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