# -- Import libraries from langchain.prompts import PromptTemplate from PIL import Image from streamlit.logger import get_logger from streamlit_player import st_player from langchain.tools import DuckDuckGoSearchRun 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 st.set_page_config(layout="wide") @st.cache_data def get_args(): # -- 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 logger = get_logger(__name__) # -- 3. Setup constants args = parser.parse_args() return args, logger @st.cache_data def get_podcast_data(path): podcast_url_video_df = pd.read_csv(path, sep=';') return podcast_url_video_df @st.cache_resource(experimental_allow_widgets=True) def get_basics_comp(emb_model, model, default_system_prompt_link, _logger, podcast_url_video_df, img_size=100): 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((img_size, img_size)) with st.sidebar.container(): st.markdown( """

""", unsafe_allow_html=True, ) genre = st.sidebar.radio( "Seleccione el LLM", ["LLAMA", "GPT"] ) st.sidebar.info('Modelo LLAMA: ' + str(model).split('/')[-1] + '\nModelo GPT: gpt-3.5-turbo', icon="ℹ️") podcast_list = list(podcast_url_video_df['podcast_name_lit'].apply(lambda x: x.replace("'", ""))) video_option = st.sidebar.selectbox( "Seleccione el podcast", podcast_list, on_change=clean_chat ) # -- Add icons with st.sidebar.container(): st.markdown( """

""", unsafe_allow_html=True, ) video_option_joined = '_'.join(video_option.replace(': Entrevista a ', ' ').lower().split(' ')).replace("\'", "") video_option_joined_path = "{}_transcription.txt".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("\'", "") st.title("[Podcast: {}]({})".format(video_option.replace("'", "").title(), youtube_video_url)) # -- 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 nlp, retriever = utils.setup_app(video_option_joined_path, emb_model, model, _logger) # -- 6. Setup model together.api_key = os.environ["TOGETHER_API_KEY"] #together.Models.start(model) return together, nlp, retriever, video_option, video_option_joined_path, default_system_prompt, youtube_video_url, genre def clean_chat(): st.session_state.conversation = None st.session_state.chat_history = None st.session_state.messages = [{'role': 'assistant', 'content': 'Nuevo chat creado'}] def main(): args, logger = get_args() B_INST, E_INST = "[INST]", "[/INST]" B_SYS, E_SYS = "<>\n", "\n<>\n\n" 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 WIDTH = 50 SIDE = (100 - WIDTH) / 2 podcast_url_video_df = get_podcast_data(PODCAST_URL_VIDEO_PATH) together, 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 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) # --------------------------------------------------------------------- if st.button('Info.'): search = DuckDuckGoSearchRun() character_name = video_option.replace("'", "").title().split("Entrevista A ")[-1] info = search.run("¿Quien es {}?".format(character_name)) character_info = utils.get_character_info_gpt(info, character=character_name) st.info(character_info) _, 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!"): with st.chat_message("user"): st.markdown(prompt) st.session_state.messages.append({"role": "user", "content": prompt}) with st.chat_message("assistant"): if 'GPT' not in genre: if prompt.lower() == 'resume': llm_response = utils.summarise_doc(video_option_joined_path, model_name='llama', model=MODEL) st.markdown(llm_response) else: llm_response = qa_chain(prompt)['result'] llm_response = utils.process_llm_response(llm_response) 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: 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: if prompt.lower() == 'resume': llm_response = utils.summarise_doc(video_option_joined_path, model_name='gpt') st.markdown(llm_response) else: llm_response = utils.get_gpt_response(video_option_joined_path, prompt, logger) llm_response = utils.process_llm_response(llm_response) 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: 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()