diff --git a/LLM/09_rag_langchain.ipynb b/LLM/09_rag_langchain.ipynb
index f26045c..86833d0 100644
--- a/LLM/09_rag_langchain.ipynb
+++ b/LLM/09_rag_langchain.ipynb
@@ -627,7 +627,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "#from langchain_community.vectorstores.chroma import Chroma\n",
@@ -703,6 +705,251 @@
     "        print(f\"An error occurred: {str(e)}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Ipywidgets Implementation"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import ipywidgets as widgets\n",
+    "from IPython.display import display, clear_output\n",
+    "import time\n",
+    "import os\n",
+    "import sys\n",
+    "\n",
+    "# Set up widgets for the interface\n",
+    "source_type_dropdown = widgets.Dropdown(\n",
+    "    options=['url', 'local'],\n",
+    "    value='local',\n",
+    "    description='Source Type:',\n",
+    "    style={'description_width': 'initial'},\n",
+    "    layout=widgets.Layout(width='300px')\n",
+    ")\n",
+    "\n",
+    "source_input = widgets.Text(\n",
+    "    description='Source:',\n",
+    "    placeholder='Enter URL or filename from data folder',\n",
+    "    style={'description_width': 'initial'},\n",
+    "    layout=widgets.Layout(width='600px')\n",
+    ")\n",
+    "\n",
+    "file_list = widgets.Select(\n",
+    "    options=[],\n",
+    "    description='Available Files:',\n",
+    "    disabled=False,\n",
+    "    layout=widgets.Layout(width='400px', height='150px', display='none')\n",
+    ")\n",
+    "\n",
+    "question_input = widgets.Text(\n",
+    "    placeholder='Ask a question about the document...',\n",
+    "    layout=widgets.Layout(width='800px')\n",
+    ")\n",
+    "\n",
+    "submit_button = widgets.Button(\n",
+    "    description='Ask',\n",
+    "    button_style='primary',\n",
+    "    layout=widgets.Layout(width='100px')\n",
+    ")\n",
+    "\n",
+    "exit_button = widgets.Button(\n",
+    "    description='Exit',\n",
+    "    button_style='danger',\n",
+    "    layout=widgets.Layout(width='100px')\n",
+    ")\n",
+    "\n",
+    "model_status = widgets.HTML(value=\"<b>Status:</b> Ready to load document\")\n",
+    "response_area = widgets.Output(layout=widgets.Layout(border='1px solid #ddd', padding='10px', width='900px', height='300px'))\n",
+    "\n",
+    "# Main widget container (for easier cleanup)\n",
+    "main_container = widgets.VBox()\n",
+    "\n",
+    "# Setup components\n",
+    "embedding_fn = initialize_embedding_fn()\n",
+    "vector_store = None\n",
+    "qachain = None\n",
+    "\n",
+    "model_name_or_path = \"TheBloke/Llama-2-7B-Chat-GGUF\"\n",
+    "model_basename = \"llama-2-7b-chat.Q4_K_M.gguf\"\n",
+    "MODEL_PATH = hf_hub_download(repo_id=model_name_or_path, filename=model_basename)\n",
+    "chat_model = create_llm(MODEL_PATH)\n",
+    "\n",
+    "# Create base prompt template\n",
+    "prompt_template = \"\"\"\n",
+    "Answer the question based on the context below. Keep your answer concise.\n",
+    "If you don't know, just say \"I don't know.\"\n",
+    "\n",
+    "Context: {context}\n",
+    "\n",
+    "Question: {question}\n",
+    "Answer:\n",
+    "\"\"\"\n",
+    "prompt = PromptTemplate(template=prompt_template, input_variables=[\"context\", \"question\"])\n",
+    "chain_type_kwargs = {\"prompt\": prompt}\n",
+    "\n",
+    "# Function to update file list\n",
+    "def update_file_list():\n",
+    "    data_dir = os.path.join(os.getcwd(), \"data\")\n",
+    "    if os.path.exists(data_dir):\n",
+    "        files = os.listdir(data_dir)\n",
+    "        file_list.options = files\n",
+    "        if files:\n",
+    "            file_list.value = files[0]\n",
+    "    else:\n",
+    "        file_list.options = [\"No files found in data directory\"]\n",
+    "\n",
+    "# Handler for source type change\n",
+    "def source_type_changed(change):\n",
+    "    if change['new'] == 'local':\n",
+    "        update_file_list()\n",
+    "        file_list.layout.display = 'block'\n",
+    "    else:\n",
+    "        file_list.layout.display = 'none'\n",
+    "\n",
+    "# Handler for file selection\n",
+    "def file_selected(change):\n",
+    "    if change['new'] and source_type_dropdown.value == 'local':\n",
+    "        source_input.value = change['new']\n",
+    "\n",
+    "# Widget handlers\n",
+    "def load_document_button_click(b):\n",
+    "    global vector_store, qachain\n",
+    "    \n",
+    "    with response_area:\n",
+    "        clear_output()\n",
+    "        source = source_input.value\n",
+    "        source_type = source_type_dropdown.value\n",
+    "        \n",
+    "        if not source:\n",
+    "            print(\"Please enter a source URL or filename\")\n",
+    "            return\n",
+    "        \n",
+    "        model_status.value = \"<b>Status:</b> Loading document...\"\n",
+    "        try:\n",
+    "            # Get or create embeddings for the current document\n",
+    "            vector_store = get_or_create_embeddings(source, source_type, embedding_fn)\n",
+    "            \n",
+    "            # Setup retriever and chain\n",
+    "            retriever = vector_store.as_retriever(search_kwargs={\"k\": 4})\n",
+    "            qachain = chains.RetrievalQA.from_chain_type(\n",
+    "                llm=chat_model,\n",
+    "                retriever=retriever,\n",
+    "                chain_type=\"stuff\",\n",
+    "                chain_type_kwargs=chain_type_kwargs,\n",
+    "                return_source_documents=False\n",
+    "            )\n",
+    "            \n",
+    "            model_status.value = \"<b>Status:</b> Model ready! Ask your questions.\"\n",
+    "            print(\"Document loaded successfully! You can now ask questions.\")\n",
+    "        except Exception as e:\n",
+    "            model_status.value = f\"<b>Status:</b> Error loading document\"\n",
+    "            print(f\"Error: {str(e)}\")\n",
+    "\n",
+    "class WidgetStreamHandler(BaseCallbackHandler):\n",
+    "    def __init__(self, output_widget):\n",
+    "        self.output_widget = output_widget\n",
+    "        self.generated_text = \"\"\n",
+    "        \n",
+    "    def on_llm_new_token(self, token, **kwargs):\n",
+    "        self.generated_text += token\n",
+    "        with self.output_widget:\n",
+    "            clear_output(wait=True)\n",
+    "            print(self.generated_text)\n",
+    "\n",
+    "def ask_question_button_click(b):\n",
+    "    question = question_input.value\n",
+    "    \n",
+    "    if not question:\n",
+    "        with response_area:\n",
+    "            clear_output()\n",
+    "            print(\"Please enter a question\")\n",
+    "        return\n",
+    "    \n",
+    "    if vector_store is None or qachain is None:\n",
+    "        with response_area:\n",
+    "            clear_output()\n",
+    "            print(\"Please load a document first\")\n",
+    "        return\n",
+    "    \n",
+    "    with response_area:\n",
+    "        clear_output()\n",
+    "        model_status.value = \"<b>Status:</b> Generating response...\"\n",
+    "        stream_handler = WidgetStreamHandler(response_area)\n",
+    "        \n",
+    "        try:\n",
+    "            start_time = time.time()\n",
+    "            qachain.invoke(\n",
+    "                {\n",
+    "                    \"query\": question,\n",
+    "                    \"max_tokens\": 512,\n",
+    "                    \"temperature\": 0.7\n",
+    "                },\n",
+    "                config={\"callbacks\": [stream_handler]}\n",
+    "            )\n",
+    "            elapsed = time.time() - start_time\n",
+    "            model_status.value = f\"<b>Status:</b> Response generated in {elapsed:.2f} seconds\"\n",
+    "            \n",
+    "        except Exception as e:\n",
+    "            model_status.value = \"<b>Status:</b> Error generating response\"\n",
+    "            print(f\"Error: {str(e)}\")\n",
+    "\n",
+    "def exit_application(b):\n",
+    "    # Clear all widget outputs\n",
+    "    with response_area:\n",
+    "        clear_output()\n",
+    "    \n",
+    "    # Clean up resources\n",
+    "    global vector_store, qachain\n",
+    "    vector_store = None\n",
+    "    qachain = None\n",
+    "    \n",
+    "    # Clear the main container and show exit message\n",
+    "    main_container.children = [widgets.HTML(\"<h3>RAG application has been closed. You can run this cell again to restart.</h3>\")]\n",
+    "\n",
+    "# Connect handlers\n",
+    "source_type_dropdown.observe(source_type_changed, names='value')\n",
+    "file_list.observe(file_selected, names='value')\n",
+    "\n",
+    "load_document_button = widgets.Button(\n",
+    "    description='Load Document',\n",
+    "    button_style='info',\n",
+    "    layout=widgets.Layout(width='150px')\n",
+    ")\n",
+    "load_document_button.on_click(load_document_button_click)\n",
+    "submit_button.on_click(ask_question_button_click)\n",
+    "exit_button.on_click(exit_application)\n",
+    "\n",
+    "# Initialize the file list if \"local\" is selected\n",
+    "if source_type_dropdown.value == 'local':\n",
+    "    update_file_list()\n",
+    "    file_list.layout.display = 'block'\n",
+    "\n",
+    "# Create button row\n",
+    "button_row = widgets.HBox([question_input, submit_button, exit_button])\n",
+    "\n",
+    "# Create header with title and exit button\n",
+    "header = widgets.HTML(\"<h3>RAG Interactive Interface</h3>\")\n",
+    "\n",
+    "# Build the main container\n",
+    "main_container.children = [\n",
+    "    header,\n",
+    "    widgets.HBox([source_type_dropdown, source_input, load_document_button]),\n",
+    "    file_list,\n",
+    "    button_row,\n",
+    "    model_status,\n",
+    "    response_area\n",
+    "]\n",
+    "\n",
+    "# Display the interface\n",
+    "display(main_container)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -771,7 +1018,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.12"
   }
  },
  "nbformat": 4,
diff --git a/LLM/rag/requirements.txt b/LLM/rag/requirements.txt
index d6c3beb..6d123dd 100644
--- a/LLM/rag/requirements.txt
+++ b/LLM/rag/requirements.txt
@@ -1,4 +1,4 @@
-langchain==0.3.19
+langchain==0.3.24
 langchain-community==0.3.23
 langchain-core==0.3.56
 langchain-huggingface==0.1.2