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adjust streamlit rag app and dependencies files
Browse filesCo-authored-by: Brandon Vargus [email protected]
Co-authored-by: Daniel Foley [email protected]
Co-authored-by: Jinanshi Mehta [email protected]
Co-authored-by: Enrico Collautti [email protected]
- Dockerfile +4 -4
- requirements.txt +10 -0
- streamlit-rag-app.py +4 -4
Dockerfile
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@@ -82,7 +82,7 @@ COPY --chown=user . /app
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# Set environment variables for
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@@ -94,12 +94,12 @@ ENV PORT=7860
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ENV
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ENV CHAINLIT_HOST="0.0.0.0"
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@@ -108,4 +108,4 @@ ENV CHAINLIT_HOST="0.0.0.0"
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# Change the CMD to use chainlit
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CMD ["
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# Set environment variables for Streamlit
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ENV STREAMLIT_SERVER_PORT=7860
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ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
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# Change the CMD to use chainlit
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CMD ["streamlit", "run", "streamlit-rag-app.py", "--server.port", "7860", "--server.address", "0.0.0.0"]
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requirements.txt
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@@ -9,3 +9,13 @@ pydantic==2.7.3
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pydantic-settings==2.6.1
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pydantic_core==2.18.4
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pydantic-settings==2.6.1
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pydantic_core==2.18.4
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sentence_transformers
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streamlit
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python-dotenv
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openai
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faiss-cpu
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streamlit-rag-app.py
CHANGED
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@@ -49,15 +49,15 @@ def setup_qa_chain(vector_store):
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def main():
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# Set page title and header
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st.set_page_config(page_title="
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st.title("
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# Sidebar for initialization
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st.sidebar.header("Initialize Knowledge Base")
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if st.sidebar.button("Load Data"):
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try:
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# Load and preprocess the JSON file
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json_data = load_json_file("
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st.session_state.vector_store = setup_vector_store_from_json(json_data)
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st.session_state.qa_chain = setup_qa_chain(st.session_state.vector_store)
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st.sidebar.success("Knowledge base loaded successfully!")
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@@ -66,7 +66,7 @@ def main():
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# Query input and processing
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st.header("Ask a Question")
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query = st.text_input("Enter your question about
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if query:
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# Check if vector store and QA chain are initialized
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def main():
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# Set page title and header
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st.set_page_config(page_title="LibRAG, page_icon="π")
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st.title("Boston Public Library Database π")
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# Sidebar for initialization
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st.sidebar.header("Initialize Knowledge Base")
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if st.sidebar.button("Load Data"):
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try:
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# Load and preprocess the JSON file
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json_data = load_json_file(".json")
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st.session_state.vector_store = setup_vector_store_from_json(json_data)
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st.session_state.qa_chain = setup_qa_chain(st.session_state.vector_store)
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st.sidebar.success("Knowledge base loaded successfully!")
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# Query input and processing
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st.header("Ask a Question")
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query = st.text_input("Enter your question about BPL's database")
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if query:
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# Check if vector store and QA chain are initialized
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