Update app.py

app.py

@@ -131,7 +131,7 @@ def get_basics_comp(emb_model, model, default_system_prompt_link, _logger, podca
     # -- 6. Setup model
     together.api_key = os.environ["TOGETHER_API_KEY"]
     #together.Models.start(model)
-    return together, translator, nlp, retriever, video_option, video_option_joined_path, default_system_prompt, youtube_video_url
+    return together, translator, nlp, retriever, video_option, video_option_joined_path, default_system_prompt, youtube_video_url, genre
 
 def clean_chat():
     st.session_state.conversation = None
@@ -155,9 +155,9 @@ def main():
     
     podcast_url_video_df = get_podcast_data(PODCAST_URL_VIDEO_PATH)
 
-    together, translator, nlp, retriever, video_option, video_option_joined_path, default_system_prompt, youtube_video_url = get_basics_comp(EMB_MODEL, MODEL, 
-                                                                                                                                             DEFAULT_SYSTEM_PROMPT_LINK, logger, 
-                                                                                                                                             podcast_url_video_df, img_size=100)
+    together, translator, nlp, retriever, video_option, 
+    video_option_joined_path, default_system_prompt, youtube_video_url, genre = get_basics_comp(EMB_MODEL, MODEL, DEFAULT_SYSTEM_PROMPT_LINK, logger, 
+                                                                                                podcast_url_video_df, img_size=100)
 
     # -- 6. Setup prompt template + llm chain
     instruction = """CONTEXTO:/n/n {context}/n
@@ -191,24 +191,28 @@ RESPUESTA: """
             st.markdown(prompt)
         st.session_state.messages.append({"role": "user", "content": prompt})
         with st.chat_message("assistant"):
-            llm_response, cleaned_prompt = qa_chain(prompt)
-            llm_response = utils.process_llm_response(llm_response, nlp)
-            st.markdown(llm_response)
-            start_time_str_list = []; start_time_seconds_list = []; end_time_seconds_list = []
-            for response in llm_response.split('\n'):
-                if re.search(r'(\d{2}:\d{2}:\d{2}(.\d{6})?)', response) != None:
-                    start_time_str, start_time_seconds, _, end_time_seconds = utils.add_hyperlink_and_convert_to_seconds(response, cleaned_prompt)
-                    start_time_str_list.append(start_time_str)
-                    start_time_seconds_list.append(start_time_seconds)
-                    end_time_seconds_list.append(end_time_seconds)
-
-            if start_time_str_list:
-                for start_time_seconds, start_time_str, end_time_seconds in zip(start_time_seconds_list, start_time_str_list, end_time_seconds_list):
-                    st.markdown("__Fragmento: " + start_time_str + "__")
-                    _, container, _ = st.columns([SIDE, WIDTH, SIDE])
-                    with container:
-                        st_player(youtube_video_url.replace("?enablejsapi=1", "") + f'?start={start_time_seconds}&end={end_time_seconds}')
-
+            if not genre.contains('GPT'):
+                llm_response, cleaned_prompt = qa_chain(prompt)
+                llm_response = utils.process_llm_response(llm_response, nlp)
+                st.markdown(llm_response)
+                start_time_str_list = []; start_time_seconds_list = []; end_time_seconds_list = []
+                for response in llm_response.split('\n'):
+                    if re.search(r'(\d{2}:\d{2}:\d{2}(.\d{6})?)', response) != None:
+                        start_time_str, start_time_seconds, _, end_time_seconds = utils.add_hyperlink_and_convert_to_seconds(response, cleaned_prompt)
+                        start_time_str_list.append(start_time_str)
+                        start_time_seconds_list.append(start_time_seconds)
+                        end_time_seconds_list.append(end_time_seconds)
+    
+                if start_time_str_list:
+                    for start_time_seconds, start_time_str, end_time_seconds in zip(start_time_seconds_list, start_time_str_list, end_time_seconds_list):
+                        st.markdown("__Fragmento: " + start_time_str + "__")
+                        _, container, _ = st.columns([SIDE, WIDTH, SIDE])
+                        with container:
+                            st_player(youtube_video_url.replace("?enablejsapi=1", "") + f'?start={start_time_seconds}&end={end_time_seconds}')
+            else:
+                llm_response = utils.get_gpt_response(prompt)
+                st.markdown(llm_response)
+                
         st.session_state.messages.append({"role": "assistant", "content": llm_response})
 # -- Sample: streamlit run app.py -- --DEFAULT_SYSTEM_PROMPT_LINK=https://raw.githubusercontent.com/AlbertoUAH/Castena/main/prompts/default_system_prompt.txt --PODCAST_URL_VIDEO_PATH=https://raw.githubusercontent.com/AlbertoUAH/Castena/main/data/podcast_youtube_video.csv --TRANSCRIPTION=worldcast_roberto_vaquero --MODEL=togethercomputer/llama-2-7b-chat --EMB_MODEL=BAAI/bge-base-en-v1.5
 if __name__ == '__main__':