diff --git "a/qa.ipynb" "b/qa.ipynb"
--- "a/qa.ipynb"
+++ "b/qa.ipynb"
@@ -1,44 +1,62 @@
 {
  "cells": [
   {
-   "cell_type": "markdown",
-   "id": "82e03251",
-   "metadata": {},
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "383d6fa9",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-03-22T17:00:55.200350Z",
+     "iopub.status.busy": "2023-03-22T17:00:55.199620Z",
+     "iopub.status.idle": "2023-03-22T17:00:55.219766Z",
+     "shell.execute_reply": "2023-03-22T17:00:55.217755Z"
+    },
+    "tags": [
+     "hide_inp"
+    ]
+   },
+   "outputs": [],
    "source": [
-    "# QA"
+    "desc = \"\"\"\n",
+    "### Question Answering with Retrieval\n",
+    "\n",
+    "Chain that answers questions with embeedding based retrieval. [[Code](https://github.com/srush/MiniChain/blob/main/examples/qa.py)]\n",
+    "\n",
+    "(Adapted from [OpenAI Notebook](https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb).)\n",
+    "\"\"\""
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "e773337a",
+   "id": "51bf7e4c",
    "metadata": {},
    "source": [
-    "Questions answering with embeddings.  Adapted from [OpenAI\n",
-    "Notebook](https://github.com/openai/openai-cookbook/blob/main/examples/Question_answering_using_embeddings.ipynb)."
+    "$"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "id": "86d12b2c",
+   "execution_count": 2,
+   "id": "ab7925a4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:42.801781Z",
-     "iopub.status.busy": "2023-02-27T15:19:42.801407Z",
-     "iopub.status.idle": "2023-02-27T15:19:43.539157Z",
-     "shell.execute_reply": "2023-02-27T15:19:43.538385Z"
+     "iopub.execute_input": "2023-03-22T17:00:55.226549Z",
+     "iopub.status.busy": "2023-03-22T17:00:55.226361Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.643976Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.643271Z"
     }
    },
    "outputs": [],
    "source": [
     "import datasets\n",
     "import numpy as np\n",
-    "from minichain import EmbeddingPrompt, TemplatePrompt, show_log, start_chain"
+    "from minichain import prompt, show, OpenAIEmbed, OpenAI\n",
+    "from manifest import Manifest"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "64a5bf4e",
+   "id": "0725197d",
    "metadata": {},
    "source": [
     "We use Hugging Face Datasets as the database by assigning\n",
@@ -47,22 +65,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "320e7cb9",
+   "execution_count": 3,
+   "id": "d2c2312f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:43.541998Z",
-     "iopub.status.busy": "2023-02-27T15:19:43.541697Z",
-     "iopub.status.idle": "2023-02-27T15:19:43.623765Z",
-     "shell.execute_reply": "2023-02-27T15:19:43.623118Z"
-    },
-    "lines_to_next_cell": 2
+     "iopub.execute_input": "2023-03-22T17:00:56.646848Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.646502Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.714869Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.714309Z"
+    }
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ba9ee3f061c54bff8b58428a0040bf9b",
+       "model_id": "7ec1305895ad44a29163c6c51f641600",
        "version_major": 2,
        "version_minor": 0
       },
@@ -82,7 +99,7 @@
        "})"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -94,73 +111,115 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf93dbd4",
+   "id": "1b2badf2",
+   "metadata": {},
+   "source": [
+    "Fast KNN retieval prompt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "456c5610",
    "metadata": {
-    "lines_to_next_cell": 2
+    "execution": {
+     "iopub.execute_input": "2023-03-22T17:00:56.717227Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.717039Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.720303Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.719854Z"
+    },
+    "lines_to_next_cell": 1
    },
+   "outputs": [],
    "source": [
-    "Fast KNN retieval prompt"
+    "@prompt(OpenAIEmbed())\n",
+    "def get_neighbors(model, inp, k):\n",
+    "    embedding = model(inp)\n",
+    "    res = olympics.get_nearest_examples(\"embeddings\", np.array(embedding), k)\n",
+    "    return res.examples[\"content\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "dc0ae0e5",
+   "execution_count": 5,
+   "id": "61ae797c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:43.626751Z",
-     "iopub.status.busy": "2023-02-27T15:19:43.626367Z",
-     "iopub.status.idle": "2023-02-27T15:19:43.630279Z",
-     "shell.execute_reply": "2023-02-27T15:19:43.629736Z"
+     "iopub.execute_input": "2023-03-22T17:00:56.722475Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.722183Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.725075Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.724640Z"
     },
-    "lines_to_next_cell": 2
+    "lines_to_next_cell": 1
+   },
+   "outputs": [],
+   "source": [
+    "@prompt(OpenAI(),\n",
+    "        template_file=\"qa.pmpt.tpl\")\n",
+    "def get_result(model, query, neighbors):\n",
+    "    return model(dict(question=query, docs=neighbors))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "0d7639e8",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2023-03-22T17:00:56.727258Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.726952Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.729629Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.729172Z"
+    }
    },
    "outputs": [],
    "source": [
-    "class KNNPrompt(EmbeddingPrompt):\n",
-    "    def find(self, out, inp):\n",
-    "        res = olympics.get_nearest_examples(\"embeddings\", np.array(out), 3)\n",
-    "        return {\"question\": inp, \"docs\": res.examples[\"content\"]}"
+    "def qa(query):\n",
+    "    n = get_neighbors(query, 3)\n",
+    "    return get_result(query, n)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "0d87d002",
+   "id": "fb5a255a",
    "metadata": {
     "lines_to_next_cell": 2
    },
    "source": [
-    "QA prompt to ask question with examples"
+    "$"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "b4f90048",
+   "execution_count": 7,
+   "id": "399bbfeb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:43.633024Z",
-     "iopub.status.busy": "2023-02-27T15:19:43.632612Z",
-     "iopub.status.idle": "2023-02-27T15:19:43.636053Z",
-     "shell.execute_reply": "2023-02-27T15:19:43.635457Z"
+     "iopub.execute_input": "2023-03-22T17:00:56.731957Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.731562Z",
+     "iopub.status.idle": "2023-03-22T17:00:56.734263Z",
+     "shell.execute_reply": "2023-03-22T17:00:56.733828Z"
     }
    },
    "outputs": [],
    "source": [
-    "class QAPrompt(TemplatePrompt):\n",
-    "    template_file = \"qa.pmpt.tpl\""
+    "questions = [\"Who won the 2020 Summer Olympics men's high jump?\",\n",
+    "             \"Why was the 2020 Summer Olympics originally postponed?\",\n",
+    "             \"In the 2020 Summer Olympics, how many gold medals did the country which won the most medals win?\",\n",
+    "             \"What is the total number of medals won by France?\",\n",
+    "             \"What is the tallest mountain in the world?\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "51607268",
+   "execution_count": 8,
+   "id": "ba3a7294",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:43.638631Z",
-     "iopub.status.busy": "2023-02-27T15:19:43.638243Z",
-     "iopub.status.idle": "2023-02-27T15:19:48.087701Z",
-     "shell.execute_reply": "2023-02-27T15:19:48.086901Z"
+     "iopub.execute_input": "2023-03-22T17:00:56.736360Z",
+     "iopub.status.busy": "2023-03-22T17:00:56.736081Z",
+     "iopub.status.idle": "2023-03-22T17:00:57.115392Z",
+     "shell.execute_reply": "2023-03-22T17:00:57.114736Z"
     }
    },
    "outputs": [
@@ -168,1694 +227,59 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Italian athlete Gianmarco Tamberi and Qatari athlete Mutaz Essa Barshim emerged as joint winners of the event following a tie between both of them as they cleared 2.37m. Both Tamberi and Barshim agreed to share the gold medal.\n"
+      "Running on local URL:  http://127.0.0.1:7861\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
      ]
-    }
-   ],
-   "source": [
-    "with start_chain(\"qa\") as backend:\n",
-    "    question = \"Who won the 2020 Summer Olympics men's high jump?\"\n",
-    "    prompt = KNNPrompt(backend.OpenAIEmbed()).chain(QAPrompt(backend.OpenAI()))\n",
-    "    result = prompt(question)\n",
-    "    print(result)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "d98b9fce",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:48.092056Z",
-     "iopub.status.busy": "2023-02-27T15:19:48.091273Z",
-     "iopub.status.idle": "2023-02-27T15:19:48.143041Z",
-     "shell.execute_reply": "2023-02-27T15:19:48.142453Z"
     },
-    "tags": [
-     "hide_inp"
-    ]
-   },
-   "outputs": [
     {
      "data": {
       "text/html": [
-       "\n",
-       "<!-- <link rel=\"stylesheet\" href=\"https://cdn.rawgit.com/Chalarangelo/mini.css/v3.0.1/dist/mini-default.min.css\"> -->\n",
-       " <main class=\"container\">\n",
-       "\n",
-       "<h3>QAPrompt</h3>\n",
-       "\n",
-       "<dl>\n",
-       "  <dt>Input:</dt>\n",
-       "  <dd>\n",
-       "<div class=\"highlight\"><pre><span></span><span class=\"p\">{</span><span class=\"s1\">&#39;question&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;Who won the race?&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;docs&#39;</span><span class=\"p\">:</span> <span class=\"p\">[</span><span class=\"s1\">&#39;doc1&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;doc2&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;doc3&#39;</span><span class=\"p\">]}</span>\n",
-       "</pre></div>\n",
-       "\n",
-       "\n",
-       "  </dd>\n",
-       "\n",
-       "  <dt> Full Prompt: </dt>\n",
-       "  <dd>\n",
-       "    <details>\n",
-       "      <summary>Prompt</summary>\n",
-       "      <p>Answer the question as truthfully as possible using the provided context, and if the answer is not contained within the text below, say \"I don't know.\"<br><br>Context:<br><br><br>* doc1<br><br>* doc2<br><br>* doc3<br><br><br> Q: <div style='color:red'>Who won the race?</div><br><br> A: <br></p>\n",
-       "    </details>\n",
-       "  </dd>\n",
-       "\n",
-       "  <dt> Response: </dt>\n",
-       "  <dd>\n",
-       "    Joe Bob\n",
-       "  </dd>\n",
-       "\n",
-       "  <dt>Value:</dt>\n",
-       "  <dd>\n",
-       "<div class=\"highlight\"><pre><span></span><span class=\"n\">Joe</span> <span class=\"n\">Bob</span>\n",
-       "</pre></div>\n",
-       "\n",
-       "  </dd>\n",
-       "</main>\n"
+       "<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": [
-       "HTML(html='\\n<!-- <link rel=\"stylesheet\" href=\"https://cdn.rawgit.com/Chalarangelo/mini.css/v3.0.1/dist/mini-default.min.css\"> -->\\n <main class=\"container\">\\n\\n<h3>QAPrompt</h3>\\n\\n<dl>\\n  <dt>Input:</dt>\\n  <dd>\\n<div class=\"highlight\"><pre><span></span><span class=\"p\">{</span><span class=\"s1\">&#39;question&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;Who won the race?&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;docs&#39;</span><span class=\"p\">:</span> <span class=\"p\">[</span><span class=\"s1\">&#39;doc1&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;doc2&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;doc3&#39;</span><span class=\"p\">]}</span>\\n</pre></div>\\n\\n\\n  </dd>\\n\\n  <dt> Full Prompt: </dt>\\n  <dd>\\n    <details>\\n      <summary>Prompt</summary>\\n      <p>Answer the question as truthfully as possible using the provided context, and if the answer is not contained within the text below, say \"I don\\'t know.\"<br><br>Context:<br><br><br>* doc1<br><br>* doc2<br><br>* doc3<br><br><br> Q: <div style=\\'color:red\\'>Who won the race?</div><br><br> A: <br></p>\\n    </details>\\n  </dd>\\n\\n  <dt> Response: </dt>\\n  <dd>\\n    Joe Bob\\n  </dd>\\n\\n  <dt>Value:</dt>\\n  <dd>\\n<div class=\"highlight\"><pre><span></span><span class=\"n\">Joe</span> <span class=\"n\">Bob</span>\\n</pre></div>\\n\\n  </dd>\\n</main>\\n')"
+       "<IPython.core.display.HTML object>"
       ]
      },
-     "execution_count": 6,
      "metadata": {},
-     "output_type": "execute_result"
+     "output_type": "display_data"
     }
    ],
    "source": [
+    "gradio = show(qa,\n",
+    "              examples=questions,\n",
+    "              subprompts=[get_neighbors, get_result],\n",
+    "              description=desc,\n",
+    "              code=open(\"qa.py\", \"r\").read().split(\"$\")[1].strip().strip(\"#\").strip(),\n",
+    "              )\n",
+    "if __name__ == \"__main__\":\n",
+    "    gradio.launch()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "524d2c29",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "500edc1f",
+   "metadata": {},
+   "source": [
+    "# + tags=[\"hide_inp\"]\n",
     "QAPrompt().show(\n",
     "    {\"question\": \"Who won the race?\", \"docs\": [\"doc1\", \"doc2\", \"doc3\"]}, \"Joe Bob\"\n",
-    ")"
+    ")\n",
+    "# -"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "27d24e28",
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2023-02-27T15:19:48.146156Z",
-     "iopub.status.busy": "2023-02-27T15:19:48.145762Z",
-     "iopub.status.idle": "2023-02-27T15:19:48.294393Z",
-     "shell.execute_reply": "2023-02-27T15:19:48.293653Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[38;5;15m6483e094-0601-4a93-8394-c753301f1a18\u001b[1m\u001b[0m\n",
-      "└── \u001b[38;5;5m<class '__main__.KNNPrompt'>\u001b[0m/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:43Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.570s\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mInput Function\u001b[0m/2/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:43Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.000s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4minput\u001b[0m: Who won the 2020 Summer Olympics men's high jump?\u001b[0m\n",
-      "    │   └── \u001b[38;5;5mInput Function\u001b[0m/2/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:43Z\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mPrompted\u001b[0m/3/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:43Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.565s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4mprompt\u001b[0m: Who won the 2020 Summer Olympics men's high jump?\u001b[0m\n",
-      "    │   └── \u001b[38;5;5mPrompted\u001b[0m/3/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mResult\u001b[0m/4/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.005s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4mresult\u001b[0m: \u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m0\u001b[0m: 0.011016231030225754\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1\u001b[0m: -0.0031887420918792486\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m2\u001b[0m: 0.014024118892848492\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m3\u001b[0m: -0.022197451442480087\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m4\u001b[0m: 0.007824316620826721\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m5\u001b[0m: 0.027616726234555244\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m6\u001b[0m: -0.02050948143005371\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m7\u001b[0m: -0.026829853653907776\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m8\u001b[0m: -0.011498508043587208\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m9\u001b[0m: -0.005558881442993879\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m10\u001b[0m: 0.015267887152731419\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1463\u001b[0m: -0.007684709504246712\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1465\u001b[0m: -0.0018640656489878893\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1466\u001b[0m: -0.018542297184467316\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1467\u001b[0m: 0.027210598811507225\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1468\u001b[0m: 0.011790413409471512\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1469\u001b[0m: -0.0016292727086693048\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1470\u001b[0m: 0.004413472954183817\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1471\u001b[0m: -0.009118850342929363\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1472\u001b[0m: 0.009175961837172508\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1473\u001b[0m: 0.010679906234145164\u001b[0m\n",
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-      "    │   ��   ├── \u001b[38;5;4m1475\u001b[0m: -0.02063639648258686\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1481\u001b[0m: -0.018504222854971886\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1482\u001b[0m: 0.007215123623609543\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1483\u001b[0m: -0.011187566444277763\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1484\u001b[0m: -0.0037947616074234247\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1486\u001b[0m: 3.628978811320849e-05\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1487\u001b[0m: 0.052796684205532074\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1489\u001b[0m: -0.0043976083397865295\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1491\u001b[0m: -0.0002260675246361643\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1492\u001b[0m: 0.02561146765947342\u001b[0m\n",
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-      "    │   │   ├── \u001b[38;5;4m1495\u001b[0m: -0.048836931586265564\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1496\u001b[0m: -0.009068083949387074\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1497\u001b[0m: 0.002593827433884144\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1498\u001b[0m: -0.004245310090482235\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1499\u001b[0m: -0.011536583304405212\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1500\u001b[0m: 0.004607018083333969\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1501\u001b[0m: -0.019151488319039345\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1502\u001b[0m: -0.0019782891031354666\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1503\u001b[0m: 0.015610557980835438\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1504\u001b[0m: 0.022387824952602386\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1505\u001b[0m: -0.04741548374295235\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1506\u001b[0m: 0.0008186024497263134\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1507\u001b[0m: 0.0338609516620636\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1508\u001b[0m: -0.004549906589090824\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1509\u001b[0m: 0.009309222921729088\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1510\u001b[0m: 0.021892854943871498\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1511\u001b[0m: -0.001743496279232204\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1512\u001b[0m: 0.012450371868908405\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1513\u001b[0m: 0.02125827968120575\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1514\u001b[0m: 0.00810987502336502\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1515\u001b[0m: -0.004318286199122667\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1516\u001b[0m: -0.011403322219848633\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1517\u001b[0m: 0.004702204838395119\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1518\u001b[0m: -0.005130542907863855\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1519\u001b[0m: -0.018669212237000465\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1520\u001b[0m: -0.013744905591011047\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1521\u001b[0m: 0.03401324898004532\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1522\u001b[0m: -0.03388633206486702\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1523\u001b[0m: 0.0006504399352706969\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1524\u001b[0m: 0.00017609470523893833\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1525\u001b[0m: 0.013046872802078724\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1526\u001b[0m: 0.003867737716063857\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1527\u001b[0m: -0.007297618314623833\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1528\u001b[0m: 0.015674015507102013\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1529\u001b[0m: -0.005381200462579727\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1530\u001b[0m: -0.01728583686053753\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1531\u001b[0m: 0.019760681316256523\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1532\u001b[0m: 0.003734476864337921\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1533\u001b[0m: -0.0210679080337286\u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4m1534\u001b[0m: 0.002953949151560664\u001b[0m\n",
-      "    │   │   └── \u001b[38;5;4m1535\u001b[0m: -0.016092834994196892\u001b[0m\n",
-      "    │   └── \u001b[38;5;5mResult\u001b[0m/4/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m\n",
-      "    └── \u001b[38;5;5m<class '__main__.KNNPrompt'>\u001b[0m/5\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m\n",
-      "\n",
-      "\u001b[38;5;15m16863091-c5ac-408a-8ccc-46724b433a5d\u001b[1m\u001b[0m\n",
-      "└── \u001b[38;5;5m<class '__main__.QAPrompt'>\u001b[0m/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m3.869s\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mInput Function\u001b[0m/2/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.003s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4minput\u001b[0m: \u001b[0m\n",
-      "    │   │   ├── \u001b[38;5;4mdocs\u001b[0m: \u001b[0m\n",
-      "    │   │   │   ├── \u001b[38;5;4m0\u001b[0m: The men's high jump event at the 2020 Summer Olympics took place between 30 July and 1 August 2021 at the Olympic Stadium. 33 athletes from 24 nations competed; the total possible number depended on how many nations would use universality places to enter athletes in addition to the 32 qualifying through mark or ranking (no universality places were used in 2021). Italian athlete Gianmarco Tamberi along with Qatari athlete Mutaz Essa Barshim emerged as joint winners of the event following a tie between both of them as they cleared 2.37m. Both Tamberi and Barshim agreed to share the gold medal in a rare instance where the athletes of different nations had agreed to share the same medal in the history of Olympics. Barshim in particular was heard to ask a competition official \"Can we have two golds?\" in response to being offered a 'jump off'. Maksim Nedasekau of Belarus took bronze. The medals were the first ever in the men's high jump for Italy and Belarus, the first gold in the men's high jump for Italy and Qatar, and the third consecutive medal in the men's high jump for Qatar (all by Barshim). Barshim became only the second man to earn three medals in high jump, joining Patrik Sjöberg of Sweden (1984 to 1992).\u001b[0m\n",
-      "    │   │   │   ├── \u001b[38;5;4m1\u001b[0m: The men's long jump event at the 2020 Summer Olympics took place between 31 July and 2 August 2021 at the Japan National Stadium. Approximately 35 athletes were expected to compete; the exact number was dependent on how many nations use universality places to enter athletes in addition to the 32 qualifying through time or ranking (1 universality place was used in 2016). 31 athletes from 20 nations competed. Miltiadis Tentoglou won the gold medal, Greece's first medal in the men's long jump. Cuban athletes Juan Miguel Echevarría and Maykel Massó earned silver and bronze, respectively, the nation's first medals in the event since 2008.\u001b[0m\n",
-      "    │   │   │   └── \u001b[38;5;4m2\u001b[0m: The men's pole vault event at the 2020 Summer Olympics took place between 31 July and 3 August 2021 at the Japan National Stadium. 29 athletes from 18 nations competed. Armand Duplantis of Sweden won gold, with Christopher Nilsen of the United States earning silver and Thiago Braz of Brazil taking bronze. It was Sweden's first victory in the event and first medal of any color in the men's pole vault since 1952. Braz, who had won in 2016, became the ninth man to earn multiple medals in the pole vault.\u001b[0m\n",
-      "    │   │   └── \u001b[38;5;4mquestion\u001b[0m: Who won the 2020 Summer Olympics men's high jump?\u001b[0m\n",
-      "    │   └── \u001b[38;5;5mInput Function\u001b[0m/2/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mPrompted\u001b[0m/3/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:44Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m3.865s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4mprompt\u001b[0m: Answer the question as truthfully as possible using the provided context, and if the answer is not contained within the text below, say \"I don't know.\"⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   Context:⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   * The men's high jump event at the 2020 Summer Olympics took place between 30 July and 1 August 2021 at the Olympic Stadium. 33 athletes from 24 nations competed; the total possible number depended on how many nations would use universality places to enter athletes in addition to the 32 qualifying through mark or ranking (no universality places were used in 2021). Italian athlete Gianmarco Tamberi along with Qatari athlete Mutaz Essa Barshim emerged as joint winners of the event following a tie between both of them as they cleared 2.37m. Both Tamberi and Barshim agreed to share the gold medal in a rare instance where the athletes of different nations had agreed to share the same medal in the history of Olympics. Barshim in particular was heard to ask a competition official \"Can we have two golds?\" in response to being offered a 'jump off'. Maksim Nedasekau of Belarus took bronze. The medals were the first ever in the men's high jump for Italy and Belarus, the first gold in the men's high jump for Italy and Qatar, and the third consecutive medal in the men's high jump for Qatar (all by Barshim). Barshim became only the second man to earn three medals in high jump, joining Patrik Sjöberg of Sweden (1984 to 1992).⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   * The men's long jump event at the 2020 Summer Olympics took place between 31 July and 2 August 2021 at the Japan National Stadium. Approximately 35 athletes were expected to compete; the exact number was dependent on how many nations use universality places to enter athletes in addition to the 32 qualifying through time or ranking (1 universality place was used in 2016). 31 athletes from 20 nations competed. Miltiadis Tentoglou won the gold medal, Greece's first medal in the men's long jump. Cuban athletes Juan Miguel Echevarría and Maykel Massó earned silver and bronze, respectively, the nation's first medals in the event since 2008.⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   * The men's pole vault event at the 2020 Summer Olympics took place between 31 July and 3 August 2021 at the Japan National Stadium. 29 athletes from 18 nations competed. Armand Duplantis of Sweden won gold, with Christopher Nilsen of the United States earning silver and Thiago Braz of Brazil taking bronze. It was Sweden's first victory in the event and first medal of any color in the men's pole vault since 1952. Braz, who had won in 2016, became the ninth man to earn multiple medals in the pole vault.⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │    Q: Who won the 2020 Summer Olympics men's high jump?⏎\n",
-      "    │   │   ⏎\n",
-      "    │   │    A: ⏎\n",
-      "    │   │   \u001b[0m\n",
-      "    │   └── \u001b[38;5;5mPrompted\u001b[0m/3/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:48Z\u001b[2m\u001b[0m\n",
-      "    ├── \u001b[38;5;5mResult\u001b[0m/4/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:48Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m0.000s\u001b[2m\u001b[0m\n",
-      "    │   ├── \u001b[38;5;4mresult\u001b[0m: Italian athlete Gianmarco Tamberi and Qatari athlete Mutaz Essa Barshim emerged as joint winners of the event following a tie between both of them as they cleared 2.37m. Both Tamberi and Barshim agreed to share the gold medal.\u001b[0m\n",
-      "    │   └── \u001b[38;5;5mResult\u001b[0m/4/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:48Z\u001b[2m\u001b[0m\n",
-      "    └── \u001b[38;5;5m<class '__main__.QAPrompt'>\u001b[0m/5\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:48Z\u001b[2m\u001b[0m\n",
-      "\n",
-      "\u001b[38;5;15m8f704116-b88c-4e34-a26a-196b09fbe252\u001b[1m\u001b[0m\n",
-      "└── \u001b[38;5;5mqa\u001b[0m/1\u001b[0m ⇒ \u001b[38;5;2mstarted\u001b[0m \u001b[38;5;15m2023-02-27 15:19:43Z\u001b[2m\u001b[0m ⧖ \u001b[38;5;4m4.445s\u001b[2m\u001b[0m\n",
-      "    └── \u001b[38;5;5mqa\u001b[0m/2\u001b[0m ⇒ \u001b[38;5;2msucceeded\u001b[0m \u001b[38;5;15m2023-02-27 15:19:48Z\u001b[2m\u001b[0m\n",
-      "\n"
-     ]
-    }
-   ],
+   "cell_type": "markdown",
+   "id": "599833ea",
+   "metadata": {},
    "source": [
     "show_log(\"qa.log\")"
    ]
@@ -1885,23 +309,7 @@
   "widgets": {
    "application/vnd.jupyter.widget-state+json": {
     "state": {
-     "1ee1ec3a4c414bd48972ae72e83cb441": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "ProgressStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "ProgressStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "bar_color": null,
-       "description_width": ""
-      }
-     },
-     "21967c4930bd4a16875d93a9dd0b899d": {
+     "0e04d7f51add4bc0a2d621f6fb5d59a8": {
       "model_module": "@jupyter-widgets/base",
       "model_module_version": "2.0.0",
       "model_name": "LayoutModel",
@@ -1954,43 +362,30 @@
        "width": null
       }
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-     "44721359c38d4a5e9dff7836beac706b": {
-      "model_module": "@jupyter-widgets/controls",
-      "model_module_version": "2.0.0",
-      "model_name": "HTMLStyleModel",
-      "state": {
-       "_model_module": "@jupyter-widgets/controls",
-       "_model_module_version": "2.0.0",
-       "_model_name": "HTMLStyleModel",
-       "_view_count": null,
-       "_view_module": "@jupyter-widgets/base",
-       "_view_module_version": "2.0.0",
-       "_view_name": "StyleView",
-       "background": null,
-       "description_width": "",
-       "font_size": null,
-       "text_color": null
-      }
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