Develop

.gitignore

@@ -2,4 +2,5 @@
 code/embeddings_text.csv
 code/utilities/__pycache__
 .env
-__pycache__
+__pycache__
+backuppage

code/OpenAI_Queries.py

@@ -145,7 +145,6 @@ def get_languages():
     st.set_page_config(layout="wide", menu_items=menu_items)
 
     llm_helper = LLMHelper(custom_prompt=st.session_state.custom_prompt, temperature=st.session_state.custom_temperature)
-
     # Get available languages for translation
     available_languages = get_languages()
 
@@ -166,74 +165,5 @@ def get_languages():
     col1, col2, col3 = st.columns([2,2,2])
     with col1:
         st.button("Check deployment", on_click=check_deployment)
-    with col3:
-        with st.expander("Settings"):
-            # model = st.selectbox(
-            #     "OpenAI GPT-3 Model",
-            #     [os.environ['OPENAI_ENGINE']]
-            # )
-            # st.tokens_response = st.slider("Tokens response length", 100, 500, 400)
-            st.slider("Temperature", min_value=0.0, max_value=1.0, step=0.1, key='custom_temperature')
-            st.text_area("Custom Prompt", key='custom_prompt', on_change=check_variables_in_prompt, placeholder= custom_prompt_placeholder,help=custom_prompt_help, height=150)
-            st.selectbox("Language", [None] + list(available_languages.keys()), key='translation_language')
-
-
-    question = st.text_input("Azure OpenAI Semantic Answer", value=st.session_state['askedquestion'], key="input"+str(st.session_state ['input_message_key']), on_change=questionAsked)
-
-    # Answer the question if any
-    if st.session_state.askedquestion != '':
-        st.session_state['question'] = st.session_state.askedquestion
-        st.session_state.askedquestion = ""
-        st.session_state['question'], \
-        st.session_state['response'], \
-        st.session_state['context'], \
-        st.session_state['sources'] = llm_helper.get_semantic_answer_lang_chain(st.session_state['question'], [])
-        st.session_state['response'], followup_questions_list = llm_helper.extract_followupquestions(st.session_state['response'])
-        st.session_state['followup_questions'] = followup_questions_list
-
-    sourceList = []
-
-    # Display the sources and context - even if the page is reloaded
-    if st.session_state['sources'] or st.session_state['context']:
-        st.session_state['response'], sourceList, matchedSourcesList, linkList, filenameList = llm_helper.get_links_filenames(st.session_state['response'], st.session_state['sources'])
-        st.write("<br>", unsafe_allow_html=True)
-        st.markdown("Answer: " + st.session_state['response'])
-
-    # Display proposed follow-up questions which can be clicked on to ask that question automatically
-    if len(st.session_state['followup_questions']) > 0:
-        st.write("<br>", unsafe_allow_html=True)
-        st.markdown('**Proposed follow-up questions:**')
-    with st.container():
-        for questionId, followup_question in enumerate(st.session_state['followup_questions']):
-            if followup_question:
-                str_followup_question = re.sub(r"(^|[^\\\\])'", r"\1\\'", followup_question)
-                st.button(str_followup_question, key=1000+questionId, on_click=ask_followup_question, args=(followup_question, ))
-
-    if st.session_state['sources'] or st.session_state['context']:
-        # Buttons to display the context used to answer
-        st.write("<br>", unsafe_allow_html=True)
-        st.markdown('**Document sources:**')
-        for id in range(len(sourceList)):
-            st.markdown(f"[{id+1}] {sourceList[id]}")
-
-        # Details on the question and answer context
-        st.write("<br><br>", unsafe_allow_html=True)
-        with st.expander("Question and Answer Context"):
-            if not st.session_state['context'] is None and st.session_state['context'] != []:
-                for content_source in st.session_state['context'].keys():
-                    st.markdown(f"#### {content_source}")
-                    for context_text in st.session_state['context'][content_source]:
-                        st.markdown(f"{context_text}")
-
-            st.markdown(f"SOURCES: {st.session_state['sources']}") 
-
-    for questionId, followup_question in enumerate(st.session_state['followup_questions']):
-        if followup_question:
-            str_followup_question = re.sub(r"(^|[^\\\\])'", r"\1\\'", followup_question)
-
-    if st.session_state['translation_language'] and st.session_state['translation_language'] != '':
-        st.write(f"Translation to other languages, 翻译成其他语言, النص باللغة العربية")
-        st.write(f"{llm_helper.translator.translate(st.session_state['response'], available_languages[st.session_state['translation_language']])}")		
-
 except Exception:
     st.error(traceback.format_exc())