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Zhi Zhou
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Add in_context_chatcompletions_example_restapi sample code
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‎Basic_Samples/GPT-4V/config.json‎

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"OPENAI_API_BASE":"https://<Your Azure Resource Name>.openai.azure.com",
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"OPENAI_API_VERSION":"<OpenAI API Version>",
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"VISION_API_ENDPOINT": "https://<Your Azure Vision Resource Name>.cognitiveservices.azure.com"
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"VISION_API_ENDPOINT": "https://<Your Azure Vision Resource Name>.cognitiveservices.azure.com",
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"AZURE_SEARCH_SERVICE_ENDPOINT": "https://<Your Azure Search Resource Name>.search.windows.net",
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"AZURE_SEARCH_INDEX_NAME": "<Your Azure Search Index Name>"
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}

‎Basic_Samples/GPT-4V/in_context_chatcompletions_example_restapi.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "759f9ec0",
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"metadata": {},
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"source": [
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"<h1 align =\"center\"> REST API In Context Learning Samples</h1>\n",
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"<hr>\n",
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" \n",
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"# Chat Completions"
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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": 1,
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"id": "f4b3d21a",
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"metadata": {},
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"outputs": [],
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"source": [
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"import json\n",
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"import os\n",
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"import requests\n",
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"import base64"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5b2d4a0f",
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"metadata": {},
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"source": [
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"### Setup Parameters\n",
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"\n",
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"\n",
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"Here we will load the configurations from _config.json_ file to setup search_service_endpoint, search_index_name, search_query_key, deployment_name, openai_api_base, openai_api_key and openai_api_version."
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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": 3,
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"id": "fd85fb30",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load config values\n",
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"with open(r'config.json') as config_file:\n",
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" config_details = json.load(config_file)\n",
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"\n",
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"# Setting up the Azure Search service endpoint.e.g. https://<your search service name>.search.windows.net \n",
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"search_service_endpoint = config_details['AZURE_SEARCH_SERVICE_ENDPOINT']\n",
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"\n",
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"# Setting up the Azure Search service index\n",
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"search_index_name = config_details['AZURE_SEARCH_INDEX_NAME']\n",
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"\n",
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"# Setting up the Azure Search service query key\n",
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"search_query_key = os.getenv(\"AZURE_SEARCH_QUERY_KEY\")\n",
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"\n",
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"# Setting up the deployment name\n",
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"deployment_name = config_details['GPT-4V_MODEL']\n",
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"\n",
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"# The base URL for your Azure OpenAI resource. e.g. \"https://<your resource name>.openai.azure.com\"\n",
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"openai_api_base = config_details['OPENAI_API_BASE']\n",
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"\n",
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"# The API key for your Azure OpenAI resource.\n",
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"openai_api_key = os.getenv(\"OPENAI_API_KEY\")\n",
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"\n",
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"# Currently OPENAI API have the following versions available: 2022-12-01. All versions follow the YYYY-MM-DD date structure.\n",
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"openai_api_version = config_details['OPENAI_API_VERSION']"
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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": 4,
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"id": "b6165c63",
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"metadata": {},
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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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"It's a Gala apple.\n"
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]
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}
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],
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"source": [
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"# Create Azure Search index (the link will be updated once it goes public)\n",
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"# https://github.com/zhizhoualan/cognitive-search-vector-pr/blob/main/demo-python/code/azure-search-vector-image-index-creation-python-sample.ipynb\n",
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"\n",
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"# System messages and user prompt\n",
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"sys_message = \"You are an AI assistant that helps people find information.\"\n",
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"user_prompt = \"What is the type of this apple?\"\n",
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"\n",
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"# Encode the image in base64\n",
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"image_file_path = \"../../common/images/test_Gala.jpeg\" # Update with your image path\n",
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"with open(image_file_path, 'rb') as image_file:\n",
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" encoded_image = base64.b64encode(image_file.read()).decode('ascii')\n",
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" \n",
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"# Construct the API request URL\n",
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"api_url = f\"{openai_api_base}/openai/deployments/{deployment_name}/extensions/chat/completions?api-version={openai_api_version}\"\n",
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"\n",
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"# Including the api-key in HTTP headers\n",
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"headers = {\n",
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" \"Content-Type\": \"application/json\",\n",
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" \"api-key\": openai_api_key,\n",
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"}\n",
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"\n",
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"# Payload for the request\n",
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"payload = {\n",
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" \"dataSources\": [\n",
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" {\n",
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" \"type\": \"AzureCognitiveSearch\",\n",
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" \"parameters\": {\n",
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" \"endpoint\": search_service_endpoint,\n",
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" \"key\": search_query_key,\n",
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" \"indexName\": search_index_name\n",
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" }\n",
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" }\n",
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" ],\n",
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" \"messages\": [\n",
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" {\n",
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" \"role\": \"system\",\n",
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" \"content\": [\n",
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" sys_message\n",
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" ]\n",
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" },\n",
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" {\n",
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" \"role\": \"user\",\n",
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" \"content\": [\n",
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" user_prompt, # Pass the prompt\n",
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" {\n",
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" \"image\": encoded_image #Pass the encoded image\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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" \"temperature\": 0.7,\n",
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" \"top_p\": 0.95,\n",
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" \"max_tokens\": 800\n",
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"}\n",
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"\n",
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"# Send the request and handle the response\n",
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"try:\n",
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" response = requests.post(api_url, headers=headers, json=payload)\n",
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" response.raise_for_status() # Raise an error for bad HTTP status codes\n",
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" response_content = response.json()\n",
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" print(response_content['choices'][0]['message']['content'])\n",
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"except requests.RequestException as e:\n",
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" raise SystemExit(f\"Failed to make the request. Error: {e}\")"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.18"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎common/images/test_Gala.jpeg‎

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