Update app.py

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:
@@ -315,18 +315,18 @@ def archive_current_container(database_name, container_name, client):
 # 🔍 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_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 +351,6 @@ 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