2d665c9a67
### Sandbox Agents This release adds **Sandbox Agents**, a beta SDK surface for running agents with a persistent, isolated workspace. Sandbox agents keep the normal `Agent` and `Runner` flow, but add workspace manifests, sandbox-native capabilities, sandbox clients, snapshots, and resume support so agents can work over real files, run commands, edit repositories, generate artifacts, and continue work across runs. Key pieces: - `SandboxAgent`: an `Agent` with sandbox defaults such as `default_manifest`, sandbox instructions, capabilities, and `run_as`. - `Manifest`: a fresh-workspace contract for files, directories, local files, local directories, Git repos, environment, users, groups, and mounts. - `SandboxRunConfig`: per-run sandbox wiring for client creation, live session injection, serialized session resume, manifest overrides, snapshots, and materialization concurrency limits. - Built-in capabilities for shell access, filesystem editing and image inspection, skills, memory, and compaction. - Workspace snapshots and serialized sandbox session state for reconnecting to existing work or seeding a fresh sandbox from saved contents. ### Sandbox clients and hosted providers Sandbox agents now support local, containerized, and hosted execution backends: - `UnixLocalSandboxClient` for fast local development. - `DockerSandboxClient` for container isolation and image parity. - Hosted sandbox clients for Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, and Vercel through optional extras. The release also adds provider-specific examples and mount strategies for common storage backends, including S3, Cloudflare R2, Google Cloud Storage, Azure Blob Storage, and S3 Files where supported by the selected backend. ### Sandbox memory Adds a sandbox memory capability that lets future sandbox-agent runs learn from prior runs. Memory stores extracted lessons in the sandbox workspace, injects a concise summary into later runs, and uses progressive disclosure so agents can search deeper rollout summaries only when useful. Memory supports: - Read-only or generate-only modes. - Live updates when the agent discovers stale memory. - Multi-turn grouping through `conversation_id`, SDK `Session`, `RunConfig.group_id`, or generated run IDs. - Separate memory layouts for isolating memory across agents or workflows. - S3-backed examples for persisted memory across runs. ### Workspace mounts, snapshots, and resume This release adds a full workspace entry and mount model for sandbox sessions: - Local files and directories. - Synthetic files and directories. - Git repository entries. - Remote storage mounts for S3, R2, GCS, Azure Blob Storage, and S3 Files. - Provider-specific mount strategies across Docker, Modal, Cloudflare, Blaxel, Daytona, E2B, and Runloop. - Portable snapshots with path normalization, symlink preservation, mount-safe snapshotting, and remote snapshot support. - Resume paths through runner-managed `RunState`, explicit `SandboxSessionState`, or saved snapshots. ### Examples and tutorials Adds a large `examples/sandbox/` suite covering: - Local Unix and Docker sandbox runners. - Docker mount smoke tests for S3, GCS, Azure Blob Storage, and S3 Files. - Sandbox coding tasks with skills. - Sandbox agents as tools and handoff patterns. - Memory examples, including multi-agent/multi-turn memory and S3-backed memory. - Tax-prep and healthcare-support workflows. - Dataroom QA and metric extraction tutorials. - Repository code review tutorial. - Vision website clone tutorial. - Provider examples for Blaxel, Cloudflare, Daytona, E2B, Modal, Runloop, Temporal, and Vercel. ### Runtime, tracing, and model plumbing The release includes the runtime plumbing needed to make sandbox agents work naturally inside the existing SDK: - Runner-managed sandbox preparation, capability binding, session lifecycle, state serialization, and resume behavior. - Sandbox-aware `RunState` serialization. - Unified sandbox tracing with SDK spans. - Token usage on tracing spans. - Runner-managed prompt cache key defaults. - OpenAI agent registration and harness ID configuration. - Safer redaction of sensitive MCP tool outputs when sensitive tracing is disabled. - Additional OpenAI client/model utilities and Chat Completions coverage. ## Documentation & Other Changes - docs: add Asqav to external tracing processors list. - docs: update translated document pages. Co-authored-by: Abdulrahman Alfozan <alfozan@openai.com> Co-authored-by: Aditya Singh <60082699+adityasingh2400@users.noreply.github.com> Co-authored-by: Andi Liu <andi@openai.com> Co-authored-by: Aron <263346377+aron-cf@users.noreply.github.com> Co-authored-by: ashwinnathan-openai <ashwinnathan@openai.com> Co-authored-by: Codex <noreply@openai.com> Co-authored-by: cploujoux <cploujoux@blaxel.ai> Co-authored-by: elainegan-openai <168589666+elainegan-openai@users.noreply.github.com> Co-authored-by: Elias Freider <freider@users.noreply.github.com> Co-authored-by: Erik Dunteman <erik@erikds-macbook-air.local> Co-authored-by: Jason Liu <jasonliu@openai.com> Co-authored-by: Jason Steving <32336750+jasonsteving99@users.noreply.github.com> Co-authored-by: Kazuhiro Sera <seratch@openai.com> Co-authored-by: Lovre Pešut <lovre.pesut@gmail.com> Co-authored-by: Lucas Wang <lucas_wang@lucas-futures.com> Co-authored-by: Matt Brockman <matt.brockman@e2b.dev> Co-authored-by: Mish Ushakov <mishushakov@users.noreply.github.com> Co-authored-by: Naresh <ghostwriternr@gmail.com> Co-authored-by: nicholasclark-openai <nicholasclark@openai.com> Co-authored-by: qiyaoq-oai <qiyaoq@openai.com> Co-authored-by: Scott Trinh <scott@scotttrinh.com> Co-authored-by: tode-rl <tony@runloop.ai> Co-authored-by: Wendy Jiao <wendyjiao@openai.com>
78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
from __future__ import annotations
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from types import SimpleNamespace
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from typing import Any, cast
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import pytest
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from agents.tracing.processors import BackendSpanExporter
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from agents.tracing.spans import Span
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from agents.tracing.traces import Trace
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@pytest.mark.asyncio
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async def test_processor_api_key(monkeypatch):
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# If the API key is not set, it should be None
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monkeypatch.delenv("OPENAI_API_KEY", None)
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processor = BackendSpanExporter()
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assert processor.api_key is None
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# If we set it afterwards, it should be the new value
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processor.set_api_key("test_api_key")
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assert processor.api_key == "test_api_key"
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@pytest.mark.asyncio
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async def test_processor_api_key_from_env(monkeypatch):
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# If the API key is not set at creation time but set before access time, it should be the new
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# value
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monkeypatch.delenv("OPENAI_API_KEY", None)
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processor = BackendSpanExporter()
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# If we set it afterwards, it should be the new value
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monkeypatch.setenv("OPENAI_API_KEY", "foo_bar_123")
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assert processor.api_key == "foo_bar_123"
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def test_exporter_uses_item_api_keys(monkeypatch):
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class DummyItem:
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def __init__(self, key: str | None, payload: dict[str, str]):
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self.tracing_api_key = key
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self._payload = payload
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def export(self) -> dict[str, str]:
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return self._payload
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calls: list[dict[str, Any]] = []
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def fake_post(*, url, headers, json):
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calls.append({"url": url, "headers": headers, "json": json})
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return SimpleNamespace(status_code=200, text="ok")
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exporter = BackendSpanExporter()
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exporter.set_api_key("global-key")
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monkeypatch.setattr(exporter, "_client", SimpleNamespace(post=fake_post))
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exporter.export(
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cast(
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list[Trace | Span[Any]],
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[
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DummyItem("key-a", {"id": "a"}),
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DummyItem(None, {"id": "b"}),
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DummyItem("key-b", {"id": "c"}),
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],
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)
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)
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assert len(calls) == 3
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auth_by_first_item = {
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tuple(entry["id"] for entry in call["json"]["data"]): call["headers"]["Authorization"]
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for call in calls
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}
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assert ("a",) in auth_by_first_item
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assert ("b",) in auth_by_first_item
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assert ("c",) in auth_by_first_item
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assert auth_by_first_item[("a",)] == "Bearer key-a"
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assert auth_by_first_item[("c",)] == "Bearer key-b"
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assert auth_by_first_item[("b",)] == "Bearer global-key"
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