diff --git a/week2/community-contributions/Wk2_Day3_sharathir_ollama.ipynb b/week2/community-contributions/Wk2_Day3_sharathir_ollama.ipynb
new file mode 100644
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+++ b/week2/community-contributions/Wk2_Day3_sharathir_ollama.ipynb
@@ -0,0 +1,191 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0f1f62c4-ed03-4401-88d5-3445464a8421",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from dotenv import load_dotenv\n",
+    "from openai import OpenAI\n",
+    "import gradio as gr\n",
+    "import ollama"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f8103014-012c-4648-9111-75993ce4d46a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_message = \"You are a helpful assistant\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8fca0b4-9db7-4f74-865b-503ee19a832f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chat(message, history):\n",
+    "    messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
+    "\n",
+    "    stream = ollama.chat(model=\"llama3.2\", messages=messages, stream=True)\n",
+    "\n",
+    "    result = \"\"\n",
+    "    for chunk in stream:\n",
+    "        result += chunk['message']['content'] or \"\"\n",
+    "        yield result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "61de58a0-5972-4aca-93ad-a4bd3878a50b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d448f8c5-2bb5-448d-8ae4-894b905214a7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_message = \"You are a helpful assistant in a clothes store. You should try to gently encourage \\\n",
+    "the customer to try items that are on sale. Hats are 60% off, and most other items are 50% off. \\\n",
+    "For example, if the customer says 'I'm looking to buy a hat', \\\n",
+    "you could reply something like, 'Wonderful - we have lots of hats - including several that are part of our sales event.'\\\n",
+    "Encourage the customer to buy hats if they are unsure what to get.\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "465968cf-aa7f-46b2-857f-a6819f2b14ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "873ab86b-ecb8-4f68-b520-50b29b7fd7be",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_message += \"\\nIf the customer asks for shoes, you should respond that shoes are not on sale today, \\\n",
+    "but remind the customer to look at hats!\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c63ced30-1109-4409-b255-1f72f8c6172f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "054f1406-c240-4849-8618-064985e76d86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chat(message, history):\n",
+    "\n",
+    "    global system_message\n",
+    "    if 'belt' in message:\n",
+    "        system_message += \" The store does not sell belts; if you are asked for belts, be sure to point out other items on sale.\"\n",
+    "    messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n",
+    "\n",
+    "    stream = ollama.chat(model=\"llama3.2\", messages=messages, stream=True)\n",
+    "\n",
+    "    result = \"\"\n",
+    "    for chunk in stream:\n",
+    "        result += chunk['message']['content'] or \"\"\n",
+    "        yield result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "b1086d8a-5b5a-4b59-9a61-e76078f930cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7869\n",
+      "* To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7869/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gr.ChatInterface(fn=chat, type=\"messages\").launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c558ab19-b907-4b0c-8a4f-37c8b731f9b5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}