unsloth/studio/backend/tests/test_openai_code_execution.py
Roland Tannous c0cc975c91
fix(studio): handle expired OpenAI shell-tool containers without surfacing error in chat (#5547)
* fix(studio): transparent retry on expired OpenAI shell container

* fix(studio): drop expired OpenAI containers before send
2026-05-18 05:47:57 -07:00

537 lines
18 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""
Unit tests for OpenAI's server-side `shell` tool translation in
`_stream_openai_responses`.
Covers:
- Request body: ``enabled_tools=["code_execution"]`` on the OpenAI
cloud base_url appends ``{"type": "shell", "environment": {"type":
"container_auto"}}`` to ``tools``.
- Container reuse: when ``openai_code_exec_container_id`` is provided,
the outgoing ``environment.type`` flips to ``"container_reference"``
and the id propagates.
- Cloud guard: code_execution on a non-cloud base_url (e.g. a local
OpenAI-compat preset / ollama / llama.cpp / vLLM) does NOT add the
shell tool, preventing a guaranteed 400 from those servers.
- SSE translation: a `shell_call` + `shell_call_output` pair emits one
``_toolEvent`` `tool_start` (`tool_name="code_execution"`,
`arguments.kind="bash"`) and one `tool_end` whose `result` contains
the joined stdout from the shell_call_output entries.
- Container surfacing: container_id captured from
`response.completed.container_id` is emitted as a synthetic
`container_ready` `_toolEvent` (only when it differs from the
inbound id).
- Stale-container handling: 400 with "container expired" body emits a
`container_invalidated` event before propagating the error.
"""
import asyncio
import json
import httpx
from core.inference import external_provider as ep_mod
from core.inference.external_provider import ExternalProviderClient
def _drive(coro):
return asyncio.new_event_loop().run_until_complete(coro)
async def _collect(agen):
out = []
async for line in agen:
out.append(line)
return out
def _mock_http_client(monkeypatch, handler):
transport = httpx.MockTransport(handler)
monkeypatch.setattr(ep_mod, "_http_client", httpx.AsyncClient(transport = transport))
def _make_client(base_url: str = "https://api.openai.com/v1") -> ExternalProviderClient:
return ExternalProviderClient(
provider_type = "openai",
base_url = base_url,
api_key = "sk-test",
)
def _openai_sse(events: list[dict]) -> bytes:
chunks: list[str] = []
for event in events:
chunks.append(f"event: {event['type']}")
chunks.append(f"data: {json.dumps(event)}")
chunks.append("")
return ("\n".join(chunks) + "\n").encode("utf-8")
def _tool_events(lines: list[str]) -> list[dict]:
out: list[dict] = []
for line in lines:
if not line.startswith("data:"):
continue
raw = line[len("data:") :].strip()
if not raw or raw == "[DONE]":
continue
try:
parsed = json.loads(raw)
except json.JSONDecodeError:
continue
if isinstance(parsed, dict) and "_toolEvent" in parsed:
out.append(parsed["_toolEvent"])
return out
def test_shell_tool_added_on_cloud_with_container_auto(monkeypatch):
captured: dict = {}
def handler(request: httpx.Request) -> httpx.Response:
captured["body"] = json.loads(request.content.decode("utf-8"))
return httpx.Response(
200,
content = _openai_sse([{"type": "response.completed", "response": {}}]),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
async for _ in client._stream_openai_responses(
messages = [{"role": "user", "content": "compute 2+2"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
):
pass
await client.close()
_drive(run())
tools = captured["body"].get("tools") or []
assert {
"type": "shell",
"environment": {"type": "container_auto"},
} in tools
def test_shell_tool_uses_container_reference_when_id_supplied(monkeypatch):
captured: dict = {}
def handler(request: httpx.Request) -> httpx.Response:
captured["body"] = json.loads(request.content.decode("utf-8"))
return httpx.Response(
200,
content = _openai_sse([{"type": "response.completed", "response": {}}]),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
async for _ in client._stream_openai_responses(
messages = [{"role": "user", "content": "what did i write earlier"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
openai_code_exec_container_id = "cntr_abc123",
):
pass
await client.close()
_drive(run())
tools = captured["body"].get("tools") or []
assert {
"type": "shell",
"environment": {
"type": "container_reference",
"container_id": "cntr_abc123",
},
} in tools
def test_shell_tool_refused_for_non_cloud_base_url(monkeypatch):
captured: dict = {}
def handler(request: httpx.Request) -> httpx.Response:
captured["body"] = json.loads(request.content.decode("utf-8"))
return httpx.Response(
200,
content = _openai_sse([{"type": "response.completed", "response": {}}]),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client(base_url = "http://localhost:11434/v1")
async for _ in client._stream_openai_responses(
messages = [{"role": "user", "content": "hi"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
):
pass
await client.close()
_drive(run())
tools = captured["body"].get("tools") or []
# Shell tool must NOT leak to local OpenAI-compat servers — those
# 400 on the unknown tool type.
assert all(t.get("type") != "shell" for t in tools)
def test_shell_call_emits_tool_start_and_end(monkeypatch):
sse_events = [
{
"type": "response.output_item.added",
"item": {
"type": "shell_call",
"id": "scall_1",
"action": {"commands": ["ls -la"]},
},
},
{
"type": "response.output_item.done",
"item": {
"type": "shell_call",
"id": "scall_1",
"action": {"commands": ["ls -la"]},
"status": "completed",
},
},
{
"type": "response.output_item.done",
"item": {
"type": "shell_call_output",
"id": "scout_1",
"call_id": "scall_1",
"output": [
{
"stdout": "total 24\ndrwxr-xr-x .",
"stderr": "",
"outcome": {"type": "exit", "exit_code": 0},
}
],
},
},
{"type": "response.completed", "response": {}},
]
def handler(request: httpx.Request) -> httpx.Response:
return httpx.Response(
200,
content = _openai_sse(sse_events),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "list files"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
)
)
lines = _drive(run())
events = _tool_events(lines)
starts = [e for e in events if e["type"] == "tool_start"]
ends = [e for e in events if e["type"] == "tool_end"]
assert len(starts) == 1
assert len(ends) == 1
assert starts[0]["tool_name"] == "code_execution"
assert starts[0]["tool_call_id"] == "scall_1"
assert starts[0]["arguments"] == {"kind": "bash", "command": "ls -la"}
assert ends[0]["tool_call_id"] == "scall_1"
assert "total 24" in ends[0]["result"]
def test_container_ready_emitted_when_new_id_surfaces(monkeypatch):
sse_events = [
{
"type": "response.completed",
"response": {"container_id": "cntr_new_456"},
},
]
def handler(request: httpx.Request) -> httpx.Response:
return httpx.Response(
200,
content = _openai_sse(sse_events),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "do stuff"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
)
)
lines = _drive(run())
events = _tool_events(lines)
ready = [e for e in events if e["type"] == "container_ready"]
assert len(ready) == 1
assert ready[0]["container_id"] == "cntr_new_456"
def test_container_ready_not_emitted_when_id_unchanged(monkeypatch):
sse_events = [
{
"type": "response.completed",
"response": {"container_id": "cntr_same_789"},
},
]
def handler(request: httpx.Request) -> httpx.Response:
return httpx.Response(
200,
content = _openai_sse(sse_events),
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "do stuff"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
openai_code_exec_container_id = "cntr_same_789",
)
)
lines = _drive(run())
events = _tool_events(lines)
# No churn — id matches the one already on the thread record.
assert not any(e["type"] == "container_ready" for e in events)
def test_stale_container_emits_invalidated(monkeypatch):
def handler(request: httpx.Request) -> httpx.Response:
return httpx.Response(
400,
content = json.dumps(
{
"error": {
"message": "container has expired",
"type": "invalid_request_error",
}
}
).encode("utf-8"),
headers = {"content-type": "application/json"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "hi"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
openai_code_exec_container_id = "cntr_stale_999",
)
)
lines = _drive(run())
events = _tool_events(lines)
invalidated = [e for e in events if e["type"] == "container_invalidated"]
assert len(invalidated) == 1
def test_expired_container_triggers_transparent_retry(monkeypatch):
"""When OpenAI 400s with 'Container is expired' on a request that
carried container_reference, the streamer retries once with the
container field stripped. The user never sees an error line — only
container_invalidated, then the normal stream from the retry.
"""
calls: list[dict] = []
def handler(request: httpx.Request) -> httpx.Response:
body = json.loads(request.content.decode("utf-8"))
calls.append(body)
# Find the shell tool entry to inspect environment.type.
shell_env_type = None
for tool in body.get("tools", []) or []:
if tool.get("type") == "shell":
shell_env_type = tool.get("environment", {}).get("type")
break
# First call carries container_reference -> 400 expired.
# Retry omits container -> normal SSE stream.
if shell_env_type == "container_reference":
return httpx.Response(
400,
content = json.dumps(
{
"error": {
"message": "Container is expired.",
"type": "invalid_request_error",
}
}
).encode("utf-8"),
headers = {"content-type": "application/json"},
)
# Successful retry: minimal SSE — a completed response with a
# fresh container_id so container_ready latches.
sse = _openai_sse(
[
{
"type": "response.completed",
"response": {"container_id": "cntr_fresh_111"},
},
]
)
return httpx.Response(
200,
content = sse,
headers = {"content-type": "text/event-stream"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "hi"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
openai_code_exec_container_id = "cntr_stale_999",
)
)
lines = _drive(run())
events = _tool_events(lines)
# Two outbound HTTP calls were made: the expired-container attempt
# then the retry without the container field.
assert len(calls) == 2
shell_types = []
for body in calls:
for tool in body.get("tools", []) or []:
if tool.get("type") == "shell":
shell_types.append(tool.get("environment", {}).get("type"))
assert shell_types == ["container_reference", "container_auto"]
# container_invalidated emitted (frontend will null its stored id).
assert any(e.get("type") == "container_invalidated" for e in events)
# container_ready emitted from the retry stream with the fresh id.
assert any(
e.get("type") == "container_ready" and e.get("container_id") == "cntr_fresh_111"
for e in events
)
# CRUCIALLY: no SSE error line surfaced to the chat — only completion.
error_lines = [
line
for line in lines
if line.startswith("data:") and '"error"' in line and '"_toolEvent"' not in line
]
assert error_lines == [], f"unexpected error line(s): {error_lines}"
def test_expired_container_retries_only_once(monkeypatch):
"""If the retry ALSO fails (any 4xx, expired or otherwise), the
error is surfaced normally — no infinite retry loop.
"""
call_count = {"n": 0}
def handler(request: httpx.Request) -> httpx.Response:
call_count["n"] += 1
return httpx.Response(
400,
content = json.dumps(
{
"error": {
"message": "Container is expired.",
"type": "invalid_request_error",
}
}
).encode("utf-8"),
headers = {"content-type": "application/json"},
)
_mock_http_client(monkeypatch, handler)
async def run():
client = _make_client()
return await _collect(
client._stream_openai_responses(
messages = [{"role": "user", "content": "hi"}],
model = "gpt-5.5",
temperature = 0.7,
top_p = 0.95,
max_tokens = 4096,
enable_thinking = None,
reasoning_effort = None,
enabled_tools = ["code_execution"],
openai_code_exec_container_id = "cntr_stale_999",
)
)
lines = _drive(run())
# Exactly two calls (first + one retry). Third would mean an
# infinite loop.
assert call_count["n"] == 2
# The second failure surfaces normally as an error SSE line.
error_lines = [
line for line in lines if '"error"' in line and "_toolEvent" not in line
]
assert len(error_lines) >= 1