Update app.py

app.py

@@ -229,7 +229,7 @@ def FileSidebar():
 
                 # gpt
                 try:
-                    st.write('🔍Running..')
+                    #st.write('🔍Running..')
                     response2 = chat_with_model(user_prompt, file_contents, model_choice)
                     filename2 = generate_filename(file_contents, choice)
                     create_file(filename2, user_prompt, response, should_save)
@@ -242,13 +242,13 @@ def FileSidebar():
             
         if next_action=='search':
             file_content_area = st.text_area("File Contents:", file_contents, height=500)
-            st.write('🔍Running..')
+            #st.write('🔍Running..')
 
             user_prompt = file_contents
 
             # gpt
             try:
-                st.write('🔍Running with GPT.')
+                #st.write('🔍Running with GPT.')
                 response2 = chat_with_model(user_prompt, file_contents, model_choice)
                 filename2 = generate_filename(file_contents, choice)
                 create_file(filename2, user_prompt, response, should_save)
@@ -356,7 +356,7 @@ def search_glossary(query):
 
     query2 = PromptPrefix + query # Add prompt preface for method step task behavior
     # st.write('## ' + query2)
-    st.write('## 🔍 Running with GPT.')  #  -------------------------------------------------------------------------------------------------
+    #st.write('## 🔍 Running with GPT.')  #  -------------------------------------------------------------------------------------------------
     response = chat_with_model(query2)    
     filename = generate_filename(query2 + ' --- ' + response, "md")
     create_file(filename, query, response, should_save)
@@ -746,7 +746,7 @@ def StreamLLMChatResponse(prompt):
     try:
         endpoint_url = API_URL
         hf_token = API_KEY
-        st.write('Running client ' + endpoint_url)
+        #st.write('Running client ' + endpoint_url)
         client = InferenceClient(endpoint_url, token=hf_token)
         gen_kwargs = dict(
             max_new_tokens=512,
@@ -1140,34 +1140,6 @@ def StreamMedChatResponse(topic):
     st.write(f"Showing resources or questions related to: {topic}")
 
 
-
-def add_medical_exam_buttons():
-    # Medical exam terminology descriptions
-    descriptions = {
-        "White Blood Cells 🌊": "3 Q&A with emojis about types, facts, function, inputs and outputs of white blood cells 🎥",
-        "CT Imaging🦠": "3 Q&A with emojis on CT Imaging post surgery, how to, what to look for 💊",
-        "Hematoma 💉": "3 Q&A with emojis about hematoma and infection care and study including bacteria cultures and tests or labs💪",
-        "Post Surgery Wound Care 🍌": "3 Q&A with emojis on wound care, and good bedside manner 🩸",
-        "Healing and humor 💊": "3 Q&A with emojis on stories and humor about healing and caregiving 🚑",
-        "Psychology of bedside manner 🧬": "3 Q&A with emojis on bedside manner and how to make patients feel at ease🛠",
-        "CT scan 💊": "3 Q&A with analysis on infection using CT scan and packing for skin, cellulitus and fascia 🩺"
-    }
-
-    # Expander for medical topics
-    with st.expander("Medical Licensing Exam Topics 📚", expanded=False):
-        st.markdown("🩺 **Important**: Variety of topics for medical licensing exams.")
-
-        # Create buttons for each description with unique keys
-        for idx, (label, content) in enumerate(descriptions.items()):
-            button_key = f"button_{idx}"
-            if st.button(label, key=button_key):
-                st.write(f"Running {label}")
-                input='Create markdown outline for definition of topic ' + label + ' also short quiz with appropriate emojis and definitions for:  ' + content
-                response=StreamLLMChatResponse(input)
-                filename = generate_filename(response, 'txt')   
-                create_file(filename, input, response, should_save)
-
-
                 
 
 # 17. Main
@@ -1318,7 +1290,7 @@ def main():
         query_params = st.query_params
         #query = (query_params.get('q') or query_params.get('query') or [''])[0]
         query = (query_params.get('q') or query_params.get('query') or [''])
-        st.markdown('# Running query: ' + query)
+        #st.markdown('# Running query: ' + query)
         if query: search_glossary(query)
     except:
         st.markdown(' ')