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import pinecone
from sentence_transformers import SentenceTransformer
import logging
PINECONE_KEY = st.secrets["PINECONE_KEY"] # app.pinecone.io
INDEX_ID = 'youtube-search'
st.markdown("<link rel='stylesheet' type='text/css' href='https://huggingface.co/spaces/danbestie/yt-ex/raw/main/styles.css'>", unsafe_allow_html=True)
@st.experimental_singleton
def init_pinecone():
pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
return pinecone.Index(INDEX_ID)
@st.experimental_singleton
def init_retriever():
return SentenceTransformer("multi-qa-mpnet-base-dot-v1")
def make_query(query, retriever, top_k=10, include_values=True, include_metadata=True, filter=None):
xq = retriever.encode([query]).tolist()
logging.info(f"Query: {query}")
attempt = 0
while attempt < 3:
try:
xc = st.session_state.index.query(
xq,
top_k=top_k,
include_values=include_values,
include_metadata=include_metadata,
filter=filter
)
matches = xc['matches']
break
except:
# force reload
pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
st.session_state.index = pinecone.Index(INDEX_ID)
attempt += 1
matches = []
if len(matches) == 0:
logging.error(f"Query failed")
return matches
st.session_state.index = init_pinecone()
retriever = init_retriever()
def card(thumbnail: str, title: str, urls: list, contexts: list, starts: list, ends: list, publication: str):
meta = [(e, s, u, c) for e, s, u, c in zip(ends, starts, urls, contexts)]
meta.sort(reverse=False)
text_content = []
current_start = 0
current_end = 0
for end, start, url, context in meta:
# reformat seconds to timestamp
time = start / 60
mins = f"0{int(time)}"[-2:]
secs = f"0{int(round((time - int(mins))*60, 0))}"[-2:]
timestamp = f"{mins}:{secs}"
if start < current_end and start > current_start:
# this means it is a continuation of the previous sentence
text_content[-1][0] = text_content[-1][0].split(context[:10])[0]
text_content.append([f"[{timestamp}] {context.capitalize()}", url])
else:
text_content.append(["xxLINEBREAKxx", ""])
text_content.append([f"[{timestamp}] {context}", url])
current_start = start
current_end = end
html_text = ""
for text, url in text_content:
if text == "xxLINEBREAKxx":
html_text += "<br>"
else:
html_text += f"<small><a href={url}>{text.strip()}... </a></small>"
print(text)
html = f"""
<div class="container-fluid">
<div class="row align-items-start">
<div class="col-md-4 col-sm-4">
<div class="position-relative">
<a href={urls[0]}><img src={thumbnail} class="img-fluid" style="width: 192px; height: 106px"></a>
</div>
</div>
<div class="col-md-8 col-sm-8">
<h2>{title}</h2>
</div>
<div class="col-md-8 col-sm-8">
<h2>{publication}</h2>
</div>
<div>
{html_text}
<br><br>
"""
return st.markdown(html, unsafe_allow_html=True)
publication_map = {
'los angeles times': 'los angeles times',
'breitbart': 'breitbart',
'vox': 'vox',
'cnn': 'cnn',
'new york post': 'new york post',
'new york times': 'new york times'
}
st.write("""
# Example
""")
st.info("""
YouTube search built as [explained here](https://pinecone.io/learn/openai-whisper)!
*The current search scope is limited to a few videos talking about ML, NLP, and vector search*. Add requests for channels to include in the [*Community* tab](https://huggingface.co/spaces/jamescalam/ask-youtube/discussions).
""")
st.markdown("""
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.0.0/dist/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
""", unsafe_allow_html=True)
query = st.text_input("Search!", "")
with st.expander("Advanced Options"):
publication_options = st.multiselect(
'Publications to Search',
['los angeles times','breitbart','vox','new york post','cnn','new york times'],
['los angeles times','breitbart','vox','new york post','cnn','new york times']
)
if query != "":
publications = [publication_map[name] for name in publication_options]
print(f"query: {query}")
filter = {'$and': [
{'publication': {'$in': publications}}
# {'category': {'$in': ['longform', 'newspaper']}}
]
}
matches = make_query(
query, retriever, top_k=5,
filter=filter
)
results = {}
order = []
for context in matches:
video_id = context['metadata']['url'].split('/')[-1]
if video_id not in results:
results[video_id] = {
'title': context['metadata']['title'],
'thumbnail': context['metadata']['thumbnail'],
'urls': [f"{context['metadata']['url']}"],
'contexts': [context['metadata']['text']],
'starts': [int(context['metadata']['start_second'])],
'ends': [int(context['metadata']['end_second'])],
'publication': context['metadata']['publication'],
'category': context['metadata']['category']
}
order.append(video_id)
else:
results[video_id]['urls'].append(
f"{context['metadata']['url']}"
)
results[video_id]['contexts'].append(
context['metadata']['text']
)
results[video_id]['starts'].append(int(context['metadata']['start_second']))
results[video_id]['ends'].append(int(context['metadata']['end_second']))
# now display cards
for video_id in order:
card(
thumbnail=results[video_id]['thumbnail'],
title=results[video_id]['title'],
urls=results[video_id]['urls'],
contexts=results[video_id]['contexts'],
starts=results[video_id]['starts'],
ends=results[video_id]['ends'],
publication=results[video_id]['publication']
) |