Fixed issue with suggestions

app.py

@@ -62,20 +62,8 @@ def clean_text(text):
     return re.sub(r"(For more information, follow the links provided:).*", "", text, flags=re.DOTALL)
 
 def parse_suggestions(response):
-    start_tag = "<SGs>"
-    end_tag = "</SGs>"
-    
-    start_index = response.find(start_tag)
-    end_index = response.find(end_tag) + len(end_tag)
-    
-    if start_index == -1 or end_index == -1:
-        return []
-
-    suggestions_xml = response[start_index:end_index]
-    
-    root = ET.fromstring(suggestions_xml)
-    suggestions = [suggestion.text for suggestion in root.findall('SG')]
-    
+    suggestions = re.findall(r'<SG>(.*?)</SG>', response)
+    suggestions = ["" if suggestion == "Suggestion" else suggestion for suggestion in suggestions]
     return suggestions
 
 def get_answer(query, history, temperature, top_p, max_token_count):
@@ -85,7 +73,7 @@ def get_answer(query, history, temperature, top_p, max_token_count):
     max_words = math.floor(max_token_count*0.75)
 
     retrievalResults, retrieve_execution_time = retrieve(query)
-    highest_score = retrievalResults[0]['score']
+    highest_score = retrievalResults[0]['score'] if retrievalResults else 0
 
     if highest_score > 0.45:
         contexts = get_contexts(retrievalResults)
@@ -127,14 +115,10 @@ def get_answer(query, history, temperature, top_p, max_token_count):
     If necessary, reduce the amount of detail provided to keep the response within the word limit but still complete.
 
     Additionally, only if there is sufficient remaining token capacity, provide 2 or 3 related questions that the user might want to ask next based on the topic.
-    If possible, use the following structure for these suggested questions:
-    <SGs>
-        <SG>First related question</SG>
-        <SG>Second related question</SG>
-        <SG>Third related question</SG>
-    </SGs>
+    Format these suggested questions as follows, leaving the <SG> tags empty if no suggestions are generated:
+    <SGs><SG>Suggestion</SG><SG>Suggestion</SG><SG>Suggestion</SG></SGs>
     
-    Ensure these suggested questions are brief, relevant, and encourage further exploration on the topic.
+    Ensure these suggested questions are brief, relevant, and encourage further exploration on the topic.   
     Assistant:
     """
 
@@ -164,20 +148,23 @@ 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']
     
-    suggestions = parse_suggestions(response_text)
+    print("response_text:\n")
+    pp.pprint(response_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)
+    suggestions = parse_suggestions(response_text)
 
     response_json = {
         "response_text": response_text.split('<SGs>')[0].strip(),
         "suggestions": suggestions,
-        "article_urls": article_urls_text
+        "article_ids": unique_article_ids
     }
+
+    if response_json["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_json_str = json.dumps(response_json, indent=4)
-    # print("Response Json:\n", response_json_str)
+    response_json_str = json.dumps(response_json, indent=4)
+    print("Response Json:\n", response_json_str)
 
     prompt_and_time = f"""
     Prompt:
@@ -185,7 +172,7 @@ def get_answer(query, history, temperature, top_p, max_token_count):
     Retrieve execution time: {retrieve_execution_time} seconds
     Invoke model execution time: {invoke_model_time} seconds
     """
-    return response_json["response_text"] + response_json["article_urls"], prompt_and_time, response_json["suggestions"] 
+    return response_json["response_text"] + article_urls_text, prompt_and_time, response_json["suggestions"]
 
 def format_chat_history(chat_history):
     prompt = ""
@@ -201,12 +188,21 @@ def respond(message, chat_history, temperature=0.9, top_p=0.6, max_token_count=5
 
     stream, prompt_and_time, suggestions = get_answer(message, formatted_history, temperature, top_p, max_token_count)
 
+    suggestion1_visible = bool(suggestions[0])
+    suggestion2_visible = bool(suggestions[1])
+    suggestion3_visible = bool(suggestions[2])
+
     for idx, text_token in enumerate(stream):
         if idx == 0 and text_token.startswith(" "):
             text_token = text_token[1:]
 
         chat_history[-1][1] += text_token
-        yield "", chat_history, prompt_and_time, suggestions[0], suggestions[1], suggestions[2]
+        yield (
+            "", chat_history, prompt_and_time, 
+            suggestions[0], suggestion1_visible, 
+            suggestions[1], suggestion2_visible, 
+            suggestions[2], suggestion3_visible
+        )
     
 def clear_chat_history():
     return '', []
@@ -218,11 +214,15 @@ def main():
         }
     """) as demo:
         chatbot = gr.Chatbot([[None, initial_message]], height=600)
+        
+        suggestion1_visible = gr.State(value=True)
+        suggestion2_visible = gr.State(value=True)
+        suggestion3_visible = gr.State(value=True)
 
         with gr.Row():
-            suggestion1 = gr.Button("How to edit RFID crew badge?", elem_classes="suggestion-button")
-            suggestion2 = gr.Button("What types of RFID tags exist?", elem_classes="suggestion-button")
-            suggestion3 = gr.Button("Is it possible to delete a facility?", elem_classes="suggestion-button")
+            suggestion1 = gr.Button("How to edit RFID crew badge?", elem_classes="suggestion-button", visible=suggestion1_visible)
+            suggestion2 = gr.Button("What types of RFID tags exist?", elem_classes="suggestion-button", visible=suggestion2_visible)
+            suggestion3 = gr.Button("Is it possible to delete a facility?", elem_classes="suggestion-button", visible=suggestion3_visible)
 
         msg = gr.Textbox(label="Question")
         
@@ -235,33 +235,35 @@ def main():
         btn = gr.Button("Submit")
         clear = gr.Button("Clear history")
 
-        btn.click(
-            respond, 
-            inputs=[msg, chatbot, temperature, top_p, max_token_count], 
-            outputs=[msg, chatbot, prompt_and_time, suggestion1, suggestion2, suggestion3]
-        )
+        inputs= [
+            msg, chatbot, temperature, top_p, max_token_count
+        ]
+        outputs = [
+            msg, chatbot, prompt_and_time,
+            suggestion1, suggestion1_visible,
+            suggestion2, suggestion2_visible,
+            suggestion3, suggestion3_visible
+        ]
+        
+        btn.click(respond, inputs=inputs, outputs=outputs)
 
         suggestion1.click(lambda s: s, inputs=suggestion1, outputs=msg).then(
             respond, 
-            inputs=[msg, chatbot, temperature, top_p, max_token_count], 
-            outputs=[msg, chatbot, prompt_and_time, suggestion1, suggestion2, suggestion3]
+            inputs=inputs, 
+            outputs=outputs
         )
         suggestion2.click(lambda s: s, inputs=suggestion2, outputs=msg).then(
             respond, 
-            inputs=[msg, chatbot, temperature, top_p, max_token_count], 
-            outputs=[msg, chatbot, prompt_and_time, suggestion1, suggestion2, suggestion3]
+            inputs=inputs, 
+            outputs=outputs
         )
         suggestion3.click(lambda s: s, inputs=suggestion3, outputs=msg).then(
             respond, 
-            inputs=[msg, chatbot, temperature, top_p, max_token_count], 
-            outputs=[msg, chatbot, prompt_and_time, suggestion1, suggestion2, suggestion3]
-        )
-    
-        msg.submit(
-            respond, 
-            inputs=[msg, chatbot, temperature, top_p, max_token_count],
-            outputs=[msg, chatbot, prompt_and_time, suggestion1, suggestion2, suggestion3]
+            inputs=inputs, 
+            outputs=outputs
         )
+
+        msg.submit(respond, inputs=inputs, outputs=outputs)
     
         clear.click(clear_chat_history, outputs=[msg, chatbot, prompt_and_time])