bitagent_subnet-main/docs/OTF-example.rt.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## SN20 BitAgent\n",
    "\n",
    "### Setting up ...\n",
    "- importing standard libraries + bittensor, no special sauce required\n",
    "- fetching subnet 20\n",
    "- setting up wallet and validator\n",
    "- getting top miner\n",
    "- providing protocol (QnATask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[34m2024-04-07 17:47:36.518\u001b[0m | \u001b[1m      INFO      \u001b[0m | You are connecting to finney network with endpoint wss://entrypoint-finney.opentensor.ai:443.\n",
      "\u001b[34m2024-04-07 17:47:36.519\u001b[0m | \u001b[33m\u001b[1m    WARNING     \u001b[0m | We strongly encourage running a local subtensor node whenever possible. This increases decentralization and resilience of the network.\n",
      "\u001b[34m2024-04-07 17:47:36.519\u001b[0m | \u001b[33m\u001b[1m    WARNING     \u001b[0m | In a future release, local subtensor will become the default endpoint. To get ahead of this change, please run a local subtensor node and point to it.\n",
      "\u001b[34m2024-04-07 17:47:36.833\u001b[0m | \u001b[1m      INFO      \u001b[0m | Connected to finney network and wss://entrypoint-finney.opentensor.ai:443.\n",
      "Top Miner UID for Subnet 20:  197\n"
     ]
    }
   ],
   "source": [
    "import asyncio\n",
    "import requests\n",
    "import bittensor as bt \n",
    "from rich import print as rprint\n",
    "from typing import Optional,List\n",
    "\n",
    "# working with subnet 20 / upsilon / BitAgent\n",
    "subnet = bt.metagraph(netuid=20)\n",
    "\n",
    "# Wallet and validator setup\n",
    "WALLET_NAME = \"TODO\" # TODO\n",
    "HOTKEY_NAME = \"TODO\" # TODO\n",
    "vali_wallet =  bt.wallet(name=WALLET_NAME, hotkey=HOTKEY_NAME)\n",
    "vali_dendrite = bt.dendrite(wallet=vali_wallet)\n",
    "\n",
    "# get the TOP miner on the subnet\n",
    "top_miner_uid = int(subnet.I.argmax())\n",
    "print(\"Top Miner UID for Subnet 20: \", top_miner_uid)\n",
    "\n",
    "# the request protocol\n",
    "class QnATask(bt.Synapse):\n",
    "    urls: List[str] = []   # not used right now\n",
    "    datas: List[dict] = [] # used to pass in relevant context, could be a company knowledge base or a set of wikipedia pages\n",
    "    prompt: str = \"\"       # the query / prompt\n",
    "    response: Optional[dict] = {}\n",
    "    timeout: Optional[float] = 3.0\n",
    "    miner_uids: Optional[List[int]] = [top_miner_uid] # put our TOP miner into the network as the miner to query (if empty list, a random list of miners will be selected)\n",
    "\n",
    "    def toJSON(self):\n",
    "        return {\"prompt\": self.prompt, \n",
    "                \"urls\": self.urls, \n",
    "                \"datas\": self.datas, \n",
    "                \"response\": self.response,\n",
    "                \"miner_uids\": self.miner_uids,\n",
    "                \"dendrite_process_time\": self.dendrite.process_time,\n",
    "                \"dendrite_status_code\": self.dendrite.status_code,\n",
    "                \"axon_status_code\": self.axon.status_code,}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two ways to query SN20 \n",
    "\n",
    "### First way is to use your registered validator to query directly to the TOP miner\n",
    "- build a task (QnATask) with a \"prompt\" and optional \"datas\"\n",
    "- query the network\n",
    "- see response answer (1)\n",
    "- see top citation (2)\n",
    "- see full response object (3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 - Response showing answer from miner: \n",
      "\t  Meow eats grapes, berries, and occasional bananas.\n",
      "2 - Response's topmost relevant citation from miner: \n",
      "\t [{'context': 'meow prefers to eat grapes and berries, but also eats the occassional banana', 'source': 'source 3'}]\n",
      "3 - Full response: \n",
      "\t [QnATask(timeout=3.0, urls=[], datas=[{'source': 'source 1', 'context': 'Some irrelevant context'}, {'source': 'source 2', 'context': 'meow is a monkey in the jungle'}, {'source': 'source 3', 'context': 'meow prefers to eat grapes and berries, but also eats the occassional banana'}, {'source': 'source 4', 'context': 'meow climbs trees for fun'}, {'source': 'source 5', 'context': 'meow is afraid of snakes, but loves bunnies'}], prompt='hey, what does the meow eat?', response={'response': ' Meow eats grapes, berries, and occasional bananas.', 'citations': [{'context': 'meow prefers to eat grapes and berries, but also eats the occassional banana', 'source': 'source 3'}], 'context': 'meow prefers to eat grapes and berries, but also eats the occassional banana'}, miner_uids=[197])]\n"
     ]
    }
   ],
   "source": [
    "task = QnATask(prompt=\"hey, what does the meow eat?\", \n",
    "               datas=[{\"source\": \"source 1\", \"context\": \"Some irrelevant context\"},\n",
    "                      {\"source\": \"source 2\", \"context\": \"meow is a monkey in the jungle\"},\n",
    "                      {\"source\": \"source 3\", \"context\": \"meow prefers to eat grapes and berries, but also eats the occassional banana\"},\n",
    "                      {\"source\": \"source 4\", \"context\": \"meow climbs trees for fun\"},\n",
    "                      {\"source\": \"source 5\", \"context\": \"meow is afraid of snakes, but loves bunnies\"}])\n",
    "\n",
    "responses = vali_dendrite.query(\n",
    "    axons=[subnet.axons[top_miner_uid]],\n",
    "    synapse=task,\n",
    "    deserialize=False,\n",
    "    timeout=task.timeout,\n",
    ")\n",
    "\n",
    "response = responses[0].response\n",
    "print(\"1 - Response showing answer from miner: \\n\\t\", response['response'])\n",
    "print(\"2 - Response's topmost relevant citation from miner: \\n\\t\", response['citations'])\n",
    "print(\"3 - Full response: \\n\\t\", responses)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Second way is to use your validator (or any wallet) to query one of the subnet validators\n",
    "- we'll use the same QnATask from above, but we'll change the prompt\n",
    "- query the network via validator axon\n",
    "- we are specifying the miner uid for our QnATask to be the TOP miner uid\n",
    "- see response answer (1)\n",
    "- see top citation (2)\n",
    "- see full response object (3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 - Response showing answer: \n",
      "\t  Meow fears snakes the most.\n",
      "2 - Response's topmost relevant citation: \n",
      "\t [{'context': 'meow is afraid of snakes, but loves bunnies', 'source': 'source 5'}]\n",
      "3 - Full response: \n",
      "\t [QnATask(timeout=3.0, urls=[], datas=[{'source': 'source 1', 'context': 'Some irrelevant context'}, {'source': 'source 2', 'context': 'meow is a monkey in the jungle'}, {'source': 'source 3', 'context': 'meow prefers to eat grapes and berries, but also eats the occassional banana'}, {'source': 'source 4', 'context': 'meow climbs trees for fun'}, {'source': 'source 5', 'context': 'meow is afraid of snakes, but loves bunnies'}], prompt='What does meow fear the most?', response={'response': ' Meow fears snakes the most.', 'citations': [{'context': 'meow is afraid of snakes, but loves bunnies', 'source': 'source 5'}], 'context': 'meow is afraid of snakes, but loves bunnies'}, miner_uids=[])]\n"
     ]
    }
   ],
   "source": [
    "task.prompt = \"What does meow fear the most?\"\n",
    "\n",
    "responses = vali_dendrite.query(\n",
    "    axons=[subnet.axons[0]],\n",
    "    synapse=task,\n",
    "    deserialize=False,\n",
    "    timeout=task.timeout,\n",
    ")\n",
    "response = responses[0].response\n",
    "print(\"1 - Response showing answer: \\n\\t\", response['response'])\n",
    "print(\"2 - Response's topmost relevant citation: \\n\\t\", response['citations'])\n",
    "print(\"3 - Full response: \\n\\t\", responses)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Demonstration of all task types and scoring / incentives ...\n",
    "## Generating tasks from the Task API\n",
    "We'll get tasks from the Task API that are far more complicated than the one above - \n",
    "- Summarization Task\n",
    "- QnA with Citations Task\n",
    "- QnA Logic Task"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "### Setting up ...\n",
    "- methods to \n",
    "  - get the top miner, \n",
    "  - fetch a task \n",
    "  - get miner response and \n",
    "  - evaluate a task\n",
    "- setup task IDs for QnA with Citations, Pet Tricks and Summarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "qna_task = (3,1)\n",
    "pet_tricks_task = (6,6)\n",
    "summarization_task = (8,1)\n",
    "\n",
    "def get_top_miner_uid(subnet):\n",
    "    return subnet.I.argmax()\n",
    "\n",
    "def get_task(task_id, sub_task_id):\n",
    "    # keep trying in case it's being restarted \n",
    "    while True:\n",
    "        try:\n",
    "            resp = requests.post(\"https://roguetensor.com/api/task_api/get_new_task\", json={\"task_id\": task_id, \"sub_task_id\": sub_task_id}).json()\n",
    "            return resp\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def eval_task(task_id, response):\n",
    "    # keep trying in case it's being restarted \n",
    "    while True:\n",
    "        try:\n",
    "            resp = requests.post(\"https://roguetensor.com/api/task_api/evaluate_task_response\", json={\"task_id\": task_id, \"response\": response.toJSON()}).json()\n",
    "            return resp\n",
    "        except:\n",
    "            pass\n",
    "\n",
    "def get_miner_response_to_task(subnet, validator, miner_uid, task):\n",
    "    print(\"Fetching response from TOP miner: \", miner_uid)\n",
    "\n",
    "    response = None\n",
    "    while not response:\n",
    "        response = asyncio.run(validator.call(\n",
    "            # Send the query to selected miner axons in the network.\n",
    "            target_axon=subnet.axons[miner_uid],\n",
    "            # Construct a query. \n",
    "            synapse=task,\n",
    "            # All responses have the deserialize function called on them before returning.\n",
    "            # You are encouraged to define your own deserialization function.\n",
    "            deserialize=True,\n",
    "            timeout=25.0\n",
    "        ))\n",
    "        return response\n",
    "\n",
    "def evaluate_miner(subnet, validator, miner_uid, task_id, sub_task_id):\n",
    "    task_json = get_task(task_id, sub_task_id)\n",
    "    gen_task_id = task_json[\"task\"][\"task_id\"]\n",
    "    task = QnATask(prompt=task_json['task']['prompt'], datas=task_json['task']['datas'], urls=task_json['task']['urls'])\n",
    "    print(\"Got task with prompt: \", task_json['task']['prompt'][:60] + \" ...\")\n",
    "    miner_response = get_miner_response_to_task(subnet, validator, miner_uid, task)\n",
    "    print(\"Miner response:\", miner_response.response['response'][:100] + \" ...\")\n",
    "    eval = eval_task(gen_task_id, miner_response)\n",
    "    return miner_response, *eval[\"result\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generated Summary Task Example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got task with prompt:  Summarize this and make sure to be concise:  Did you attend  ...\n",
      "Fetching response from TOP miner:  197\n",
      "Miner response:  Pamela and Marie both did not attend the independence march. Pamela stayed at home due to concerns  ...\n",
      "Scores:  2.25 2.25\n"
     ]
    }
   ],
   "source": [
    "task_id, sub_task_id = summarization_task\n",
    "miner_response, score, max_score, results, correct_answer_optional = evaluate_miner(subnet, vali_dendrite, top_miner_uid, task_id, sub_task_id)\n",
    "print(\"Scores: \", score, max_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The results the miner would see:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not error</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You successfully responded to the request.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not take a long time</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded to the request in </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">0.8873927593231201</span><span style=\"color: #008000; text-decoration-color: #008000\">.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Return summary shorter than original</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a valid summary length.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Return valid summary</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a valid summary.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> reward.\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;34mDoes not error\u001b[0m\n",
       "✅ \u001b[32mYou successfully responded to the request.\u001b[0m\n",
       "You received \u001b[1;36m0.25\u001b[0m of \u001b[1;36m0.25\u001b[0m reward.\n",
       "\u001b[1;34mDoes not take a long time\u001b[0m\n",
       "✅ \u001b[32mYou responded to the request in \u001b[0m\u001b[1;32m0.8873927593231201\u001b[0m\u001b[32m.\u001b[0m\n",
       "You received \u001b[1;36m0.5\u001b[0m of \u001b[1;36m0.5\u001b[0m reward.\n",
       "\u001b[1;34mReturn summary shorter than original\u001b[0m\n",
       "✅ \u001b[32mYou responded with a valid summary length.\u001b[0m\n",
       "You received \u001b[1;36m0.5\u001b[0m of \u001b[1;36m0.5\u001b[0m reward.\n",
       "\u001b[1;34mReturn valid summary\u001b[0m\n",
       "✅ \u001b[32mYou responded with a valid summary.\u001b[0m\n",
       "You received \u001b[1;36m1.0\u001b[0m of \u001b[1;36m1.0\u001b[0m reward.\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rprint((\"\\n\").join(results)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generated QnA with Citations Task Example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got task with prompt:   \"What was the purpose of integrating Crashlytics into Fireb ...\n",
      "Fetching response from TOP miner:  197\n",
      "Miner response:  The purpose of integrating Crashlytics into Firebase was to bring the best of both platforms togeth ...\n",
      "Scores:  5.25 5.25\n"
     ]
    }
   ],
   "source": [
    "task_id, sub_task_id = qna_task\n",
    "miner_response, score, max_score, results, correct_answer_optional = evaluate_miner(subnet, vali_dendrite, top_miner_uid, task_id, sub_task_id)\n",
    "print(\"Scores: \", score, max_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The results the miner would see:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not error</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You successfully responded to the request.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not take a long time</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded to the request in </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">0.8485991954803467</span><span style=\"color: #008000; text-decoration-color: #008000\">.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Returns expected citation source(s)</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You correctly identified some or all of the correct citation sources </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">(</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">1</span><span style=\"color: #008000; text-decoration-color: #008000\">/</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">1</span><span style=\"color: #008000; text-decoration-color: #008000\"> identified</span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">)</span><span style=\"color: #008000; text-decoration-color: #008000\">.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.5</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.5</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Returns a relevant response</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a relevant response compared to the context.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Returns a unique response</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a novel response compared to the context.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Returns valid response</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a valid response.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> reward.\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;34mDoes not error\u001b[0m\n",
       "✅ \u001b[32mYou successfully responded to the request.\u001b[0m\n",
       "You received \u001b[1;36m0.25\u001b[0m of \u001b[1;36m0.25\u001b[0m reward.\n",
       "\u001b[1;34mDoes not take a long time\u001b[0m\n",
       "✅ \u001b[32mYou responded to the request in \u001b[0m\u001b[1;32m0.8485991954803467\u001b[0m\u001b[32m.\u001b[0m\n",
       "You received \u001b[1;36m0.5\u001b[0m of \u001b[1;36m0.5\u001b[0m reward.\n",
       "\u001b[1;34mReturns expected citation \u001b[0m\u001b[1;34msource\u001b[0m\u001b[1;34m(\u001b[0m\u001b[1;34ms\u001b[0m\u001b[1;34m)\u001b[0m\n",
       "✅ \u001b[32mYou correctly identified some or all of the correct citation sources \u001b[0m\u001b[1;32m(\u001b[0m\u001b[1;32m1\u001b[0m\u001b[32m/\u001b[0m\u001b[1;32m1\u001b[0m\u001b[32m identified\u001b[0m\u001b[1;32m)\u001b[0m\u001b[32m.\u001b[0m\n",
       "You received \u001b[1;36m1.5\u001b[0m of \u001b[1;36m1.5\u001b[0m reward.\n",
       "\u001b[1;34mReturns a relevant response\u001b[0m\n",
       "✅ \u001b[32mYou responded with a relevant response compared to the context.\u001b[0m\n",
       "You received \u001b[1;36m1.0\u001b[0m of \u001b[1;36m1.0\u001b[0m reward.\n",
       "\u001b[1;34mReturns a unique response\u001b[0m\n",
       "✅ \u001b[32mYou responded with a novel response compared to the context.\u001b[0m\n",
       "You received \u001b[1;36m1.0\u001b[0m of \u001b[1;36m1.0\u001b[0m reward.\n",
       "\u001b[1;34mReturns valid response\u001b[0m\n",
       "✅ \u001b[32mYou responded with a valid response.\u001b[0m\n",
       "You received \u001b[1;36m1.0\u001b[0m of \u001b[1;36m1.0\u001b[0m reward.\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rprint((\"\\n\").join(results)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generated Pet Tricks QnA Logic Task Example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got task with prompt:  Given the following Trick Descriptions with numerical IDs:\n",
      "  ...\n",
      "Fetching response from TOP miner:  197\n",
      "Miner response: 4 ...\n",
      "Scores:  1.75 1.75\n"
     ]
    }
   ],
   "source": [
    "task_id, sub_task_id = pet_tricks_task\n",
    "miner_response, score, max_score, results, correct_answer_optional = evaluate_miner(subnet, vali_dendrite, top_miner_uid, task_id, sub_task_id)\n",
    "print(\"Scores: \", score, max_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The results the miner would see:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not error</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You successfully responded to the request.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.25</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Does not take a long time</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded to the request in </span><span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">0.3985426425933838</span><span style=\"color: #008000; text-decoration-color: #008000\">.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.5</span> reward.\n",
       "<span style=\"color: #000080; text-decoration-color: #000080; font-weight: bold\">Returns expected value</span>\n",
       "✅ <span style=\"color: #008000; text-decoration-color: #008000\">You responded with a valid answer.</span>\n",
       "You received <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> of <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span> reward.\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;34mDoes not error\u001b[0m\n",
       "✅ \u001b[32mYou successfully responded to the request.\u001b[0m\n",
       "You received \u001b[1;36m0.25\u001b[0m of \u001b[1;36m0.25\u001b[0m reward.\n",
       "\u001b[1;34mDoes not take a long time\u001b[0m\n",
       "✅ \u001b[32mYou responded to the request in \u001b[0m\u001b[1;32m0.3985426425933838\u001b[0m\u001b[32m.\u001b[0m\n",
       "You received \u001b[1;36m0.5\u001b[0m of \u001b[1;36m0.5\u001b[0m reward.\n",
       "\u001b[1;34mReturns expected value\u001b[0m\n",
       "✅ \u001b[32mYou responded with a valid answer.\u001b[0m\n",
       "You received \u001b[1;36m1.0\u001b[0m of \u001b[1;36m1.0\u001b[0m reward.\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rprint((\"\\n\").join(results)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "## That's It!\n",
    "\n",
    "You saw how to:\n",
    " 1) Query the top miner uid\n",
    " 2) Demonstrate each reward/penalty mechanism/Scoring of the top miner response\n",
    " 3) Query the subnet 2 different ways (as a validator to a miner and through a registered validator axon)"
   ]
  }
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