Update app.py

app.py

@@ -540,39 +540,38 @@ def search_glossary(query):  # 🔍Run------------------------------------------
 
     # ArXiv searcher ~-<>-~
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    result = client.predict(
+    response2 = client.predict(
     		query,	
     		100,	
     		"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"
     )
-    st.markdown(result)
     st.write('🔍Run 2 - Multi-Agent Systems is Complete')
 
 # experimental 45 - - - - - - - - - - - - -<><><><><>
         
     # 🔍Run PaperSummarizer
-    PaperSummarizer = '  Create a diagram graphical representation of this: Summarize this paper set with short emoji outlines and preserve links, shortening it significantly. Create emoji filled short summaries per paper structured as markdown tables and outlines and show full markdown code listing.  '
-    result = str(result).replace('\n', ' ').replace('|', '   ')
-    response2 = chat_with_model45(PaperSummarizer + result)        
+    PaperSummarizer = '  Create a paper summary as a markdown table clustering the features with short emoji outlines and preserve links, shortening it significantly. 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 streamlit python app.  '
+    # = str(result).replace('\n', ' ').replace('|', '   ')
+    response3 = chat_with_model45(PaperSummarizer + response1 + response2)        
     st.write('🔍Run 3 - Paper Summarizer is Complete.')
 
     # 🔍Run AppSpecifier
-    AppSpecifier = '  Design and write a creative superpower creating specification for a genius coder which has the scientific methods of steps and functions defined in a multiple markdown topic table and outline ensemble which serves as a thesis and comprehensive plan to build.'
-    result = str(result).replace('\n', ' ').replace('|', '   ')
-    response3 = chat_with_model45(AppSpecifier + response2 + query)        
+    AppSpecifier = '  Design and write a streamlit python app specification that implements each scientific method steps as function defined and described as a sorted and grouped topic table to outline the AI pipeline ensemble implementing code as full plan to build.'
+    #result = str(result).replace('\n', ' ').replace('|', '   ')
+    response4 = chat_with_model45(AppSpecifier + response3)        
     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.  '
-    result = str(result).replace('\n', ' ').replace('|', '   ')
-    response4 = chat_with_model45(PythonAppCoder + response3 + query)        
+    #result = str(result).replace('\n', ' ').replace('|', '   ')
+    response5 = chat_with_model45(PythonAppCoder + response4)        
     st.write('🔍Run Python AppCoder is Complete.')
 
 # experimental 45 - - - - - - - - - - - - -<><><><><>
     
-    responseAll = query + response1 + response2 + response3 + response4
+    responseAll = query + response1 + response2 + response3 + response4 + response5
     filename = generate_filename(responseAll, "md")
     create_file(filename, query, responseAll, should_save)
     #queries = query + specquery + codequery + webquery