Update backup11.app.py

backup11.app.py

@@ -54,7 +54,7 @@ LOCAL_APP_URL = "https://huggingface.co/spaces/awacke1/AzureCosmosDBUI"
 CosmosDBUrl = 'https://portal.azure.com/#@AaronCWackergmail.onmicrosoft.com/resource/subscriptions/003fba60-5b3f-48f4-ab36-3ed11bc40816/resourceGroups/datasets/providers/Microsoft.DocumentDB/databaseAccounts/acae-afd/dataExplorer'
 
 # 🤖 Anthropic configuration - Teaching machines to be more human (and funnier)
-client = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
+anthropicclient = anthropic.Anthropic(api_key=os.environ.get("ANTHROPIC_API_KEY"))
 
 # 🧠 Initialize session state - Because even apps need a good memory
 if "chat_history" not in st.session_state:
@@ -311,22 +311,33 @@ def archive_current_container(database_name, container_name, client):
     except Exception as e:
         return f"An error occurred while archiving data: {str(e)} 😢"
 
+def gen_AI_IO_filename(display_query, output):
+    # Get current time in Central Time Zone with milliseconds
+    now_central = datetime.now(pytz.timezone("America/Chicago"))
+    timestamp = now_central.strftime("%Y-%m-%d-%I-%M-%S-%f-%p")
+    
+    # Limit components to prevent excessive filename length
+    display_query = display_query[:50]  # Truncate display_query to 50 chars
+    output_snippet = re.sub(r'[^A-Za-z0-9]+', '_', output[:100])  # Truncate output_snippet to 100 chars
+
+    filename = f"{timestamp} - {display_query} - {output_snippet}.md"
+    return filename
         
 # 🔍 Search glossary - Finding needles in digital haystacks
 def search_glossary(query):
     st.markdown(f"### 🔍 SearchGlossary for: {query}")
-    # Dropdown for model selection
-    model_options = ['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']
-    #model_choice = st.selectbox('🧠 Select LLM Model', options=model_options, index=1)
-    # Dropdown for database selection
+    model_options = ['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2']
+    model_choice = st.selectbox('🧠 Select LLM Model', options=model_options, index=1, key=f"model_choice_{id(query)}")
     database_options = ['Semantic Search', 'Arxiv Search - Latest - (EXPERIMENTAL)']
-    #database_choice = st.selectbox('📚 Select Database', options=database_options, index=0)
+    database_choice = st.selectbox('📚 Select Database', options=database_options, index=0, key=f"database_choice_{id(query)}")
+    
     # 🕵️‍♂️ Searching the glossary for: query
     all_results = ""
-    #st.markdown(f"- {query}")
-
+    # Limit the query display to 80 characters
+    display_query = query[:80] + "..." if len(query) > 80 else query
+    st.markdown(f"🕵️‍♂️ Running ArXiV AI Analysis with Query: {display_query} - ML model: {model_choice} and Option: {database_options}")
     
-    # 🔍 ArXiv RAG researcher expert ~-<>-~ Paper Summary & Ask LLM
+    # 🔍 ArXiV RAG researcher expert ~-<>-~ Paper Summary & Ask LLM
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
     # 🔍 ArXiv RAG researcher expert ~-<>-~ Paper Summary & Ask LLM - api_name: /ask_llm
     result = client.predict(
@@ -351,11 +362,6 @@ def search_glossary(query):
     st.markdown(result2)
     #st.code(result2, language="python", line_numbers=True)
 
-
-
-
-    
-    
     # 🔍 ArXiv RAG researcher expert ~-<>-~ Paper Summary & Ask LLM - api_name: /update_with_rag_md
     response2 = client.predict(
         message=query,	# str  in 'parameter_13' Textbox component
@@ -373,33 +379,23 @@ def search_glossary(query):
     #st.code(response2[1], language="python", line_numbers=True, wrap_lines=True)
 
 
-    # Persist AI Results to Markdown Files
-    try:
-        filename = generate_filename(result, "md")
-        create_file(filename, query, result)
-        #st.session_state.chat_history.append({"assistant": query, "ArXiV": result})
-    except:
-        st.markdown('1 error')
-    try:
-        filename = generate_filename(result2, "md")
-        create_file(filename, query, result2)
-        #st.session_state.chat_history.append({"assistant": query, "ArXiV": result2})
-    except:
-        st.markdown('2 error')        
-    try:
-        filename = generate_filename(response2[0], "md")
-        create_file(filename, query, response2[0])
-        #st.session_state.chat_history.append({"assistant": query, "ArXiV": response2[0]})
-    except:
-        st.markdown('3 error')            
-    try:
-        filename = generate_filename(response2[1], "md")
-        create_file(filename, query, response2[1])
-        #st.session_state.chat_history.append({"assistant": query, "ArXiV": response2[1]})
-    except:
-        st.markdown('4 error')           
+    # ✅ Persist AI Results to Markdown Files
+    filename = gen_AI_IO_filename(display_query, result)
+    create_file(filename, query, result)
+    st.markdown(f"✅ File saved as: `{filename}`")
+
+    filename = gen_AI_IO_filename(display_query, result2)
+    create_file(filename, query, result2)
+    st.markdown(f"✅ File saved as: `{filename}`")
+
+    filename = gen_AI_IO_filename(display_query, response2[0])
+    create_file(filename, query, response2[0])
+    st.markdown(f"✅ File saved as: `{filename}`")
+
+    filename = gen_AI_IO_filename(display_query, response2[1])
+    create_file(filename, query, response2[1])
+    st.markdown(f"✅ File saved as: `{filename}`")
 
-    
     return result, result2, response2