Update app.py

app.py

@@ -37,9 +37,9 @@ def display_app_header():
     # Add a description of the app
     st.markdown("""This app allows you to generate EAD/XML archival descriptions. See this serie of blog posts for explanations : 
                 
-    - https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm
-    - https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm-rag-23
-    - https://iaetbibliotheques.fr/2024/12/comment-apprendre-lead-a-un-llm-fine-tuning-33
+    - [https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm](https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm)
+    - [https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm-rag-23](https://iaetbibliotheques.fr/2024/11/comment-apprendre-lead-a-un-llm-rag-23)
+    - [https://iaetbibliotheques.fr/2024/12/comment-apprendre-lead-a-un-llm-fine-tuning-33](https://iaetbibliotheques.fr/2024/12/comment-apprendre-lead-a-un-llm-fine-tuning-33)
     """)
     st.markdown("---")
 
@@ -48,7 +48,7 @@ history_col, main_col = setup_page()
 
 def setup_sidebar():    
     groq_models = ["llama3-70b-8192", "llama-3.1-70b-versatile","llama3-8b-8192", "llama-3.1-8b-instant", "mixtral-8x7b-32768","gemma2-9b-it", "gemma-7b-it"]
-    selected_groq_models = st.sidebar.radio("Choose a Groq models", groq_models)
+    selected_groq_models = st.sidebar.radio("Choose a model (used in tabs 1, 2 and 3)", groq_models)
     return selected_groq_models
 
 def create_groq_llm(model):
@@ -193,25 +193,6 @@ def setup_rag_tab(llm):
     
     return chain
 
-"""def setup_local_fine_tuned_tab(query):
-    st.header("Fine-tuned Zephir model")
-
-    llm = Llama(
-        model_path="assets/FineZephir-sft-instruct-ead-Q5_K_M.gguf",
-        n_ctx=1024,
-        verbose=False
-    )
-    output = llm.create_chat_completion(
-        messages = [
-            {"role": "system", "content": "You are an archivist expert in EAD format."},
-            {
-                "role": "user",
-                "content": query
-            }
-        ]
-    )
-    return output["choices"][0]["message"]["content"]"""
-
 def setup_fine_tuned_tab():
     st.header("Fine-tuned Zephir model")
     
@@ -305,17 +286,6 @@ with main_col:
                     st.markdown(st.session_state.response_rag)
                     
             # Process for Tab 4 - Fine-tuned model
-            """with tab4:
-                st.session_state.response_fine_tuned = set_up_fine_tuned_tab(query)
-                soup = BeautifulSoup(st.session_state.response_fine_tuned, "lxml-xml")    
-                with st.chat_message("assistant"):
-                    st.code(soup.prettify(), language="xml-doc")"""
-            """with tab4:
-                llm = create_aws_ollama_llm()
-                fine_tuned_chain = setup_fine-tuned_tab(llm)
-                st.session_state.response_fine_tuned = fine_tuned_chain.invoke(query)
-                with st.chat_message("assistant"):
-                    st.markdown(st.session_state.response_fine_tuned)"""
             with tab4:
                 st.write("Coming soon...")