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Create app.py

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  1. app.py +14 -0
app.py ADDED
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+ import streamlit as st
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+
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+ from gradio_client import Client
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+
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+ client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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+ result = client.predict(
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+ "Hello!!", # str in 'Search' Textbox component
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+ 4, # float (numeric value between 4 and 10) in 'Top n results as context' Slider component
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+ "Semantic Search - up to 10 Mar 2024", # Literal['Semantic Search - up to 10 Mar 2024', 'Arxiv Search - Latest - (EXPERIMENTAL)'] in 'Search Source' Dropdown component
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+ "mistralai/Mixtral-8x7B-Instruct-v0.1", # Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] in 'LLM Model' Dropdown component
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+ api_name="/update_with_rag_md"
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+ )
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+ print(result)
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+