diff --git a/week1/community-contributions/week1_assignments_raju/week1_exercise.ipynb b/week1/community-contributions/week1_assignments_raju/week1_exercise.ipynb
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@@ -0,0 +1,189 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4",
+      "authorship_tag": "ABX9TyP5A+4jBwHa+8xeTeQY7q1j"
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**Assignment**: build a tool that takes a technical question, and responds with an explanation."
+      ],
+      "metadata": {
+        "id": "jc57C2kha5-g"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "H8kU5EtiYEiU"
+      },
+      "outputs": [],
+      "source": [
+        "#install ollama\n",
+        "!curl -fsSL https://ollama.com/install.sh | sh"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Start Ollama server\n",
+        "\n",
+        "import subprocess\n",
+        "\n",
+        "# Start the command in a background process\n",
+        "process = subprocess.Popen([\"ollama\", \"serve\"])\n",
+        "\n",
+        "# The kernel can continue execution while the process runs in the background\n",
+        "print(\"The 'ollama serve' process is running in the background.\")"
+      ],
+      "metadata": {
+        "id": "KGsTG4x2cbye"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#test server\n",
+        "import requests\n",
+        "\n",
+        "requests.get(\"http://localhost:11434\").content"
+      ],
+      "metadata": {
+        "id": "J_sgo2BUbJUc"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#download llama model\n",
+        "!ollama pull llama3.2"
+      ],
+      "metadata": {
+        "id": "myfRsLSAcYrG"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def create_messages(user_query):\n",
+        "  system_prompt = \"\"\"\n",
+        "You are a helpful technical assistant who knows programming languages.\n",
+        "You will answer the question about given code by explaining what that code does.\n",
+        "  \"\"\"\n",
+        "  user_prompt = \"Answer the below technical question:\\n\" + user_query\n",
+        "  messages = [\n",
+        "      {\"role\":\"system\", \"content\":system_prompt},\n",
+        "      {\"role\":\"user\", \"content\":user_prompt},\n",
+        "  ]\n",
+        "  return messages"
+      ],
+      "metadata": {
+        "id": "tEwjDW2scoiM"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from openai import OpenAI\n",
+        "\n",
+        "OLLAMA_BASE_URL = \"http://localhost:11434/v1\"\n",
+        "\n",
+        "ollama_api = OpenAI(base_url=OLLAMA_BASE_URL, api_key='ollama')"
+      ],
+      "metadata": {
+        "id": "AWTsU3RggDWl"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Llama model working good with code tasks(explanation)\n",
+        "\n",
+        "def call_model(question, enable_stream = False):\n",
+        "  response = ollama_api.chat.completions.create(\n",
+        "        model = \"llama3.2\",\n",
+        "        messages = create_messages(question),\n",
+        "        stream = enable_stream\n",
+        "    )\n",
+        "  return response"
+      ],
+      "metadata": {
+        "id": "2uCECVbii1Ul"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Test - normal call\n",
+        "\n",
+        "result = call_model(\"\"\"\n",
+        "what below python code does, correct if it is wrong:\n",
+        "[x for x in range(5)].map(lambda x:x**2)\n",
+        "\"\"\")\n",
+        "display(result.choices[0].message.content)"
+      ],
+      "metadata": {
+        "id": "Uck-yp44jP2P"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Test with streaming - simulates typewriting\n",
+        "from IPython.display import display, update_display\n",
+        "\n",
+        "stream = call_model(\"explain in just 2 or 3 lines, what - a,b = b,a - does in python\", True)\n",
+        "\n",
+        "response=\"\"\n",
+        "display_handle = display(\"\", display_id=True)\n",
+        "for chunk in stream:\n",
+        "  response += chunk.choices[0].delta.content or \"\"\n",
+        "  update_display(response, display_id = display_handle.display_id)\n"
+      ],
+      "metadata": {
+        "id": "-g7VHt78jTtl"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "process.kill()"
+      ],
+      "metadata": {
+        "id": "c-A0bFmKrA0O"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
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