Update app.py

app.py

@@ -542,7 +542,7 @@ def search_glossary(query):  # 🔍Run------------------------------------------
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
     response1 = client.predict(
     		query,	
-    		100,	
+    		10,	
     		"Semantic Search - up to 10 Mar 2024",	# Literal['Semantic Search - up to 10 Mar 2024', 'Arxiv Search - Latest - (EXPERIMENTAL)']  in 'Search Source' Dropdown component
     		"mistralai/Mixtral-8x7B-Instruct-v0.1",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
     		api_name="/update_with_rag_md"
@@ -552,19 +552,19 @@ def search_glossary(query):  # 🔍Run------------------------------------------
 # experimental 45 - - - - - - - - - - - - -<><><><><>
         
     # 🔍Run PaperSummarizer
-    PaperSummarizer = '  Create a paper summary as a markdown table with paper links clustering the features writing short markdown emoji outlines to extract three main ideas from summary. For each one create three simple points led by an emoji of the main three steps needed as method step process for implementing the idea as a single app.py streamlit python app.  '
+    PaperSummarizer = '  Create a paper summary as a markdown table with paper links clustering the features writing short markdown emoji outlines to extract three main ideas from each of the ten summaries. For each one create three simple points led by an emoji of the main three steps needed as method step process for implementing the idea as a single app.py streamlit python app.  '
     # = str(result).replace('\n', ' ').replace('|', '   ')
     response2 = chat_with_model45(PaperSummarizer + str(response1))        
     st.write('🔍Run 3 - Paper Summarizer is Complete.')
 
     # 🔍Run AppSpecifier
-    AppSpecifier = '  Design and write a streamlit python code listing and specification that implements each scientific method steps as a function and markdown table in comments with original paper link to outline the AI pipeline ensemble implementing code as full plan to build.'
+    AppSpecifier = '  Design and write a streamlit python code listing and specification that implements each scientific method steps as ten functions keeping specification in a markdown table in the function comments with original paper link to outline the AI pipeline ensemble implementing code as full plan to build.'
     #result = str(result).replace('\n', ' ').replace('|', '   ')
     response3 = chat_with_model45(AppSpecifier + str(response2))        
     st.write('🔍Run 4 - AppSpecifier is Complete.')
     
     # 🔍Run PythonAppCoder
-    PythonAppCoder = '  Create a streamlit python app implementing the following list of features using appropriate libraries and function design using streamlit.  Show full code listing as output with no commentary.  '
+    PythonAppCoder = '  Create a streamlit python app implementing the following list of features using appropriate libraries and function design using streamlit.  Show full code listing for the ten function app as output with no commentary.  '
     #result = str(result).replace('\n', ' ').replace('|', '   ')
     response4 = chat_with_model45(PythonAppCoder + str(response3))        
     st.write('🔍Run Python AppCoder is Complete.')