torbjorn/my-pal-mcp-server
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactor: cleanup

Browse Source
This commit is contained in:
Fahad
2025-10-02 11:47:09 +04:00
parent 7fe9fc49f8
commit 6ec2033f34
1 changed files with 5 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
providers/openai_compatible.py
View File

@@ -534,16 +534,14 @@ class OpenAICompatibleProvider(ModelProvider):
resolved_model = self._resolve_model_name(model_name)
# Use the effective temperature we calculated earlier
if effective_temperature is not None:
supports_sampling = effective_temperature is not None
if supports_sampling:
completion_params["temperature"] = effective_temperature
supports_temperature = True
else:
# Model doesn't support temperature
supports_temperature = False
# Add max tokens if specified and model supports it
# O3/O4 models that don't support temperature also don't support max_tokens
if max_output_tokens and supports_temperature:
if max_output_tokens and supports_sampling:
completion_params["max_tokens"] = max_output_tokens
# Add any additional OpenAI-specific parameters
@@ -551,7 +549,7 @@ class OpenAICompatibleProvider(ModelProvider):
for key, value in kwargs.items():
if key in ["top_p", "frequency_penalty", "presence_penalty", "seed", "stop", "stream"]:
# Reasoning models (those that don't support temperature) also don't support these parameters
if not supports_temperature and key in ["top_p", "frequency_penalty", "presence_penalty"]:
if not supports_sampling and key in ["top_p", "frequency_penalty", "presence_penalty"]:
continue # Skip unsupported parameters for reasoning models
completion_params[key] = value