Upload application.py

application.py

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+# -- Import libraries
+from   langchain.prompts           import PromptTemplate
+from   PIL                         import Image
+from   streamlit.logger            import get_logger
+from streamlit_player              import st_player
+import pandas                      as pd
+import streamlit                   as st
+import urllib.request
+import argparse
+import together
+import logging
+import requests
+import utils
+import spacy
+import time
+import os
+import re
+
+def main():
+    st.set_page_config(layout="wide")
+
+    # -- 1. Setup arguments
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--DEFAULT_SYSTEM_PROMPT_LINK', type=str, default="https://raw.githubusercontent.com/AlbertoUAH/Castena/main/prompts/default_system_prompt.txt", help='Valor para DEFAULT_SYSTEM_PROMPT_LINK')
+    parser.add_argument('--PODCAST_URL_VIDEO_PATH', type=str, default="https://raw.githubusercontent.com/AlbertoUAH/Castena/main/data/podcast_youtube_video.csv", help='Valor para PODCAST_URL_VIDEO_PATH')
+    parser.add_argument('--TRANSCRIPTION', type=str, default='worldcast_roberto_vaquero', help='Name of the trascription')
+    parser.add_argument('--MODEL', type=str, default='togethercomputer/llama-2-13b-chat', help='Model name')
+    parser.add_argument('--EMB_MODEL', type=str, default='sentence-transformers/paraphrase-multilingual-mpnet-base-v2', help='Embedding model name')
+    os.system("python -m spacy download es_core_news_lg")
+
+    # -- 2. Setup env and logger
+    os.environ["TOGETHER_API_KEY"] = "6101599d6e33e3bda336b8d007ca22e35a64c72cfd52c2d8197f663389fc50c5"
+    logger = get_logger(__name__)
+
+    # -- 3. Setup constants
+    B_INST, E_INST = "[INST]", "[/INST]"
+    B_SYS, E_SYS   = "<<SYS>>\n", "\n<</SYS>>\n\n"
+    args = parser.parse_args()
+    PODCAST_URL_VIDEO_PATH     = args.PODCAST_URL_VIDEO_PATH
+    DEFAULT_SYSTEM_PROMPT_LINK = args.DEFAULT_SYSTEM_PROMPT_LINK
+    TRANSCRIPTION              = args.TRANSCRIPTION
+    TRANSCRIPTION_PATH         = '{}_transcription.txt'.format(TRANSCRIPTION)
+    MODEL                      = args.MODEL
+    EMB_MODEL                  = args.EMB_MODEL
+    SOCIAL_ICONS               = {
+        "LinkedIn": ["https://www.linkedin.com/in/alberto-fernandez-hernandez-3a3474136/", "https://icon.signature.email/social/linkedin-circle-medium-0077b5-FFFFFF.png", ],
+        "GitHub": ["https://github.com/AlbertoUAH", "https://icon.signature.email/social/github-circle-medium-24292e-FFFFFF.png"]
+    }
+    social_icons_html = [f"<a href='{SOCIAL_ICONS[platform][0]}' target='_blank' style='margin-right: 10px;'><img class='social-icon' src='{SOCIAL_ICONS[platform][1]}'' alt='{platform}''></a>" for platform in SOCIAL_ICONS]
+
+    together.api_key = os.environ["TOGETHER_API_KEY"]
+    together.Models.start(MODEL)
+    podcast_url_video_df = pd.read_csv(PODCAST_URL_VIDEO_PATH, sep=';')
+
+    r = requests.get("https://raw.githubusercontent.com/AlbertoUAH/Castena/main/media/castena-animated-icon.gif", stream=True)
+    icon = Image.open(r.raw)
+    icon = icon.resize((100, 100))
+    st.sidebar.image(icon)
+    video_option = st.sidebar.selectbox(
+        "Seleccione el podcast",
+        list(podcast_url_video_df['podcast_name_lit'].apply(lambda x: x.replace("'", "")))
+    )
+    video_option_joined = '_'.join(video_option.replace(': Entrevista a ', ' ').lower().split(' ')).replace("\'", "")
+    video_option_joined_path = "{}_transcription.txt".format(video_option_joined)
+    print("Filtering: {}".format(video_option_joined))
+    youtube_video_url   = list(podcast_url_video_df[podcast_url_video_df['podcast_name'].str.contains(video_option_joined)]['youtube_video_url'])[0].replace("\'", "")
+
+    # -- 4. Setup request for system prompt
+    f = urllib.request.urlopen(DEFAULT_SYSTEM_PROMPT_LINK)
+    DEFAULT_SYSTEM_PROMPT = str(f.read(), 'UTF-8')
+
+    # -- 5. Setup app
+    translator, nlp, retriever = utils.setup_app(video_option_joined_path, EMB_MODEL, MODEL, logger)
+
+
+    # -- 6. Setup prompt template + llm chain
+    instruction = """CONTEXTO:/n/n {context}/n
+
+PREGUNTA: {question}
+
+RESPUESTA: """
+    prompt_template = utils.get_prompt(instruction, DEFAULT_SYSTEM_PROMPT, B_SYS, E_SYS, B_INST, E_INST, logger)
+
+    llama_prompt = PromptTemplate(
+        template=prompt_template, input_variables=["context", "question"]
+    )
+    chain_type_kwargs = {"prompt": llama_prompt}
+
+    qa_chain = utils.create_llm_chain(MODEL, retriever, chain_type_kwargs, logger, video_option_joined_path)
+
+    # ---------------------------------------------------------------------
+    # -- 7. Setup Streamlit app
+    st.title("[Podcast: {}]({})".format(video_option.replace("'", "").title(), youtube_video_url))
+
+    width = 50
+    side = (100 - width) / 2
+    _, container, _ = st.columns([side, width, side])
+    with container:
+        st_player(utils.typewrite(youtube_video_url))
+
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+    if prompt := st.chat_input("¡Pregunta lo que quieras!"):
+        st.session_state.messages.append({"role": "user", "content": prompt})
+        with st.chat_message("user"):
+            st.markdown(prompt)
+
+        with st.chat_message("assistant"):
+            llm_response = 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)
+                    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:
+                width = 40
+                side = (100 - width) / 2
+                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}')
+
+        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__':
+    main()