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55b7a20
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1 Parent(s): 92c52e1

Update kadiApy_ragchain.py

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  1. kadiApy_ragchain.py +4 -4
kadiApy_ragchain.py CHANGED
@@ -244,14 +244,14 @@ class KadiApyRagchain:
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- def formulate_question(self, source_code):
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  """
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  Generate a response using the retrieved contexts and the LLM.
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  """
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  prompt = f"""
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  You are a Python programming assistant specialized in the "Kadi-APY" library.
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  The "Kadi-APY" library is a Python package designed to facilitate interaction with the REST-like API of a software platform called Kadi4Mat.
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- Your task is to formulate the next logical question a programmer would ask themselves to implement and run the method provided in the "context".
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  "Context" contains snippets from the source code and metadata that provide details about the method.
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@@ -260,8 +260,8 @@ class KadiApyRagchain:
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  - Focus on determining the entry point of the class to which the method belongs.
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  - Avoid vague or general questions; be precise about the next actionable steps.
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- Context:
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- {context}
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  """
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  return self.llm.invoke(prompt).content
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+ def formulate_question(self, code_contexts):
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  """
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  Generate a response using the retrieved contexts and the LLM.
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  """
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  prompt = f"""
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  You are a Python programming assistant specialized in the "Kadi-APY" library.
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  The "Kadi-APY" library is a Python package designed to facilitate interaction with the REST-like API of a software platform called Kadi4Mat.
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+ Your task is to formulate the next logical question a programmer would ask themselves to implement and run the method provided in "Code-contexts".
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  "Context" contains snippets from the source code and metadata that provide details about the method.
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  - Focus on determining the entry point of the class to which the method belongs.
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  - Avoid vague or general questions; be precise about the next actionable steps.
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+ Code-contexts:
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+ {code_contexts}
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  """
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  return self.llm.invoke(prompt).content
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