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app.py
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with col1:
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st.markdown(
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"""
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# Instructions
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1. Obtain an [API Key](https://cloud.llamaindex.ai/api-key) from LlamaParse to parse your document.
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run = st.button("Answer", type="primary")
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if parsed_document is not None and run
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index = VectorStoreIndex.from_documents(parsed_document)
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query_engine = index.as_query_engine(
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similarity_top_k=similarity_top_k,
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with col1:
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st.markdown(
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"""
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# Introduction
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This app builds a [retrieval-augmented generation](https://en.wikipedia.org/wiki/Retrieval-augmented_generation) model that let's you ask "talk" to your document, ask questions, summarize, and extract data.
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:clap: The workflow relies on:
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* [OpenAI](https://platform.openai.com/apps)
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* [LlamaParse](https://cloud.llamaindex.ai/)
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* [LlamaIndex](https://cloud.llamaindex.ai/)
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:warning: This tool is provided "as-is" without warranty.
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# Instructions
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1. Obtain an [API Key](https://cloud.llamaindex.ai/api-key) from LlamaParse to parse your document.
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run = st.button("Answer", type="primary")
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if parsed_document is not None and run:
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index = VectorStoreIndex.from_documents(parsed_document)
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query_engine = index.as_query_engine(
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similarity_top_k=similarity_top_k,
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