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fix param for openai (#7483)

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This commit is contained in:
centdix
2026-01-05 10:56:27 +00:00
committed by GitHub
parent 26964e7f56
commit 7b29159a43
3 changed files with 242 additions and 3 deletions
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backend/windmill-worker/src/ai/providers/openai.rs
+3 -3
View File
@@ -217,7 +217,7 @@ pub struct ResponsesApiRequest<'a> {
#[serde(skip_serializing_if = "Option::is_none")]
pub temperature: Option<f32>,
#[serde(skip_serializing_if = "Option::is_none")]
pub max_completion_tokens: Option<u32>,
pub max_output_tokens: Option<u32>,
#[serde(skip_serializing_if = "Option::is_none")]
pub text: Option<ResponsesApiTextFormat>,
}
@@ -395,7 +395,7 @@ impl OpenAIQueryBuilder {
tools,
stream: Some(true),
temperature: args.temperature,
max_completion_tokens: args.max_tokens,
max_output_tokens: args.max_tokens,
text,
};
@@ -440,7 +440,7 @@ impl OpenAIQueryBuilder {
tools,
stream: None, // Image generation doesn't use streaming
temperature: args.temperature,
max_completion_tokens: args.max_tokens,
max_output_tokens: args.max_tokens,
text: None, // No structured output for image generation
};
integration_tests/ai_agent_tests/conftest.py
+12
View File
@@ -219,6 +219,8 @@ def create_ai_agent_flow(
streaming: bool | None = None,
include_user_images: bool = False,
output_type: str | None = None,
temperature: float | None = None,
max_completion_tokens: int | None = None,
) -> dict[str, Any]:
"""
Create a FlowValue for an AI agent.
@@ -231,6 +233,8 @@ def create_ai_agent_flow(
streaming: Optional flag to enable streaming responses
include_user_images: If True, adds user_images input from flow_input
output_type: Optional output type ("text" or "image")
temperature: Optional temperature for sampling (0.0-2.0)
max_completion_tokens: Optional maximum tokens for completion
Returns:
A FlowValue dictionary ready to be sent to preview_flow
@@ -257,6 +261,14 @@ def create_ai_agent_flow(
if output_type is not None:
input_transforms["output_type"] = {"type": "static", "value": output_type}
# Add temperature if provided
if temperature is not None:
input_transforms["temperature"] = {"type": "static", "value": temperature}
# Add max_completion_tokens if provided
if max_completion_tokens is not None:
input_transforms["max_completion_tokens"] = {"type": "static", "value": max_completion_tokens}
module_value = {
"type": "aiagent",
"input_transforms": input_transforms,
integration_tests/ai_agent_tests/test_completion_params.py
+227
View File
@@ -0,0 +1,227 @@
"""
Completion parameter tests for AI agents.
Tests that AI agents correctly handle temperature and max_completion_tokens:
- Default parameters (undefined)
- Low temperature (0.0 - deterministic)
- High temperature (0.9 - more random)
- Low max_completion_tokens (10 - short response)
- High max_completion_tokens (4096 - longer response allowed)
- Combined parameters
"""
import pytest
from .conftest import AIAgentTestClient, create_ai_agent_flow
from .providers import ALL_PROVIDERS, get_provider_ids
class TestCompletionParams:
"""Test AI agent temperature and max_completion_tokens parameters."""
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_default_params(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with default parameters (no temperature or max_completion_tokens).
This serves as a baseline to ensure the agent works without these params.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant. Be concise.",
output_type="text",
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "What is 2 + 2? Answer with just the number."},
)
assert result is not None
# Result should contain the answer
result_str = str(result)
assert "4" in result_str, f"Expected '4' in result: {result}"
print(f"Default params result from {provider_config['name']}: {result}")
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_low_temperature(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with temperature=0.0 (deterministic output).
Low temperature should produce more focused, consistent responses.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant. Be concise.",
output_type="text",
temperature=0.0,
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "What is 2 + 2? Answer with just the number."},
)
assert result is not None
result_str = str(result)
assert "4" in result_str, f"Expected '4' in result: {result}"
print(f"Low temperature (0.0) result from {provider_config['name']}: {result}")
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_high_temperature(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with temperature=0.9 (more random output).
High temperature should still produce valid responses.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant. Be concise.",
output_type="text",
temperature=0.9,
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "What is 2 + 2? Answer with just the number."},
)
assert result is not None
# With high temperature, the model might be more creative but should still respond
result_str = str(result)
# We just verify we got a non-empty response
assert len(result_str) > 0, f"Expected non-empty result: {result}"
print(f"High temperature (0.9) result from {provider_config['name']}: {result}")
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_low_max_tokens(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with max_completion_tokens=10 (short response).
The response should be truncated or very short.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant.",
output_type="text",
max_completion_tokens=10,
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "Explain the theory of relativity in detail."},
)
assert result is not None
# The response should be truncated due to low max_tokens
# We verify we got some response (even if truncated)
result_str = str(result)
assert len(result_str) > 0, f"Expected non-empty result: {result}"
print(f"Low max_tokens (10) result from {provider_config['name']}: {result}")
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_high_max_tokens(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with max_completion_tokens=4096 (longer response allowed).
The model should be able to produce longer responses if needed.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant. Be concise.",
output_type="text",
max_completion_tokens=4096,
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "What is 2 + 2? Answer with just the number."},
)
assert result is not None
result_str = str(result)
assert "4" in result_str, f"Expected '4' in result: {result}"
print(f"High max_tokens (4096) result from {provider_config['name']}: {result}")
@pytest.mark.parametrize(
"provider_config",
ALL_PROVIDERS,
ids=get_provider_ids(ALL_PROVIDERS),
)
def test_combined_params(
self,
client: AIAgentTestClient,
setup_providers,
provider_config,
):
"""
Test with both temperature and max_completion_tokens set.
Verifies that both parameters work together correctly.
"""
flow_value = create_ai_agent_flow(
provider_input_transform=provider_config["input_transform"],
system_prompt="You are a helpful assistant. Be concise.",
output_type="text",
temperature=0.5,
max_completion_tokens=100,
)
result = client.run_preview_flow(
flow_value=flow_value,
args={"user_message": "What is 2 + 2? Answer with just the number."},
)
assert result is not None
result_str = str(result)
assert "4" in result_str, f"Expected '4' in result: {result}"
print(f"Combined params (temp=0.5, max_tokens=100) result from {provider_config['name']}: {result}")
if __name__ == "__main__":
pytest.main([__file__, "-v", "-s"])