Spaces:
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Update app.py
Browse files
app.py
CHANGED
@@ -139,6 +139,57 @@ pipeline.connect("prompt_builder", "llm")
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# Initialize Streamlit app
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st.title("Code Assistant Chat")
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tabs = ["Data Fetching","Assistant"]
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selected_tab = st.sidebar.radio("Select a Tab", tabs)
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# Initialize Streamlit app
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st.title("Code Assistant Chat")
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st.subheader("Frequently Asked Questions")
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st.markdown("""
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<style>
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.streamlit-expanderHeader {
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background-color: #f0f2f6;
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border: 1px solid #ddd;
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border-radius: 5px;
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padding: 10px;
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}
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.streamlit-expanderContent {
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background-color: #ffffff;
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border: 1px solid #ddd;
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border-radius: 5px;
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padding: 10px;
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}
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</style>
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""", unsafe_allow_html=True)
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with st.expander("How can I use this space?"):
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st.markdown("""
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This space is created based on steps described in [this Medium article](https://medium.com/towards-data-science/using-llama-3-for-building-ai-agents-7e74f79d1ccc). To use this space:
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1. Create a Redis Cloud account and set up a database
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2. Add your Redis credentials to this space
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3. Enter your preferred GitHub repository clone URL for data fetching and indexing
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""")
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with st.expander("Do I need a Gemini API key?"):
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st.markdown("""
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No, you don't need to provide a Gemini API key for testing this repository.
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- This repo includes a Gemini free tier API key itself.
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- However, if you encounter any resource exhaustion error:
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- Consider cloning this space
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- Add your own key as the `GEMINI_API_KEY` secret
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""")
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with st.expander("I don't want to create a Redis database. Can I still check the output?"):
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st.markdown("""
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Absolutely! Here's what you can do:
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1. Send me a message on LinkedIn mentioning your requirement
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2. I'll provide you with preconfigured database credentials
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3. Enter these credentials in the appropriate fields
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4. You'll then be able to use the assistant as you wish
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> **Important**: Please use the provided credentials responsibly and for testing purposes only.
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""")
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tabs = ["Data Fetching","Assistant"]
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selected_tab = st.sidebar.radio("Select a Tab", tabs)
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