forked from phoenix/litellm-mirror
406 lines
13 KiB
Text
Vendored
406 lines
13 KiB
Text
Vendored
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "ZwuaylskLxFu",
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"outputId": "d684d6a3-32fe-4beb-c378-c39134bcf8cc"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting litellm==0.1.363\n",
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" Downloading litellm-0.1.363-py3-none-any.whl (34 kB)\n",
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"Requirement already satisfied: openai<0.28.0,>=0.27.8 in /usr/local/lib/python3.10/dist-packages (from litellm==0.1.363) (0.27.8)\n",
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"Requirement already satisfied: python-dotenv<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from litellm==0.1.363) (1.0.0)\n",
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"Requirement already satisfied: tiktoken<0.5.0,>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from litellm==0.1.363) (0.4.0)\n",
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"Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->litellm==0.1.363) (2.31.0)\n",
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"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->litellm==0.1.363) (4.65.0)\n",
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"Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from openai<0.28.0,>=0.27.8->litellm==0.1.363) (3.8.5)\n",
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"Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken<0.5.0,>=0.4.0->litellm==0.1.363) (2022.10.31)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->litellm==0.1.363) (3.2.0)\n",
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"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->litellm==0.1.363) (3.4)\n",
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"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->litellm==0.1.363) (1.26.16)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.20->openai<0.28.0,>=0.27.8->litellm==0.1.363) (2023.7.22)\n",
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"Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (23.1.0)\n",
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"Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (6.0.4)\n",
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"Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (4.0.2)\n",
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"Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (1.9.2)\n",
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"Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (1.4.0)\n",
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"Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->openai<0.28.0,>=0.27.8->litellm==0.1.363) (1.3.1)\n",
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"Installing collected packages: litellm\n",
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" Attempting uninstall: litellm\n",
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" Found existing installation: litellm 0.1.362\n",
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" Uninstalling litellm-0.1.362:\n",
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" Successfully uninstalled litellm-0.1.362\n",
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"Successfully installed litellm-0.1.363\n"
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]
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}
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],
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"source": [
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"!pip install litellm==\"0.1.363\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"id": "W216G__XL19Q"
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},
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"outputs": [],
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"source": [
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"# @title Import litellm & Set env variables\n",
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"import litellm\n",
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"import os\n",
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"\n",
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"os.environ[\"ANTHROPIC_API_KEY\"] = \" \" #@param"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "ff1lKwUMMLJj",
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"outputId": "bfddf6f8-36d4-45e5-92dc-349083fa41b8"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\n",
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" Result from claude-instant-1 {'choices': [{'finish_reason': 'stop', 'index': 0, 'message': {'role': 'assistant', 'content': \" The Los Angeles Dodgers won the 2020 World Series, defeating the Tampa Bay Rays 4-2. It was the Dodgers' first World Series title since 1988.\"}}], 'created': 1691536677.2676156, 'model': 'claude-instant-1', 'usage': {'prompt_tokens': 30, 'completion_tokens': 32, 'total_tokens': 62}}\n",
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"\n",
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"\n",
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" Result from claude-2 {'choices': [{'finish_reason': 'stop', 'index': 0, 'message': {'role': 'assistant', 'content': ' The Los Angeles Dodgers won'}}], 'created': 1691536677.944753, 'model': 'claude-2', 'usage': {'prompt_tokens': 30, 'completion_tokens': 5, 'total_tokens': 35}}\n"
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]
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}
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],
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"source": [
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"# @title Request Claude Instant-1 and Claude-2\n",
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"messages = [\n",
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" {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
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" {\"role\": \"user\", \"content\": \"Who won the world series in 2020?\"}\n",
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" ]\n",
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"\n",
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"result = litellm.completion('claude-instant-1', messages)\n",
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"print(\"\\n\\n Result from claude-instant-1\", result)\n",
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"result = litellm.completion('claude-2', messages, max_tokens=5, temperature=0.2)\n",
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"print(\"\\n\\n Result from claude-2\", result)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "06hWKnNQMrV-",
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"outputId": "7fdec0eb-d4a9-4882-f9c4-987ff9a31114"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" Here\n",
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"'s\n",
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" a\n",
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" quick\n",
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" overview\n",
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" of\n",
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" how\n",
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" a\n",
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" court\n",
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" case\n",
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" can\n",
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" reach\n",
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" the\n",
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" U\n",
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".\n",
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"S\n",
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".\n",
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" Supreme\n",
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" Court\n",
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":\n",
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"\n",
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"\n",
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"-\n",
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" The\n",
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" case\n",
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" must\n",
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" first\n",
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" be\n",
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" heard\n",
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" in\n",
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" a\n",
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" lower\n",
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" trial\n",
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" court\n",
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" (\n",
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"either\n",
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" a\n",
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" state\n",
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" court\n",
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" or\n",
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" federal\n",
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" district\n",
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" court\n",
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").\n",
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" The\n",
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" trial\n",
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" court\n",
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" makes\n",
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" initial\n",
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" r\n",
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"ulings\n",
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" and\n",
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" produces\n",
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" a\n",
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" record\n",
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" of\n",
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" the\n",
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" case\n",
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".\n",
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"\n",
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"\n",
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"-\n",
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" The\n",
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" losing\n",
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" party\n",
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" can\n",
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" appeal\n",
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" the\n",
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" decision\n",
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" to\n",
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" an\n",
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" appeals\n",
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" court\n",
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" (\n",
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"a\n",
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" state\n",
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" appeals\n",
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" court\n",
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" for\n",
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" state\n",
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" cases\n",
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",\n",
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" or\n",
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" a\n",
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" federal\n",
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" circuit\n",
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" court\n",
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" for\n",
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" federal\n",
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" cases\n",
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").\n",
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" The\n",
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" appeals\n",
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" court\n",
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" reviews\n",
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" the\n",
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" trial\n",
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" court\n",
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"'s\n",
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" r\n",
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"ulings\n",
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" and\n",
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" can\n",
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" affirm\n",
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",\n",
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" reverse\n",
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",\n",
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" or\n",
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" modify\n",
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" the\n",
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" decision\n",
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".\n",
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"\n",
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"\n",
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"-\n",
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" If\n",
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" a\n",
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" party\n",
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" is\n",
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" still\n",
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" unsat\n",
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"isf\n",
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"ied\n",
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" after\n",
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" the\n",
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" appeals\n",
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" court\n",
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" rules\n",
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",\n",
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" they\n",
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" can\n",
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" petition\n",
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" the\n",
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" Supreme\n",
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" Court\n",
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" to\n",
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" hear\n",
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" the\n",
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" case\n",
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" through\n",
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" a\n",
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" writ\n",
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" of\n",
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" cert\n",
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"ior\n",
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"ari\n",
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".\n",
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" \n",
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"\n",
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"\n",
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"-\n",
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" The\n",
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" Supreme\n",
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" Court\n",
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" gets\n",
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" thousands\n",
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" of\n",
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" cert\n",
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" petitions\n",
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" every\n",
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" year\n",
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" but\n",
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" usually\n",
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" only\n",
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" agrees\n",
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" to\n",
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" hear\n",
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" about\n",
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" 100\n",
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"-\n",
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"150\n",
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" of\n",
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" cases\n",
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" that\n",
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" have\n",
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" significant\n",
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" national\n",
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" importance\n",
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" or\n",
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" where\n",
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" lower\n",
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" courts\n",
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" disagree\n",
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" on\n",
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" federal\n",
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" law\n",
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".\n",
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" \n",
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"\n",
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"\n",
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"-\n",
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" If\n",
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" 4\n",
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" out\n",
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" of\n",
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" the\n",
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" 9\n",
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" Just\n",
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"ices\n",
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" vote\n",
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" to\n",
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" grant\n",
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" cert\n",
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" (\n",
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"agree\n",
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" to\n",
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" hear\n",
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" the\n",
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" case\n",
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"),\n",
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" it\n",
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" goes\n",
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" on\n",
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" the\n",
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" Supreme\n",
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" Court\n",
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"'s\n",
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" do\n",
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"cket\n",
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" for\n",
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" arguments\n",
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".\n",
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"\n",
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"\n",
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"-\n",
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" The\n",
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" Supreme\n",
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" Court\n",
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" then\n",
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" hears\n",
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" oral\n",
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" arguments\n",
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",\n",
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" considers\n",
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" written\n",
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" brief\n",
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"s\n",
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",\n",
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" examines\n",
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" the\n",
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" lower\n",
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" court\n",
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" records\n",
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",\n",
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" and\n",
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" issues\n",
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" a\n",
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" final\n",
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" ruling\n",
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" on\n",
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" the\n",
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" case\n",
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",\n",
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" which\n",
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" serves\n",
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" as\n",
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" binding\n",
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" precedent\n"
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]
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}
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],
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"source": [
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"# @title Streaming Example: Request Claude-2\n",
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"messages = [\n",
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" {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
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" {\"role\": \"user\", \"content\": \"how does a court case get to the Supreme Court?\"}\n",
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" ]\n",
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"\n",
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"result = litellm.completion('claude-2', messages, stream=True)\n",
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"for part in result:\n",
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" print(part.choices[0].delta.content or \"\")\n",
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"\n"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3",
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"name": "python3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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