Files
agent-framework/python/packages/devui/tests/devui/test_server.py
T
Eduard van Valkenburg 3dc59c83b5 Python: [BREAKING] Moved to a single get_response and run API (#3379)
* WIP

* big update to new ResponseStream model

* fixed tests and typing

* fixed tests and typing

* fixed tools typevar import

* fix

* mypy fix

* mypy fixes and some cleanup

* fix missing quoted names

* and client

* fix  imports agui

* fix anthropic override

* fix agui

* fix ag ui

* fix import

* fix anthropic types

* fix mypy

* refactoring

* updated typing

* fix 3.11

* fixes

* redid layering of chat clients and agents

* redid layering of chat clients and agents

* Fix lint, type, and test issues after rebase

- Add @overload decorators to AgentProtocol.run() for type compatibility
- Add missing docstring params (middleware, function_invocation_configuration)
- Fix TODO format (TD002) by adding author tags
- Fix broken observability tests from upstream:
  - Replace non-existent use_instrumentation with direct instantiation
  - Replace non-existent use_agent_instrumentation with AgentTelemetryLayer mixin
  - Fix get_streaming_response to use get_response(stream=True)
  - Add AgentInitializationError import
  - Update streaming exception tests to match actual behavior

* Fix AgentExecutionException import error in test_agents.py

- Replace non-existent AgentExecutionException with AgentRunException

* Fix test import and asyncio deprecation issues

- Add 'tests' to pythonpath in ag-ui pyproject.toml for utils_test_ag_ui import
- Replace deprecated asyncio.get_event_loop().run_until_complete with asyncio.run

* Fix azure-ai test failures

- Update _prepare_options patching to use correct class path
- Fix test_to_azure_ai_agent_tools_web_search_missing_connection to clear env vars

* Convert ag-ui utils_test_ag_ui.py to conftest.py

- Move test utilities to conftest.py for proper pytest discovery
- Update all test imports to use conftest instead of utils_test_ag_ui
- Remove old utils_test_ag_ui.py file
- Revert pythonpath change in pyproject.toml

* fix: use relative imports for ag-ui test utilities

* fix agui

* Rename Bare*Client to Raw*Client and BaseChatClient

- Renamed BareChatClient to BaseChatClient (abstract base class)
- Renamed BareOpenAIChatClient to RawOpenAIChatClient
- Renamed BareOpenAIResponsesClient to RawOpenAIResponsesClient
- Renamed BareAzureAIClient to RawAzureAIClient
- Added warning docstrings to Raw* classes about layer ordering
- Updated README in samples/getting_started/agents/custom with layer docs
- Added test for span ordering with function calling

* Fix layer ordering: FunctionInvocationLayer before ChatTelemetryLayer

This ensures each inner LLM call gets its own telemetry span, resulting in
the correct span sequence: chat -> execute_tool -> chat

Updated all production clients and test mocks to use correct ordering:
- ChatMiddlewareLayer (first)
- FunctionInvocationLayer (second)
- ChatTelemetryLayer (third)
- BaseChatClient/Raw...Client (fourth)

* Remove run_stream usage

* Fix conversation_id propagation

* Python: Add BaseAgent implementation for Claude Agent SDK (#3509)

* Added ClaudeAgent implementation

* Updated streaming logic

* Small updates

* Small update

* Fixes

* Small fix

* Naming improvements

* Updated imports

* Addressed comments

* Updated package versions

* Update Claude agent connector layering

* fix test and plugin

* Store function middleware in invocation layer

* Fix telemetry streaming and ag-ui tests

* Remove legacy ag-ui tests folder

* updates

* Remove terminate flag from FunctionInvocationContext, use MiddlewareTermination instead

- Remove terminate attribute from FunctionInvocationContext
- Add result attribute to MiddlewareTermination to carry function results
- FunctionMiddlewarePipeline.execute() now lets MiddlewareTermination propagate
- _auto_invoke_function captures context.result in exception before re-raising
- _try_execute_function_calls catches MiddlewareTermination and sets should_terminate
- Fix handoff middleware to append to chat_client.function_middleware directly
- Update tests to use raise MiddlewareTermination instead of context.terminate
- Add middleware flow documentation in samples/concepts/tools/README.md
- Fix ag-ui to use FunctionMiddlewarePipeline instead of removed create_function_middleware_pipeline

* fix: remove references to removed terminate flag in purview tests, add type ignore

* fix: move _test_utils.py from package to test folder

* fix: call get_final_response() to trigger context provider notification in streaming test

* fix: correct broken links in tools README

* docs: clarify default middleware behavior in summary table

* fix: ensure inner stream result hooks are called when using map()/from_awaitable()

* Fix mypy type errors

* Address PR review comments on observability.py

- Remove TODO comment about unconsumed streams, add explanatory note instead
- Remove redundant _close_span cleanup hook (already called in _finalize_stream)
- Clarify behavior: cleanup hooks run after stream iteration, if stream is not
  consumed the span remains open until garbage collected

* Remove gen_ai.client.operation.duration from span attributes

Duration is a metrics-only attribute per OpenTelemetry semantic conventions.
It should be recorded to the histogram but not set as a span attribute.

* Remove duration from _get_response_attributes, pass directly to _capture_response

Duration is a metrics-only attribute. It's now passed directly to _capture_response
instead of being included in the attributes dict that gets set on the span.

* Remove redundant _close_span cleanup hook in AgentTelemetryLayer

_finalize_stream already calls _close_span() in its finally block,
so adding it as a separate cleanup hook is redundant.

* Use weakref.finalize to close span when stream is garbage collected

If a user creates a streaming response but never consumes it, the cleanup
hooks won't run. Now we register a weak reference finalizer that will close
the span when the stream object is garbage collected, ensuring spans don't
leak in this scenario.

* Fix _get_finalizers_from_stream to use _result_hooks attribute

Renamed function to _get_result_hooks_from_stream and fixed it to
look for the _result_hooks attribute which is the correct name in
ResponseStream class.

* Add missing asyncio import in test_request_info_mixin.py

* Fix leftover merge conflict marker in image_generation sample

* Update integration tests

* Fix integration tests: increase max_iterations from 1 to 2

Tests with tool_choice options require at least 2 iterations:
1. First iteration to get function call and execute the tool
2. Second iteration to get the final text response

With max_iterations=1, streaming tests would return early with only
the function call/result but no final text content.

* Fix duplicate function call error in conversation-based APIs

When using conversation_id (for Responses/Assistants APIs), the server
already has the function call message from the previous response. We
should only send the new function result message, not all messages
including the function call which would cause a duplicate ID error.

Fix: When conversation_id is set, only send the last message (the tool
result) instead of all response.messages.

* Add regression test for conversation_id propagation between tool iterations

Port test from PR #3664 with updates for new streaming API pattern.
Tests that conversation_id is properly updated in options dict during
function invocation loop iterations.

* Fix tool_choice=required to return after tool execution

When tool_choice is 'required', the user's intent is to force exactly one
tool call. After the tool executes, return immediately with the function
call and result - don't continue to call the model again.

This fixes integration tests that were failing with empty text responses
because with tool_choice=required, the model would keep returning function
calls instead of text.

Also adds regression tests for:
- conversation_id propagation between tool iterations (from PR #3664)
- tool_choice=required returns after tool execution

* Document tool_choice behavior in tools README

- Add table explaining tool_choice values (auto, none, required)
- Explain why tool_choice=required returns immediately after tool execution
- Add code example showing the difference between required and auto
- Update flow diagram to show the early return path for tool_choice=required

* Fix tool_choice=None behavior - don't default to 'auto'

Remove the hardcoded default of 'auto' for tool_choice in ChatAgent init.
When tool_choice is not specified (None), it will now not be sent to the
API, allowing the API's default behavior to be used.

Users who want tool_choice='auto' can still explicitly set it either in
default_options or at runtime.

Fixes #3585

* Fix tool_choice=none should not remove tools

In OpenAI Assistants client, tools were not being sent when
tool_choice='none'. This was incorrect - tool_choice='none' means
the model won't call tools, but tools should still be available
in the request (they may be used later in the conversation).

Fixes #3585

* Add test for tool_choice=none preserving tools

Adds a regression test to ensure that when tool_choice='none' is set but
tools are provided, the tools are still sent to the API. This verifies
the fix for #3585.

* Fix tool_choice=none should not remove tools in all clients

Apply the same fix to OpenAI Responses client and Azure AI client:
- OpenAI Responses: Remove else block that popped tool_choice/parallel_tool_calls
- Azure AI: Remove tool_choice != 'none' check when adding tools

When tool_choice='none', the model won't call tools, but tools should
still be sent to the API so they're available for future turns.

Also update README to clarify tool_choice=required supports multiple tools.

Fixes #3585

* Keep tool_choice even when tools is None

Move tool_choice processing outside of the 'if tools' block in OpenAI
Responses client so tool_choice is sent to the API even when no tools
are provided.

* Update test to match new parallel_tool_calls behavior

Changed test_prepare_options_removes_parallel_tool_calls_when_no_tools to
test_prepare_options_preserves_parallel_tool_calls_when_no_tools to reflect
that parallel_tool_calls is now preserved even when no tools are present,
consistent with the tool_choice behavior.

* Fix ChatMessage API and Role enum usage after rebase

- Update ChatMessage instantiation to use keyword args (role=, text=, contents=)
- Fix Role enum comparisons to use .value for string comparison
- Add created_at to AgentResponse in error handling
- Fix AgentResponse.from_updates -> from_agent_run_response_updates
- Fix DurableAgentStateMessage.from_chat_message to convert Role enum to string
- Add Role import where needed

* Fix additional ChatMessage API and method name changes

- Fix ChatMessage usage in workflow files (use text= instead of contents= for strings)
- Fix AgentResponse.from_updates -> from_agent_run_response_updates in workflow files
- Fix test files for ChatMessage and Role enum usage

* Fix remaining ChatMessage API usage in test files

* Fix more ChatMessage and Role API changes in source and test files

- Fix ChatMessage in _magentic.py replan method
- Fix Role enum comparison in test assertions
- Fix remaining test files with old ChatMessage syntax

* Fix ChatMessage and Role API changes across packages

- Add Role import where missing
- Fix ChatMessage signature: positional args to keyword args (role=, text=, contents=)
- Fix Role enum comparisons: .role.value instead of .role string
- Fix FinishReason enum usage in ag-ui event converters
- Rename AgentResponse.from_updates to from_agent_run_response_updates in ag-ui

Fixes API compatibility after Types API Review improvements merge

* Fix ChatMessage and Role API changes in github_copilot tests

* Fix ChatMessage and Role API changes in redis and github_copilot packages

- Fix redis provider: Role enum comparison using .value
- Fix redis tests: ChatMessage signature and Role comparisons
- Fix github_copilot tests: ChatMessage signature and Role comparisons
- Update docstring examples in redis chat message store

* Fix ChatMessage and Role API changes in devui package

- Fix executor: ChatMessage signature change
- Fix conversations: Role enum to string conversion in two places
- Fix tests: ChatMessage signatures and Role comparisons

* Fix ChatMessage and Role API changes in a2a and lab packages

- Fix a2a tests: Role comparisons and ChatMessage signatures
- Fix lab tau2 source: Role enum comparison in flip_messages, log_messages, sliding_window
- Fix lab tau2 tests: ChatMessage signatures and Role comparisons

* Remove duplicate test files from ag-ui/tests (tests are in ag_ui_tests)

* Fix ChatMessage and Role API changes across packages

After rebasing on upstream/main which merged PR #3647 (Types API Review
improvements), fix all packages to use the new API:

- ChatMessage: Use keyword args (role=, text=, contents=) instead of
  positional args
- Role: Compare using .value attribute since it's now an enum

Packages fixed:
- ag-ui: Fixed Role value extraction bugs in _message_adapters.py
- anthropic: Fixed ChatMessage and Role comparisons in tests
- azure-ai: Fixed Role comparison in _client.py
- azure-ai-search: Fixed ChatMessage and Role in source/tests
- bedrock: Fixed ChatMessage signatures in tests
- chatkit: Fixed ChatMessage and Role in source/tests
- copilotstudio: Fixed ChatMessage and Role in tests
- declarative: Fixed ChatMessage in _executors_agents.py
- mem0: Fixed ChatMessage and Role in source/tests
- purview: Fixed ChatMessage in source/tests

* Fix mypy errors for ChatMessage and Role API changes

- durabletask: Use str() fallback in role value extraction
- core: Fix ChatMessage in _orchestrator_helpers.py to use keyword args
- core: Add type ignore for _conversation_state.py contents deserialization
- ag-ui: Fix type ignore comments (call-overload instead of arg-type)
- azure-ai-search: Fix get_role_value type hint to accept Any
- lab: Move get_role_value to module level with Any type hint

* Improve CI test timeout configuration

- Increase job timeout from 10 to 15 minutes
- Reduce per-test timeout to 60s (was 900s/300s)
- Add --timeout_method thread for better timeout handling
- Add --timeout-verbose to see which tests are slow
- Reduce retries from 3 to 2 and delay from 10s to 5s

This ensures individual test timeouts are shorter than the job
timeout, providing better visibility when tests hang.

With 60s timeout and 2 retries, worst case per test is ~180s.

* Fix ChatMessage API usage in docstrings and source

- Fix ChatMessage positional args in docstrings: _serialization.py, _threads.py, _middleware.py
- Fix ChatMessage in tau2 runner.py
- Fix role comparison in _orchestrator_helpers.py to use .value
- Fix role comparison in _group_chat.py docstring example
- Fix role assertions in test_durable_entities.py to use .value

* Revert tool_choice/parallel_tool_calls changes - must be removed when no tools

OpenAI API requires tool_choice and parallel_tool_calls to only be
present when tools are specified. Restored the logic that removes
these options when there are no tools.

- Restored check in _chat_client.py to remove tool_choice and
  parallel_tool_calls when no tools present
- Restored same logic in _responses_client.py
- Reverted test to expect the correct behavior

* fixed issue in tests

* fix: resolve merge conflict markers in ag-ui tests

* fix: restructure ag-ui tests and fix Role/FinishReason to use string types

* fix: streaming function invocation and middleware termination

- Refactor streaming function invocation to use get_final_response() on inner streams
- Fix MiddlewareTermination to accept result parameter for passing results
- Fix _AutoHandoffMiddleware to use MiddlewareTermination instead of context.terminate
- Fix AgentMiddlewareLayer.run() to properly forward function/chat middleware
- Remove duplicate middleware registration in AgentMiddlewareLayer.__init__
- Fix exception handling in _auto_invoke_function to properly capture termination
- Fix mypy errors in core package
- Update tests to use stream=True parameter for unified run API

* fix all tests command

* Refactor integration tests to use pytest fixtures

- Merge testutils.py into conftest.py for azurefunctions integration tests
- Merge dt_testutils.py into conftest.py for durabletask integration tests
- Convert all integration tests to use fixtures instead of direct imports
  (fixes ModuleNotFoundError with --import-mode=importlib)
- Add sample_helper fixture for azurefunctions tests
- Add agent_client_factory and orchestration_helper fixtures for durabletask
- Integration tests now skip with descriptive messages when services unavailable
- Restructure devui tests into tests/devui/ with proper conftest.py
- Add test organization guidelines to CODING_STANDARD.md
- Remove __init__.py from test directories per pytest best practices

* Fix pytest_collection_modifyitems to only skip integration tests

The hook was skipping all tests in the test session, not just
integration tests. Now it only skips items in the integration_tests
directory.

* Fix mem0 tests failing on Python 3.13

Use patch.object on the imported module instead of @patch with string
path to ensure the mock takes effect regardless of import timing.

* fix mem0

* another attempt for mem0

* fix for mem0

* fix mem0

* Increase worker initialization wait time in durabletask tests

Increase from 2 to 8 seconds to allow time for:
- Python startup and module imports
- Azure OpenAI client creation
- Agent registration with DTS worker
- Worker connection to DTS

This helps prevent test failures in CI where the first tests may run
before the worker is fully ready to process requests.

* Fix streaming test to use ResponseStream with finalizer

The _consume_stream method now expects a ResponseStream that can provide
a final AgentResponse via get_final_response(). Update the test to use
ResponseStream with AgentResponse.from_updates as the finalizer.

* Fix MockToolCallingAgent to use new ResponseStream API and update samples

* small updates to run_stream to run

* fix sub workflow

* temp fix for az func test

---------

Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
2026-02-05 20:09:58 +00:00

405 lines
14 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
"""Focused tests for server functionality."""
import asyncio
import tempfile
from pathlib import Path
import pytest
from agent_framework_devui import DevServer
from agent_framework_devui._utils import extract_executor_message_types, select_primary_input_type
from agent_framework_devui.models._openai_custom import AgentFrameworkRequest
class _StubExecutor:
"""Simple executor stub exposing handler metadata."""
def __init__(self, *, input_types=None, handlers=None):
if input_types is not None:
self.input_types = list(input_types)
if handlers is not None:
self._handlers = dict(handlers)
# Note: test_entities_dir fixture is provided by conftest.py
async def test_server_health_endpoint(test_entities_dir):
"""Test /health endpoint."""
server = DevServer(entities_dir=test_entities_dir)
executor = await server._ensure_executor()
# Test entity count
entities = await executor.discover_entities()
assert len(entities) > 0
# Framework name is now hardcoded since we simplified to single framework
async def test_server_entities_endpoint(test_entities_dir):
"""Test /v1/entities endpoint."""
server = DevServer(entities_dir=test_entities_dir)
executor = await server._ensure_executor()
entities = await executor.discover_entities()
assert len(entities) >= 1
# Should find at least one agent
agent_entities = [e for e in entities if e.type == "agent"]
assert len(agent_entities) >= 1, "Should discover at least one agent"
# Verify agents have required properties
for agent in agent_entities:
assert agent.id, "Agent should have an ID"
assert agent.name, "Agent should have a name"
async def test_server_execution_sync(test_entities_dir):
"""Test sync execution endpoint."""
server = DevServer(entities_dir=test_entities_dir)
executor = await server._ensure_executor()
entities = await executor.discover_entities()
agent_id = entities[0].id
# Use metadata.entity_id for routing
request = AgentFrameworkRequest(
metadata={"entity_id": agent_id},
input="San Francisco",
stream=False,
)
response = await executor.execute_sync(request)
assert response.model == "devui" # Response model defaults to 'devui' when not specified
assert len(response.output) > 0
async def test_server_execution_streaming(test_entities_dir):
"""Test streaming execution endpoint."""
server = DevServer(entities_dir=test_entities_dir)
executor = await server._ensure_executor()
entities = await executor.discover_entities()
agent_id = entities[0].id
# Use metadata.entity_id for routing
request = AgentFrameworkRequest(
metadata={"entity_id": agent_id},
input="New York",
stream=True,
)
event_count = 0
async for _event in executor.execute_streaming(request):
event_count += 1
if event_count > 5: # Limit for testing
break
assert event_count > 0
def test_configuration():
"""Test basic configuration."""
server = DevServer(entities_dir="test", port=9000, host="localhost")
assert server.port == 9000
assert server.host == "localhost"
assert server.entities_dir == "test"
assert server.cors_origins == ["*"]
assert server.ui_enabled
def test_extract_executor_message_types_prefers_input_types():
"""Input types property is used when available."""
stub = _StubExecutor(input_types=[str, dict])
types = extract_executor_message_types(stub)
assert types == [str, dict]
def test_extract_executor_message_types_falls_back_to_handlers():
"""Handlers provide message metadata when input_types missing."""
stub = _StubExecutor(handlers={str: object(), int: object()})
types = extract_executor_message_types(stub)
assert str in types
assert int in types
def test_select_primary_input_type_prefers_string_and_dict():
"""Primary type selection prefers user-friendly primitives."""
string_first = select_primary_input_type([dict[str, str], str])
dict_first = select_primary_input_type([dict[str, str]])
fallback = select_primary_input_type([int, float])
assert string_first is str
assert dict_first is dict
assert fallback is int
@pytest.mark.asyncio
async def test_credential_cleanup() -> None:
"""Test that async credentials are properly closed during server cleanup."""
from unittest.mock import AsyncMock, Mock
from agent_framework import ChatAgent
# Create mock credential with async close
mock_credential = AsyncMock()
mock_credential.close = AsyncMock()
# Create mock chat client with credential
mock_client = Mock()
mock_client.async_credential = mock_credential
mock_client.model_id = "test-model"
mock_client.function_invocation_configuration = None
# Create agent with mock client
agent = ChatAgent(name="TestAgent", chat_client=mock_client, instructions="Test agent")
# Create DevUI server with agent
server = DevServer()
server._pending_entities = [agent]
await server._ensure_executor()
# Run cleanup
await server._cleanup_entities()
# Verify credential.close() was called
assert mock_credential.close.called, "Async credential close should have been called"
assert mock_credential.close.call_count == 1
@pytest.mark.asyncio
async def test_credential_cleanup_error_handling() -> None:
"""Test that credential cleanup errors are handled gracefully."""
from unittest.mock import AsyncMock, Mock
from agent_framework import ChatAgent
# Create mock credential that raises error on close
mock_credential = AsyncMock()
mock_credential.close = AsyncMock(side_effect=Exception("Close failed"))
# Create mock chat client with credential
mock_client = Mock()
mock_client.async_credential = mock_credential
mock_client.model_id = "test-model"
mock_client.function_invocation_configuration = None
# Create agent with mock client
agent = ChatAgent(name="TestAgent", chat_client=mock_client, instructions="Test agent")
# Create DevUI server with agent
server = DevServer()
server._pending_entities = [agent]
await server._ensure_executor()
# Run cleanup - should not raise despite credential error
await server._cleanup_entities()
# Verify close was attempted
assert mock_credential.close.called
@pytest.mark.asyncio
async def test_multiple_credential_attributes() -> None:
"""Test that we check all common credential attribute names."""
from unittest.mock import AsyncMock, Mock
from agent_framework import ChatAgent
# Create mock credentials
mock_cred1 = Mock()
mock_cred1.close = Mock()
mock_cred2 = AsyncMock()
mock_cred2.close = AsyncMock()
# Create mock chat client with multiple credential attributes
mock_client = Mock()
mock_client.credential = mock_cred1
mock_client.async_credential = mock_cred2
mock_client.model_id = "test-model"
mock_client.function_invocation_configuration = None
# Create agent with mock client
agent = ChatAgent(name="TestAgent", chat_client=mock_client, instructions="Test agent")
# Create DevUI server with agent
server = DevServer()
server._pending_entities = [agent]
await server._ensure_executor()
# Run cleanup
await server._cleanup_entities()
# Verify both credentials were closed
assert mock_cred1.close.called, "Sync credential should be closed"
assert mock_cred2.close.called, "Async credential should be closed"
def test_ui_mode_configuration():
"""Test UI mode configuration."""
dev_server = DevServer(mode="developer")
assert dev_server.mode == "developer"
user_server = DevServer(mode="user")
assert user_server.mode == "user"
@pytest.mark.asyncio
async def test_api_restrictions_in_user_mode():
"""Test that developer APIs are restricted in user mode."""
from fastapi.testclient import TestClient
# Create servers with different modes
dev_server = DevServer(mode="developer")
user_server = DevServer(mode="user")
dev_app = dev_server.create_app()
user_app = user_server.create_app()
dev_client = TestClient(dev_app)
user_client = TestClient(user_app)
# Test 1: Health endpoint should work in both modes
assert dev_client.get("/health").status_code == 200
assert user_client.get("/health").status_code == 200
# Test 2: Meta endpoint should reflect correct mode
dev_meta = dev_client.get("/meta").json()
assert dev_meta["ui_mode"] == "developer"
user_meta = user_client.get("/meta").json()
assert user_meta["ui_mode"] == "user"
# Test 3: Entity listing should work in both modes
assert dev_client.get("/v1/entities").status_code == 200
assert user_client.get("/v1/entities").status_code == 200
# Test 4: Entity info should be accessible in both modes (UI needs this)
dev_response = dev_client.get("/v1/entities/test_agent/info")
assert dev_response.status_code in [200, 404, 500] # Not 403
user_response = user_client.get("/v1/entities/test_agent/info")
# Should return 404 (entity doesn't exist) or 500 (other error), but NOT 403 (forbidden)
# User mode needs entity info to display workflows/agents in the UI
assert user_response.status_code in [200, 404, 500] # Not 403
# Test 5: Hot reload should be restricted in user mode
dev_response = dev_client.post("/v1/entities/test_agent/reload")
assert dev_response.status_code in [200, 404, 500] # Not 403
user_response = user_client.post("/v1/entities/test_agent/reload")
assert user_response.status_code == 403
error_data = user_response.json()
error = error_data.get("detail", {}).get("error") or error_data.get("error")
assert "developer mode" in error["message"].lower()
# Test 6: Deployment endpoints should be restricted in user mode
# List deployments (simplest test - no payload needed)
user_response = user_client.get("/v1/deployments")
assert user_response.status_code == 403
error_data = user_response.json()
error = error_data.get("detail", {}).get("error") or error_data.get("error")
assert "developer mode" in error["message"].lower()
# Get deployment
user_response = user_client.get("/v1/deployments/test-id")
assert user_response.status_code == 403
# Delete deployment
user_response = user_client.delete("/v1/deployments/test-id")
assert user_response.status_code == 403
# Test 7: Conversation endpoints should work in both modes
dev_response = dev_client.post("/v1/conversations", json={})
assert dev_response.status_code == 200
user_response = user_client.post("/v1/conversations", json={})
assert user_response.status_code == 200
# Test 8: Chat endpoint should work in both modes
chat_payload = {"model": "test_agent", "input": "Hello"}
dev_response = dev_client.post("/v1/responses", json=chat_payload)
# 200=success, 400=missing entity_id in metadata, 404=entity not found
assert dev_response.status_code in [200, 400, 404]
user_response = user_client.post("/v1/responses", json=chat_payload)
assert user_response.status_code in [200, 400, 404]
if __name__ == "__main__":
# Simple test runner
async def run_tests():
with tempfile.TemporaryDirectory() as temp_dir:
temp_path = Path(temp_dir)
# Create test agent
agent_file = temp_path / "weather_agent.py"
agent_file.write_text("""
class WeatherAgent:
name = "Weather Agent"
description = "Gets weather information"
def run(self, input_str, *, stream: bool = False, thread=None, **kwargs):
return f"Weather in {input_str} is sunny"
""")
server = DevServer(entities_dir=str(temp_path))
executor = await server._ensure_executor()
entities = await executor.discover_entities()
if entities:
request = AgentFrameworkRequest(
metadata={"entity_id": entities[0].id},
input="test location",
stream=False,
)
await executor.execute_sync(request)
asyncio.run(run_tests())
@pytest.mark.asyncio
async def test_checkpoint_api_endpoints(test_entities_dir):
"""Test checkpoint list and delete API endpoints."""
from agent_framework._workflows._checkpoint import WorkflowCheckpoint
server = DevServer(entities_dir=test_entities_dir)
executor = await server._ensure_executor()
# Create a conversation
conversation = executor.conversation_store.create_conversation(metadata={"name": "Test Session"})
conv_id = conversation.id
# Get checkpoint storage and add a checkpoint
storage = executor.checkpoint_manager.get_checkpoint_storage(conv_id)
checkpoint = WorkflowCheckpoint(
checkpoint_id="test_checkpoint_1",
workflow_id="test_workflow",
state={"key": "value"},
iteration_count=1,
)
await storage.save_checkpoint(checkpoint)
# Test list checkpoints endpoint
checkpoints = await storage.list_checkpoints()
assert len(checkpoints) == 1
assert checkpoints[0].checkpoint_id == "test_checkpoint_1"
assert checkpoints[0].workflow_id == "test_workflow"
# Test delete checkpoint endpoint
deleted = await storage.delete_checkpoint("test_checkpoint_1")
assert deleted is True
# Verify checkpoint was deleted
remaining = await storage.list_checkpoints()
assert len(remaining) == 0
# Test delete non-existent checkpoint
deleted = await storage.delete_checkpoint("nonexistent")
assert deleted is False