style

Author: joschkabraun

parea/client.py

@@ -113,7 +113,7 @@ def trace_dspy(self):
         try:
             import openai
 
-            if openai.version.__version__.startswith('0.'):
+            if openai.version.__version__.startswith("0."):
                 self.wrap_openai_client(openai, "dspy")
             else:
                 self.auto_trace_openai_clients("dspy")

parea/cookbook/dspy/dspy_examples.py

@@ -21,25 +21,27 @@
 dspy.settings.configure(rm=colbertv2_wiki17_abstracts)
 
 
-#Define a simple signature for basic question answering
+# Define a simple signature for basic question answering
 class BasicQA(dspy.Signature):
     """Answer questions with short factoid answers."""
+
     question = dspy.InputField()
     answer = dspy.OutputField(desc="often between 1 and 5 words")
 
+
 # Pass signature to Predict module
 generate_answer = dspy.Predict(BasicQA)
 
 # Call the predictor on a particular input.
-question='What is the color of the sky?'
+question = "What is the color of the sky?"
 pred = generate_answer(question=question)
 
 print(f"Question: {question}")
 print(f"Predicted Answer: {pred.answer}")
 question = "What's something great about the ColBERT retrieval model ?!?abc"
 
 # 1) Declare with a signature, and pass some config.
-classify = dspy.ChainOfThought('question -> answer', n=1)
+classify = dspy.ChainOfThought("question -> answer", n=1)
 
 # 2) Call with input argument.
 response = classify(question=question)
@@ -51,14 +53,16 @@ class BasicQA(dspy.Signature):
 # Define a simple signature for basic question answering
 class BasicQA(dspy.Signature):
     """Answer questions with short factoid answers."""
+
     question = dspy.InputField()
     answer = dspy.OutputField(desc="often between 1 and 5 words")
 
-#Pass signature to ChainOfThought module
+
+# Pass signature to ChainOfThought module
 generate_answer = dspy.ChainOfThought(BasicQA)
 
 # Call the predictor on a particular input.
-question='What is the color of the sky?12'
+question = "What is the color of the sky?12"
 pred = generate_answer(question=question)
 
 print(f"Question: {question}")
@@ -67,9 +71,11 @@ class BasicQA(dspy.Signature):
 
 class BasicQA(dspy.Signature):
     """Answer questions with short factoid answers."""
+
     question = dspy.InputField()
     answer = dspy.OutputField(desc="often between 1 and 5 words")
 
+
 # Example completions generated by a model for reference
 completions = [
     dspy.Prediction(rationale=" I recall  that during clear days, the sky often appears this colo12r", answer="blue"),
@@ -81,25 +87,27 @@ class BasicQA(dspy.Signature):
 compare_answers = dspy.MultiChainComparison(BasicQA)
 
 # Call the MultiChainComparison on the completions
-question = ' What is the color of th e sky14?'
+question = " What is the color of th e sky14?"
 final_pred = compare_answers(completions, question=question)
 
 print(f"Question: {question}")
 print(f"Final Predicted Answer (after comparison): {final_pred.answer}")
 print(f"Final Rationale: {final_pred.rationale}")
 
 
-#Define a simple signature for basic question answering
+# Define a simple signature for basic question answering
 class GenerateAnswer(dspy.Signature):
     """Answer questions with short factoid answers."""
+
     question = dspy.InputField()
     answer = dspy.OutputField(desc="often between 1 and 5 words")
 
+
 # Pass signature to ProgramOfThought Module
 pot = dspy.ProgramOfThought(GenerateAnswer)
 
-#Call the ProgramOfThought module on a particular input
-question = 'Sarah  has 5 applez. She buys 123 more apples from the store. How many apples does Sarah have now?'
+# Call the ProgramOfThought module on a particular input
+question = "Sarah  has 5 applez. She buys 123 more apples from the store. How many apples does Sarah have now?"
 result = pot(question=question)
 
 print(f"Question: {question}")
@@ -125,14 +133,14 @@ class BasicQA(dspy.Signature):
 print(f"Final Predicted Answer (after ReAct process): {result.answer}")
 
 
-query='Where was the first FIFA World Cup held?12'
+query = "Where was the first FIFA World Cup held?12"
 
 
 # Call the retriever on a particular query.
 retrieve = dspy.Retrieve(k=3)
 topK_passages = retrieve(query).passages
 
-print(f"Top {retrieve.k} passages for question: {query} \n", '-' * 30, '\n')
+print(f"Top {retrieve.k} passages for question: {query} \n", "-" * 30, "\n")
 
 for idx, passage in enumerate(topK_passages):
-    print(f'{idx+1}]', passage, '\n')
+    print(f"{idx+1}]", passage, "\n")

parea/utils/trace_integrations/dspy.py

@@ -23,7 +23,7 @@ def instrument(self) -> None:
                 module=_DSP_MODULE_NAME,
                 name=lm.__name__ + ".basic_request",
                 factory=CopyableFunctionWrapper,
-                args=(_GeneralDSPyWrapper('request'),),
+                args=(_GeneralDSPyWrapper("request"),),
             )
 
         # Predict is a concrete (non-abstract) class that may be invoked
@@ -46,12 +46,11 @@ def instrument(self) -> None:
                 args=(_PredictForwardWrapper(),),
             )
 
-
         wrap_object(
             module=_DSPY_MODULE_NAME,
             name="Retrieve.forward",
             factory=CopyableFunctionWrapper,
-            args=(_GeneralDSPyWrapper('forward'),),
+            args=(_GeneralDSPyWrapper("forward"),),
         )
 
         wrap_object(
@@ -61,7 +60,7 @@ def instrument(self) -> None:
             # forward method and invokes that method using __call__.
             name="Module.__call__",
             factory=CopyableFunctionWrapper,
-            args=(_GeneralDSPyWrapper('forward'),),
+            args=(_GeneralDSPyWrapper("forward"),),
         )
 
         # At this time, there is no common parent class for retriever models as
@@ -71,7 +70,7 @@ def instrument(self) -> None:
             module=_DSP_MODULE_NAME,
             name="ColBERTv2.__call__",
             factory=CopyableFunctionWrapper,
-            args=(_GeneralDSPyWrapper('__call__'),),
+            args=(_GeneralDSPyWrapper("__call__"),),
         )