set model via default config instead

patchwork/patchflows/PRReview/PRReview.py

@@ -120,7 +120,8 @@ def run(self) -> dict:
 Ensure that you include all rules in your response, even if there\'s no violation. The output should directly reflect the reasoning in your thinking section.
 ''',
                     json_schema={"review": "The markdown text of the reviews"},
-                    model="claude-3-5-sonnet-latest")
+                    **self.inputs
+                )
             ).run()
 
             llm2_outputs = SimplifiedLLMOnce(
@@ -136,7 +137,8 @@ def run(self) -> dict:
 You should return an empty response if there are no code reviews that is actionable or useful.
 ''',
                     json_schema={"review": "The reviews curated"},
-                    model="claude-3-5-sonnet-latest")
+                    **self.inputs
+                )
             ).run()
 
             review = llm2_outputs.get("review")

patchwork/patchflows/PRReview/defaults.yml

@@ -1,7 +1,4 @@
 # PRReview Inputs
-diff_summary: long
-diff_suggestion: false
-
 
 # ReadPRDiffs Inputs
 # github_api_key: required-for-github-scm
@@ -14,7 +11,7 @@ diff_suggestion: false
 # CallLLM Inputs
 # openai_api_key: required-for-chatgpt
 # google_api_key: required-for-gemini
-# model: gpt-4o
+ model: gpt-4o-mini
 # client_base_url: https://api.openai.com/v1
 # Example HF model
 # client_base_url: https://api-inference.huggingface.co/models/codellama/CodeLlama-70b-Instruct-hf/v1

patchwork/step.py

@@ -73,8 +73,6 @@ def __init__(self, inputs: DataPoint):
         self.run = self.__managed_run
 
     def __init_subclass__(cls, input_class: Optional[Type] = None, output_class: Optional[Type] = None, **kwargs):
-        if cls.__name__ == "PreparePR":
-            print(1)
         input_class = input_class or getattr(cls, "input_class", None)
         if input_class is not None and not is_typeddict(input_class):
             input_class = None