adjust streamlit rag app and dependencies files

Co-authored-by: Brandon Vargus bmv2021@bu.edu
Co-authored-by: Daniel Foley daf@bu.edu
Co-authored-by: Jinanshi Mehta jinanshi@bu.edu
Co-authored-by: Enrico Collautti enricoll@bu.edu

Dockerfile

@@ -82,7 +82,7 @@ COPY --chown=user . /app
 
 
 
-# Set environment variables for Chainlit
+# Set environment variables for Streamlit
 
 
 
@@ -94,12 +94,12 @@ ENV PORT=7860
 
 
 
-ENV CHAINLIT_SERVER_PORT=7860
+ENV STREAMLIT_SERVER_PORT=7860
 
 
 
-ENV CHAINLIT_HOST="0.0.0.0"
 
+ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
 
 
 
@@ -108,4 +108,4 @@ ENV CHAINLIT_HOST="0.0.0.0"
 
 # Change the CMD to use chainlit
 
-CMD ["chainlit", "run", "app.py","--port","7860"]
+CMD ["streamlit", "run", "streamlit-rag-app.py", "--server.port", "7860", "--server.address", "0.0.0.0"]

requirements.txt

@@ -9,3 +9,13 @@ pydantic==2.7.3
 pydantic-settings==2.6.1
 
 pydantic_core==2.18.4
+
+sentence_transformers
+
+streamlit
+
+python-dotenv
+
+openai
+
+faiss-cpu

streamlit-rag-app.py

@@ -49,15 +49,15 @@ def setup_qa_chain(vector_store):
 
 def main():
     # Set page title and header
-    st.set_page_config(page_title="Football Players RAG App", page_icon="⚽")
-    st.title("Football Players Knowledge Base 🏆")
+    st.set_page_config(page_title="LibRAG, page_icon="📖")
+    st.title("Boston Public Library Database 📚")
 
     # Sidebar for initialization
     st.sidebar.header("Initialize Knowledge Base")
     if st.sidebar.button("Load Data"):
         try:
             # Load and preprocess the JSON file
-            json_data = load_json_file("football_players.json")
+            json_data = load_json_file(".json")
             st.session_state.vector_store = setup_vector_store_from_json(json_data)
             st.session_state.qa_chain = setup_qa_chain(st.session_state.vector_store)
             st.sidebar.success("Knowledge base loaded successfully!")
@@ -66,7 +66,7 @@ def main():
 
     # Query input and processing
     st.header("Ask a Question")
-    query = st.text_input("Enter your question about football players:")
+    query = st.text_input("Enter your question about BPL's database")
 
     if query:
         # Check if vector store and QA chain are initialized