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Merge branch 'main' of github.com:crewAIInc/crewAI into devin/1741108142-custom-llm-support

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Lorenze Jay
2025-03-10 09:34:33 -07:00
parent 709941c4c7 7122a29a20
commit 0cece5fd59
26 changed files with 5382 additions and 426 deletions
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5
tests/agent_test.py
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@@ -18,6 +18,7 @@ from crewai.tools.tool_calling import InstructorToolCalling
from crewai.tools.tool_usage import ToolUsage
from crewai.utilities import RPMController
from crewai.utilities.events import crewai_event_bus
from crewai.utilities.events.llm_events import LLMStreamChunkEvent
from crewai.utilities.events.tool_usage_events import ToolUsageFinishedEvent
@@ -259,9 +260,7 @@ def test_cache_hitting():
def handle_tool_end(source, event):
received_events.append(event)
with (
patch.object(CacheHandler, "read") as read,
):
with (patch.object(CacheHandler, "read") as read,):
read.return_value = "0"
task = Task(
description="What is 2 times 6? Ignore correctness and just return the result of the multiplication tool, you must use the tool.",

2571
tests/cassettes/test_crew_kickoff_streaming_usage_metrics.yaml Normal file
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1760
tests/cassettes/test_crew_kickoff_usage_metrics.yaml
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50
tests/crew_test.py
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@@ -2,6 +2,7 @@
import hashlib
import json
import os
from concurrent.futures import Future
from unittest import mock
from unittest.mock import MagicMock, patch
@@ -35,6 +36,11 @@ from crewai.utilities.events.crew_events import (
from crewai.utilities.rpm_controller import RPMController
from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
# Skip streaming tests when running in CI/CD environments
skip_streaming_in_ci = pytest.mark.skipif(
os.getenv("CI") is not None, reason="Skipping streaming tests in CI/CD environments"
)
ceo = Agent(
role="CEO",
goal="Make sure the writers in your company produce amazing content.",
@@ -948,6 +954,7 @@ def test_api_calls_throttling(capsys):
moveon.assert_called()
@skip_streaming_in_ci
@pytest.mark.vcr(filter_headers=["authorization"])
def test_crew_kickoff_usage_metrics():
inputs = [
@@ -960,6 +967,7 @@ def test_crew_kickoff_usage_metrics():
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
llm=LLM(model="gpt-4o"),
)
task = Task(
@@ -968,12 +976,50 @@ def test_crew_kickoff_usage_metrics():
agent=agent,
)
# Use real LLM calls instead of mocking
crew = Crew(agents=[agent], tasks=[task])
results = crew.kickoff_for_each(inputs=inputs)
assert len(results) == len(inputs)
for result in results:
# Assert that all required keys are in usage_metrics and their values are not None
# Assert that all required keys are in usage_metrics and their values are greater than 0
assert result.token_usage.total_tokens > 0
assert result.token_usage.prompt_tokens > 0
assert result.token_usage.completion_tokens > 0
assert result.token_usage.successful_requests > 0
assert result.token_usage.cached_prompt_tokens == 0
@skip_streaming_in_ci
@pytest.mark.vcr(filter_headers=["authorization"])
def test_crew_kickoff_streaming_usage_metrics():
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
llm=LLM(model="gpt-4o", stream=True),
max_iter=3,
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
# Use real LLM calls instead of mocking
crew = Crew(agents=[agent], tasks=[task])
results = crew.kickoff_for_each(inputs=inputs)
assert len(results) == len(inputs)
for result in results:
# Assert that all required keys are in usage_metrics and their values are greater than 0
assert result.token_usage.total_tokens > 0
assert result.token_usage.prompt_tokens > 0
assert result.token_usage.completion_tokens > 0
@@ -3973,3 +4019,5 @@ def test_crew_with_knowledge_sources_works_with_copy():
assert crew_copy.knowledge_sources == crew.knowledge_sources
assert len(crew_copy.agents) == len(crew.agents)
assert len(crew_copy.tasks) == len(crew.tasks)
assert len(crew_copy.tasks) == len(crew.tasks)

3
tests/llm_test.py
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@@ -219,7 +219,7 @@ def test_get_custom_llm_provider_gemini():
def test_get_custom_llm_provider_openai():
llm = LLM(model="gpt-4")
assert llm._get_custom_llm_provider() == "openai"
assert llm._get_custom_llm_provider() == None
def test_validate_call_params_supported():
@@ -285,6 +285,7 @@ def test_o3_mini_reasoning_effort_medium():
assert isinstance(result, str)
assert "Paris" in result
def test_context_window_validation():
"""Test that context window validation works correctly."""
# Test valid window size

170
tests/utilities/cassettes/test_llm_emits_stream_chunk_events.yaml Normal file
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tests/utilities/cassettes/test_llm_no_stream_chunks_when_streaming_disabled.yaml Normal file
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156
tests/utilities/test_events.py
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@@ -1,3 +1,4 @@
import os
from datetime import datetime
from unittest.mock import Mock, patch
@@ -38,6 +39,7 @@ from crewai.utilities.events.llm_events import (
LLMCallFailedEvent,
LLMCallStartedEvent,
LLMCallType,
LLMStreamChunkEvent,
)
from crewai.utilities.events.task_events import (
TaskCompletedEvent,
@@ -48,6 +50,11 @@ from crewai.utilities.events.tool_usage_events import (
ToolUsageErrorEvent,
)
# Skip streaming tests when running in CI/CD environments
skip_streaming_in_ci = pytest.mark.skipif(
os.getenv("CI") is not None, reason="Skipping streaming tests in CI/CD environments"
)
base_agent = Agent(
role="base_agent",
llm="gpt-4o-mini",
@@ -615,3 +622,152 @@ def test_llm_emits_call_failed_event():
assert len(received_events) == 1
assert received_events[0].type == "llm_call_failed"
assert received_events[0].error == error_message
@skip_streaming_in_ci
@pytest.mark.vcr(filter_headers=["authorization"])
def test_llm_emits_stream_chunk_events():
"""Test that LLM emits stream chunk events when streaming is enabled."""
received_chunks = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(LLMStreamChunkEvent)
def handle_stream_chunk(source, event):
received_chunks.append(event.chunk)
# Create an LLM with streaming enabled
llm = LLM(model="gpt-4o", stream=True)
# Call the LLM with a simple message
response = llm.call("Tell me a short joke")
# Verify that we received chunks
assert len(received_chunks) > 0
# Verify that concatenating all chunks equals the final response
assert "".join(received_chunks) == response
@skip_streaming_in_ci
@pytest.mark.vcr(filter_headers=["authorization"])
def test_llm_no_stream_chunks_when_streaming_disabled():
"""Test that LLM doesn't emit stream chunk events when streaming is disabled."""
received_chunks = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(LLMStreamChunkEvent)
def handle_stream_chunk(source, event):
received_chunks.append(event.chunk)
# Create an LLM with streaming disabled
llm = LLM(model="gpt-4o", stream=False)
# Call the LLM with a simple message
response = llm.call("Tell me a short joke")
# Verify that we didn't receive any chunks
assert len(received_chunks) == 0
# Verify we got a response
assert response and isinstance(response, str)
@pytest.mark.vcr(filter_headers=["authorization"])
def test_streaming_fallback_to_non_streaming():
"""Test that streaming falls back to non-streaming when there's an error."""
received_chunks = []
fallback_called = False
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(LLMStreamChunkEvent)
def handle_stream_chunk(source, event):
received_chunks.append(event.chunk)
# Create an LLM with streaming enabled
llm = LLM(model="gpt-4o", stream=True)
# Store original methods
original_call = llm.call
# Create a mock call method that handles the streaming error
def mock_call(messages, tools=None, callbacks=None, available_functions=None):
nonlocal fallback_called
# Emit a couple of chunks to simulate partial streaming
crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 1"))
crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk="Test chunk 2"))
# Mark that fallback would be called
fallback_called = True
# Return a response as if fallback succeeded
return "Fallback response after streaming error"
# Replace the call method with our mock
llm.call = mock_call
try:
# Call the LLM
response = llm.call("Tell me a short joke")
# Verify that we received some chunks
assert len(received_chunks) == 2
assert received_chunks[0] == "Test chunk 1"
assert received_chunks[1] == "Test chunk 2"
# Verify fallback was triggered
assert fallback_called
# Verify we got the fallback response
assert response == "Fallback response after streaming error"
finally:
# Restore the original method
llm.call = original_call
@pytest.mark.vcr(filter_headers=["authorization"])
def test_streaming_empty_response_handling():
"""Test that streaming handles empty responses correctly."""
received_chunks = []
with crewai_event_bus.scoped_handlers():
@crewai_event_bus.on(LLMStreamChunkEvent)
def handle_stream_chunk(source, event):
received_chunks.append(event.chunk)
# Create an LLM with streaming enabled
llm = LLM(model="gpt-3.5-turbo", stream=True)
# Store original methods
original_call = llm.call
# Create a mock call method that simulates empty chunks
def mock_call(messages, tools=None, callbacks=None, available_functions=None):
# Emit a few empty chunks
for _ in range(3):
crewai_event_bus.emit(llm, event=LLMStreamChunkEvent(chunk=""))
# Return the default message for empty responses
return "I apologize, but I couldn't generate a proper response. Please try again or rephrase your request."
# Replace the call method with our mock
llm.call = mock_call
try:
# Call the LLM - this should handle empty response
response = llm.call("Tell me a short joke")
# Verify that we received empty chunks
assert len(received_chunks) == 3
assert all(chunk == "" for chunk in received_chunks)
# Verify the response is the default message for empty responses
assert "I apologize" in response and "couldn't generate" in response
finally:
# Restore the original method
llm.call = original_call