Spaces:
Sleeping
Sleeping
File size: 3,135 Bytes
f4cbf67 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
import streamlit as st
from src.file_loader import load_file
from src.rag_pipeline import build_rag_pipeline, get_relevant_docs
from src.model_utils import load_hf_model, generate_answer
from src.utils import get_font_css
st.set_page_config(page_title="AI Chatbot", page_icon=":robot_face:", layout="wide")
st.markdown(get_font_css(), unsafe_allow_html=True)
st.sidebar.image("assets/logo.png", width=180)
st.sidebar.title("AI Chatbot")
st.sidebar.markdown("Upload a file to get started:")
uploaded_file = st.sidebar.file_uploader(
"Upload PDF, CSV, or XLSX", type=["pdf", "csv", "xlsx"]
)
model_name = st.sidebar.text_input(
"HuggingFace Model (text-generation)", value="amiguel/GM_Qwen1.8B_Finetune"
)
embedding_model = st.sidebar.text_input(
"Embedding Model", value="sentence-transformers/all-MiniLM-L6-v2"
)
st.sidebar.markdown("---")
st.sidebar.markdown("Powered by [Your Company]")
st.markdown(
"""
<div style="display: flex; align-items: center; margin-bottom: 1rem;">
<img src="app/assets/logo.png" width="60" style="margin-right: 1rem;">
<h1 style="font-family: 'Tw Cen MT', sans-serif; margin: 0;">AI Chatbot</h1>
</div>
""",
unsafe_allow_html=True,
)
if uploaded_file:
with st.spinner("Processing file..."):
text = load_file(uploaded_file)
docs = [{"page_content": chunk, "metadata": {}} for chunk in text]
retriever = build_rag_pipeline(docs, embedding_model)
st.success("File processed and indexed!")
with st.spinner("Loading model..."):
text_gen = load_hf_model(model_name)
st.success("Model loaded!")
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
user_input = st.text_input("Ask a question about your document:", key="user_input")
if st.button("Send", use_container_width=True) and user_input:
with st.spinner("Generating answer..."):
context_docs = get_relevant_docs(retriever, user_input)
context = " ".join([doc["page_content"] for doc in context_docs])
answer = generate_answer(text_gen, user_input, context)
st.session_state.chat_history.append(("user", user_input))
st.session_state.chat_history.append(("bot", answer))
for sender, msg in st.session_state.chat_history:
if sender == "user":
st.markdown(
f"""
<div style="background: #e6f0fa; border-radius: 10px; padding: 10px; margin-bottom: 5px; text-align: right; font-family: 'Tw Cen MT', sans-serif;">
<b>You:</b> {msg}
</div>
""",
unsafe_allow_html=True,
)
else:
st.markdown(
f"""
<div style="background: #f4f4f4; border-radius: 10px; padding: 10px; margin-bottom: 10px; text-align: left; font-family: 'Tw Cen MT', sans-serif;">
<b>AI:</b> {msg}
</div>
""",
unsafe_allow_html=True,
)
else:
st.info("Please upload a PDF, CSV, or XLSX file to begin.")
|