pass to ``Runner.run``.
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STRIX_DEFAULT_MAX_TURNS = 300
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# Retry: 5 attempts with ``min(90, 2*2^n)`` backoff. 4xx auth/validation
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# errors are excluded from the retryable status list — they can't be
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# fixed by retrying and should fail fast.
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_DEFAULT_RETRY = ModelRetrySettings(
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max_retries=5,
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backoff=ModelRetryBackoffSettings(
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initial_delay=2.0,
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max_delay=90.0,
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multiplier=2.0,
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jitter=False,
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),
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policy=retry_policies.any(
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retry_policies.provider_suggested(),
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retry_policies.network_error(),
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retry_policies.http_status((429, 500, 502, 503, 504)),
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),
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)
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def make_run_config(
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*,
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sandbox_session: BaseSandboxSession | None,
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model: str = "anthropic/claude-sonnet-4-6",
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reasoning_effort: Literal["low", "medium", "high"] | None = None,
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model_settings_override: ModelSettings | None = None,
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sandbox_client: Any | None = None,
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) -> RunConfig:
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"""Build a ``RunConfig`` with Strix defaults.
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Note: ``max_turns`` is not a ``RunConfig`` field — pass it directly
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to ``Runner.run``. ``STRIX_DEFAULT_MAX_TURNS`` is the budget Strix
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uses.
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Args:
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sandbox_session: Live sandbox session shared by every agent in
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this scan (one container per scan; see
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:mod:`strix.runtime.session_manager`). ``None`` is allowed
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for unit tests and dry runs.
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model: Model alias passed to ``MultiProvider``. Defaults to the
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production Anthropic alias.
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reasoning_effort: ``"low" | "medium" | "high"``; routes to
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``ModelSettings.reasoning``.
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model_settings_override: Optional per-run ``ModelSettings``
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merged over factory defaults.
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sandbox_client: Optional pre-built sandbox client (Strix Docker
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subclass). The SDK instantiates its built-in if a session is
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supplied without a client.
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"""
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base_settings = ModelSettings(
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parallel_tool_calls=False,
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tool_choice="required",
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retry=_DEFAULT_RETRY,
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)
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if reasoning_effort is not None:
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base_settings = base_settings.resolve(
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ModelSettings(reasoning=Reasoning(effort=reasoning_effort)),
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)
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if model_settings_override is not None:
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base_settings = base_settings.resolve(model_settings_override)
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sandbox_config = (
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SandboxRunConfig(client=sandbox_client, session=sandbox_session)
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if sandbox_session is not None
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else None
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)
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return RunConfig(
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model=model,
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model_provider=build_multi_provider(),
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model_settings=base_settings,
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sandbox=sandbox_config,
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call_model_input_filter=inject_messages_filter,
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tracing_disabled=False,
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trace_include_sensitive_data=False,
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)
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def make_agent_context(
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*,
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bus: AgentMessageBus,
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sandbox_session: BaseSandboxSession | None,
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agent_id: str,
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parent_id: str | None,
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tracer: Any | None,
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model: str = "anthropic/claude-sonnet-4-6",
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model_settings: ModelSettings | None = None,
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max_turns: int = 300,
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is_whitebox: bool = False,
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diff_scope: dict[str, Any] | None = None,
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run_id: str | None = None,
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sandbox_client: Any | None = None,
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agent_factory: Any | None = None,
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caido_client: Any | None = None,
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) -> dict[str, Any]:
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"""Build the per-agent ``context`` dict passed to ``Runner.run(context=...)``.
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The canonical place where bus, sandbox handles, identity, tracer
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reference, and per-agent toggles live. Tools, hooks, and
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``inject_messages_filter`` reach in via ``ctx.context.get(...)``.
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``agent_factory`` is a callable ``(name, skills) -> agents.Agent`` —
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the ``create_agent`` graph tool uses it to spin up children that
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inherit the same wiring. ``sandbox_client`` is the host-side Docker
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subclass, reused across child runs.
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"""
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return {
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"bus": bus,
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"sandbox_session": sandbox_session,
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"sandbox_client": sandbox_client,
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"caido_client": caido_client,
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"agent_id": agent_id,
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"parent_id": parent_id,
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"tracer": tracer,
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"model": model,
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"model_settings": model_settings,
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"max_turns": max_turns,
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"turn_count": 0,
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"agent_finish_called": False,
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"is_whitebox": is_whitebox,
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"diff_scope": diff_scope,
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"run_id": run_id,
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"agent_factory": agent_factory,
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}
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