Upload app.py

app.py

@@ -0,0 +1,81 @@
+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.")