diff --git a/eval_protocol/rewards/code_execution.py b/eval_protocol/rewards/code_execution.py index 68f060ee..0f9293c8 100644 --- a/eval_protocol/rewards/code_execution.py +++ b/eval_protocol/rewards/code_execution.py @@ -833,7 +833,10 @@ def execute_code_with_e2b( "error": "API key is required for E2B execution. Set it using the api_key parameter or E2B_API_KEY environment variable.", } - with Sandbox(api_key=api_key) as sandbox: + # E2B v2's factory carries the sandbox access token required by envd. + # Retain constructor support for older optional code-interpreter SDKs. + sandbox_factory = getattr(Sandbox, "create", Sandbox) + with sandbox_factory(api_key=api_key) as sandbox: stdout = [] stderr = [] @@ -849,8 +852,6 @@ def capture_stderr(output): else: stderr.append(str(output)) - sandbox.on_exit = lambda *args: None # type: ignore[method-assign, assignment] - if language.lower() in ["python", "py"]: file_path = "/code/script.py" cmd = "python3 /code/script.py" @@ -866,7 +867,9 @@ def capture_stderr(output): try: fs_handler = None - if _E2B_SOURCE == "e2b_code_interpreter": + if hasattr(sandbox, "files"): + fs_handler = sandbox.files + elif _E2B_SOURCE == "e2b_code_interpreter": if hasattr(sandbox, "filesystem"): fs_handler = sandbox.filesystem elif _E2B_SOURCE == "e2b": diff --git a/pyproject.toml b/pyproject.toml index 69962040..68f73314 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -25,13 +25,13 @@ dependencies = [ "openai>=1.78.1", "aiosqlite", "aiohttp", - "mcp>=1.9.2", + "mcp>=1.30.0,<2", "PyYAML>=5.0", "hydra-core>=1.3.2", "omegaconf>=2.3.0", "httpx>=0.24.0", "anthropic>=0.59.0", - "litellm==1.84.3", + "litellm==1.105.0", "pytest>=6.0.0", "pytest-asyncio>=0.21.0", "peewee>=3.18.2", @@ -70,7 +70,8 @@ dev = [ "versioneer>=0.20", "openai>=1.78.1", "pre-commit", - "e2b", + # Reproducible v2 sandbox tests without changing the optional tracing stack. + "e2b==2.34.0", "pytest-cov", "pytest-xdist", "docker==7.1.0", diff --git a/scripts/run_sharded_tests.sh b/scripts/run_sharded_tests.sh index 6c492100..16fff56d 100755 --- a/scripts/run_sharded_tests.sh +++ b/scripts/run_sharded_tests.sh @@ -71,9 +71,11 @@ if [ "$DRY_RUN" = "--dry-run" ]; then fi # Run tests for this shard +# Keep evaluation tests and their shared-processor verification in the same worker. # shellcheck disable=SC2086 exec pytest \ -n auto \ + --dist=loadfile \ --ignore=eval_protocol/benchmarks/ \ --ignore=eval_protocol/quickstart/ \ -v --durations=10 \ diff --git a/tests/klavis_helpers.py b/tests/klavis_helpers.py new file mode 100644 index 00000000..e2e5304b --- /dev/null +++ b/tests/klavis_helpers.py @@ -0,0 +1,93 @@ +"""Helpers shared by live Klavis evaluations and offline tests.""" + +import json +import logging +import os + +from openai import AsyncOpenAI +from pydantic import BaseModel + +from eval_protocol.models import EvaluateResult, EvaluationRow, Message + +logger = logging.getLogger(__name__) +MODEL = os.environ.get("EP_KLAVIS_MODEL", "accounts/fireworks/models/gpt-oss-120b") + + +class ResponseFormat(BaseModel): + score: float + + +async def judge_klavis_response(row: EvaluationRow) -> EvaluationRow: + """Judge a completed Klavis rollout; service errors must fail the live test.""" + ground_truth = row.ground_truth + + async with AsyncOpenAI( + api_key=os.environ["FIREWORKS_API_KEY"], base_url="https://api.fireworks.ai/inference/v1" + ) as client: + response = await client.chat.completions.create( + model=MODEL, + messages=[ + { + "role": "system", + "content": "You are judging the output of the model versus the ground truth. Return score = 1 if the output contains the ground truth, 0 otherwise.", + }, + { + "role": "user", + "content": f"Final model output: {row.messages[-1].content}\nGround truth: {ground_truth}", + }, + ], + response_format={ + "type": "json_schema", + "json_schema": {"name": "ResponseFormat", "schema": ResponseFormat.model_json_schema()}, + }, + ) + response_text = response.choices[0].message.content + logger.info("response_text: %s", response_text) + try: + parsed = json.loads(response_text or "{}") + score = parsed.get("score", 0.0) + except (json.JSONDecodeError, TypeError): + logger.warning("Failed to parse response as JSON: %s", response_text) + score = 0.0 + + row.evaluation_result = EvaluateResult(score=score, reason=response_text) + return row + + +def klavis_gmail_sandbox_dataset_adapter(rows: list[dict]) -> list[EvaluationRow]: + """Dataset adapter for sandbox JSONL rows. + + Supports the new schema: + - initialize_data: dict (passed to Klavis sandbox initializer) + - messages: str (task instruction) + - ground_truth: dict (expected final sandbox state) + + """ + adapted: list[EvaluationRow] = [] + system_prompt = ( + "You are a helpful assistant with access to Gmail. " + "You can send emails, draft emails, and manage messages, etc." + ) + + for r in rows: + if isinstance(r.get("messages"), str) and "initialize_data" in r: + init_data = r.get("initialize_data") or {} + task = r.get("messages") or "" + ground_truth = r.get("ground_truth") + + row = EvaluationRow( + messages=[ + Message(role="system", content=system_prompt), + Message(role="user", content=task), + ], + ground_truth=ground_truth, + ) + row.input_metadata.session_data = { + "initialize_data": init_data, + "task": task, + } + adapted.append(row) + else: + adapted.append(EvaluationRow(**r)) + + return adapted diff --git a/tests/pytest/test_pytest_klavis_mcp.py b/tests/pytest/test_pytest_klavis_mcp.py index 73b13220..7a6897e6 100644 --- a/tests/pytest/test_pytest_klavis_mcp.py +++ b/tests/pytest/test_pytest_klavis_mcp.py @@ -1,66 +1,25 @@ -from eval_protocol.models import EvaluateResult, EvaluationRow, Message -from eval_protocol.pytest import AgentRolloutProcessor, evaluation_test -from openai import AsyncOpenAI -import json -from pydantic import BaseModel -import logging - -logger = logging.getLogger(__name__) import os +import pytest -class ResponseFormat(BaseModel): - score: float - - -""" -You should copy https://painted-tennis-ebc.notion.site/MCPMark-Source-Hub-23181626b6d7805fb3a7d59c63033819 -into your Notion for the notion test. -""" +from eval_protocol.models import EvaluationRow +from eval_protocol.pytest import AgentRolloutProcessor +from eval_protocol.pytest.evaluation_test import evaluation_test +from tests.klavis_helpers import MODEL, judge_klavis_response +# Live datasets require a Klavis connection to Gmail/Notion and their seeded test data. +@pytest.mark.skipif( + not (os.environ.get("KLAVIS_AUTH_TOKEN") and os.environ.get("FIREWORKS_API_KEY")), + reason="Live Klavis MCP test requires KLAVIS_AUTH_TOKEN and FIREWORKS_API_KEY", +) @evaluation_test( input_dataset=["tests/pytest/datasets/klavis_mcp_test.jsonl"], rollout_processor=AgentRolloutProcessor(), - completion_params=[{"model": "fireworks_ai/accounts/fireworks/models/kimi-k2p5"}], + completion_params=[{"model": f"fireworks_ai/{MODEL}"}], mode="pointwise", mcp_config_path="tests/pytest/mcp_configurations/klavis_strata_mcp.json", ) async def test_pytest_klavis_mcp(row: EvaluationRow) -> EvaluationRow: - ground_truth = row.ground_truth - # check if the final messages contains the ground truth - - async with AsyncOpenAI( - api_key=os.environ["FIREWORKS_API_KEY"], base_url="https://api.fireworks.ai/inference/v1" - ) as client: - response = await client.chat.completions.create( - model="accounts/fireworks/models/kimi-k2p5", - messages=[ - { - "role": "system", - "content": "You are judging the output of the model versus the ground truth. Return score = 1 if the output contains the ground truth, 0 otherwise.", - }, - { - "role": "user", - "content": f"Final model output: {row.messages[-1].content}\nGround truth: {ground_truth}", - }, - ], - response_format={ - "type": "json_schema", - "json_schema": {"name": "ResponseFormat", "schema": ResponseFormat.model_json_schema()}, - }, - ) - response_text = response.choices[0].message.content - logger.info("response_text: %s", response_text) - try: - parsed = json.loads(response_text or "{}") - score = parsed.get("score", 0.0) - except (json.JSONDecodeError, TypeError): - logger.warning("Failed to parse response as JSON: %s", response_text) - score = 0.0 - - row.evaluation_result = EvaluateResult( - score=score, - reason=response_text, - ) - return row + assert row.rollout_status.is_finished(), row.rollout_status + return await judge_klavis_response(row) diff --git a/tests/pytest/test_pytest_klavis_sandbox.py b/tests/pytest/test_pytest_klavis_sandbox.py index f5619251..32901c66 100644 --- a/tests/pytest/test_pytest_klavis_sandbox.py +++ b/tests/pytest/test_pytest_klavis_sandbox.py @@ -2,73 +2,43 @@ import logging import os -from eval_protocol.models import EvaluateResult, EvaluationRow, Message -from eval_protocol.pytest import KlavisSandboxRolloutProcessor, evaluation_test +import pytest from openai import AsyncOpenAI from pydantic import BaseModel +from eval_protocol.models import EvaluateResult, EvaluationRow +from eval_protocol.pytest import KlavisSandboxRolloutProcessor +from eval_protocol.pytest.evaluation_test import evaluation_test +from tests.klavis_helpers import MODEL, klavis_gmail_sandbox_dataset_adapter + logger = logging.getLogger(__name__) class ResponseFormat(BaseModel): score: float - - -def klavis_gmail_sandbox_dataset_adapter(rows: list[dict]) -> list[EvaluationRow]: - """Dataset adapter for sandbox JSONL rows. - - Supports the new schema: - - initialize_data: dict (passed to Klavis sandbox initializer) - - messages: str (task instruction) - - ground_truth: dict (expected final sandbox state) - - """ - adapted: list[EvaluationRow] = [] - system_prompt = ( - "You are a helpful assistant with access to Gmail. " - "You can send emails, draft emails, and manage messages, etc." - ) - - for r in rows: - if isinstance(r.get("messages"), str) and "initialize_data" in r: - init_data = r.get("initialize_data") or {} - task = r.get("messages") or "" - ground_truth = r.get("ground_truth") - - row = EvaluationRow( - messages=[ - Message(role="system", content=system_prompt), - Message(role="user", content=task), - ], - ground_truth=ground_truth, - ) - row.input_metadata.session_data = { - "initialize_data": init_data, - "task": task, - } - adapted.append(row) - else: - adapted.append(EvaluationRow(**r)) - - return adapted +@pytest.mark.skipif( + not (os.environ.get("KLAVIS_API_KEY") and os.environ.get("FIREWORKS_API_KEY")), + reason="Live Klavis Gmail test requires KLAVIS_API_KEY and FIREWORKS_API_KEY", +) @evaluation_test( input_dataset=["tests/pytest/datasets/klavis_gmail_sandbox_test.jsonl"], rollout_processor=KlavisSandboxRolloutProcessor( server_name="gmail", ), - completion_params=[{"model": "fireworks_ai/accounts/fireworks/models/kimi-k2p5"}], + completion_params=[{"model": f"fireworks_ai/{MODEL}"}], mode="pointwise", dataset_adapter=klavis_gmail_sandbox_dataset_adapter, ) async def test_pytest_gmail_sandbox(row: EvaluationRow) -> EvaluationRow: """ Evaluate Gmail sandbox results by comparing with ground truth using LLM judge. - + The sandbox data is exported after agent execution and compared with expected output. Sandbox data is available in row.execution_metadata.extra["sandbox_data"]. """ + assert row.rollout_status.is_finished(), row.rollout_status ground_truth = row.ground_truth sandbox_data = row.execution_metadata.extra.get("sandbox_data", {}) if row.execution_metadata.extra else {} final_message = row.messages[-1].content if row.messages else "" @@ -83,11 +53,10 @@ async def test_pytest_gmail_sandbox(row: EvaluationRow) -> EvaluationRow: async with AsyncOpenAI( api_key=os.environ["FIREWORKS_API_KEY"], base_url="https://api.fireworks.ai/inference/v1" ) as client: - evaluation_prompt = f"""You are evaluating an AI agent's performance on a Gmail sandbox task. Task: -{task or (row.messages[-1].content if row.messages else 'N/A')} +{task or (row.messages[-1].content if row.messages else "N/A")} Initial Gmail Sandbox State (initialize_data): {json.dumps(initialize_data, indent=2, default=str)} @@ -110,7 +79,7 @@ async def test_pytest_gmail_sandbox(row: EvaluationRow) -> EvaluationRow: try: response = await client.chat.completions.create( - model="accounts/fireworks/models/kimi-k2p5", + model=MODEL, messages=[ { "role": "system", @@ -134,9 +103,6 @@ async def test_pytest_gmail_sandbox(row: EvaluationRow) -> EvaluationRow: row.evaluation_result = EvaluateResult(score=score) except Exception as e: logger.error(f"Error during LLM evaluation: {str(e)}", exc_info=True) - row.evaluation_result = EvaluateResult( - score=0.0, - reason=f"Evaluation error: {str(e)}", - ) + raise return row diff --git a/tests/test_e2b_sdk_compatibility.py b/tests/test_e2b_sdk_compatibility.py new file mode 100644 index 00000000..961e3fa8 --- /dev/null +++ b/tests/test_e2b_sdk_compatibility.py @@ -0,0 +1,83 @@ +"""Exercise both E2B SDK APIs without provisioning a sandbox.""" + +from types import SimpleNamespace +from unittest.mock import MagicMock, Mock + +import pytest + +from eval_protocol.rewards import code_execution + + +@pytest.fixture(params=["modern", "legacy"]) +def sandbox_api(request, monkeypatch): + filesystem = Mock(spec=["make_dir", "write"]) + commands = Mock(spec=["run"]) + attributes = {"commands": commands} + attributes["files" if request.param == "modern" else "_filesystem"] = filesystem + sandbox = SimpleNamespace(**attributes) + context = MagicMock() + context.__enter__.return_value = sandbox + constructor = Mock(return_value=context) + factory = Mock(return_value=context) + + class Sandbox: + def __new__(cls, **kwargs): + return constructor(**kwargs) + + if request.param == "modern": + Sandbox.create = factory + + monkeypatch.setattr(code_execution, "Sandbox", Sandbox, raising=False) + monkeypatch.setattr(code_execution, "_HAS_E2B", True) + monkeypatch.setattr(code_execution, "_E2B_SOURCE", "e2b") + return SimpleNamespace( + filesystem=filesystem, + commands=commands, + context=context, + constructor=constructor, + factory=factory, + modern=request.param == "modern", + ) + + +@pytest.mark.parametrize( + "language,code,path,command,output", + [ + ("python", "print(5)", "/code/script.py", "python3 /code/script.py", "5"), + ("javascript", "console.log(true)", "/code/script.js", "node /code/script.js", "true"), + ], +) +def test_execute_with_sdk_factory(sandbox_api, language, code, path, command, output): + def run(cmd, on_stdout, on_stderr, timeout): + assert cmd == command + assert timeout == 15 + on_stdout(SimpleNamespace(line=output)) + return SimpleNamespace(exit_code=0) + + sandbox_api.commands.run.side_effect = run + result = code_execution.execute_code_with_e2b(code, language=language, timeout=15, api_key="test-key") + + assert result == {"success": True, "output": output, "error": None} + sandbox_api.filesystem.write.assert_called_once_with(path, code) + chosen = sandbox_api.factory if sandbox_api.modern else sandbox_api.constructor + unused = sandbox_api.constructor if sandbox_api.modern else sandbox_api.factory + chosen.assert_called_once_with(api_key="test-key") + unused.assert_not_called() + sandbox_api.context.__exit__.assert_called_once() + + +def test_write_failure_cleans_up_sandbox(sandbox_api): + sandbox_api.filesystem.write.side_effect = RuntimeError("missing sandbox access token") + result = code_execution.execute_code_with_e2b("print(5)", api_key="test-key") + assert result["success"] is False + assert "missing sandbox access token" in result["error"] + sandbox_api.commands.run.assert_not_called() + sandbox_api.context.__exit__.assert_called_once() + + +def test_command_failure_cleans_up_sandbox(sandbox_api): + sandbox_api.commands.run.side_effect = RuntimeError("command timed out") + result = code_execution.execute_code_with_e2b("print(5)", api_key="test-key") + assert result["success"] is False + assert "command timed out" in result["error"] + sandbox_api.context.__exit__.assert_called_once() diff --git a/tests/test_klavis_evaluation.py b/tests/test_klavis_evaluation.py new file mode 100644 index 00000000..5764a244 --- /dev/null +++ b/tests/test_klavis_evaluation.py @@ -0,0 +1,64 @@ +"""Klavis judging and authorization checks that do not require live credentials.""" + +from types import SimpleNamespace +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from eval_protocol.mcp.mcp_multi_client import MCPMultiClient +from eval_protocol.models import EvaluationRow, Message +from tests import klavis_helpers as klavis +from tests.klavis_helpers import klavis_gmail_sandbox_dataset_adapter + + +@pytest.fixture +def judge_client(monkeypatch): + client = SimpleNamespace(chat=SimpleNamespace(completions=SimpleNamespace(create=AsyncMock()))) + context = MagicMock() + context.__aenter__ = AsyncMock(return_value=client) + context.__aexit__ = AsyncMock(return_value=False) + monkeypatch.setattr(klavis, "AsyncOpenAI", lambda **kwargs: context) + monkeypatch.setenv("FIREWORKS_API_KEY", "test-key") + return client.chat.completions.create + + +@pytest.mark.parametrize("response,score", [('{"score":1}', 1.0), ('{"score":0}', 0.0), ("bad json", 0.0)]) +async def test_klavis_judge(judge_client, response, score): + judge_client.return_value = SimpleNamespace(choices=[SimpleNamespace(message=SimpleNamespace(content=response))]) + row = EvaluationRow(messages=[Message(role="assistant", content="five emails")], ground_truth="five emails") + result = await klavis.judge_klavis_response(row) + assert result.evaluation_result.score == score + params = judge_client.call_args.kwargs + assert params["model"] == klavis.MODEL + assert "five emails" in params["messages"][-1]["content"] + assert params["response_format"]["json_schema"]["schema"] == klavis.ResponseFormat.model_json_schema() + + +async def test_klavis_judge_service_error_fails(judge_client): + judge_client.side_effect = RuntimeError("model unavailable") + row = EvaluationRow(messages=[Message(role="assistant", content="answer")]) + with pytest.raises(RuntimeError, match="model unavailable"): + await klavis.judge_klavis_response(row) + + +def test_klavis_authorization_configuration(monkeypatch): + client = MCPMultiClient(config_path="tests/pytest/mcp_configurations/klavis_strata_mcp.json") + config = client.config.mcpServers["klavis-strata"] + assert config.url == "https://strata.klavis.ai/mcp/" + monkeypatch.setenv("KLAVIS_AUTH_TOKEN", "test-token") + assert client._process_headers({"Authorization": config.authorization}) == {"Authorization": "Bearer test-token"} + monkeypatch.delenv("KLAVIS_AUTH_TOKEN") + with pytest.raises(ValueError, match="KLAVIS_AUTH_TOKEN"): + client._process_headers({"Authorization": config.authorization}) + + +def test_klavis_gmail_dataset_adapter(): + initial = {"emails": []} + expected = {"emails": [{"subject": "Hello"}]} + rows = klavis_gmail_sandbox_dataset_adapter( + [{"initialize_data": initial, "messages": "Send hello", "ground_truth": expected}] + ) + assert len(rows) == 1 + assert rows[0].messages[-1].content == "Send hello" + assert rows[0].ground_truth == expected + assert rows[0].input_metadata.session_data == {"initialize_data": initial, "task": "Send hello"} diff --git a/tests/test_retry_mechanism.py b/tests/test_retry_mechanism.py index 861793c1..24ef3d9a 100644 --- a/tests/test_retry_mechanism.py +++ b/tests/test_retry_mechanism.py @@ -119,10 +119,6 @@ def test_retry_mechanism_mock_verification(): print(f" Batch calls made: {mock_tracker.batch_call.call_count}") print(f" Total row processing calls: {mock_tracker.process_row_call.call_count}") - if mock_tracker.process_row_call.call_count == 0: - print("⚠️ No calls recorded yet. The evaluation test may not have run or completed.") - return - # Get all rollout_ids that were processed call_args = mock_tracker.process_row_call.call_args_list rollout_ids = [call[0][0] for call in call_args] diff --git a/uv.lock b/uv.lock index 0b5acb3a..ecd2d466 100644 --- a/uv.lock +++ b/uv.lock @@ -2,7 +2,8 @@ version = 1 revision = 3 requires-python = ">=3.10" resolution-markers = [ - "python_full_version >= '3.13'", + "python_full_version >= '3.14'", + "python_full_version == '3.13.*'", "python_full_version == '3.12.*'", "python_full_version == '3.11.*'", "python_full_version < '3.11'", @@ -41,7 +42,8 @@ name = "ag-ui-protocol" version = "0.1.8" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "pydantic" }, + { name = "pydantic", version = "2.11.7", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.14'" }, + { name = "pydantic", version = "2.12.5", source = { registry = "https://pypi.org/simple" }, marker = 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