Update app.py

app.py

@@ -23,9 +23,7 @@ CONTAINER_NAME = os.environ.get("COSMOS_CONTAINER_NAME")
 Key = os.environ.get("Key")  # 🔑 Don't forget your key!
 
 # 🏠 Your local app URL (Change this to your app's URL)
-#LOCAL_APP_URL = "http://localhost:8501"
-LOCAL_APP_URL = "https://huggingface.co/spaces/awacke1/AzureCosmosDBUI"
-
+LOCAL_APP_URL = "http://localhost:8501"
 
 # 🤖 OpenAI configuration
 #openai.api_key = os.environ.get("OPENAI_API_KEY")
@@ -259,57 +257,6 @@ def create_and_save_file(content, file_type="md", prompt=None, is_image=False, s
 
     return filename
 
-
-
- # 🔍Search Glossary 
-# @st.cache_resource
-def search_glossary(query): 
-    all=""
-    st.markdown(f"- {query}")
-    
-    # 🔍Run 1 - ArXiv RAG researcher expert ~-<>-~ 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
-            #"mistralai/Mistral-7B-Instruct-v0.2",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
-            "google/gemma-7b-it",	# 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,	
-    		10,	
-    		"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.write('🔍Run of Multi-Agent System Paper References is Complete')
-    responseall = response2 + response1[0] + response1[1]
-    st.markdown(responseall)
-    return responseall
-    
-def display_content_or_image(query):
-    for category, terms in transhuman_glossary.items():
-        for term in terms:
-            if query.lower() in term.lower():
-                st.subheader(f"Found in {category}:")
-                st.write(term)
-                return True  # Return after finding and displaying the first match
-    image_dir = "images"  # Example directory where images are stored
-    image_path = f"{image_dir}/{query}.png"  # Construct image path with query
-    if os.path.exists(image_path):
-        st.image(image_path, caption=f"Image for {query}")
-        return True
-    st.warning("No matching content or image found.")
-    return False
-
-
 # 🎈 Let's modify the main app to be more fun!
 def main():
     st.title("🐙Git🌌Cosmos💫 - Azure Cosmos DB and Github Agent")
@@ -332,34 +279,16 @@ def main():
     if 'cloned_doc' not in st.session_state:
         st.session_state.cloned_doc = None
 
-    
-    # ⚙️q= Run ArXiv search from query parameters
+    # ⚙️ q= Run ArXiv search from query parameters
     try:
         query_params = st.query_params
-        query = (query_params.get('q') or query_params.get('query') or [''])
-        if len(query) > 1: 
-            #result = search_arxiv(query)
-            result2 = search_glossary(result) 
-    
-            filesearch = PromptPrefix + query
-            st.markdown(filesearch)
-            process_text(filesearch)
-    except:
+        query = (query_params.get('q') or query_params.get('query') or [''])[0]
+        if query:
+            # 🕵️‍♂️ We have a query! Let's process it!
+            process_text(query)
+            st.stop()  # Stop further execution
+    except Exception as e:
         st.markdown(' ')
-    
-    if 'action' in st.query_params:
-        action = st.query_params()['action'][0]  # Get the first (or only) 'action' parameter
-        if action == 'show_message':
-            st.success("Showing a message because 'action=show_message' was found in the URL.")
-        elif action == 'clear':
-            clear_query_params()
-            #st.rerun()
-    
-    if 'query' in st.query_params:
-        query = st.query_params['query'][0]  # Get the query parameter
-        # Display content or image based on the query
-        display_content_or_image(query)
-
 
     # 🔐 Automatic Login
     if Key: