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Update app.py
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app.py
CHANGED
@@ -7,26 +7,27 @@ import os
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import streamlit as st
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from PIL import Image
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corpus_ids = str(os.environ['corpus_ids']).split(',')
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questions = list(eval(os.environ['examples']))
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cfg = OmegaConf.create({
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'customer_id': str(os.environ['customer_id']),
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'corpus_ids': corpus_ids,
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'api_key': str(os.environ['api_key']),
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'title': os.environ['title'],
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'description': os.environ['description'],
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'examples': questions,
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'source_data_desc': os.environ['source_data_desc']
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})
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vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_ids)
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def launch_bot():
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def generate_response(question):
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response = vq.submit_query(question)
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return response
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st.set_page_config(page_title=cfg.title, layout="wide")
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# left side content
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@@ -72,4 +73,5 @@ def launch_bot():
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st.session_state.messages.append(message)
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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 launch_bot():
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def generate_response(question):
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response = vq.submit_query(question)
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return response
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corpus_ids = str(os.environ['corpus_ids']).split(',')
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questions = list(eval(os.environ['examples']))
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cfg = OmegaConf.create({
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'customer_id': str(os.environ['customer_id']),
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'corpus_ids': corpus_ids,
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'api_key': str(os.environ['api_key']),
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'title': os.environ['title'],
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'description': os.environ['description'],
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'examples': questions,
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'source_data_desc': os.environ['source_data_desc']
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})
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if vq is None:
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vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_ids)
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st.set_page_config(page_title=cfg.title, layout="wide")
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# left side content
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st.session_state.messages.append(message)
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if __name__ == "__main__":
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vq = None
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launch_bot()
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