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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dlkGfzwyvtj7"
+      },
+      "source": [
+        "#Getting Started with Google A2A (Agent-to-Agent) Communication\n",
+        "\n",
+        "\n",
+        "### Google's Agent-to-Agent (A2A) protocol, a standardized way for AI agents to communicate and collaborate.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "QoMd2ejqx-WH"
+      },
+      "source": [
+        "## What You'll Build\n",
+        "#### we are going to build three blockchain agnet\n",
+        "\n",
+        "\n",
+        "1. blockchain Learning Agent  -This is blokcchain learning agnet its goal to geach blockcahin concept in easy langguage\n",
+        "2. blockchain search Agent  -  this agnet will search new company lunch on blockchain ( eg SUI blockchain so new company lunch on sui blockchain like that )\n",
+        "3. Host Agent - Orchestrates the other agents to provide comprehensive insights"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1AE0hiFyyBAD"
+      },
+      "source": [
+        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+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "AKt_t8V-yeUy"
+      },
+      "source": [
+        "### **Prerequisites**\n",
+        "*   Python 3.11+\n",
+        "*   Google Cloud Project with Vertex AI enabled\n",
+        "*   Basic understanding of  Python\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "z8LtG5sj2eOX"
+      },
+      "source": [
+        "### Setup and Installation\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "-231fRkG2jF_"
+      },
+      "outputs": [],
+      "source": [
+        "%pip install --upgrade -q google-genai google-adk==1.9.0 a2a-sdk==0.3.0 python-dotenv aiohttp uvicorn requests mermaid-python nest-asyncio\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "wGowE-nY2tHd"
+      },
+      "source": [
+        "### 1. Introduction to A2A\n",
+        "\n",
+        "## What is Agent-to-Agent (A2A) Communication?\n",
+        "\n",
+        "A2A is a standardized protocol that enables AI agents to:\n",
+        "\n",
+        "\n",
+        "\n",
+        "*   **Discover** each other's capabilities\n",
+        "*   **Communicate** using a common JSON-RPC based protocol\n",
+        "*   **Collaborate** to solve complex tasks\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "E7gvaknx3QxE"
+      },
+      "outputs": [],
+      "source": [
+        "## Environment Configuration\n",
+        "\n",
+        "import sys\n",
+        "\n",
+        "from a2a.client import client as real_client_module\n",
+        "from a2a.client.card_resolver import A2ACardResolver\n",
+        "\n",
+        "\n",
+        "class PatchedClientModule:\n",
+        "    def __init__(self, real_module) -> None:\n",
+        "        for attr in dir(real_module):\n",
+        "            if not attr.startswith('_'):\n",
+        "                setattr(self, attr, getattr(real_module, attr))\n",
+        "        self.A2ACardResolver = A2ACardResolver\n",
+        "\n",
+        "\n",
+        "patched_module = PatchedClientModule(real_client_module)\n",
+        "sys.modules['a2a.client.client'] = patched_module  # type: ignore"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "54GueHkb76rz"
+      },
+      "source": [
+        "### AI Agent we use Google LLM or we can Model so we need to set there API key."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tgrxoYx18Ug_"
+      },
+      "outputs": [],
+      "source": [
+        "from google.colab import userdata\n",
+        "import os\n",
+        "\n",
+        "# Set the API key as an environment variable\n",
+        "os.environ[\"GOOGLE_API_KEY\"] = \"AIzaSyBzn0GasdfjsbfkbqQOKvvaYFNKUCMlcil7Ln8\" # use your aown api key this one is rovoked"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "DtyMABy18dWr"
+      },
+      "source": [
+        "# Agent 1: Blockcahin learnig Agent\n",
+        "\n",
+        "\n",
+        "This agent will anser complex blockcahin releted question in easy language.\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dujKj6rw9Bwk"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "rA9qEk-O80hq"
+      },
+      "outputs": [],
+      "source": [
+        "from google.adk.agents import Agent\n",
+        "\n",
+        "\n",
+        "blochchain_learning = Agent(\n",
+        "    model = \"gemini-2.5-flash\",\n",
+        "    name = \"blochchain_learning\",\n",
+        "    instruction=\"this agent will answer  question reatled  to blockchain and web 3.0 . \"\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "tkLhMoa69hXG"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "pH4HMT5r-aZt"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "cbf0Uxcw-vNO"
+      },
+      "outputs": [],
+      "source": [
+        "# ab hum create karne walel hai agentcard is blockc learing agnet ke liyue\n",
+        "#agnetCart\n",
+        "\n",
+        "from a2a.types import AgentCard\n",
+        "from a2a.types import TransportProtocol\n",
+        "from a2a.types import AgentSkill\n",
+        "\n",
+        "#visitng card\n",
+        "blochchain_learning_card = AgentCard(\n",
+        "    name=\"blochchain_learning\",\n",
+        "    url=\"http://localhost:8001\",\n",
+        "    description=\"this agent will answer  question reatled  to blockchain and web 3.0 . \",\n",
+        "    capabilities={\"streaming\": True},\n",
+        "    default_input_modes=['text'],\n",
+        "    default_output_modes=['text'],\n",
+        "    preferred_transport=TransportProtocol.jsonrpc,\n",
+        "    version='1.0.0',\n",
+        "   skills = [\n",
+        "        AgentSkill(\n",
+        "            id = 'blckcahin_agent',\n",
+        "            name=\"blckcahin_search\",\n",
+        "            description=\"this agnet till find rectnt web 3 company usiong web search \",\n",
+        "            tags = ['web_search', 'treading_blockchain', 'search_expert'],\n",
+        "            examples=[\n",
+        "                \"give me top sui based company using web search \",\n",
+        "                \"give me top solalana based company using web search \",\n",
+        "                \"give me top xrp based company using web search\",\n",
+        "            ]\n",
+        "\n",
+        "        )\n",
+        "    ]\n",
+        "\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "UIshkmU5BZ6O"
+      },
+      "source": [
+        "### Now we create the\n",
+        "\n",
+        "*   blockcahin learnig Agent\n",
+        "*   It's Agent Card :- Agent skill overview\n",
+        "*   Agent Skill :- more indepth skill\n",
+        "\n",
+        "\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "oN77l4VABvOL"
+      },
+      "source": [
+        "## similar we create the Agent2 which is Blockchain_search_Agent"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "5u_qae_eClmD"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "qUmkR0PvCEti"
+      },
+      "outputs": [],
+      "source": [
+        "from google.adk.agents import Agent\n",
+        "from google.adk.tools import  google_search\n",
+        "\n",
+        "\n",
+        "blckcahin_search = Agent(\n",
+        "    model = \"gemini-2.5-flash\",\n",
+        "    name = \"blckcahin_search\",\n",
+        "    instruction=\"this agnet till find rectnt web 3 company usiong web search.\",\n",
+        "    tools=[google_search]\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "z94RXV2pCotY"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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a9kgE0jDzNgSNW+XPGSTnj6c8xo2nw6V8erG1bWr3V9Q/sqVrmW6kDFCWG1QAAEGOdo9c969C1vwRoOtQael/ayNJYII7a4jneOaNQMY3qQx/Emq8Xw68LRLYbNLAlsZjPDMJ5BL5hxlmcNufOB94kcU1UglYTpybuY3hDj40fEAHqYbAj3/AHRqpot34g8e3OuTL4gbQ9Hsr+WwW3sYU89hHjLvK+dhOewrsdQ8HaJf+JLbX5rRl1aDbtnjldNwU5AYA4YfUVQ1T4c+GdT1O5v7iwkSe6ObkQXMkSXH++isFb34570lUjuHJLY5X4DC0TSfGCadcPc2i61cCKeR97SrsTDlu5PXPetT9nuNU+EWhlRguZ2b3PnyD+grqNM8I6FpWs3Oqabp6Wt5cxCGUxOyoy8ceWDsH3RyBmrvh/RbDw9pFvpej2/2exg3eXFvZ9u5ix5Yknkk9aKlVSTt1sOFNq1zzjwPqR0az+KOpCIy/YtWvLkRg43FYw2PxxVHUbbVte+Gk/iPxX4tlh0+4sDdiw06NLeIbkysTPy75JAIzyeK9S03QNM006kbO1VP7Rma4ugzM4ldhhiQxIGR2HHtWDp/w08K6fexXFtpzbYnMsVvJcSSQRuf4ljZioP4cdqaqx3E6crWF+D5B+GPhvByPsaVzPxrvrTTfEfw/vNRZVtYdULSO3RBhfmPsDz+Fd94Z8NaT4YtJbXQ7U2tvLIZWjEruoY+gYnaPYYFO1zw7pOuzWcmr2aXTWjM8Idm2gsu1sqDhgRxg5FQpxVRy6FuDcOU534zajZWvwv1x7qWMpc2xhgGQfMd+E2+vPPHYZrH1HVtc0fTfh/4V02aCx1PVLUQzXtzH5gg8mFCwC5ALEnAz/Xja034W+ENO1KG9g0nfNA2+BZp5JEhOc/KjMQOeenFb3ifw1pPiezjttbtBcJE4kiYOyPGw7qykEH6GqU4KyJcJPU8p8R6V/ZPxS8CDUfEV9rGrzXUjutwyKkUezAKxqAEyfzx7V2Ou+HbHXPFl1e+HPEc2keJ7SJIbs2pWQFCMoJYm4b2/wD1VcPw08KPYPaXGmtcB5luGmluJWnZ1BCnzd2/gEjGcVP4g8AeHdeu47u+snW9RBF9ognkikZAMAMykFug65purF21EqbV9DA8Oaxrmqf8Jp4V1W4tr7U9MhEcV9bJ5Ym82JioZeisCOcf0yea+EWg6rqvgLTZNM8a6hYpEGiks4reE/Z3DHKnK5z359a9W8L+GtI8L6ebPQ7NLaFm3uQSzSN6sxySfqaxtY+GvhfVNQnvprCSC6uDmaS1uJIPNPcsEYAk+uMmhVY6pA6UtGzzrxb4fgtPgz40XRtZk1uSbUPtV5NtUHzVkjMowvHG3ca9eg13Sf8AhFk1pbmFdI+zCbzdw2qmOn17Y9eKsaVounaTo8elafZww6ciGMQBcqVPUHPXOTnPXPNczZfCzwdZ3wuoNGTIfzVieaR4Vf1EZYr+lJ1Iy+IapuOxkfs5sj/DC1aNdqG5nKr6DzDxT/jp+40jw3qFwCdOsNctbi84yBECQSfbJA/Gu50DRNP8P6f9h0i3+z2u9pNm9n+ZjljliT1q3e2lvfWk1rewxz20ylJIpFDK6nqCDU+0XtOcrkfJylPWNd0zSNEk1e/vIo9OjQSGYHcGB6bcfezxjHWuC1qeO2+Ovhq9ujttL7SJba1dxtHnbyxHPQlSBj3ArZsPhb4Psb6G6g0nLQP5kUctxLJFG3qEZiv6V0XiLw/pXiSw+xa3ZRXduG3qr5BVvVWGCp9waalCL0E4yktTh/j5Is3hjTNMgO7U77U7dLRB97cGyWA9AO/uKl8ToG+N/gokZK2d4R7HZj+tbvh/4f8AhvQdRW/sNPJvlBVJ7ieSd0B7KXY7eOOK2bnRNPutbstXnt92o2aPHBNvYbFcYYYBwc+4oVSKVl5hyN6s4j4hosnxQ+GwcAgT3p/ERKR+op/xU/5GT4f/APYZX/0A12moaJp+oappuo3lv5l5pzO1rJvYeWXG1uAcHIHcGjVdE0/VrnT7jULfzZbCYXFs29l8uTGM8EZ+hyKSqJW8hum9Tzvxbf2lh8efCLXzpGJrCaGN34AkYkKM+/T8an/aCljl8GW2lRsp1PUb63is4wcuX3g5A9AOM+49aPF2iW+t/F/RrfU7EXemvpE6Sh0JTO/I57HuO9dFofw88M6Jq41Sy04nUF4Se4nknaMYx8u9jj69a05orlbM1GTujL8U61rd78QLTwloV/BpIbTzqE17JAJpGHmbAkat8ueMknPH055jRtPh0r49WNq2tXur6h/ZUrXMt1IGKEsNqgAAIMc7ffPevSPE/hDRfEsttNqtqzXNtnyLiGV4ZY89cMhBx7VRi+HXhaJbDZpYEtjKZ4ZhNIJfMOMszhtz5wPvEjikqsUhunJsxPCcan42+O5CPnW2sVB9jHz/ACFO1rj47eHMd9JuAf8Avqu1tNE0+z1q/wBWt7fZqF+sa3Eu9jvCDC8E4GB6AUT6Jp8+u22sy2+7UraJoIpt7DajdRtzg/iM1PtFe/kV7N2t5nAeI7uHwP8AFOLXLl/J0fXrNoLx/wCFLiBdyMfcplR+Nanwdspj4cuNev026hr9y+oyA9Ujb/VJ9AmCP96uW8d61pXxSh07wx4cS4vt97HNeXRt5I0s4kzuO5wPmIOAB1ya9igijghjhhRUijUIirwFAGABTm7QSe4oK8m1scf8ZUZ/hf4jCDJ+yk/gCCf5VJearZ2vwpbUHuIvsv8AZIKvuGGJiwAPUk4AHrXWXEMVzBJBcRpLDIpR0cZVlIwQQeorjdN+F/hLTr1bm10xgULNHE9xI8UbHqyoWIB5OD27YqYSjy2ZUoyvdHOeE7XQtQ+Bnh/T/E9wlvZXkaQo7SeWwlMhKbW7NkZ/A54zTtYn8S/DyfR5rjxH/bukXN7FYm1vYFW4UPwGWReXI9xXdHwnobeGE8PSadFJo0a7FtpCzhRnIwxO7Oe+c1laJ8NfDGj6rBqNtYyS3duMQPc3Ek3k/wC6HYgH37VaqR1bI9nLSxlXf/JwNj/2Lz/+j6b4TjU/G3x3IR8621ioPsY+f5Cu3fRNPfxAmuNb51RLc2izb24iLbtu3O3rznGaLTRNPs9av9Wt7fZqF+sa3Eu9jvCDC8E4GB6AVPtFa3kUqbvfzOK1rj47eHMd9JuM/wDfVYr3mr2PxR8VQ+Cv7NmaRbeTUINTcxKkxj+UxFTuYFcFsjGeh5r0+fRNPn1221mW33albRNBFNvYbUbqNucH8RmvD9vhZdV1ef4w2V7/AG0bt0huJ4JzA1vn92IjENuBz15561pTakvkZ1E0eq/D/wAN3miRane61cQXGs6rc/arprcERIcYVEzzgDueeak+KGknW/h9r1io3SPatJGB3dPnX/x5RXF/Cizgj8a6rdeE7TULPwY9miqlyJFjlut+d8Syc7duQff8K9cIyMHpWU24zuaQSlCx4vonlfFLU7yeVg9tb+HY7LJ5CXVyu92HuoVRUXgDVJPFvibwXDc58/w/pc8l2p5IuN32cBv9rCM3416n4V8L6N4UsprTw/ZLZ280pmdQ7PliAM5Yk9AOOlGieFtG0PVNT1HSrFbe81J/MupA7N5jZJzgkheWJ4xWjrR1S+RKpPS55bpekahc/F7xvaQeJLrRLuY29zGsUUbm5i2EAjeD93px610+heGo7H4iQXWp+LbjVdbhsXC2s0UaMIGYDJ2gcbvWul8T+DtC8TvDJrNgs1xACIp0dopUHoHUg49ulL4W8I6L4X+0NpFqyTXJBmnlkaWSTHQFmJOB6dKTrJoFSaZw/wAHtQsh40+IWnb0XUDrEs+wnDPHuI49cEHPpuHrVm/lj1D4/wCkpYsskmnaVKb1kOdgZsKh98kHHvW/qXw38K6j9oa40zE0909606TyLIJmxuZWDZUHA4HHHStLwr4S0TwpbyxaDYJaiY7pX3M7yH/aZiSep79zSdSO63sNQlszU1SW0h027k1Jo0sViYztL90Jg7s+2M15Zc6JqfhDwpcaz4H8XFtBtrdryHT7+NbiFkA3bUlyGUHsPU/jXrM0Uc8LxTIskUilXRxkMDwQR3FcN/wqXwd9oV/7MkMKyeaLU3Mpg3df9Xu24z26VNOcY7lVIt7HH/Ei8m11fhjr32uTRrW5lLPcgK32aSaNCh+YY7MMn61qeMfBc82iGHxR8Qb/APs2aWNMS28Khn3jYAQM5yB0/lmvStV0jT9W0uTTdRs4LixdQpgdflwOmB2x2x0rm9I+GnhbStTt761sJXmtjut1nuZZkhPqquxAPv2q1WVu1iHSdyh4i1jXdT+IS+FND1GDSI4rAX0920AmlfL7dqK3ygdMkg1zfhewg0v4+SWq6xeateDQ2N1Pdyh2WQyqQgAACgLtO0etei+JvB2ieJLm3udUtXN5bgrDcwTPDKgPYMhBxyeD61Ut/h74Xt5NNkh0tUn06QywTLNIsm8kMWZg2XyQPvZoVWKVgdOTdzC8CRr/AMLe+JMhA3g6eoPoDC2f5CovGEsenfGnwffaiyx2U1pcWkMrnCpOe2exYEAetd5YaJp9hq2panaW/l32pGM3Um9j5nlqVTgnAwCegHvSeINC0zxDpr2GtWUV5aMQ3lyDoR3BHIPuOan2i5r+RXs3y2F1fXNO0iewh1C5WKa+nW2t0wWaRz0AA5x6noO9cRoEan47+KZCBvXTLZQfQE8/yFbvh34feGvD2oi/07Tz9tVdiTTzSTNGvou9jt444rat9E0+31y71iG326ldRpDNNvY7kX7o25wMewpKUY3SHyydmzivFHHxs8E472d6D/3wK9GrOutE0+61uy1ee336jZI8cEu9hsVxhhgHBz7g1o1EpXS8ioxs2FQ2l1b3kImtJ4p4iSN8ThlyOvIovZhb2c8xilmEcbOYol3O+BnCjuT2Fcl8KPDbeGvDU0L2osjeXct4LMOX+zK+Ase4k5IVVz75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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "8NltTkSuCqjd"
+      },
+      "outputs": [],
+      "source": [
+        "blckcahin_search_card = AgentCard(\n",
+        "    name=\"blckcahin_search\",\n",
+        "    url=\"http://localhost:8002\",\n",
+        "    description=\"this agnet till find rectnt web 3 company usiong web search \",\n",
+        "    capabilities={\"streaming\": True},\n",
+        "    default_input_modes=['text'],\n",
+        "    default_output_modes=['text'],\n",
+        "    preferred_transport=TransportProtocol.jsonrpc,\n",
+        "    version='1.0.0',\n",
+        "    skills = [\n",
+        "        AgentSkill(\n",
+        "            id = 'blckcahin_agent',\n",
+        "            name=\"blckcahin_search\",\n",
+        "            description=\"this agnet till find rectnt web 3 company usiong web search \",\n",
+        "            tags = ['web_search', 'treading_blockchain', 'search_expert'],\n",
+        "            examples=[\n",
+        "                \"give me top sui based company using web search \",\n",
+        "                \"give me top solalana based company using web search \",\n",
+        "                \"give me top xrp based company using web search\",\n",
+        "            ]\n",
+        "        )\n",
+        "    ]\n",
+        "\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "I_2HNczHD4C2"
+      },
+      "source": [
+        "### Now I Create HOST AGENT\n",
+        "\n",
+        "The Host Agent coordinates between the other two agents  :-\n",
+        "*   Blockchain Learnig Agent\n",
+        "*   Blockcahin Search Agent\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Sxa9vb89GPYR"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "5Lt1gUZgETl3"
+      },
+      "source": [
+        "### By How Host Agent Communicate with other two Agent .\n",
+        "\n",
+        "\n",
+        "## Using Remote A2A"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mhbWT7jSGd5_"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "D4mVgNUAGf3u"
+      },
+      "source": [
+        "# for this we need to make Remote A2A for each Agent So ."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "DEi71LezHD4P"
+      },
+      "outputs": [],
+      "source": [
+        "from google.adk.agents.remote_a2a_agent import RemoteA2aAgent\n",
+        "\n",
+        "\n",
+        "from a2a.utils.constants import AGENT_CARD_WELL_KNOWN_PATH\n",
+        "from google.adk.agents import SequentialAgent\n",
+        "\n",
+        "blochchain_learning_remote = RemoteA2aAgent(\n",
+        "    name=\"blochchain_learning\",\n",
+        "    description=\"this agent will answer  question reatled  to blockchain and web 3.0\",\n",
+        "    agent_card=f'http://localhost:8001{AGENT_CARD_WELL_KNOWN_PATH}'\n",
+        ")\n",
+        "\n",
+        "\n",
+        "\n",
+        "blckcahin_search_remote = RemoteA2aAgent(\n",
+        "    name=\"blckcahin_search\",\n",
+        "    description=\"this agnet till find rectnt web 3 company usiong web search\",\n",
+        "    agent_card=f'http://localhost:8002{AGENT_CARD_WELL_KNOWN_PATH}'\n",
+        ")\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "t5gDVQyLGzLg"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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HgWXxM3irTPsAvFthB/pEUu/Z5u77jNjG5euOtAHtmp+I9E0q5FvqmsabZTlQ3lXF0kbYPQ4Yg44NX7S5gvLaO4s54ri3kG5JYnDKw9QRwRXy/8AtK/Crxn4z+Ikep+GtG+22IsYoTL9qhj+cM5Iw7g9x2r3n4TaRfaD8NvDulatB9nv7S0WKaLer7GHUZUkH8DQBpW3izw5dXMdva6/pE1xIwRIo7yNmZj2ADZJrQ1LUbLS7b7Rqd5bWdvkL5txKsa5PQZYgZr43+GnwT+IOi/Enw/qupeH/JsLXUIp5pfttu21A2ScLISePQV9A/tIeFdZ8Y/Dd9K8OWf2y/N3FKIvNSP5Vzk5cgd/WgD0HStb0rWDKNJ1OxvjFjzPstwkuzOcZ2k4zg/lUep+I9E0q5+z6prOm2VwVD+XcXSRtg9DhiDjg14n+yp8PfFHgWXxMfFWmfYBeLbCD/SIpd+zzd33GbGNy9cda5n9pX4VeM/GfxFj1Pw1o322xFjFCZftUMfzhnJGHcHuO1AH1DaXMF5bR3FnPFPbyDcksTh1ceoI4IrKtfFnh27uY7a11/SJriRgiRR3kbMzHsAGyTWb8JtIvtB+G/h3StWg+z39paJFNFvV9jDqMqSD+Br5Z+GnwT+IOi/Enw/qup+H/JsLW/jnml+227bUDZJwshJ49BQB9kalqNlpdt9o1O8trO3yF824lWNcnoMkgZqHStb0rWDKNJ1OxvvKx5n2W4SXZnOM7ScZwfyrgf2ivCWseNfh02k+HrdLi+N3FLseRYxtXdk5YgdxXJfst/DjxL4Ak8SnxPZxWwvRbCDZOkm7Z5u77pOPvLQB7PqfiPRNKuRb6nrOm2VwVDeVcXSRtg9DhiDjg1ftLmC8to7iznint5BuSWJwyuPUEcEV8y/tH/CPxf43+IUeq+HdPhuLIWUUJd7mOM7lZyRhiD3Fe6/CrRr3w98OvD+k6pGsV9Z2iRTIrBgrDqMjg0AaFr4s8O3dzHbWuv6RNcSMESKO8jZmY9gA2Sa0NS1Gx0u2+0aneW1nb5C+bcSrGuT0GWIGa+P/AIbfAvx5ofxG0DVtR0u3jsbS/jnmcXcTEIGyTgNk175+0V4S1fxr8Om0nw9bpcXxu4pdjyLGNq7snLEDvQB32k63pWsGX+ydTsb4xY8z7LcJLsznGdpOM4P5VHqfiPRNKuRb6nrOm2VwVDeVcXSRtg9DhiDjg14x+y38OPEvgCTxKfE9nFbC9FsINk6Sbtnm7vuk4++tc3+0f8I/GHjf4hJqvh2whuLIWUUJd7mOM7lZyRhiD3FAH01aXMF5bR3FnPFPbyDcksThlceoI4IrKtfFnh27uY7e11/SJ7iRgiRR3kbMzHsAGyTWf8K9HvfD/wAOvD+k6pGsV9Z2iRTIrBgrDqMjg18v/DX4FePND+IugatqWmQR2NpfRzzOLuJiqBsk4DZNAH2BqWo2Wl232jU7y2s7fIXzbiVY1yegySBmotK1vStY83+ydTsb7yseZ9luEl2ZzjO0nGcH8jXn/wC0V4R1jxr8OjpPh63S4vjdxS7HkWMbV3ZOWIHcVyn7Lfw48S+AH8SnxPZxWwvRbCDZOkm7Z5u77pOPvrQB7NqfiPRNKufs+p6xptlcbQ3lXF0kbYPQ4Yg44q/aXMF5bR3FpNFPbyLuSWJwysPUEcEV8y/tHfCPxh42+ISar4d0+G4shZRQl3uY4zuVnJGGIPcV7t8K9HvfD/w68P6TqkaxX1naJFMisGCsOoyODQBftfFnhy7uY7e11/SJ7iRgiRR3sbMxPYANkmtDUtRsdLtvtGp3ltZ2+Qvm3Eqxrk9BliBmvj/4afAvx5oXxF8P6tqWl28djaX0c8zi7iYqgbJOA2TXvf7RfhHWPGvw6Ok+HrdLi++1xS7HkWMbV3ZOWIHcUAegaVrelax5v9k6nY33lY8z7LcJLsznGdpOM4P5GotT8R6JpVz9n1PWdNs7jaG8q4ukjbB6HDEHFeM/st/DjxL4AfxKfE9nFbC9FsINk6Sbtnm7vuk4++vWuZ/aO+EfjDxt8Qk1Xw7p8NxZCyih3vcxxncrMSMMQe4oA+m7S5gvLaO4tJ4p7eQbklicMrj1BHBFZVr4s8OXdzHb2uv6RPcSMFSKO8jZmJ7ABsk1Q+Fmj3nh/wCHXh7SdUjWK+s7RIpkVgwVh1GRwa+Xvhn8C/HmhfEXw/q2paZBHY2l9HPM4u4mKoGyTgNk0AfYGpajZaXbfaNTvLazt8hfNuJVjXJ6DJIGai0nWtK1jzf7I1OxvvKx5n2WdJdmc4ztJxnB/I15/wDtF+EdY8a/Do6T4et0uL77XFNseRYxtXdk5YgdxXKfst/DjxJ4AbxMfE9nFbfbRbCDZOkm7Z5u77pOPvr19aAPZdS8R6JpVz9n1PWdNs7jaG8q4ukjbB6HDEHHFaFpcwXltHcWk8U9vINySxOGVx6gjgivmT9o34R+MPG3xDXVfDunw3FkLKKHe9zHGdyliRhiD3Fe7/CzR7zw/wDDrw/pOqRrFfWdokUyKwYKw6jI4NAF+18WeHLu5jt7XX9InuJGCpFHeRszE9gA2Sa0NS1Gx0u2+0aneW1nb5C+bcSrGuT0GWIGa+QPhn8C/HmhfEXw/q2paZbx2NpfRzTOLuJiFDZJwGya96/aL8I6x41+HZ0nw9bpcX32yKbY8ixjaobJyxA7igD0DSda0rWPN/snU7G+8rHmfZZ0l2ZzjO0nGcH8jUWp+I9E0q5+z6nrOm2dxtDeVcXSRtg9DhiDivGf2W/hx4k8AN4mPiezitvtwtvI2TpJu2ebu+6Tj769fWuZ/aN+EfjDxt8Q11Xw7p8NxZCyih3vcxxncpYkYYg9xQB9N2lzBeW0dxaTRT28g3JLE4ZWHqCOCKyrXxZ4cu7mO3tNf0ie4kYKkUd5GzOfQANkmqHws0e88P8Aw68PaTqkaxX1naJDMisGCsOoyODXy98MvgV480H4ieH9W1LTLeOxs72OaZxdxMVUNknAbJoA+wNS1Gx0u2+0aneW1nb5C+bcSrGuT0GSQM1FpOtaVrHm/wBkanY33lY8z7LOkuzOcZ2k4zg/ka8//aL8I6x41+Hf9k+HrdLi++2RTbHkWMbVDZOWIHcVyv7Lfw58SeAD4mPiezitvt32byNk6Sbtnm7vuk4++vX1oA9l1PxHoel3P2fU9Z02zuNobyri6SNsHocMQccVftLmC8to7i0mint5F3JLE4ZWHqCOCK+ZP2jfhH4w8bfENdV8O6fDcWQsood73McZ3KWJGGIPcV7v8LdHvPD/AMO/D2k6pGsV7Z2aQzIrBgrAcjI4NAF+18WeHLu5jt7TX9InuJG2pFFeRszH0ADZJrQ1LUbHS7b7Rqd5bWdvuC+bcSrGuT0GWIGa+QPhj8C/Hmg/ETw/q2p6Zbx2NnexzTOLuJiqg5JwGya95/aM8I6x42+Hf9k+HrdLi9+2RTbHkWMbVDZOWIHcUAeg6TrWlax5v9k6nY33lY8z7LOkuzOcZ2k4zg/kai1PxHoml3P2fU9Z02zuNobyri6SNsHocMQcV41+y18OfEngA+Jj4ns4rb7d9m8jZOkm7Z5u77pOPvr19a5j9o34ReMPG3xDXVfDunw3FkLOKHe9zHGdylsjDEHuKAPpu0uYLy2juLSaKe3kXcksThlceoI4IrKtfFnh27uY7e01/SJ7iRgqRRXkbM59AA2Sao/C3R7zw/8ADvw9pOqRrFfWdmkMyKwYKwHIyODXy98MPgX480H4ieHtW1PS7eOxs72OaZ1u4mKqDknAbJoA+v8AUtRsdLtvtGp3ltZ2+4L5txKsa5PQZYgZqLSda0rWPN/sjU7G+8rHmfZZ0l2ZzjO0nGcH8jXn37RnhHWPG3w7/snw9bpcX32yKbY8qxjaobJyxA7iuW/Zb+HPiTwAfE3/AAk9nFbfbvsvkbJ0k3bPN3fdJx99evrQB7LqXiPQ9Lufs+p6zptncbQ3lXF0kbYPQ4Yg4q/aXMF5bR3FpNFPbyruSWJwyuPUEcEV8x/tGfCLxh42+IY1bw9p8NxZfY4od73McZ3KWyMMQe4r3n4W6PeaB8O/D2k6pGsd7Z2aQzIrBgrAcjI4NAF618WeHLy5jt7TX9InuJG2pFFeRszn0ADZJrQ1LUbHS7b7Rqd5bWdvuC+bcSrGuT0GWIGa+P8A4YfArx5oHxE8Patqel28dlZ3sc0zrdxMVUHJOA2TXvX7RnhHWPG3w7/snw9bpcXv2yKbY8ixjaobJyxA7igD0HSda0rWPN/snU7G+8rHmfZZ0l2ZzjO0nGcH8jUWpeI9D0u5+z6nrOm2dxtDeVcXSRtg9DhiDivGv2Wvhz4k8Af8JN/wk9nFbfbvsvkbJ0k3bPN3fdJx99evrXL/ALRnwi8YeNviGNW8O6fDcWX2OKHe9zHGdylsjDEHuKAPpy1uYLy2juLSaKe3kUMksTBlYeoI4IrKtfFnh28uY7e01/SJ7iRtqRRXkbM59AA2Sao/C7R7zQPh34e0nU41jvrOzjhmRWDBWA5GRwa+Xfhf8CvHmgfEPw9q2p6Zbx2VneRzTOt3ExVQeTgNk0wPsDUtRsdLtvtGp3ltZ2+4L5txKsa5PQZYgZqLSda0rWPN/sjU7G+8rHmfZZ0l2ZzjO0nGcH8jXn37RnhDWPG3w8Gk+HrdLi9+2RTbHlWMbVDZOWIHcVy37LXw58SeAP8AhJ/+Ens4rb7d9l8jZOkm7Z5u77pOPvr19aBHsupeI9D0u5+z6nrOm2dxtDeVcXSRtg9DhiDir9pcwXltHcWk0U9vIu5JYnDK49QRwRXzH+0Z8IvGHjb4iDVvD2nw3Fj9jih3vcxxncpbIwxB7ivefhdpF5oHw78PaTqcax3tnZxwzIrBgrAcjI4NAF608WeHby5jt7TX9InuJW2pFFeRszn0ADZJq7rGr6boln9r1rULPT7XcE867nWJNx6DcxAzweK+Q/hd8C/HmgfETw9q2p6Zbx2V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+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "8Lamiq-9HWhD"
+      },
+      "source": [
+        "### Let's create Host Agent\n",
+        "\n",
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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gdKo0UUAFFFFAHufwS8beD/BHgnVtSu7bzPE6SbVRiN86N91Yzj5VGDu/PnKisXVfj944vLppLO7tNPhzlYobZHAHoS4Yn/PSuc+HHw117x7PIdKjjhsYW2y3lwSI1PXaMAlmx2H4kZr1kfAbwnoUQk8X+MhFjkgNFaj6DeWJoA6f4HeO7z4m6RrujeLba3ufKjVXkSPas0cm4FWA4BGOox19s18ueKNM/sbxLq2mc4sruW3BPUhHKg/pX2L8JdQ8CW8954f8A4k+zxie5uFViJDnAzI3LHntwO1fKPxW/5KZ4p/7CU//oZoA9V/ZV8I2l/faj4m1GNJRYMIbVXGQshGWfHqAVx9T6CsXxr8fPFGoazcf8I5dJpmlo5EAWBHkdQeGcuDgnrgYx05610/7JfiG0RdZ8N3ciJNcOLq3Vjjzfl2uo9wAp+mfSvMvGXwn8WeHdXnt49HvdQs958m5s4WmV0zwTtBKn2NAHtnwI+K2o+Nbq78PeJHH9oGBpILyBRGzAcMCBwGGQQQAOOnr89fEvRLrw5461nS766lu54Zt32iVtzyqwDqzE9yGGffNe1fs4/DfXNF8QS+JPENo+nW8Vu8cMVwNsjM2MsV6qAAeuOteRfGPXrfxL8Stb1KxkElo8qxQuOjrGipuHsdpI+tAHd/s1/D608Sahda/rkKT6bp7iOKGQZSWbGct2IUEHHckenM/wARfj7rc+sz2ng2aGw0uBzHHcCJZJJwON3zghVPYAZx+np/wDsoR8CoQ9ytol2t20lxkDyvndN5J44Cg8+lcP8A8KS8Cf8AQ+R/+BEH+NAGB4A+PviKx1m3i8Vzx6lpcrhJHMSRyQgn74KgZx1II59RV79qXwXaaVqFj4l0uJIotQcxXSRjCmXG5XGO7Ddn/dz3NaP/AApLwJ/0Pcf/AIEQf41s/tG6jo03wpsbCy1ayvri3uoAoiuEd22o6lsAntn86APLf2Z/+St6d/1wn/8ARZr2r4reJtH+GOs3mvW9kt/4q1pFSES8LBFGoXORyATzgcse4xXiv7M//JW9O/64T/8Aos1d/amuXm+KPluSVgsoUUegJZv5saAKrfHzx2bwTC9s1j/54C0TZ+f3v1r2nUrm2+L3wKu9QntEj1CKGWVVXnyriIE/KT0DAfk1fIFfVn7NZ3fBrWg3IF3cjHt5MdAHzZ4S8Sal4U1qPVdFlSK8jVkVnQOMMMHg8V9afATxlrPjHwbqmoa7PHNdQXbQoyRKgCiNGHA9ya+Mq+q/2Uf+Sc65/wBhB/8A0THQB5P/AML68e/9BG1/8BI/8K4HxRr1/wCJ9dudX1eRZb652+Y6oEB2qFHA46KKyqKACtvwTf6XpfirTr3X7M3ulwyFp7cRq5kXBGNrEA846msStbwpoV14m8Q2OjWDwx3V2+yNpiQgOCeSAT29KAPc/wDhZXwc/wChFn/8F1t/8co/4WV8HP8AoRZ//Bbbf/HKwv8Ahm7xf/0EdA/7/wA3/wAao/4Zu8X/APQR0D/v/N/8aoAu+IPiF8J7vQdSttN8GTW99NbSR28x0+3Xy5CpCtkSEjBIORXg1ewaz+z94q0nR77UrnUNDaCzgkuJFjmlLFUUsQMxgZwPWvH6ACut+FXiw+C/G+n6u6l7ZSYrlQOTE3DY9x1HuK5KigD65+I/w00f4sQWviXwxq8Ed3JEE84DfFOo6BgOVYZx69iOK8R1/wCCPjnR9zDS11CJf+WljKJM/RTh/wDx2uK8PeJNZ8OXPn6Hqd3YyZyfJkIVv95ejfiDXqfh79onxXYFF1e3sdViH3iyeTIf+BL8o/75oA8dvrO5sLl7a+t5ra4ThopkKMv1B5FQV9kwS+FPjt4MucW5gv7f93ukUefZyEZUgjqhx9Dg8Ajj5B1fT59J1W9068ULc2kzwSgHIDKxU4/EUAfRXwE8JaT4Z8F3HxB8TRo0gjea23rkwRKSNyj++xHHtjHU1wviX4+eMtS1CWTSrqLSbPP7uCKFJGA/2mdSSfpge1fQeq+HNO1L4OaboGpaoul2D2VrE9xuVfuhGAy3HJWvLf8AhSXgT/ofI/8AwIg/xoAsfBf4z6l4g1+Hw54xEF4t9ujhuvKVDux9x1ACkNgjgDk988eZfHvwdB4O8eSw6dH5em3sYurdAOI8khkHsCDj0BFeqeH/AIS+CdF13TtUg8cwvLZXMdyitcQAMUYMAeehxXP/ALWGp6bqWpeHH02+tLtkinEhgmWTaMpjODx3oApfsz+AbTxJq91rusQpPYacypDC4yskx5yR3CjBx6sPStb4mfH7VY9cudP8Gi3gsrZzF9rkjEjzMDgsoPAX04JPXjpXXfA8tpX7Pmo39vgTGO9uQR13KpA/9AFfJtAHtnhD9oLxDa3scXitLfVtMk+SbEKxyhTwSNuFP0I59RXuWtaXpGk/BTxDF4cx/ZU2mXl1Bg5XbKjv8v8As/NwPSviGvrXwTdSXf7LF40zFmj0m/iyfRfNCj8AAPwoA+Sq+qvGn/Jp9p/14WP/AKNir5Vr6q8af8mn2n/XhY/+jYqAPlWvS/2cf+SxaF/u3H/oiSvNK9L/AGcP+SxaF/u3H/oiSgDV/an/AOSoj/rxh/m1cv8ABzwX/wAJz41t9OnLLYQqbm7ZeD5akDaD2LEge2Se1dR+1P8A8lRH/XjD/Nq7H9j61XHii7OC/wDo8S+oH7wn+n5UAWvi/wDFdvA10nhLwJbWlobONVmmEQZYSRkIi9M4IJJz19ea840X48eObC/Sa91CLUbfdl7ee3jUMO4BRQR/ng16Z4p+E3g7WvEmp6nf+OI4rq6uXlkj8+AeWSx+Xk546c+lZf8AwpLwJ/0Pkf8A4EQf40Aa/wAatI0v4gfCm18daVbiO+ghWckY3NFnbJGxHXYcnPbafWvnjwJ/yPHh7/sI2/8A6NWvqeeDw14U+C2u+HrLxHY3yJp955Ra5j3szq7BQAeTuPFfLHgT/kePD3/YRt//AEatAH2D8WbrQPDBsfGeuwNeXWmq9vYWvGHmkIORnoQEPPYZOCcV8+6p+0B43u7syWdxZ2MO4lYYrZXGOwJfJP1GK7r9sK6kW28L2in9073ErD1ZRGB/6E35181UAfYXwi8Zp8WvCOs6T4ntIGuIQIrgRrhJY3B2sAc4YFT06EAjFfKN/BceHPFFzAjD7Vpl4yBiP443Izj6rXuH7IBP9s+JBng28P8A6E1eR/FMAfErxSBx/wATO5/9GNQB75+z78SvEvjPxbf2Ov3cM1tDYtOipAqEOJEXOQPRjXM/FP4w+MPD3xA1rStMvreOytZgkStbIxA2g9SMnrVL9kj/AJH/AFX/ALBj/wDo2KuJ+On/ACVrxJ/18D/0BaAMvxx4613xtJaSeIbiKdrUMsWyJY8BsZ6DnoK9+/ZD/wCRX17/AK/E/wDQK+Wq+pf2Q/8AkWNe/wCvxP8A0CgD5h1D/j/uf+urfzNe4fBvx34Q8C/D3UdQktfN8UiUxmNiPMuAeU2Nj5YwPve475UV4fqH/H/c/wDXVv5muz+G/wAMde8evJJpqRW2nxNtkvLgkIG/uqAMs2D0HHqRQBu6n8ffHV3dGS1vbSxizkRQ2qMAPTLhj+tex/BXxncfFTw3r+j+LbWC4MCpHI8abFljkDDkdAwKE5GO2OlcqPgT4P0CNX8X+MvLI5Kh4rUH2+csTXpnwl1LwOv27QvAIDxWapLcTqjYkZiRy7cuePp6UCPjDXLBtL1vUNPcktaXEkBJ9UYr/SvpP9kH/kAeIv8Ar5i/9ANfP/xD/wCR/wDE3/YTuv8A0a1fQH7IP/IA8Rf9fMX/AKAaBnzZrf8AyGb/AP6+JP8A0I1Sq7rf/IZv/wDr4k/9CNXfBmhyeJfFelaPDnN5cLGxHVUzlm/BQT+FAH0x8MY0+HP7P91r06hLy5he/G7uzgLAv0Pyf99GvnL4e+IpPDfjvSNbkkYiG5DTsSSWjb5ZPqdrNX0z+0Ro+var4T0rw/4U0m4ubcyh5/IA2xpGuEQ5PcnP/AK+ef8AhU3jr/oWr7/x3/GgD1z9rbw8JbbRfEtsoYDNlOy85U5eM/T7/wCYr5rr7Oi0DVPFPwFOh6/ZS22spZeSsc33jLEf3TZ/2tq5Pua+MiCCQRgjsaAPdv2V/B9rq+t3+v6jEkyabtjtkfkea2Tvx/sgce7Z7VT8f/HrxNd69dReGbqPTdMhkZIisCPJKoP3mLg4z1wMfjW1+yV4ktbW/wBX0C6lSOa72XFsGON7KCHUe+MHHsa4Dx98J/FPh/XbtLbR7y/09pWa3uLOFplKE8ZCglT2wf1oA9g+A/xb1Pxbqkvh3xMyyXskLSW95EgjZsD5lYDjOOQQB0NeDfFfQbrw34/1fTr27mvZFkEi3M7bnlRwGUse5wcH3Br1z9nT4a69pnilPEmvWMmnWtvE6wx3I2Su7DbnYeVABPXHavMvjj4gtvEnxM1e90+QS2aFLeKQchwihSQe4LBiD6YoA6r9m74fWvivWrnV9ZhWfS9OKqsDjKzTEZAPqqjkjvkds1q/Ez486x/bdxp/gqWCy021cxLdCJZHmxwSAwKqvpxnHOew9F/ZwtY4fgyXMy2wuZrmR5sgeX/BuOfQKDz6Vxf/AApLwJ/0Pcf/AIEQf40Ac34H+P3ibTtWgXxNOmqaY7BZcwokka55ZSgGSPQ5z7da2v2pfB1laNp/izSo0jS9k8m6EY+V3Klkk47kBsnvgd81a/4Ul4E/6HyP/wACIP8AGt74932ir8GoNKstZsr6e1e2ij8u4R3fYNpbAPpk0CPKP2Z/+St6d/1wn/8ARZr2r4reJtH+GOs3mvW9kt/4q1pFSES8LBFGoXORyATzgcse4xXiv7M//JW9O/64T/8Aos1d/amuXm+KPluSVgsoUUegJZv5saBlVvj547N4Jhe2ax/88BaJs/P73617TqVzbfF74FXeoT2iR6hFDLKqrz5VxECflJ6BgPyavkCvqz9ms7vg1rQb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+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "76n-8N5qHpDv"
+      },
+      "source": [
+        "# Also its AgentCard and AgentSkills\n",
+        "\n",
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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rouImhmGuXO+JuqNsjyp9x0r12rjsa0vhRgeOdMm1Xw1dwW+p3umSIplE9m+x/lBO3Poe9eU/s3+Gbl/B+i62PEOrpAss+dMWUfZj87ryuM+/XrXtuoQtcWFzCmN0kTIM+pBFeLfs+eL9H0rw1ZeDtVuHsvEcF1NCbOaJwzMXZhg4x3xye30pPcmaXOmw0pvEvjD4heN/Dya9fafolndo0s1vJ+/RSCFhiJ+4DhiSP7oHeuv8ReEdROk6fZ/8JzqWl6LZW+y5n3qLidgeHa4PK8H+VY3wl/5Kt8VP+vu1/lLWR8Rb/S7f4yWg+InmDwtFYeZp6yoz2rXOfmLqAQxxuGDn+H1qehG0bsb4C8QLonxYtvC+leLp/E+h6haO6PcXIuHtpkDNgSDgjap4GBz7c6Him88S6h8bm8OaLrkmm2M+jrLMcb/ACgJPmaNTwJDgLuPQEnqBWJb6rpes/HjwPd+HdOkttHFtdxQ3H2XyI7kiGQloxgEqMgZwK6T/m5z/uX/AP2pQJXtbzMprPV/h18U/CtrH4k1fV9I18y288OpTmZlkUD5geg5ZegzwRzmpviBq0198WIvDeveJL7w34dNiJoHtZhbm7mJwQZSOB1GOny+pq/8X/8Akpfwt/7CE3/tKtfxz4r8EjUpvD/jq1EcagPDJf2bGCbI5MTgHkZwTxz0pjatdXN7wPoF1oFncxT+ItQ1y2lcPbPesrvEmOm8cvnrnp0wBznyX4T6V4m+IvgeC617xlq9tZRyyRRJYSeXPIQ2S0spyW64C9MAVt/AgKniHxUnho3beBA8f9mm437fMx+88vdztzn/AMdzzXMfAX4j+HPCvw8Sx8RXM9hKJ5ZY3e2kZJ1J52MoIJB4IpX2C6dr7HbfCvVtX03xp4j8D6/qE2qNpyJdWd7OcyvC23hz3I3rye+e2Kx/DUOr/F241TWp/EWraL4dhuWtdPtdLm8lpAuMySNg5zkceuemOb/wnhufE3j/AMTePJbaa20y9iSx09Zk2tLEu3L49DsX8SR2rL+HGv2Xwoh1Lwn41eTT4oruSfT71onaK6hbHQqD8wxkj3x2o9QXS+xv+A9Y1jw/8Qb3wJ4h1CbVYzbfbtNv5+ZmjzgpIf4iCG5/2T6gDC0pvEvjD4heN/Dya9fafolndo0s1vJ+/RSCFhiJ+4DhiSP7oHetHwYJvG/xcuPG1vbzQ+HrKw+wWE8yFDdksSXUHnb8z8/TvkCX4S/8lW+Kn/X3a/ylpgruy6XOS+LvhG50/XfAFsPE2uzpc6lBaq01xuaFgUXzUOPv85z616l/wh2s2/hv+zdO8aaul2bv7Qb+6RLiXZs2+UAcALnDfXPrXL/tBb7FvBevyQyyafpGsRT3bRruKJuU5x/wHH1I9a6h28J/Ffw/sgu31DTre5DFoHkgKyBDgH7p6P8AT8qEtWNRSk0Zn/CD+Mv+ilah/wCC2H/Gu18N2F7pmjwWuqapJqt2hbfdyRLGz5YkfKvAwCB+FcV/wpbwb/z7ah/4MJv/AIqu18N6HZeHNHg0zS1kS0hLFBJI0jfMxY5ZiSeSaaRpCLT1PNfAv/JwXxD/AOve1/8ARaVa+OGu61ot54OHh6ZlurvUxb+SZCscxYAKr46rkiqvgT/k4L4h/wDXva/+i0p/xy/5GT4a/wDYwQf+hpS6GevI/U6DSvBetaXZapNF4w1S61u+iC/aLsCSCCTOS0cPRR2x2rzL4gQnwRp9xqtj8UNSu/FFqyubC5vUeOb5hlDAPujBJwcjj8a9G+PM+r23wz1KTQvtAm3IJ2ts+YsJb5yuOenX2zXmvirXPAEnwv1PSfAOnfbLtrPc729k2+BBhmknlYDHAPOSSeBSYqllojuPi94nvk+Ca+INHuZrG6uY7S4SSFyGUSMhIz9Disjxj4P8TS+D77xRc+NdXj1y2tWvlt7KQw2aBVLmNUHJ4GNxOT3qr8Tv+TXdK/68NN/lHXpfjD/klut/9gaf/wBENT3Hbmbv2OJ8UeN9dPwCsfEulsY9UuIYRPcRxhvJBbbJIFxjqPw3e1XfA3hqC4udO1rw78RNb1W3Uh7uKe7W4juMj7pQj92frkgDHB5qL4e+IrPwz8EfDN7qltdz2TReVM1vAZhEpZ8u4HRBjk+/SuL1248J3ni/w1d/CLjxHJep9pXTonjh+y/x+auAoHTPA4zntS8xX2bOt+IV/wCJJvjHoOgeHtabTYb7TZDKzL5iphnJdUPBfC4BNZPjbT9a+FI07xPY+KNb1ewF2kOpWepT+aro/Vk4AU8cd+R2BBm+JOt23h34+eF9Tv0uGtIdKl81oIjIY1JkG8qOdozk47VV+JXimw+Ki6b4N8Eyy34uLuOW/u1hdYraFckklgOe/wCGOpoYm1r3Op+JmvavfeLtC8D+GbxtPudSia7u79OXhtxn7n+0drc/T1yMHxdpuufCiyg8T6X4k1rWtNhmRNRsdVuPODxuwXchwNrbiPzHOMg6PxJtbnwv8R/D3jqK0mutHtrVtP1BYELvBGSxWTA5IBfn/d96zPiZ4vsPiToK+EPAcj6reajLF9pmSF1itYVcPvdmAxyo4+vfAI/Mb633Nj4zeJNW09/BE/he4bzdQ1BY0iLlI596jYr46rlhV2bwBqNtouqzXPjbxHNf3MQkllWcIisuSRGmMIp6Y9BWP8YLRLHVPhXaRElLfW7aJSepCsgH8q9b1CFriwuYUxukiZBn1IIp7vUpLmbueJfs3+Gbl/B+ja2PEOrpAss+dMWUfZj87ryuM+/XrVXSfGmgeDfjb8QJPEl/9jS5NssR8mSTcVQZ+4px1HWr37Pni/R9K8NWXg7Vbh7LxHBdTQmzmicMWLswwcY745Pb6VqfDn/kuXxJ+lr/AOgUlsrEJaR5TI1HWE+KnxE8Iy+FbS6k0fQro3lzqc0JjjPKkRrnkk7MY9/QE1f8V6h4lvfja3hrRNVlsrO70dXlkzuFsPMJaRFPHmEDYD23Z7V7LXkn/Nzn/cv/APtSm1YuUWuu7IvGVxqngTQ9F8KeHNWv7/XNfvmhgv8AU5fOeBPl3tnHbcMDHcnrVfxR4P8AEPgnQbnxLoPjLXtRv9PT7Tc22pT+bb3Ma/fGz+H5cnqTxwR1Gv8AGvSdR+1+FvFWkWkl9J4euzNPaxDLyQvt3lR3I2frntWZ44+KGi+JfCN7ofg159X13VoGtIrSK3cNGHG12csAFCgnv19skDFJJN3+Rzvx8nPib4VaT4rtdRv4LW6W3B04SDySWJJLDHLKeM+1d5rDT/CzwTr2t3Ouatr8gSMQR6lKHCSbiqgYAwCXBPstcx8VfCd5pX7PNnpFuhuZ9LWCSfywT0PzkewLE/QZrX8W6po/xg+G+taZ4QvludQSKK4ELo0bK4bcEO4AZO1lyDgHvikLVNvrYr6Z8PPE2r6HDrGpeOtftvEdzF56xwT7LWFmGQhiA5A4BwR06Ve8JfEueX4W6xrmvQL/AGroTyWt3GnyiWZMBSPTcWAPoc44qLR/jJ4esvDcEOuG6tPEVtEsM+lNbSecZlAG1RjHzHpz35rK8K/D/V774P8Aim01SIWmteIp5b8W7nHlMSrIjehJXn0Dc8ij0BafCT+GvBXiPxhoVt4i8QeNNesNSv4xcwW2mz+Tb2yMMoNnf5SM8g84JPU6PxA1nXtO/wCEU8EaNqbPr+rjy59VeMBo40UeZIFHAY/MR6YPOcGqXg34s6FoXhSy0rxe9zpWvaZClpNZSW0hdygCqy4UghgAfx9MGm+P5LyTV/BPxJ0vS7+W0sFcXtm8JW4igkUgvs/2Qz5/A9MmnpbQNOXTcg8X+Htf+G+jN4p0LxVrmr/YnV72x1W486OeMkK23j5SMjnrjvxgyftAahDq/wAKtB1K2z5F5f2dxHnrtdGYZ/A0z4i/EDS/G/hafwz4EeXWdX1ULFsjhdVgj3As8hYAKMDH40nxz0g6J8F9DsVLSxaVcWccsiqfuopTcfqcfnS9Aez5dj2yvMv2gtX1DRfBNpc6TeT2dw2owRmSFyrFTuyMjtwK1fGvxJ0jwt4e0nWmhutQsdTkRYGtUByrLuDfMR26DrXN/tMnPw+sj/1FLf8Ak1U3oaTl7rsS/HLXr/S7zwvYJqtzomiajcvHqGp24w8SgLtUNg7M5PPt6A1veA/DH9k3rX+m+MdV1vRZ4dqW93crdKHyDvWT0xngevWrPj3xV4f0IQWPi21lbS71WD3EtoZrVSCMJIQDgnqBjt2rzXwN/Y//AAuW3b4YmY+HHtZDrAhD/ZRJhvL27uN2dvTtnH8VLqQ9JGlp39r/ABX8R69INe1PRfC+lXLWFvHpkvlS3Mi/ed3weOhA9x6Em94U1LWPB/xLi8Fa3qlzrOnalbNdabeXTbp0ZQS0bt/FwrHP09cDJ8HaxbfCfXvEWh+LjLZaVfX73+nagYmeKYOAChKg4YBV4+vtm5okrfEL4w6f4o0uGYeGtDtZIYLyWMoLuZwynYDglQG6/wCz70l+Il07kEsnibxF8ZfGPhyx8RXOmaPDFayuYvmljBhT5Yc8JuZiWbrwKf4Zj1XwP8ZbTwzJrupaxo2r2L3EY1GYyyRSJuJw3/AD0xndyOAau+Df+TifiD/16Wf/AKKjo8Vf8nHeCv8AsHXP/oEtO3ULdfMreK9Q8S3vxsbw1omqy2Vnd6OryyZ3C2HmEtIinjzCBsB7bs9qj+KUWqfD34a2SaLr+q3V4dXiIub65MkjBg2UYjHyZA4+tXf+bnP+5f8A/alN/adYp8PrFgrORqsBCqMk8PwKOjYP4ZMZ4n8BeJ4tFvNdj8da2/iK3ha4WOKQR2ZKjcYxEB0OMck9siprv4pywfA+z8Xrbxvql0ot44sHYbjcUJx1xlWbHpge9ReLvjH4en8N3lloL3l34hu4Xt4NO+ySLMkrDbhwRgFSckAnOOKzta+G2qJ+z9p3h+zUSa3YMt/5QI+aXezsgPQkByB6lR60vQO/Ia1j8MvEVxYw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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "I7drSIz7Heyz"
+      },
+      "outputs": [],
+      "source": [
+        "host_agent = SequentialAgent(\n",
+        "    name = \"host_agent\",\n",
+        "    # blockain_learnig_remote , blckcahin_search_remote\n",
+        "    # ye abhi host right --> 2 agent\n",
+        "    sub_agents = [blochchain_learning_remote ,blckcahin_search_remote ]\n",
+        ")\n",
+        "\n",
+        "\n",
+        "\n",
+        "host_agent_card = AgentCard(\n",
+        "    name=\"host_agent\",\n",
+        "    url=\"http://localhost:8003\",\n",
+        "    description=\"This agent is analyed the query and take decision which agnet need tocalll \",\n",
+        "\n",
+        "    capabilities={\"streaming\": True},\n",
+        "    default_input_modes=['text'],\n",
+        "    default_output_modes=['text'],\n",
+        "    preferred_transport=TransportProtocol.jsonrpc, #mcp\n",
+        "    version='1.0.0',\n",
+        "    skills = [\n",
+        "        AgentSkill(\n",
+        "            id = 'host_agents',\n",
+        "            name=\"host_agents\",\n",
+        "            description=\"This agent is analyed the query and take decision which agnet need tocalll \",\n",
+        "            tags = ['web_search', 'treading_blockchain', 'search_expert',\"indeify_whcih_agent\", \"learnign\"],\n",
+        "            examples=[\n",
+        "                \"give me top sui based company using web search \",\n",
+        "                \"give me top solalana based company using web search \",\n",
+        "                \"give me top xrp based company using web search\",\n",
+        "                \"what is sui\",\n",
+        "                \"what is bitcoin\",\n",
+        "                \"what is xrp\"\n",
+        "            ]\n",
+        "        )\n",
+        "    ],\n",
+        "\n",
+        ")\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "B5a5apjYJBr8"
+      },
+      "source": [
+        "### Starting the A2A Servers\n",
+        "\n",
+        "Create function to run each agent as an A2A server:\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "qrGijdSSJXV6"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1Pu3m8n1Jhir"
+      },
+      "outputs": [],
+      "source": [
+        "from google.adk.runners import Runner\n",
+        "from google.adk.sessions import InMemorySessionService\n",
+        "from google.adk.memory.in_memory_memory_service import InMemoryMemoryService\n",
+        "from google.adk.artifacts import InMemoryArtifactService\n",
+        "from google.adk.a2a.executor.a2a_agent_executor import (\n",
+        "    A2aAgentExecutor, A2aAgentExecutorConfig\n",
+        ")\n",
+        "from a2a.server.apps import A2AStarletteApplication\n",
+        "from a2a.server.request_handlers import DefaultRequestHandler\n",
+        "from a2a.server.tasks import InMemoryTaskStore\n",
+        "\n",
+        "def create_agent_a2a_server(agent, agent_card):\n",
+        "    \"\"\"\n",
+        "    Creates the A2A server for the agent with proper session, memory, and artifact services.\n",
+        "    \"\"\"\n",
+        "    # Runner is responsible for running the agent\n",
+        "    runner = Runner(\n",
+        "        app_name=agent.name,\n",
+        "        agent=agent,\n",
+        "        artifact_service=InMemoryArtifactService(),  # Stores agent outputs\n",
+        "        session_service=InMemorySessionService(),    # Handles session context\n",
+        "        memory_service=InMemoryMemoryService()       # Handles long-term memory\n",
+        "    )\n",
+        "\n",
+        "    # Create executor configuration for A2A agent execution\n",
+        "    config = A2aAgentExecutorConfig()\n",
+        "\n",
+        "    # Initialize the executor with the runner and configuration\n",
+        "    executor = A2aAgentExecutor(runner=runner, config=config)\n",
+        "\n",
+        "    # Set up request handler with the executor and task store\n",
+        "    request_handler = DefaultRequestHandler(\n",
+        "        agent_executor=executor,\n",
+        "        task_store=InMemoryTaskStore()\n",
+        "    )\n",
+        "\n",
+        "    # Return the A2AStarlette application with the agent card and request handler\n",
+        "    return A2AStarletteApplication(\n",
+        "        agent_card=agent_card,\n",
+        "        http_handler=request_handler\n",
+        "    )\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "rLvSUbyfJyWT"
+      },
+      "outputs": [],
+      "source": [
+        "import nest_asyncio\n",
+        "import asyncio  # Add this import\n",
+        "import uvicorn\n",
+        "import threading\n",
+        "import time\n",
+        "\n",
+        "# Apply nest_asyncio to allow asyncio to run inside Jupyter or other non-blocking environments\n",
+        "nest_asyncio.apply()\n",
+        "\n",
+        "# Store server tasks\n",
+        "server_tasks: list[asyncio.Task] = []\n",
+        "\n",
+        "\n",
+        "async def run_agent_server(agent, agent_card, port) -> None:\n",
+        "    \"\"\"Run a single agent server.\"\"\"\n",
+        "    app = create_agent_a2a_server(agent, agent_card)\n",
+        "\n",
+        "    config = uvicorn.Config(\n",
+        "        app.build(),\n",
+        "        host='127.0.0.1',\n",
+        "        port=port,\n",
+        "        log_level='warning',\n",
+        "        loop='none',  # Important: let uvicorn use the current loop\n",
+        "    )\n",
+        "\n",
+        "    server = uvicorn.Server(config)\n",
+        "    await server.serve()\n",
+        "\n",
+        "\n",
+        "async def start_all_servers() -> None:\n",
+        "    \"\"\"Start all servers in the same event loop.\"\"\"\n",
+        "    # Create tasks for all servers\n",
+        "    tasks = [\n",
+        "        asyncio.create_task(\n",
+        "            run_agent_server(blochchain_learning, blochchain_learning_card, 8001)\n",
+        "        ),\n",
+        "        asyncio.create_task(\n",
+        "            run_agent_server(blckcahin_search, blckcahin_search_card, 8002)\n",
+        "        ),\n",
+        "        asyncio.create_task(\n",
+        "            run_agent_server(host_agent, host_agent_card, 8003)\n",
+        "        ),\n",
+        "    ]\n",
+        "\n",
+        "    # Give servers time to start\n",
+        "    await asyncio.sleep(2)\n",
+        "\n",
+        "    print(' All agent servers started!')\n",
+        "    print('   - blockain_learning _Agent: http://127.0.0.1:8001')\n",
+        "    print('   - search  Agent: http://127.0.0.1:8002')\n",
+        "    print('   - Host Agent: http://127.0.0.1:8003')\n",
+        "\n",
+        "    # Keep servers running\n",
+        "    try:\n",
+        "        await asyncio.gather(*tasks)\n",
+        "    except KeyboardInterrupt:\n",
+        "        print('Shutting down servers...')\n",
+        "\n",
+        "\n",
+        "# Run in a background thread\n",
+        "def run_servers_in_background() -> None:\n",
+        "    loop = asyncio.new_event_loop()\n",
+        "    asyncio.set_event_loop(loop)\n",
+        "    loop.run_until_complete(start_all_servers())\n",
+        "\n",
+        "\n",
+        "# Start the thread\n",
+        "server_thread = threading.Thread(target=run_servers_in_background, daemon=True)\n",
+        "server_thread.start()\n",
+        "\n",
+        "# Wait for servers to be ready\n",
+        "time.sleep(3)\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "UqwWnQaoR_Ej"
+      },
+      "source": [
+        "# A2A Client\n",
+        "\n",
+        "Call the A2A agents (the 2 remote agents, and the host agent that refers to the 2 remote agents as sub agents)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "QtGf2nNmSIB5"
+      },
+      "outputs": [],
+      "source": [
+        "from a2a.client import ClientConfig, ClientFactory, create_text_message_object\n",
+        "\n",
+        "from a2a.types import TransportProtocol\n",
+        "import httpx\n",
+        "from typing import Any\n",
+        "class A2ASimpleClient:\n",
+        "    \"\"\"A2A Simple to call A2A servers.\"\"\"\n",
+        "\n",
+        "    def __init__(self, default_timeout: float = 240.0):\n",
+        "        self._agent_info_cache: dict[\n",
+        "            str, dict[str, Any] | None\n",
+        "        ] = {}  # Cache for agent metadata\n",
+        "        self.default_timeout = default_timeout\n",
+        "\n",
+        "    async def create_task(self, agent_url: str, message: str) -> str:\n",
+        "        \"\"\"Send a message following the official A2A SDK pattern.\"\"\"\n",
+        "        # Configure httpx client with timeout\n",
+        "        timeout_config = httpx.Timeout(\n",
+        "            timeout=self.default_timeout,\n",
+        "            connect=10.0,\n",
+        "            read=self.default_timeout,\n",
+        "            write=10.0,\n",
+        "            pool=5.0,\n",
+        "        )\n",
+        "\n",
+        "        async with httpx.AsyncClient(timeout=timeout_config) as httpx_client:\n",
+        "            # Check if we have cached agent card data\n",
+        "            if (\n",
+        "                agent_url in self._agent_info_cache\n",
+        "                and self._agent_info_cache[agent_url] is not None\n",
+        "            ):\n",
+        "                agent_card_data = self._agent_info_cache[agent_url]\n",
+        "            else:\n",
+        "                # Fetch the agent card\n",
+        "                agent_card_response = await httpx_client.get(\n",
+        "                    f'{agent_url}{AGENT_CARD_WELL_KNOWN_PATH}'\n",
+        "                )\n",
+        "                agent_card_data = self._agent_info_cache[agent_url] = (\n",
+        "                    agent_card_response.json()\n",
+        "                )\n",
+        "\n",
+        "            # Create AgentCard from data\n",
+        "            agent_card = AgentCard(**agent_card_data)\n",
+        "\n",
+        "            # Create A2A client with the agent card\n",
+        "            config = ClientConfig(\n",
+        "                httpx_client=httpx_client,\n",
+        "                supported_transports=[\n",
+        "                    TransportProtocol.jsonrpc,\n",
+        "                    TransportProtocol.http_json,\n",
+        "                ],\n",
+        "                use_client_preference=True,\n",
+        "            )\n",
+        "\n",
+        "            factory = ClientFactory(config)\n",
+        "            client = factory.create(agent_card)\n",
+        "\n",
+        "            # Create the message object\n",
+        "            message_obj = create_text_message_object(content=message)\n",
+        "\n",
+        "            # Send the message and collect responses\n",
+        "            responses = []\n",
+        "            async for response in client.send_message(message_obj):\n",
+        "                responses.append(response)\n",
+        "\n",
+        "            # The response is a tuple - get the first element (Task object)\n",
+        "            if (\n",
+        "                responses\n",
+        "                and isinstance(responses[0], tuple)\n",
+        "                and len(responses[0]) > 0\n",
+        "            ):\n",
+        "                task = responses[0][0]  # First element of the tuple\n",
+        "\n",
+        "                # Extract text: task.artifacts[0].parts[0].root.text\n",
+        "                try:\n",
+        "                    return task.artifacts[0].parts[0].root.text\n",
+        "                except (AttributeError, IndexError):\n",
+        "                    return str(task)\n",
+        "\n",
+        "            return 'No response received'"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "8zJ_AMxWSKUm"
+      },
+      "outputs": [],
+      "source": [
+        "async def test_host_analysis() -> None:\n",
+        "    \"\"\"Test host analysis agent.\"\"\"\n",
+        "    host_analysis = await a2a_client.create_task(\n",
+        "        'http://localhost:8003',\n",
+        "        'what is blockchian explain and give me list of copampny',\n",
+        "\n",
+        "    )\n",
+        "    print(host_analysis)\n",
+        "\n",
+        "# Initialize the client\n",
+        "a2a_client = A2ASimpleClient()\n",
+        "\n",
+        "# Run the async function\n",
+        "asyncio.run(test_host_analysis())"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "yezPvhAeTU2o"
+      },
+      "source": [
+        "![Agent-to-Agent-Protocol-A2A-Enabling-Seamless-AI-Collaboration.pdf 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+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}