revert line-length for now

02-household-queries/debugging.py

@@ -65,7 +65,9 @@ class CaptureLlmPromptHandler(BaseCallbackHandler):
     def __init__(self, printToStdOut=True):
         self.toStdout = printToStdOut
 
-    async def on_llm_start(self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) -> Any:
+    async def on_llm_start(
+        self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
+    ) -> Any:
         formatted_prompts = "\n".join(prompts).replace("```", "``")
         if self.toStdout:
             print(f"\nPROMPT:\n{formatted_prompts}")

02-household-queries/dspy_engine.py

@@ -24,7 +24,9 @@ class BasicQA(dspy.Signature):
     """Answer questions with short answers."""
 
     question = dspy.InputField()
-    answer = dspy.OutputField(desc="Respond with only one of these words: Yes, No, Maybe")
+    answer = dspy.OutputField(
+        desc="Respond with only one of these words: Yes, No, Maybe"
+    )
 
 
 def run_basic_predictor(query):
@@ -69,7 +71,9 @@ class GenerateAnswer(dspy.Signature):
 Focus on clarity and decisiveness, being concise in conveying your evaluation while catering to the specifics of the question.
 """
 
-    context = dspy.InputField(desc="may contain relevant facts used to answer the question")
+    context = dspy.InputField(
+        desc="may contain relevant facts used to answer the question"
+    )
     question = dspy.InputField()
     answer = dspy.OutputField(
         desc="Start with one of these words: Yes, No, Maybe",
@@ -206,7 +210,9 @@ def main_train(qa_pairs):
     print("Using retrieve_k =", retrieve_k)
     module: dspy.Module = RAG(retrieve_k)
 
-    filename = input("Specify compiled_module file to load optimized module or press Enter to start from scratch: ")
+    filename = input(
+        "Specify compiled_module file to load optimized module or press Enter to start from scratch: "
+    )
     if filename:
         module.load(filename)
         compiled_module = module
@@ -237,11 +243,15 @@ def main_train(qa_pairs):
     """)
     if not llm_choice:
         llm_choice = "openhermes"
-    dspy.settings.configure(lm=create_llm_model(llm_choice), rm=create_retriever_model())
+    dspy.settings.configure(
+        lm=create_llm_model(llm_choice), rm=create_retriever_model()
+    )
 
     if not filename:
         file_suffix = f"optimizer{optimizer_choice}_{retrieve_k}_{llm_choice}_{time.strftime('%Y-%m-%d-%H%M%S')}"
-        compiled_module = optimize_module(optimizer, module, training, eval_kwargs, file_suffix)
+        compiled_module = optimize_module(
+            optimizer, module, training, eval_kwargs, file_suffix
+        )
     print_optimization(compiled_module)
 
     evaluate_module(compiled_module, eval_metric, training)
@@ -335,7 +345,9 @@ def optimize_module(optimizer, module, training, eval_kwargs, file_suffix):
     print("----- optimizing ------------------")
     if eval_kwargs:
         # COPRO requires eval_kwargs whereas other optimizers don't
-        compiled_module = optimizer.compile(module, trainset=training, eval_kwargs=eval_kwargs)
+        compiled_module = optimizer.compile(
+            module, trainset=training, eval_kwargs=eval_kwargs
+        )
     else:
         compiled_module = optimizer.compile(module, trainset=training)
     compiled_module.save(f"compiled_module-{file_suffix}.json")

02-household-queries/pyproject.toml

@@ -1,3 +1,2 @@
 [tool.ruff]
-# Allow lines to be as long as 120.
-line-length = 120
+# line-length = 120