Updated prompt

app.py

@@ -55,15 +55,12 @@ def get_contexts(retrievalResults):
         contexts += retrievedResult['content']['text'] + '\n'
     return contexts
 
-def remove_link(text):
-    pattern = r"\n\nFor more information, follow the link provided: https:\/\/knowledge\.operativeiq\.com\/articles\/\d{9}"
-    cleaned_text = re.sub(pattern, '', text)
-    return cleaned_text
+def clean_text(text):
+    return re.sub(r"(Here are some related questions you might be interested in:|For more information, follow the links provided:).*", "", text, flags=re.DOTALL)
 
 def get_answer(query, history, temperature, top_p, max_token_count):
-    history = remove_link(history)
     contexts = ""
-    article_url_text = ""    
+    unique_article_ids = []
     max_words = math.floor(max_token_count*0.75)
 
     retrievalResults, retrieve_execution_time = retrieve(query)
@@ -71,39 +68,52 @@ def get_answer(query, history, temperature, top_p, max_token_count):
 
     if highest_score > 0.45:
         contexts = get_contexts(retrievalResults)
-        article_url = f"https://knowledge.operativeiq.com/articles/{retrievalResults[0]['metadata'].get('article_id')}"
-        article_url_text = f"\n\nFor more information, follow the link provided: {article_url}"
+        
+        for result in retrievalResults:
+            article_id = result['metadata'].get('article_id')
+            if article_id not in unique_article_ids:
+                unique_article_ids.append(article_id)
+            if len(unique_article_ids) == 3:
+                break
     
     PROMPT_TEMPLATE = f""" 
     System: You are an intelligent assistant helping users understand and navigate website functionalities.
     Your goal is to provide clear, accurate, and contextually relevant answers based on the information provided.
-
     Use the information enclosed in the <context> tags and refer to the conversation history in the <history> tags to answer the user's question in the <question> tags. 
     If you don't know the answer, just say that you don't know, don't try to make up an answer.
     
     Your response must:
+    - Be in the same language that used in question.
     - Be fully formed and grammatically correct without cutting off any sentences.
     - Complete a logical thought or sentence before stopping, ensuring the response doesn't end mid-sentence.
     - Be clear, easy to understand, and succinct, not exceeding {max_words} words.
     - Refer specifically to website features or actions when relevant to the user's question.
     - Avoid providing URL links or external references.
+    - Use a visually appealing and easy-to-read format. Structure information in short, clear paragraphs and, where applicable, use bullet points or numbered lists.
     
     <history>
     {history}
     </history>
-
     <context>
     {contexts}
     </context>
-
     <question>
     {query}
     </question>
-
     Provide a detailed, concise response that fully answers the user's question.
     Make sure all sentences of your reponse are completely formed and grammatically correct.
     If necessary, reduce the amount of detail provided to keep the response within the word limit but still complete.
 
+    Additionally, after your response, provide 2 or 3 related questions that the user might want to ask next based on the topic.
+    Stick strictly to this structure:
+
+    Here are some related questions you might be interested in:
+    <button style="background-color: #4CAF50; color: white; padding: 10px; margin: 5px; border: none; border-radius: 5px; cursor: pointer; font-size: 16px;">First related question</button>
+    <button style="background-color: #4CAF50; color: white; padding: 10px; margin: 5px; border: none; border-radius: 5px; cursor: pointer; font-size: 16px;">Second related question</button>
+    <button style="background-color: #4CAF50; color: white; padding: 10px; margin: 5px; border: none; border-radius: 5px; cursor: pointer; font-size: 16px;">Third related question</button>
+    
+    Ensure these suggested questions are brief, relevant, and encourage further exploration on the topic.
+
     Assistant:
     """
 
@@ -133,7 +143,10 @@ def get_answer(query, history, temperature, top_p, max_token_count):
     response_body = json.loads(response.get('body').read())
     response_text = response_body['results'][0]['outputText']
     
-    response_text += article_url_text
+    if unique_article_ids:
+        article_urls_text = "\n\nFor more information, follow the links provided:\n" + "\n".join(
+            f"· https://knowledge.operativeiq.com/articles/{article_id}" for article_id in unique_article_ids)
+        response_text += article_urls_text
 
     prompt_and_time = f"""
     Prompt:
@@ -148,11 +161,12 @@ def format_chat_history(chat_history):
     prompt = ""
     for turn in chat_history:
         user_message, bot_message = turn
-        prompt = f"{prompt}User: {user_message}\nAssistant: {bot_message}\n"
+        cleaned_message = clean_text(bot_message)
+        prompt = f"{prompt}User: {user_message}\nAssistant: {cleaned_message}\n"
     return prompt
 
 def respond(message, chat_history, temperature=0.9, top_p=0.6, max_token_count=512):
-    formatted_history = format_chat_history(chat_history)
+    formatted_history = format_chat_history(chat_history[-4:])
     chat_history.append([message, ""])
 
     stream, prompt_and_time = get_answer(message, formatted_history, temperature, top_p, max_token_count)