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wavesoumen
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7c7cb02
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Parent(s):
f5e893f
Update app.py
Browse files
app.py
CHANGED
@@ -1,6 +1,7 @@
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import streamlit as st
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from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
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import nltk
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# Download NLTK data
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nltk.download('punkt')
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@@ -12,11 +13,21 @@ captioner = pipeline("image-to-text", model="Salesforce/blip-image-captioning-ba
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tokenizer = AutoTokenizer.from_pretrained("fabiochiu/t5-base-tag-generation")
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model = AutoModelForSeq2SeqLM.from_pretrained("fabiochiu/t5-base-tag-generation")
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# Streamlit app title
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st.title("Multi-purpose Machine Learning App")
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# Create tabs for different functionalities
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tab1, tab2 = st.tabs(["Image Captioning", "Text Tag Generation"])
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# Image Captioning Tab
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with tab1:
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@@ -71,4 +82,22 @@ with tab2:
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else:
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st.warning("Please enter some text to generate tags.")
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#
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import streamlit as st
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from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
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import nltk
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from youtube_transcript_api import YouTubeTranscriptApi
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# Download NLTK data
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nltk.download('punkt')
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tokenizer = AutoTokenizer.from_pretrained("fabiochiu/t5-base-tag-generation")
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model = AutoModelForSeq2SeqLM.from_pretrained("fabiochiu/t5-base-tag-generation")
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# Function to fetch YouTube transcript
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def fetch_transcript(url):
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video_id = url.split('watch?v=')[-1]
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try:
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transcript = YouTubeTranscriptApi.get_transcript(video_id)
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transcript_text = ' '.join([entry['text'] for entry in transcript])
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return transcript_text
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except Exception as e:
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return str(e)
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# Streamlit app title
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st.title("Multi-purpose Machine Learning App")
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# Create tabs for different functionalities
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tab1, tab2, tab3 = st.tabs(["Image Captioning", "Text Tag Generation", "YouTube Transcript"])
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# Image Captioning Tab
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with tab1:
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else:
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st.warning("Please enter some text to generate tags.")
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# YouTube Transcript Tab
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with tab3:
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st.header("YouTube Video Transcript Extractor")
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# Input for YouTube URL
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youtube_url = st.text_input("Enter YouTube URL:")
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# Button to get transcript
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if st.button("Get Transcript"):
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if youtube_url:
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transcript = fetch_transcript(youtube_url)
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if "error" not in transcript.lower():
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st.success("Transcript successfully fetched!")
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st.text_area("Transcript", transcript, height=300)
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else:
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st.error(f"An error occurred: {transcript}")
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else:
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st.warning("Please enter a URL.")
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