Update kadiApy_ragchain.py

kadiApy_ragchain.py

@@ -31,8 +31,8 @@ class KadiApyRagchain:
         #doc_contexts = self.retrieve_contexts(query, k=3, filter={"dataset_category": "kadi_apy_docs"})
         #code_contexts = self.retrieve_contexts(query, k=5, filter={"dataset_category": "kadi_apy_source_code"})
 
-      #  doc_contexts = self.retrieve_contexts(query, k=3, filter={"dataset_category": "kadi_apy_docs"})
-      #  code_contexts = self.retrieve_contexts(rewritten_query, k=5, filter={"dataset_category": "kadi_apy_source_code"})
+        # doc_contexts = self.retrieve_contexts(query, k=3, filter={"dataset_category": "kadi_apy_docs"})
+        # code_contexts = self.retrieve_contexts(rewritten_query, k=5, filter={"dataset_category": "kadi_apy_source_code"})
         
         
         # Format contexts
@@ -130,39 +130,6 @@ class KadiApyRagchain:
         context = self.vector_store.similarity_search(query = query, k=k, filter=filter)       
         return context
 
-    # def generate_response(self, query, doc_context, code_context):
-    #     """
-    #     Generate a response using the retrieved contexts and the LLM.
-    #     """
-
-
-    #     prompt = f"""You are a Python programming assistant specialized in the "Kadi-APY" library. 
-    #                  The "Kadi-APY" library is a Python package designed to facilitate interaction with the REST-like API of a software platform called Kadi4Mat. 
-    #                  Your task is to answer the user's query based on the guidelines and if needed the combine understanding provided by 
-    #                  "Document snippets" with the implementation details provided by "Code Snippets."
-
-    #                  Guidelines if generating code:
-    #                     - Display the complete code first, followed by a concise explanation in no more than 5 sentences.
-                    
-    #                  General Guideline:
-    #                     - If the user's query can not be fullfilled based on the provided snippets, reply with "The API does not support the requested functionality"
-    #                     - If the user's query does not implicate any task, reply with a question asking the user to elaborate.
-               
-    #                 "Document Snippets": These contain documentation excerpts and code examples that explain how to use the "Kadi-APY" library
-    #                 Document Snippets:
-    #                 {doc_context}
-
-
-    #                 "Code Snippets": These are raw source code fragments from the implementation of the "Kadi-APY" library.
-    #                 Code Snippets:
-    #                 {code_context}
-        
-    #                 Query:
-    #                 {query}
-    #             """
-    #     return self.llm.invoke(prompt).content
-
-
     def generate_response(self, query, chat_history, doc_context, code_context):
         """
         Generate a response using the retrieved contexts and the LLM.
@@ -203,7 +170,6 @@ class KadiApyRagchain:
     
     def format_documents(self, documents):
         formatted_docs = []
-        print("################################# start of doc #######################################")
         for i, doc in enumerate(documents, start=1):
             formatted_docs.append(f"Snippet {i}: \n")            
             formatted_docs.append("\n")