Update functions.py

functions.py

@@ -47,17 +47,19 @@ def select_document_section_by_query_similarity(query: str, contexts: dict[(str,
     
     return document_similarities[0]
 
-def construct_prompt(question: str, context_embeddings: dict, df: pd.DataFrame) -> str:
+def construct_prompt(query: str, context_embeddings: dict, df: pd.DataFrame) -> str:
     """
-    Fetch relevant 
+    Construct the prompt for the ChatCompletion API
     """
-    _ , chosen_service = select_document_section_by_query_similarity(question, context_embeddings)
+    _ , chosen_service = select_document_section_by_query_similarity(query, context_embeddings)
         
     service_description = df.loc[chosen_service].description.replace("\n", " ")
-    header = "Answer the question as truthfully as possible using the provided context, and if the answer is not contained within the text below, say "
-    message = "I could not find an answer to your question, please reach out to Helpdesk."
+    introduction = "Answer the question as truthfully as possible using the provided context, and if the answer is not contained within the text below, say "
+    introduction += "I could not find an answer to your question, please reach out to Helpdesk."
+    question = f"\n\nQ: {query}"
+    message = introduction + "\n* " + "\n\nContext:\n" + service_description + question
     link = df.loc[chosen_service].link
-    return header + message + "\n* " + "\n\nContext:\n" + service_description + "\n\n Q: " + question + "\n A:", link
+    return message, link
 
 def answer_query_with_context(
     query: str,
@@ -65,24 +67,24 @@ def answer_query_with_context(
     document_embeddings: dict[(str, str), np.array],
     show_prompt: bool = False
 ) -> str:
+    
     prompt, link = construct_prompt(
         query,
         document_embeddings,
         df
     )
     
-    if show_prompt:
-        print(prompt)
-
     response = openai.ChatCompletion.create(
-                prompt=prompt,
-                **COMPLETIONS_API_PARAMS
-            )
+        model = COMPLETIONS_MODEL, # "gpt-3.5-turbo",
+        messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": prompt}
+        ]
+    )
     
     end_message = "\n\nPlease check out the relevant HMC service catalogue for more details: "+ link 
     end_message += """\n\nIf not satisfied with the answer, please email [email protected], call 909.607.7777 or visit the Helpdesk located on the Sprague first floor. """
     end_message += """Helpdesk representatives are also available for a remote chat session during normal hours on Monday - Friday, 8:00 AM - 5:00 PM PST via https://helpdesk.hmc.edu"""
-    
-    reply = response["choices"][0]["text"] + end_message
+    reply = response["choices"][0]["message"]["content"] + end_message
 
     return reply