Update app.py

app.py

@@ -676,24 +676,33 @@ Example: letter_queue = deque(random.sample(string.ascii_uppercase, 10))"""
     all = query + '   ' + response
     st.write('🔍Run 1 is Complete.')
 
-
+    # ArXiv searcher ~-<>-~
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
     result = client.predict(
-    		"What is Semantic and Episodic memory?",	# str  in 'Search' Textbox component
-    		4,	# float (numeric value between 4 and 10) in 'Top n results as context' Slider component
+    		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)
 
+# experimental 45 - - - - - - - - - - - - -<><><><><>
+    if result:
+        session_state["search_queries"].append(query)
+        #if query: 
+        #    search_arxiv(query)
+        #    search_glossary(query)
+        #st.markdown(' ')
+        
+    st.write('🔍Run 2 - Long Form Summary')
 
-    
-    # 🔍Run 1+N - plain query
-    response = chat_with_model45(result)        # experimental 45 - - - - - - - - - - - - -<><><><><>
+    # 🔍Run PaperSummarizer - plain query
+    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.  '
+    response = chat_with_model45(PaperSummarizer + result)        
     all = query + '   ' + response
-    st.write('🔍Run 1+N is Complete.')
-
+    st.write('🔍Run Paper Summarizer is Complete.')
+# experimental 45 - - - - - - - - - - - - -<><><><><>