diff --git a/week2/community-contributions/Copilot.ipynb b/week2/community-contributions/Copilot.ipynb
new file mode 100644
index 0000000..c32aad0
--- /dev/null
+++ b/week2/community-contributions/Copilot.ipynb
@@ -0,0 +1,212 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1877ad68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import requests\n",
+    "from openai import OpenAI\n",
+    "import gradio as gr\n",
+    "from dotenv import load_dotenv  \n",
+    "import google.generativeai as genai\n",
+    "from IPython.display import Markdown, display, update_display\n",
+    "load_dotenv(override=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "008056a2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
+    "google_api_key = os.getenv('GOOGLE_API_KEY')\n",
+    "\n",
+    "if openai_api_key:\n",
+    "    print(f'OpenAi api key exists and its starts with {openai_api_key[:3]}')\n",
+    "else:\n",
+    "    print(\"OpenAi api key doesn't exist\")\n",
+    "\n",
+    "if google_api_key:\n",
+    "    print('Google api key exists')\n",
+    "else:\n",
+    "    print(\"Google api key doesn't exist\")\n",
+    "\n",
+    "OPENAI_MODEL = \"gpt-4o-mini\"\n",
+    "GOOGLE_MODEL = \"gemini-1.5-flash\"\n",
+    "\n",
+    "openai = OpenAI()\n",
+    "\n",
+    "genai.configure()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5013ed7b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_msg = \"\"\"\n",
+    "You are CodeCopilot, an adaptive AI coding assistant that helps users solve problems in any programming language.\n",
+    "Always provide correct, runnable, and well-formatted code with clear explanations.\n",
+    "Adjust your style based on the user’s expertise: for beginners, break concepts down step by step with simple examples and commented code;\n",
+    "for advanced users, deliver concise, production-ready, optimized solutions with best practices and trade-off insights.\n",
+    "Ask clarifying questions when requirements are ambiguous, highlight pitfalls and edge cases,\n",
+    "and act as a collaborative pair programmer or mentor whose goal is to help users learn, build, and ship high-quality code efficiently.\n",
+    "\"\"\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "35c480a1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_prompt(prompt, history):\n",
+    "    messages = [{\"role\": \"system\", \"content\": system_msg}]\n",
+    "\n",
+    "    # history is a list of (user_msg, assistant_msg) tuples\n",
+    "    for user_msg, assistant_msg in history:\n",
+    "        if user_msg:\n",
+    "            messages.append({\"role\": \"user\", \"content\": user_msg})\n",
+    "        if assistant_msg:\n",
+    "            messages.append({\"role\": \"assistant\", \"content\": assistant_msg})\n",
+    "\n",
+    "    # new user prompt\n",
+    "    messages.append({\"role\": \"user\", \"content\": prompt})\n",
+    "    return messages"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5dfbecd0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def openai_agent(prompt, history):\n",
+    "    openai.api_key = openai_api_key\n",
+    "    messages = create_prompt(prompt, history)\n",
+    "    response = openai.chat.completions.create(\n",
+    "        model=OPENAI_MODEL,\n",
+    "        messages=messages,\n",
+    "        stream=True\n",
+    "    )\n",
+    "    sent_any = False\n",
+    "    for chunk in response:\n",
+    "        delta = chunk.choices[0].delta\n",
+    "        if delta and delta.content:\n",
+    "            sent_any = True\n",
+    "            yield delta.content\n",
+    "    if not sent_any:\n",
+    "        yield \"(no response)\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "535f7e3d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def gemini_agent(prompt, history):\n",
+    "    genai.configure(api_key=google_api_key)\n",
+    "\n",
+    "    # reuse OpenAI-style messages\n",
+    "    messages = create_prompt(prompt, history)\n",
+    "\n",
+    "    gemini_history = []\n",
+    "    for m in messages:\n",
+    "        # Gemini does NOT support system role\n",
+    "        if m[\"role\"] == \"system\":\n",
+    "            continue\n",
+    "        gemini_history.append({\n",
+    "            \"role\": m[\"role\"],\n",
+    "            \"parts\": [m[\"content\"]]\n",
+    "        })\n",
+    "    prompt_with_system = f\"{system_msg}\\n\\n{prompt}\"\n",
+    "    model = genai.GenerativeModel(GOOGLE_MODEL)\n",
+    "    chat = model.start_chat(history=gemini_history)\n",
+    "\n",
+    "    response = chat.send_message(prompt_with_system, stream=True)\n",
+    "    for chunk in response:\n",
+    "        if chunk and getattr(chunk, \"text\", None):\n",
+    "            yield chunk.text\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "21f61ff0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chat_agent(prompt, history, modelType):\n",
+    "    if modelType == \"OpenAI\":\n",
+    "        for token in openai_agent(prompt, history):\n",
+    "            yield token\n",
+    "    else:\n",
+    "        for token in gemini_agent(prompt, history):\n",
+    "            yield token\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "56686c1d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chat_fn(prompt, history, model):\n",
+    "    assistant_response = \"\"\n",
+    "    for token in chat_agent(prompt, history, model):\n",
+    "        assistant_response += token\n",
+    "        yield assistant_response \n",
+    "\n",
+    "# -------------------------------------------------------------------\n",
+    "# UI\n",
+    "# -------------------------------------------------------------------\n",
+    "with gr.Blocks() as demo:\n",
+    "    model_choice = gr.Radio([\"OpenAI\", \"Gemini\"], value=\"OpenAI\", label=\"Model\")\n",
+    "\n",
+    "    chat_ui = gr.ChatInterface(\n",
+    "        fn=chat_fn,\n",
+    "        additional_inputs=[model_choice],\n",
+    "        title=\"CodeCopilot\",\n",
+    "        description=\"An adaptive AI coding assistant that helps developers build and ship high-quality code.\"\n",
+    "    )\n",
+    "\n",
+    "demo.launch()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llms",
+   "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": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/week2/community-contributions/weather_agent.ipynb b/week2/community-contributions/weather_agent.ipynb
new file mode 100644
index 0000000..f89978a
--- /dev/null
+++ b/week2/community-contributions/weather_agent.ipynb
@@ -0,0 +1,370 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "60761989",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import requests\n",
+    "from  openai import OpenAI\n",
+    "import gradio as gr\n",
+    "import speech_recognition as sr\n",
+    "import json\n",
+    "from dotenv import load_dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e0b6610a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "OpenAI API Key exists and begins sk-proj-\n",
+      "weather API Key exists\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Initialization\n",
+    "\n",
+    "load_dotenv(override=True)\n",
+    "\n",
+    "openai_api_key = os.getenv('OPENAI_API_KEY')\n",
+    "weather_api_key = os.getenv('WEATHER_API_KEY')\n",
+    "if openai_api_key:\n",
+    "    print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
+    "else:\n",
+    "    print(\"OpenAI API Key not set\")\n",
+    "if weather_api_key:\n",
+    "    print(\"weather API Key exists\")\n",
+    "else:\n",
+    "    print(\"weather API Key not set\")\n",
+    "    \n",
+    "MODEL = \"gpt-4o-mini\"\n",
+    "openai = OpenAI()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "af9d2faf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "system_message = \"You are a helpful assistant for weather. \"\n",
+    "system_message += \"You need to fetch the current, historical and forecast the weather data using weather api and provide the response\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2c5208d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fetch_current_weather(location):\n",
+    "    url = f\"http://api.weatherapi.com/v1/current.json?key={weather_api_key}&q={location}&aqi=yes\"\n",
+    "    return requests.get(url).json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "8e6a12e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fetch_forecast_weather(location, days=3):\n",
+    "    url = f\"http://api.weatherapi.com/v1/forecast.json?key={weather_api_key}&q={location}&days={days}&aqi=yes&alerts=yes\"\n",
+    "    return requests.get(url).json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "eafc468e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fetch_historical_weather(location, date):\n",
+    "    url = f\"http://api.weatherapi.com/v1/history.json?key={weather_api_key}&q={location}&dt={date}&aqi=yes\"\n",
+    "    return requests.get(url).json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2851ed55",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Weather function used as a tool by OpenAI\n",
+    "def get_weatherapi_data(location, mode=\"current\", date=None, forecast_days=3):\n",
+    "    if mode == \"current\":\n",
+    "        return fetch_current_weather(location)\n",
+    "    elif mode == \"forecast\":\n",
+    "        return fetch_forecast_weather(location, days=forecast_days)\n",
+    "    elif mode == \"historical\":\n",
+    "        if not date:\n",
+    "            # Default: yesterday\n",
+    "            date = (datetime.date.today() - datetime.timedelta(days=1)).strftime(\"%Y-%m-%d\")\n",
+    "        return fetch_historical_weather(location, date)\n",
+    "    else:\n",
+    "        return {\"error\": \"Unknown mode.\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "368176c2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Tool schema for OpenAI tool-calling\n",
+    "weatherapi_tool_schema = [\n",
+    "  {\n",
+    "    \"type\": \"function\",\n",
+    "    \"function\": {\n",
+    "      \"name\": \"get_weatherapi_data\",\n",
+    "      \"description\": \"Fetches current, forecast, or historical weather data from WeatherAPI.com for a given location.\",\n",
+    "      \"parameters\": {\n",
+    "        \"type\": \"object\",\n",
+    "        \"properties\": {\n",
+    "          \"location\": {\n",
+    "            \"type\": \"string\",\n",
+    "            \"description\": \"Name of the city, region, or coordinates.\"\n",
+    "          },\n",
+    "          \"mode\": {\n",
+    "            \"type\": \"string\",\n",
+    "            \"enum\": [\"current\", \"forecast\", \"historical\"],\n",
+    "            \"description\": \"Type of weather data required.\"\n",
+    "          },\n",
+    "          \"date\": {\n",
+    "            \"type\": \"string\",\n",
+    "            \"description\": \"Date for historical data in YYYY-MM-DD format. Only needed if mode is 'historical'.\"\n",
+    "          },\n",
+    "          \"forecast_days\": {\n",
+    "            \"type\": \"integer\",\n",
+    "            \"description\": \"Number of forecast days (1-10). Only needed if mode is 'forecast'.\"\n",
+    "          }\n",
+    "        },\n",
+    "        \"required\": [\"location\", \"mode\"]\n",
+    "      }\n",
+    "    }\n",
+    "  }\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "bd9c4d38",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def audio_to_text(audio_filepath):\n",
+    "    if audio_filepath is None or audio_filepath == \"\":\n",
+    "        return \"\"\n",
+    "    recognizer = sr.Recognizer()\n",
+    "    try:\n",
+    "        with sr.AudioFile(audio_filepath) as source:\n",
+    "            audio = recognizer.record(source)\n",
+    "        try:\n",
+    "            transcript = recognizer.recognize_google(audio)\n",
+    "            return transcript\n",
+    "        except sr.UnknownValueError:\n",
+    "            return \"\"\n",
+    "        except sr.RequestError as e:\n",
+    "            return f\"Speech recognition service error: {e}\"\n",
+    "    except Exception as e:\n",
+    "        return f\"Error opening audio file: {str(e)}\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "61c5de82",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def chat_agent(city, mode, date, forecast_days, audio=None):\n",
+    "    user_query = city\n",
+    "    if audio:\n",
+    "        spoken_text = audio_to_text(audio)\n",
+    "    print(\"Recognized speech:\", spoken_text)\n",
+    "    if spoken_text and spoken_text.strip().lower() != \"flic en flac\":\n",
+    "        user_query = spoken_text\n",
+    "    else:\n",
+    "        if not city.strip():\n",
+    "            return \"Sorry, I could not recognize your speech. Please try again or type your city.\"\n",
+    "\n",
+    "    if not user_query.strip():\n",
+    "        return \"Please provide a location by text or speech.\"\n",
+    "\n",
+    "    # Compose tool function arguments as the LLM would\n",
+    "    args = {\n",
+    "        \"location\": user_query,\n",
+    "        \"mode\": mode\n",
+    "    }\n",
+    "    if mode == \"historical\" and date:\n",
+    "        args[\"date\"] = date\n",
+    "    if mode == \"forecast\":\n",
+    "        try:\n",
+    "            n_days = int(forecast_days)\n",
+    "        except:\n",
+    "            n_days = 3\n",
+    "        args[\"forecast_days\"] = n_days\n",
+    "\n",
+    "    openai.api_key = openai_api_key\n",
+    "\n",
+    "    # LLM call for tool use\n",
+    "    response = openai.chat.completions.create(\n",
+    "        model=\"gpt-4-0613\",\n",
+    "        messages=[{\"role\": \"user\", \"content\": f\"Get me {mode} weather for {user_query}\"+(f' on {date}' if date and mode==\"historical\" else \"\")+(f' for {forecast_days} days' if forecast_days and mode==\"forecast\" else \"\")}],\n",
+    "        tools=weatherapi_tool_schema,\n",
+    "        tool_choice={\"type\": \"function\", \"function\": {\"name\": \"get_weatherapi_data\", \"arguments\": json.dumps(args)}}\n",
+    "    )\n",
+    "    message = response.choices[0].message\n",
+    "\n",
+    "    if hasattr(message, \"tool_calls\") and message.tool_calls:\n",
+    "        tool_call = message.tool_calls[0]\n",
+    "        args2 = json.loads(tool_call.function.arguments)  # not really needed, already have args\n",
+    "        location = args2.get(\"location\", user_query)\n",
+    "        mode = args2.get(\"mode\", mode)\n",
+    "        date = args2.get(\"date\", date)\n",
+    "        forecast_days = args2.get(\"forecast_days\", forecast_days)\n",
+    "        weather_data = get_weatherapi_data(location, mode, date, forecast_days)\n",
+    "        tool_result = f\"Weather data (mode={mode}) for {location}:\\n{json.dumps(weather_data, indent=2)[:3000]}\"\n",
+    "        followup = openai.chat.completions.create(\n",
+    "            model=\"gpt-4-0613\",\n",
+    "            messages=[\n",
+    "                {\"role\": \"user\", \"content\": f\"Get me {mode} weather for {location}\"},\n",
+    "                message,\n",
+    "                {\n",
+    "                    \"role\": \"tool\",\n",
+    "                    \"tool_call_id\": tool_call.id,\n",
+    "                    \"content\": tool_result\n",
+    "                }\n",
+    "            ]\n",
+    "        )\n",
+    "        answer = followup.choices[0].message.content.strip()\n",
+    "        return answer\n",
+    "    else:\n",
+    "        return getattr(message, \"content\", \"\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "44071389",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def update_date_visibility(mode):\n",
+    "    return gr.update(visible=(mode==\"historical\"))\n",
+    "\n",
+    "def update_days_visibility(mode):\n",
+    "    return gr.update(visible=(mode==\"forecast\"))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "618a5494",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "* Running on local URL:  http://127.0.0.1:7861\n",
+      "* To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7861/\" 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": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recognized speech: Error opening audio file: FLAC conversion utility not available - consider installing the FLAC command line application by running `apt-get install flac` or your operating system's equivalent\n"
+     ]
+    }
+   ],
+   "source": [
+    "with gr.Blocks() as demo:\n",
+    "    gr.Markdown(\"## Weather Chat Agent (Current, Historical, Forecast)\")\n",
+    "\n",
+    "    with gr.Row():\n",
+    "        city_input = gr.Textbox(label=\"City/Location\")\n",
+    "        mode_input = gr.Dropdown(\n",
+    "            [\"current\", \"historical\", \"forecast\"],\n",
+    "            value=\"current\",\n",
+    "            label=\"Weather Mode\")\n",
+    "    with gr.Row():\n",
+    "        date_input = gr.Textbox(label=\"Date for historical (YYYY-MM-DD)\", visible=False)\n",
+    "        days_input = gr.Textbox(label=\"Forecast Days (for forecast)\", value=\"3\", visible=False)\n",
+    "    audio_input = gr.Audio(type=\"filepath\", format=\"wav\", label=\"Or Speak your City/Location (optional)\")\n",
+    "    output_box = gr.Textbox(label=\"Weather Info\", lines=8)\n",
+    "    btn = gr.Button(\"Get Weather\")\n",
+    "\n",
+    "    # Show/hide date and days inputs based on dropdown\n",
+    "    mode_input.change(update_date_visibility, mode_input, date_input)\n",
+    "    mode_input.change(update_days_visibility, mode_input, days_input)\n",
+    "    btn.click(\n",
+    "        chat_agent,\n",
+    "        [city_input, mode_input, date_input, days_input, audio_input],\n",
+    "        output_box\n",
+    "    )\n",
+    "\n",
+    "demo.launch()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "llms",
+   "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": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}