Brandon/improve llm structured output (#2029)

* code and tests work

* update docs

---------

Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
This commit is contained in:
Brandon Hancock (bhancock_ai)
2025-02-04 16:46:48 -05:00
committed by GitHub
parent 515478473a
commit f4bb040ad8
3 changed files with 108 additions and 2 deletions

View File

@@ -3,6 +3,7 @@ from time import sleep
from unittest.mock import MagicMock, patch
import pytest
from pydantic import BaseModel
from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
from crewai.llm import LLM
@@ -205,6 +206,52 @@ def test_llm_passes_additional_params():
assert result == "Test response"
def test_get_custom_llm_provider_openrouter():
llm = LLM(model="openrouter/deepseek/deepseek-chat")
assert llm._get_custom_llm_provider() == "openrouter"
def test_get_custom_llm_provider_gemini():
llm = LLM(model="gemini/gemini-1.5-pro")
assert llm._get_custom_llm_provider() == "gemini"
def test_get_custom_llm_provider_openai():
llm = LLM(model="gpt-4")
assert llm._get_custom_llm_provider() == "openai"
def test_validate_call_params_supported():
class DummyResponse(BaseModel):
a: int
# Patch supports_response_schema to simulate a supported model.
with patch("crewai.llm.supports_response_schema", return_value=True):
llm = LLM(
model="openrouter/deepseek/deepseek-chat", response_format=DummyResponse
)
# Should not raise any error.
llm._validate_call_params()
def test_validate_call_params_not_supported():
class DummyResponse(BaseModel):
a: int
# Patch supports_response_schema to simulate an unsupported model.
with patch("crewai.llm.supports_response_schema", return_value=False):
llm = LLM(model="gemini/gemini-1.5-pro", response_format=DummyResponse)
with pytest.raises(ValueError) as excinfo:
llm._validate_call_params()
assert "does not support response_format" in str(excinfo.value)
def test_validate_call_params_no_response_format():
# When no response_format is provided, no validation error should occur.
llm = LLM(model="gemini/gemini-1.5-pro", response_format=None)
llm._validate_call_params()
@pytest.mark.vcr(filter_headers=["authorization"])
def test_o3_mini_reasoning_effort_high():
llm = LLM(