diff --git a/week1/community-contributions/wk1-day1-deepseek-stream-summarize.ipynb b/week1/community-contributions/wk1-day1-deepseek-stream-summarize.ipynb
index 2e615ed..0e7a226 100644
--- a/week1/community-contributions/wk1-day1-deepseek-stream-summarize.ipynb
+++ b/week1/community-contributions/wk1-day1-deepseek-stream-summarize.ipynb
@@ -1,125 +1,131 @@
 {
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a767b6bc-65fe-42b2-988f-efd54125114f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "import requests\n",
-    "from dotenv import load_dotenv\n",
-    "from bs4 import BeautifulSoup\n",
-    "from IPython.display import Markdown, display, clear_output\n",
-    "from openai import OpenAI\n",
-    "\n",
-    "load_dotenv(override=True)\n",
-    "api_key = os.getenv('DEEPSEEK_API_KEY')\n",
-    "base_url=os.getenv('DEEPSEEK_BASE_URL')\n",
-    "MODEL = \"deepseek-chat\"\n",
-    "\n",
-    "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
-    "and provides a short summary, ignoring text that might be navigation related. \\\n",
-    "Respond in markdown.\"\n",
-    "\n",
-    "messages = [\n",
-    "    {\"role\": \"system\", \"content\": \"You are a snarky assistant\"},\n",
-    "    {\"role\": \"user\", \"content\": \"What is 2 + 2?\"}\n",
-    "]\n",
-    " \n",
-    "# Check the key\n",
-    "if not api_key:\n",
-    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
-    "elif not api_key.startswith(\"sk-proj-\"):\n",
-    "    print(\"An API key was found, but it doesn't start sk-proj-; Looks like you are using DeepSeek (R1) model.\")\n",
-    "elif api_key.strip() != api_key:\n",
-    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
-    "else:\n",
-    "    print(\"API key found and looks good so far!\")\n",
-    "        \n",
-    "openai = OpenAI(api_key=api_key, base_url=base_url)\n",
-    "\n",
-    "headers = {\n",
-    " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
-    "}\n",
-    "\n",
-    "class Website:\n",
-    "\n",
-    "    def __init__(self, url):\n",
-    "        \"\"\"\n",
-    "        Create this Website object from the given url using the BeautifulSoup library\n",
-    "        \"\"\"\n",
-    "        self.url = url\n",
-    "        response = requests.get(url, headers=headers)\n",
-    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
-    "        self.title = soup.title.string if soup.title else \"No title found\"\n",
-    "        for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
-    "            irrelevant.decompose()\n",
-    "        self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n",
-    "       \n",
-    "def user_prompt_for(website):\n",
-    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
-    "    user_prompt += \"\\nThe contents of this website is as follows; please provide a short summary of this website in markdown. If it includes news or announcements, then summarize these too.\\n\\n\"\n",
-    "    user_prompt += website.text\n",
-    "    return user_prompt\n",
-    "\n",
-    "def messages_for(website):\n",
-    "    return [\n",
-    "        {\"role\": \"system\", \"content\": system_prompt},\n",
-    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
-    "    ]\n",
-    "    \n",
-    "def summarize(url):\n",
-    "    website = Website(url)\n",
-    "    response = openai.chat.completions.create(\n",
-    "        model=MODEL,\n",
-    "        messages=messages_for(website),\n",
-    "        stream=True\n",
-    "    )\n",
-    "    print(\"Streaming response:\")\n",
-    "    accumulated_content = \"\"  # Accumulate the content here\n",
-    "    for chunk in response:\n",
-    "        if chunk.choices[0].delta.content:  # Check if there's content in the chunk\n",
-    "            accumulated_content += chunk.choices[0].delta.content  # Append the chunk to the accumulated content\n",
-    "            clear_output(wait=True)  # Clear the previous output\n",
-    "            display(Markdown(accumulated_content))  # Display the updated content\n",
-    "\n",
-    "def display_summary():\n",
-    "    url = str(input(\"Enter the URL of the website you want to summarize: \"))\n",
-    "    summarize(url)\n",
-    "\n",
-    "display_summary()"
-   ]
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "a767b6bc-65fe-42b2-988f-efd54125114f",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "import requests\n",
+        "from dotenv import load_dotenv\n",
+        "from bs4 import BeautifulSoup\n",
+        "from IPython.display import Markdown, display, clear_output\n",
+        "from openai import OpenAI\n",
+        "\n",
+        "load_dotenv(override=True)\n",
+        "# Deep seek API payload\n",
+        "# api_key = os.getenv('DEEPSEEK_API_KEY')\n",
+        "# base_url=os.getenv('DEEPSEEK_BASE_URL')\n",
+        "# MODEL = \"deepseek-chat\"\n",
+        "\n",
+        "# Day 2 Exercise with Ollama API\n",
+        "api_key = os.getenv('OLLAMA_API_KEY')\n",
+        "base_url = os.getenv('OLLAMA_BASE_URL')\n",
+        "MODEL = \"llama3.2\"\n",
+        "\n",
+        "system_prompt = \"You are an assistant that analyzes the contents of a website \\\n",
+        "and provides a short summary, ignoring text that might be navigation related. \\\n",
+        "Respond in markdown.\"\n",
+        "\n",
+        "messages = [\n",
+        "    {\"role\": \"system\", \"content\": \"You are a snarky assistant\"},\n",
+        "    {\"role\": \"user\", \"content\": \"What is 2 + 2?\"}\n",
+        "]\n",
+        " \n",
+        "# Check the key\n",
+        "if not api_key:\n",
+        "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
+        "elif not api_key.startswith(\"sk-proj-\"):\n",
+        "    print(\"An API key was found, but it doesn't start sk-proj-; Looks like you are using DeepSeek (R1) model.\")\n",
+        "elif api_key.strip() != api_key:\n",
+        "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
+        "else:\n",
+        "    print(\"API key found and looks good so far!\")\n",
+        "        \n",
+        "openai = OpenAI(api_key=api_key, base_url=base_url)\n",
+        "\n",
+        "headers = {\n",
+        " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
+        "}\n",
+        "\n",
+        "class Website:\n",
+        "\n",
+        "    def __init__(self, url):\n",
+        "        \"\"\"\n",
+        "        Create this Website object from the given url using the BeautifulSoup library\n",
+        "        \"\"\"\n",
+        "        self.url = url\n",
+        "        response = requests.get(url, headers=headers)\n",
+        "        soup = BeautifulSoup(response.content, 'html.parser')\n",
+        "        self.title = soup.title.string if soup.title else \"No title found\"\n",
+        "        for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
+        "            irrelevant.decompose()\n",
+        "        self.text = soup.body.get_text(separator=\"\\n\", strip=True)\n",
+        "       \n",
+        "def user_prompt_for(website):\n",
+        "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
+        "    user_prompt += \"\\nThe contents of this website is as follows; please provide a short summary of this website in markdown. If it includes news or announcements, then summarize these too.\\n\\n\"\n",
+        "    user_prompt += website.text\n",
+        "    return user_prompt\n",
+        "\n",
+        "def messages_for(website):\n",
+        "    return [\n",
+        "        {\"role\": \"system\", \"content\": system_prompt},\n",
+        "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
+        "    ]\n",
+        "    \n",
+        "def summarize(url):\n",
+        "    website = Website(url)\n",
+        "    response = openai.chat.completions.create(\n",
+        "        model=MODEL,\n",
+        "        messages=messages_for(website),\n",
+        "        stream=True\n",
+        "    )\n",
+        "    print(\"Streaming response:\")\n",
+        "    accumulated_content = \"\"  # Accumulate the content here\n",
+        "    for chunk in response:\n",
+        "        if chunk.choices[0].delta.content:  # Check if there's content in the chunk\n",
+        "            accumulated_content += chunk.choices[0].delta.content  # Append the chunk to the accumulated content\n",
+        "            clear_output(wait=True)  # Clear the previous output\n",
+        "            display(Markdown(accumulated_content))  # Display the updated content\n",
+        "\n",
+        "def display_summary():\n",
+        "    url = str(input(\"Enter the URL of the website you want to summarize: \"))\n",
+        "    summarize(url)\n",
+        "\n",
+        "display_summary()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "01c9e5e7-7510-43ef-bb9c-aa44b15d39a7",
+      "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": "3.11.11"
+    }
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "01c9e5e7-7510-43ef-bb9c-aa44b15d39a7",
-   "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": "3.11.11"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
+  "nbformat": 4,
+  "nbformat_minor": 5
 }