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Upload 3 files
Browse files- .gitattributes +1 -0
- app.py +99 -14
- header-image-2.png +3 -0
- query.py +4 -5
.gitattributes
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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header-image-2.png filter=lfs diff=lfs merge=lfs -text
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app.py
CHANGED
@@ -6,6 +6,77 @@ import requests
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import streamlit as st
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from PIL import Image
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def launch_bot():
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if 'cfg' not in st.session_state:
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@@ -22,12 +93,18 @@ def launch_bot():
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cfg = st.session_state.cfg
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vq = st.session_state.vq
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st.set_page_config(page_title="Media Demo", layout="wide")
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# left side content
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with st.sidebar:
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image = Image.open('
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st.markdown("## Welcome to Media Demo\n\n"
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"This demo uses Vectara to find the movie where a quote is from\n\n"
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st.markdown("---")
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st.markdown(
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st.markdown("---")
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st.image(image, width=250)
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st.markdown("<center> <
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st.
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if __name__ == "__main__":
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launch_bot()
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import streamlit as st
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from PIL import Image
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def inject_custom_css():
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st.markdown(
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"""
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<style>
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@import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;500;700&display=swap');
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body {
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font-family: 'Roboto', sans-serif;
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background-color: #f5f5f5;
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color: #333;
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}
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body {
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padding-top: 0px;
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}
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.stApp {
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padding-top: 10px;
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}
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.stButton>button {
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background-color: #4CAF50;
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color: white;
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padding: 10px 24px;
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border: none;
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cursor: pointer;
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border-radius: 4px;
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}
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.stButton>button:hover {
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background-color: #45a049;
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}
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.stTextInput>div>input {
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padding: 10px;
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border-radius: 4px;
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border: 1px solid #ccc;
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font-size: 16px;
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}
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.stTextInput>div>input:focus {
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border-color: #007BFF;
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outline: none;
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box-shadow: 0 0 5px rgba(0, 123, 255, 0.5);
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}
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.centered {
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display: flex;
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justify-content: center;
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align-items: center;
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}
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.sidebar .stImage {
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display: flex;
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justify-content: center;
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margin-bottom: 20px;
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}
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.css-1lcbmhc.e1fqkh3o3 { /* This targets the sidebar */
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background-color: #ffffff !important;
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color: #333 !important;
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}
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.css-1d391kg { /* This targets the sidebar headings */
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color: #333 !important;
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}
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.form-container {
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display: flex;
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justify-content: space-between;
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align-items: center;
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}
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.form-container .stTextInput {
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flex: 1;
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}
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.form-container .stButton {
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margin-left: 10px;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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def launch_bot():
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if 'cfg' not in st.session_state:
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cfg = st.session_state.cfg
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vq = st.session_state.vq
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st.set_page_config(page_title="Media Demo", layout="wide")
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inject_custom_css()
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header_image = Image.open('header-image-2.png')
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cropped_image = header_image.crop((0, 0, header_image.width, 200))
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st.image(cropped_image, use_column_width=True)
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# left side content
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with st.sidebar:
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image = Image.open('vectara-logo.png')
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st.markdown("## Welcome to Media Demo\n\n"
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"This demo uses Vectara to find the movie where a quote is from\n\n"
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"Covers movies from this [playlist](https://www.youtube.com/playlist?list=PLHPTxTxtC0ibVZrT2_WKWUl2SAxsKuKwx) of free movies")
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st.markdown("---")
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st.markdown(
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st.markdown("---")
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st.image(image, width=250)
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st.markdown("<center> <h3>\"Find that movie\" demo</h3> </center>", unsafe_allow_html=True)
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st.markdown('<div class="form-container">', unsafe_allow_html=True)
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with st.form(key='my_form'):
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question = st.text_input("Enter your movie quote:")
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submit_button = st.form_submit_button(label='Find the Match')
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st.markdown('</div>', unsafe_allow_html=True)
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if submit_button:
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movie_name, match_url, score = vq.submit_query(question)
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if score < 0.7:
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st.write("Sorry, I couldn't find a match for that quote. Please try another one.")
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else:
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video_url, start_time = match_url.split('&t=')
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start_time = start_time[:-1] # remove the trailing 's'
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col1, col2, col3 = st.columns([1, 2, 1])
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with col2:
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st.write(f"Here's a useful video for you: {movie_name}")
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st.video(video_url, start_time=int(float(start_time)))
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if __name__ == "__main__":
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launch_bot()
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header-image-2.png
ADDED
Git LFS Details
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query.py
CHANGED
@@ -27,10 +27,7 @@ class VectaraQuery():
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'start_tag': "%START_SNIPPET%",
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'end_tag': "%END_SNIPPET%",
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},
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'rerankingConfig':
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{
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'rerankerId': 272725719,
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},
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}
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]
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}
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@@ -59,6 +56,7 @@ class VectaraQuery():
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responses = res['responseSet'][0]['response'][:top_k]
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documents = res['responseSet'][0]['document']
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metadatas = []
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for x in responses:
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md = {m["name"]: m["value"] for m in x["metadata"]}
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movie_title = metadatas[0].get("doc_title", None)
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snippet_url = metadatas[0].get("url", None)
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return movie_title, snippet_url
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'start_tag': "%START_SNIPPET%",
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'end_tag': "%END_SNIPPET%",
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},
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'rerankingConfig': { 'rerankerId': 272725719 }
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}
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]
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}
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responses = res['responseSet'][0]['response'][:top_k]
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documents = res['responseSet'][0]['document']
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metadatas = []
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for x in responses:
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md = {m["name"]: m["value"] for m in x["metadata"]}
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movie_title = metadatas[0].get("doc_title", None)
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snippet_url = metadatas[0].get("url", None)
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score = responses[0]["score"]
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return movie_title, snippet_url, score
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