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Update app.py

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  1. app.py +2 -16
app.py CHANGED
@@ -9,11 +9,10 @@ import pandas as pd
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  os.makedirs("data", exist_ok=True)
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  st.set_page_config(
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- page_title="LIDA: Automatic Generation of Visualizations and Infographics",
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  page_icon="πŸ“Š",
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  )
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- st.write("# LIDA: Automatic Generation of Visualizations and Infographics using Large Language Models πŸ“Š")
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  st.sidebar.write("## Setup")
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@@ -31,21 +30,8 @@ else:
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  display_key = openai_key[:2] + "*" * (len(openai_key) - 5) + openai_key[-3:]
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  st.sidebar.write(f"OpenAI API key loaded from environment variable: {display_key}")
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- st.markdown(
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- """
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- LIDA is a library for generating data visualizations and data-faithful infographics.
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- LIDA is grammar agnostic (will work with any programming language and visualization
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- libraries e.g. matplotlib, seaborn, altair, d3 etc) and works with multiple large language
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- model providers (OpenAI, Azure OpenAI, PaLM, Cohere, Huggingface). Details on the components
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- of LIDA are described in the [paper here](https://arxiv.org/abs/2303.02927) and in this
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- tutorial [notebook](notebooks/tutorial.ipynb). See the project page [here](https://microsoft.github.io/lida/) for updates!.
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-
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- This demo shows how to use the LIDA python api with Streamlit. [More](/about).
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-
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- ----
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- """)
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-
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  # Step 2 - Select a dataset and summarization method
 
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  if openai_key:
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  # Initialize selected_dataset to None
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  selected_dataset = None
 
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  os.makedirs("data", exist_ok=True)
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  st.set_page_config(
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+ page_title="LLM Visualization on tabular data",
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  page_icon="πŸ“Š",
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  )
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  st.sidebar.write("## Setup")
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  display_key = openai_key[:2] + "*" * (len(openai_key) - 5) + openai_key[-3:]
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  st.sidebar.write(f"OpenAI API key loaded from environment variable: {display_key}")
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  # Step 2 - Select a dataset and summarization method
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+
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  if openai_key:
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  # Initialize selected_dataset to None
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  selected_dataset = None