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"""Sidebar UI components.""" |
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import streamlit as st |
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from config import SAMPLE_TEXT, EXAMPLE_QUESTIONS |
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from utils.document_processor import read_uploaded_file |
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from models.retriever import build_retriever |
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from models.llm_loader import load_qwen_llm |
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from chains.qa_chain import create_qa_chain |
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from config import QWEN_MODEL_NAME, EMBEDDING_MODEL_NAME, MAX_NEW_TOKENS, TEMPERATURE, TOP_P |
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def render_sidebar(): |
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"""Render the sidebar with upload and controls.""" |
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with st.sidebar: |
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st.header("📄 Document Upload") |
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st.download_button( |
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label="📄 Download Sample File", |
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data=SAMPLE_TEXT, |
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file_name="sample_agri.txt", |
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mime="text/plain" |
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) |
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uploaded_file = st.file_uploader( |
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"Upload your file", |
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type=["txt", "pdf"] |
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) |
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if uploaded_file is not None: |
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st.success(f"{uploaded_file.name}") |
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_handle_document_upload(uploaded_file) |
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if st.session_state.document_processed: |
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_render_example_questions() |
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if st.session_state.chat_history: |
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_render_clear_button() |
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def _handle_document_upload(uploaded_file): |
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"""Handle document processing.""" |
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if st.button("Process Document", type="primary"): |
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with st.spinner("Processing document..."): |
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try: |
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docs = read_uploaded_file(uploaded_file) |
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if len(docs) > 0: |
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retriever = build_retriever(docs, EMBEDDING_MODEL_NAME) |
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llm = load_qwen_llm( |
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QWEN_MODEL_NAME, |
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MAX_NEW_TOKENS, |
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TEMPERATURE, |
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TOP_P |
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) |
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st.session_state.qa_chain = create_qa_chain(llm, retriever) |
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st.session_state.document_processed = True |
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st.session_state.chat_history = [] |
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st.success(f"Processed {len(docs)} text chunks!") |
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st.rerun() |
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else: |
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st.error("No content found in file.") |
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except Exception as e: |
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st.error(f"Error: {str(e)}") |
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def _render_example_questions(): |
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"""Render example question buttons.""" |
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st.markdown("---") |
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st.subheader("💡 Example Questions") |
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for q in EXAMPLE_QUESTIONS: |
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if st.button(q, key=f"example_{q}"): |
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st.session_state.user_input = q |
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st.rerun() |
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def _render_clear_button(): |
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"""Render clear chat history button.""" |
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st.markdown("---") |
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if st.button("🗑️ Clear Chat History"): |
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st.session_state.chat_history = [] |
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st.rerun() |
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