Update app.py

app.py

@@ -89,36 +89,21 @@ def SpeechSynthesis(result):
 
 def parse_to_markdown(text):
     return text
-    
+        
+# Show ArXiv Scholary Articles! ----------------*************----▶️ Semantic and Episodic Memory System
 def search_arxiv(query):
-    
-    # Show ArXiv Scholary Articles! ----------------*************-------------***************----------------------------------------
-    # st.title("▶️ Semantic and Episodic Memory System")
+    start_time = time.strftime("%Y-%m-%d %H:%M:%S")
+
+
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    
     search_query = query
-    #top_n_results = st.slider(key='topnresults', label="Top n results as context", min_value=4, max_value=100, value=100)
-    #search_source = st.sidebar.selectbox(key='searchsource', label="Search Source", ["Semantic Search - up to 10 Mar 2024", "Arxiv Search - Latest - (EXPERIMENTAL)"])
     search_source = "Arxiv Search - Latest - (EXPERIMENTAL)" # "Semantic Search - up to 10 Mar 2024"
-    #llm_model = st.sidebar.selectbox(key='llmmodel', label="LLM Model", ["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mistral-7B-Instruct-v0.2", "google/gemma-7b-it", "None"])
     llm_model = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+    st.markdown('### 🔎 ' + query)
 
-    st.sidebar.markdown('### 🔎 ' + query)
-
-
+    # Search 1 - Retrieve the Papers
 
-    # ArXiv searcher ~-<>-~ Paper Summary - Ask LLM
-    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    response2 = client.predict(
-            query,	# str  in 'parameter_13' Textbox 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
-            True,	# bool  in 'Stream output' Checkbox component
-            api_name="/ask_llm"
-    )
-    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
-    st.markdown(response2)
-
-    # ArXiv searcher ~-<>-~ Paper References - Update with RAG
+    
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
     response1 = client.predict(
     		query,	
@@ -127,26 +112,46 @@ def search_arxiv(query):
     		"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.write('🔍Run of Multi-Agent System Paper References is Complete')
-    responseall = response1[0] + response1[1]
-    st.markdown(responseall)
-    result = response2 + responseall
-
-    SpeechSynthesis(result)  # Search History Reader / Writer IO Memory - Audio at Same time as Reading.
+    #st.markdown(response1)
+    lastpart=''
+    totalparts=''
+    #for parts in response1:
+    #    st.markdown(parts) # expect 2
+    #    lastpart=parts
+    #    totalparts=totalparts+parts
     
+    results = response1[0]  # Format for markdown display with links
+    results2 = response1[1]  # format for subquery without links
+    st.markdown(results)
+
+    RunSecondQuery = False
+    if RunSecondQuery:
+        # Search 2 - Retieve the Summary with Papers Context and Original Query
+        #client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
+        #newquery='Create a summary as markdown outline with emojis for query: ' + query + ' ' + totalparts
+        response2 = client.predict(
+                query,	# str  in 'parameter_13' Textbox component
+                #"mistralai/Mixtral-8x7B-Instruct-v0.1",	
+                #"mistralai/Mistral-7B-Instruct-v0.2", 
+                "google/gemma-7b-it",
+                True,	# bool  in 'Stream output' Checkbox component
+                api_name="/ask_llm"
+        )
+        st.markdown(response2)
+        results = results + response2
+
+    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
+    end_time = time.strftime("%Y-%m-%d %H:%M:%S")
+    start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
+    end_timestamp = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
+    elapsed_seconds = end_timestamp - start_timestamp
+    st.write(f"Start time: {start_time}")
+    st.write(f"Finish time: {end_time}")
+    st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
+    SpeechSynthesis(results)  # Search History Reader / Writer IO Memory - Audio at Same time as Reading.
     filename=generate_filename(query, "md")
-    create_file(filename, query, result, should_save)
-    saved_files = [f for f in os.listdir(".") if f.endswith(".md")]
-    selected_file = st.sidebar.selectbox("Saved Files", saved_files)
-
-    if selected_file:
-        file_content = load_file(selected_file)
-        st.sidebar.markdown(file_content)
-        if st.sidebar.button("🗑️ Delete"):
-            os.remove(selected_file)
-            st.warning(f"File deleted: {selected_file}")
-
-    return result
+    create_file(filename, query, results, should_save)
+    return results
             
 
 # Prompts for App, for App Product, and App Product Code
@@ -1250,7 +1255,7 @@ if GiveFeedback:
 try:
     query_params = st.query_params
     query = (query_params.get('q') or query_params.get('query') or [''])
-    if query: 
+    if len(query) > 1: 
         result = search_arxiv(query)
         #result2 = search_glossary(result) 
 except:
@@ -1388,14 +1393,14 @@ if AddAFileForContext:
                     st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
                     
 
-num_columns_video=st.slider(key="num_columns_video", label="Choose Number of Video Columns", min_value=1, max_value=15, value=10)
+num_columns_video=st.slider(key="num_columns_video", label="Choose Number of Video Columns", min_value=1, max_value=15, value=4)
 display_videos_and_links(num_columns_video)   # Video Jump Grid
 
-num_columns_images=st.slider(key="num_columns_images", label="Choose Number of Image Columns", min_value=1, max_value=10, value=4)
+num_columns_images=st.slider(key="num_columns_images", label="Choose Number of Image Columns", min_value=1, max_value=15, value=4)
 display_images_and_wikipedia_summaries(num_columns_images)   # Image Jump Grid
 
 display_glossary_grid(roleplaying_glossary)  # Word Glossary Jump Grid - Dynamically calculates columns based on details length to keep topic together
 
-num_columns_text=st.slider(key="num_columns_text", label="Choose Number of Text Columns", min_value=1, max_value=10, value=4)
+num_columns_text=st.slider(key="num_columns_text", label="Choose Number of Text Columns", min_value=1, max_value=15, value=4)
 display_buttons_with_scores(num_columns_text)  # Feedback Jump Grid