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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
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(
"""
<head>
<style>
.footer1 {
text-align: center;
}
</style>
</head>
<body>
<div class="footer1">
<img src=https://raw.githubusercontent.com/AlbertoUAH/Castena/main/media/castena-animated-icon.gif width="150" height="150">
</div>
<br>
</body>
""",
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(
"""
<head>
<style>
.footer2 {
position: fixed;
bottom: 2%;
left: 6.5%;
}
.footer2 a {
margin: 10px;
text-decoration: none;
}
</style>
</head>
<body>
<div class="footer2">
<a href="https://www.linkedin.com/in/alberto-fernandez-hernandez-3a3474136">
<img src="https://cdn-icons-png.flaticon.com/128/3536/3536505.png" width="32" height="32">
</a>
<a href="https://github.com/AlbertoUAH/Castena">
<img src="https://cdn-icons-png.flaticon.com/128/733/733553.png" width="32" height="32">
</a>
<a href="https://www.buymeacoffee.com/castena">
<img src="https://cdn-icons-png.flaticon.com/128/761/761767.png" width="32" height="32">
</a>
</div>
</body>
""",
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 = "<<SYS>>\n", "\n<</SYS>>\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() |