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ilyesAj/Bedrock-api.json

Created August 28, 2025 13:05
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Bedrock api postman collection
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Bedrock-api.json
{
"info": {
"_postman_id": "a30303a4-d220-44ec-9abb-a2ba83ef54bf",
"name": "Amazon Bedrock API",
"description": "Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI. Using Amazon Bedrock, you can easily experiment with and evaluate top FMs for your use case, privately customize them with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that execute tasks using your enterprise systems and data sources. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.\n\nThe Amazon Bedrock API Collection provides detailed information about the Amazon Bedrock API actions and their parameters and few use cases to help you get started.\n\n**Pre requisites:**\n\n1. You must have an AWS account. To create an AWS account, go to [https://console.aws.amazon.com/](https://console.aws.amazon.com/) and choose Create a new AWS account.\n \n2. Make sure that the account that you use to sign in to the AWS Management Console can create new IAM policies and roles.\n \n3. You can create a IAM user here [https://console.aws.amazon.com/iam/](https://console.aws.amazon.com/iam/) and attach the example inline policy to it. When you create the user, IAM provides a set of credentials that allow Postman to carry out Amazon Bedrock API operations.\n \n ``` json\n {\n \"Version\": \"2012-10-17\",\n \"Statement\": [\n {\n \"Sid\": \"BedrockFullAccess\",\n \"Effect\": \"Allow\",\n \"Action\": [\"bedrock:*\"],\n \"Resource\": \"*\"\n }\n ]\n }\n \n ```\n \n4. On the IAM console, in the navigation pane, choose Users. Select the user created, and then select the Security credentials tab. In the Access keys section, choose Create access key.\n \n5. Now you can use the access key and secret to [Authenticate with AWS Signature in Postman](https://learning.postman.com/docs/sending-requests/authorization/aws-signature/).\n \n6. Note you must request access to Amazon Bedrock foundation models before using them. Details here: [https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html)",
"schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json",
"_exporter_id": "16344149",
"_collection_link": "https://www.postman.com/postman/amazon-bedrock/collection/nz66lrc/amazon-bedrock-api?action=share&source=collection_link&creator=16344149"
},
"item": [
{
"name": "Actions",
"item": [
{
"name": "Prompts",
"item": [
{
"name": "{prompt_id}",
"item": [
{
"name": "GetPrompt: Retrieves the prompt for the specified prompt Id",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/playgrounds/prompts/:prompt_Id",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"playgrounds",
"prompts",
":prompt_Id"
],
"variable": [
{
"key": "prompt_Id",
"value": "I8NI3Vt370",
"description": "The Id of the prompt to retrieve"
}
]
}
},
"response": []
}
]
},
{
"name": "ListPrompts: Returns a list of all prompts stored in your prompt history",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/playgrounds/prompts?bookmarked=false&maxResults=10&Modality=TEXT_TO_TEXT",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"playgrounds",
"prompts"
],
"query": [
{
"key": "bookmarked",
"value": "false",
"description": "Return only the bookmarked prompts.\n\n"
},
{
"key": "maxResults",
"value": "10",
"description": "Maximum number of results to include in the response.\n\n"
},
{
"key": "Modality",
"value": "TEXT_TO_TEXT",
"description": "Modality of the prompt.\n\n"
}
]
}
},
"response": []
},
{
"name": "UpdatePrompt: Updates the bookmarked state of a previously saved prompt",
"request": {
"method": "PATCH",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"bookmarked\": true\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/playgrounds/prompts/:promptId ",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"playgrounds",
"prompts",
":promptId "
],
"variable": [
{
"key": "promptId ",
"value": "I8NI3Vt370"
}
]
}
},
"response": []
},
{
"name": "DeletePrompt: Delete the prompt with the specified prompt Id",
"request": {
"method": "DELETE",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/playgrounds/prompts/:promptId",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"playgrounds",
"prompts",
":promptId"
],
"variable": [
{
"key": "promptId",
"value": "I8NI3Vt370",
"description": "The Id of the prompt to delete.\n\nLength Constraints: Minimum length of 1. Maximum length of 36.\n\nPattern: ^[A-Za-z0-9]+(?:-[A-Za-z0-9]+)*$\n\nRequired: Yes"
}
]
}
},
"response": []
}
]
},
{
"name": "Fine-tune-jobs",
"item": [
{
"name": "{job_Identifier}",
"item": [
{
"name": "Stop",
"item": [
{
"name": "StopModelCustomizationJob: Stops an active model customization job",
"request": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/model-customization-jobs/:job_Identifier/stop",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model-customization-jobs",
":job_Identifier",
"stop"
],
"variable": [
{
"key": "job_Identifier",
"value": "",
"description": "Job identifier of the job to stop.\n\n"
}
]
}
},
"response": [
{
"name": "OK",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.us-east-1.amazonaws.com/fine-tunes/:fine_tune_id/cancel",
"protocol": "https",
"host": [
"bedrock",
"us-east-1",
"amazonaws",
"com"
],
"path": [
"fine-tunes",
":fine_tune_id",
"cancel"
],
"variable": [
{
"key": "fine_tune_id"
}
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
}
]
}
]
},
{
"name": "GetModelCustomizationJob: Retrieves the properties associated with a model-customization job, including the status of the job",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/model-customization-jobs/:job_Identifier",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model-customization-jobs",
":job_Identifier"
],
"variable": [
{
"key": "job_Identifier",
"value": "",
"description": "Identifier for the customization job"
}
]
}
},
"response": [
{
"name": "OK",
"originalRequest": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.us-east-1.amazonaws.com/fine-tunes",
"protocol": "https",
"host": [
"bedrock",
"us-east-1",
"amazonaws",
"com"
],
"path": [
"fine-tunes"
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
}
]
}
]
},
{
"name": "CreateModelCustomizationJob:Creates a fine-tuning job to customize a base model",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\n \"baseModelIdentifier\": \"string\",\n \"clientRequestToken\": \"string\",\n \"customModelKmsKeyId\": \"string\",\n \"customModelName\": \"string\",\n \"customModelTags\": [ \n { \n \"key\": \"string\",\n \"value\": \"string\"\n }\n ],\n \"hyperParameters\": { \n \"string\" : \"string\" \n },\n \"jobName\": \"string\",\n \"jobTags\": [ \n { \n \"key\": \"string\",\n \"value\": \"string\"\n }\n ],\n \"outputDataConfig\": { \n \"s3Uri\": \"string\"\n },\n \"roleArn\": \"string\",\n \"trainingDataConfig\": { \n \"s3Uri\": \"string\"\n },\n \"validationDataConfig\": { \n \"validators\": [ \n { \n \"s3Uri\": \"string\"\n }\n ]\n },\n \"vpcConfig\": { \n \"securityGroupIds\": [ \"string\" ],\n \"subnetIds\": [ \"string\" ]\n }\n}",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/model-customization-jobs",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model-customization-jobs"
]
}
},
"response": [
{
"name": "OK",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\n \"training_file\": \"<string>\",\n \"validation_file\": \"<string>\",\n \"model\": \"curie\",\n \"n_epochs\": 4,\n \"batch_size\": null,\n \"learning_rate_multiplier\": null,\n \"prompt_loss_weight\": 0.01,\n \"compute_classification_metrics\": false,\n \"classification_n_classes\": null,\n \"classification_positive_class\": null,\n \"classification_betas\": null,\n \"suffix\": null\n}",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock.us-east-1.amazonaws.com/fine-tunes",
"protocol": "https",
"host": [
"bedrock",
"us-east-1",
"amazonaws",
"com"
],
"path": [
"fine-tunes"
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
}
]
},
{
"name": "ListModelCustomizationJobs: Returns a list of model customization jobs that you have submitted. You can filter the jobs to return based on one or more criteria",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/model-customization-jobs",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model-customization-jobs"
],
"query": [
{
"key": "creationTimeAfter",
"value": "",
"description": "Return customization jobs created after the specified time.\n\n",
"disabled": true
},
{
"key": "creationTimeBefore",
"value": "",
"description": "Return customization jobs created before the specified time.\n\n",
"disabled": true
},
{
"key": "maxResults",
"value": "",
"description": "Maximum number of results to return in the response.\n\n",
"disabled": true
},
{
"key": "nameContains",
"value": "",
"description": "Return customization jobs only if the job name contains these characters.\n\n",
"disabled": true
},
{
"key": "nextToken",
"value": "",
"description": "Continuation token from the previous response, for Amazon Bedrock to list the next set of results.\n\n",
"disabled": true
},
{
"key": "sortBy",
"value": "",
"description": "The field to sort by in the returned list of jobs.\n\n",
"disabled": true
},
{
"key": "sortOrder",
"value": "",
"description": "The sort order of the results.\n\n",
"disabled": true
},
{
"key": "statusEquals",
"value": "",
"description": "Return customization jobs with the specified status.\n\n",
"disabled": true
}
]
}
},
"response": []
}
]
},
{
"name": "Models",
"item": [
{
"name": "{model_Identifier}",
"item": [
{
"name": "GetCustomModel: Get the properties associated with a Bedrock custom model that you have created",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/custom-models/:model_Identifier",
"protocol": "https",
"host": [
"bedrock",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"custom-models",
":model_Identifier"
],
"variable": [
{
"key": "model_Identifier",
"value": "",
"description": "Name or ARN of the custom model"
}
]
}
},
"response": []
},
{
"name": "InvokeModel: Invokes the specified Bedrock model to run inference using the input provided in the request body",
"request": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "X-Amzn-Bedrock-Save",
"value": "true",
"description": "Determines whether to save this prompt in your prompt history. Enter true or false. The default is false\n"
}
],
"body": {
"mode": "raw",
"raw": " {\"prompt\": \"\\n\\nHuman:Hello \\n\\nAssistant:\",\r\n \"temperature\": 1,\r\n \"top_p\": 1,\r\n \"top_k\": 500,\r\n \"max_tokens_to_sample\": 500,\r\n \"stop_sequences\": [\"\\n\\nHuman:\"]\r\n }",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "anthropic.claude-v2",
"description": "Identifier of the model"
}
]
}
},
"response": [
{
"name": "amazon.titan-tg1-large",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true",
"type": "text"
},
{
"key": "Content-Type",
"value": "application/json",
"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Hello world\"} ",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
"amazon.titan-tg1-large",
"invoke"
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
},
{
"name": "amazon.titan-e1t-medium",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Amazon Bedrock supports foundation models from industry-leading providers such as AI21 Labs, Anthropic, Stability AI, and Amazon. Choose the model that is best suited to achieving your unique goals.\"\n } ",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "amazon.titan-embed-text-v1",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-e1t-medium"
}
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Date",
"value": "Fri, 15 Sep 2023 19:54:38 GMT"
},
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Content-Length",
"value": "46382"
},
{
"key": "Connection",
"value": "keep-alive"
},
{
"key": "x-amzn-RequestId",
"value": "e019dd5d-c2d9-4cc7-9b63-7b3e7dbecbd9"
}
],
"cookie": [],
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{
"name": "anthropic.claude-v2",
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},
{
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},
{
"name": "ListFoundationModels: List of Bedrock foundation models that you can use",
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"method": "GET",
"header": [
{
"key": "Accept",
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],
"url": {
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},
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},
{
"name": "ListCustomModels: Returns a list of the custom models that you have created with the CreateModelCustomizationJob operation",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
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}
],
"url": {
"raw": "https://bedrock.{{AWS_Region}}.amazonaws.com/custom-models",
"protocol": "https",
"host": [
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],
"path": [
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],
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},
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"key": "creationTimeBefore",
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},
{
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"disabled": true
},
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"key": "nameContains",
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},
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"value": "",
"description": "The field to sort by in the returned list of models.\n\n",
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},
{
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"value": "",
"description": "The sort order of the results.\n\n",
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}
]
}
},
"response": []
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}
],
"description": "The following actions are supported by Bedrock API:\n\n- [CreateModelCustomizationJob](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_CreateModelCustomizationJob.html)\n \n- [DeleteCustomModel](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_DeleteCustomModel.html)\n \n- [DeletePrompt](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_DeletePrompt.html)\n \n- [GetCustomModel](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_GetCustomModel.html)\n \n- [GetModelCustomizationJob](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_GetModelCustomizationJob.html)\n \n- [GetPrompt](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_GetPrompt.html)\n \n- [InvokeModel](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_InvokeModel.html)\n \n- [InvokeModelWithResponseStream](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_InvokeModelWithResponseStream.html)\n \n- [ListCustomModels](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_ListCustomModels.html)\n \n- [ListFoundationModels](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_ListFoundationModels.html)\n \n- [ListModelCustomizationJobs](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_ListModelCustomizationJobs.html)\n \n- [ListPrompts](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_ListPrompts.html)\n \n- [StopModelCustomizationJob](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_StopModelCustomizationJob.html)\n \n- [UpdatePrompt](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_UpdatePrompt.html)"
},
{
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{
"name": "Embeddings",
"item": [
{
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"method": "POST",
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{
"key": "Content-Type",
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},
{
"key": "Accept",
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"raw": {
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}
]
}
},
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},
{
"name": "CohereEmbedding",
"request": {
"method": "POST",
"header": [],
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
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],
"path": [
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":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "cohere.embed-english-v3",
"description": "Cohere Embedding model under Amazon Bedrock have the following IDs:\ncohere.embed-english-v3\ncohere.embed-multilingual-v3"
}
]
}
},
"response": []
}
]
},
{
"name": "Generation",
"item": [
{
"name": "Generate Text",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"prompt\": \"\\n\\nHuman:story of two dogs\\n\\nAssistant:\"\n,\"max_tokens_to_sample\":100\n}",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
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"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "anthropic.claude-v2",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": [
{
"name": "Generate Email Content",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true",
"type": "text"
},
{
"key": "Content-Type",
"value": "application/json",
"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"inputText\": \"Command: Write an email from Bob, Customer Service Manager, to the customer \\\"John Doe\\\" who provided negative feedback on the service provided by our customer support engineer\",\r\n \"textGenerationConfig\": {\r\n \"maxTokenCount\": 4096,\r\n \"stopSequences\": [],\r\n \"temperature\": 0,\r\n \"topP\": 0.9\r\n }\r\n}\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
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"amazonaws",
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],
"path": [
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}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
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"value": "application/json"
}
],
"cookie": [],
"body": ""
},
{
"name": "Zero Shot Generation-Email Content",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
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"type": "text"
},
{
"key": "Content-Type",
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"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"inputText\": \"\\\"Write an email from Bob, Customer Service Manager,to the customer \\\"John Doe\\\" that provided negative feedback on the service provided by our customer support engineer.\\n\\nHuman:\",\r\n \"textGenerationConfig\": {\r\n \"maxTokenCount\": 4096,\r\n \"stopSequences\": [],\r\n \"temperature\": 0,\r\n \"topP\": 0.9\r\n }\r\n}\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
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],
"path": [
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}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
},
{
"name": "Contextual Generation-Email Content",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
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"type": "text"
},
{
"key": "Content-Type",
"value": "application/json",
"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"inputText\": \" Scenerio: \\\"feedback received from the customer: Hello Bob, I am very disappointed with the recent experience I had when I called your customer support.I was expecting an immediate call back but it took three days for us to get a call back.The first suggestion to fix the problem was incorrect. Ultimately the problem was fixed after three days.We are very unhappy with the response provided and may consider taking our business elsewhere\\\" \\n Task:Create an apology email from the Service Manager Bob to John Doe \",\r\n \"textGenerationConfig\": { \r\n \"maxTokenCount\": 4096,\r\n \"stopSequences\": [],\r\n \"temperature\": 0,\r\n \"topP\": 0.9\r\n }\r\n}\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
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"{{AWS_Region}}",
"amazonaws",
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],
"path": [
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]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
"body": ""
},
{
"name": "Generate Blog",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true",
"type": "text"
},
{
"key": "Content-Type",
"value": "application/json",
"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"inputText\": \"\\\"Command: Write me a blog about making strong business decisions as a leader.Blog: \\\"\",\r\n \"textGenerationConfig\": { \r\n \"maxTokenCount\": 4096,\r\n \"stopSequences\": [],\r\n \"temperature\": 0,\r\n \"topP\": 0.9\r\n }\r\n}\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
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],
"path": [
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]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [],
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}
]
}
]
},
{
"name": "Summarization",
"item": [
{
"name": "Summarize Text",
"event": [
{
"listen": "prerequest",
"script": {
"exec": [
""
],
"type": "text/javascript",
"packages": {}
}
},
{
"listen": "test",
"script": {
"exec": [
""
],
"type": "text/javascript",
"packages": {}
}
}
],
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"prompt\": \"\\n\\nHuman:Please provide a summary of the following text.<text>AWS took all of that feedback from customers, and today we are excited to announce Amazon Bedrock, a new service that makes FMs from AI21 Labs, Anthropic, Stability AI, and Amazon accessible via an API. Bedrock is the easiest way for customers to build and scale generative AI-based applications using FMs, democratizing access for all builders. Bedrock will offer the ability to access a range of powerful FMs for text and images—including Amazons Titan FMs, which consist of two new LLMs we’re also announcing today—through a scalable, reliable, and secure AWS managed service. With Bedrock’s serverless experience, customers can easily find the right model for what they’re trying to get done, get started quickly, privately customize FMs with their own data, and easily integrate and deploy them into their applications using the AWS tools and capabilities they are familiar with, without having to manage any infrastructure (including integrations with Amazon SageMaker ML features like Experiments to test different models and Pipelines to manage their FMs at scale).</text>\\n\\nAssistant:\",\n\"max_tokens_to_sample\":4096,\n\"temperature\":0.5,\n\"top_k\":250,\n\"top_p\":0.5,\n\"stop_sequences\":[]\n}",
"options": {
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}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
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"amazonaws",
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],
"path": [
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],
"variable": [
{
"key": "model_identifier",
"value": "anthropic.claude-v2",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": [
{
"name": "amazon.titan-tg1-large",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true",
"type": "text"
},
{
"key": "Content-Type",
"value": "application/json",
"name": "Content-Type",
"type": "text"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"inputText\": \"\\\"Please provide a summary of the following text. Do not add any information that is not mentioned in the text below. \\n <text> \\n AWS took all of that feedback from customers, and today we are excited to announce Amazon Bedrock, \\n a new service that makes FMs from AI21 Labs, Anthropic, Stability AI, and Amazon accessible via an API. \\n Bedrock is the easiest way for customers to build and scale generative AI-based applications using FMs, \\n democratizing access for all builders. Bedrock will offer the ability to access a range of powerful FMs \\n for text and images—including Amazons Titan FMs, which consist of two new LLMs we’re also announcing \\n today—through a scalable, reliable, and secure AWS managed service. With Bedrock’s serverless experience, \\n customers can easily find the right model for what they’re trying to get done, get started quickly, privately \\n customize FMs with their own data, and easily integrate and deploy them into their applications using the AWS \\n tools and capabilities they are familiar with, without having to manage any infrastructure (including integrations \\n with Amazon SageMaker ML features like Experiments to test different models and Pipelines to manage their FMs at scale). </text>\\\"\",\r\n \"textGenerationConfig\": {\r\n \"maxTokenCount\": 4096,\r\n \"stopSequences\": [],\r\n \"temperature\": 0,\r\n \"topP\": 0.9\r\n }\r\n}\r\n}",
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}
},
"url": {
"raw": "https://bedrock-runtime.us-east-1.amazonaws.com/model/amazon.titan-tg1-large/invoke",
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],
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}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
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],
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}
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}
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},
{
"name": "QuestionAnswering",
"item": [
{
"name": "Task",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"\\\"System: You are an helpful assistant. Answer questions in a concise way. \\n Question: How can I fix a flat tire on my Audi A8? \\n Answer:\\\"\",\n\"textGenerationConfig\":{\n \"maxTokenCount\":4096,\n \"stopSequences\":[],\n \"temperature\":0,\n \"topP\":0.9\n }\n } ",
"options": {
"raw": {
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"language": "json"
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}
},
"url": {
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],
"variable": [
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"key": "model_identifier",
"value": "amazon.titan-tg1-large",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": [
{
"name": "Product Features",
"originalRequest": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Answer based on context: \\n The newest and most innovative Kindle yet lets you take notes on millions of books and documents, write lists and journals, and more. \\n For readers who have always wished they could write in their eBooks, Amazon’s new Kindle lets them do just that. The Kindle Scribe is the first Kindle for reading and writing and allows users to supplement their books and documents with notes, lists, and more. \\n Here’s everything you need to know about the Kindle Scribe, including frequently asked questions. \\n The Kindle Scribe makes it easy to read and write like you would on paper \\n The Kindle Scribe features a 10.2-inch, glare-free screen (the largest of all Kindle devices), crisp 300 ppi resolution, and 35 LED front lights that automatically adjust to your environment. Further personalize your experience with the adjustable warm light, font sizes, line spacing, and more. \\n It comes with your choice of the Basic Pen or the Premium Pen, which you use to write on the screen like you would on paper. They also attach magnetically to your Kindle and never need to be charged. The Premium Pen includes a dedicated eraser and a customizable shortcut button. \\n The Kindle Scribe has the most storage options of all Kindle devices: choose from 8 GB, 16 GB, or 32 GB to suit your level of reading and writing. \\n Question:what are the key features of new Kindle? \\n Answer:\",\n\"textGenerationConfig\":{\n \"maxTokenCount\":4096,\n \"stopSequences\":[],\n \"temperature\":0,\n \"topP\":0.9\n }\n } ",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
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],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "amazon.titan-tg1-large",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Date",
"value": "Sat, 16 Sep 2023 05:44:11 GMT"
},
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Content-Length",
"value": "222"
},
{
"key": "Connection",
"value": "keep-alive"
},
{
"key": "x-amzn-RequestId",
"value": "1a256f1c-ec0b-43df-be6b-a83f90866360"
}
],
"cookie": [],
"body": "{\n \"inputTextTokenCount\": 305,\n \"results\": [\n {\n \"tokenCount\": 39,\n \"outputText\": \"\\nThe key features of new Kindle are:\\n1.Largest of all Kindle devices\\n2.Crisp 300 ppi resolution\\n3.35 LED front lights\",\n \"completionReason\": \"FINISH\"\n }\n ]\n}"
}
]
}
]
},
{
"name": "ChatBot",
"item": [
{
"name": "MessageAPI",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\n \"system\": \"You are Claude, an AI assistant created by Anthropic to be helpful, harmless, and honest. Your goal is to provide informative and substantive responses to queries while avoiding potential harms.\",\n \"anthropic_version\": \"bedrock-2023-05-31\",\n \"max_tokens\": 1024,\n \"messages\": [\n {\"role\": \"user\", \"content\": \"Hello there.\"},\n {\"role\": \"assistant\", \"content\": \"Hi, I'm Claude. How can I help you?\"},\n {\"role\": \"user\", \"content\": \"Can you explain LLMs in plain English?\"}\n ]\n}",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
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],
"path": [
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":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "anthropic.claude-3-sonnet-20240229-v1:0",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": []
}
]
},
{
"name": "Translate",
"item": [
{
"name": "Translate to Multiple Languages",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"\\\"Statement: \\\"My name is Arthur\\\" \\n Task:Translate Statement to German, Spanish & French \",\n\"textGenerationConfig\":{\n \"maxTokenCount\":4096,\n \"stopSequences\":[],\n \"temperature\":0,\n \"topP\":0.9\n }\n } ",
"options": {
"raw": {
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"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "amazon.titan-tg1-large",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": []
}
]
},
{
"name": "Generate SQL",
"item": [
{
"name": "Generate SQL",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Create SQL statement from instruction. \\n Database: Customers(CustomerID, CustomerName, ContactName, Address, City, PostalCode, Country) \\n Request: all the countries we have customers in without repetitions. \\n SQL statement: SELECT DISTINCT Country FROM Customers; \\n ## \\n Create SQL statement from instruction. \\n Database: Orders(OrderID, CustomerID, EmployeeID, OrderDate, ShipperID) \\n Request: select all the orders from customer id 1. \\n SQL statement: SELECT * FROM Orders WHERE CustomerID = 1; \\n ## \\n Create SQL statement from instruction. Database: Products(ProductID, ProductName, SupplierID, CategoryID, Unit, Price) \\n Request: selects all products from categories 1 and 7 \\n SQL statement: SELECT * FROM Products WHERE CategoryID = 1 OR CategoryID = 7; \\n ## \\n Create SQL statement from instruction. \\n Database: Customers(CustomerID, CustomerName, ContactName, Address, City, PostalCode, Country) \\n Request: change the first customer's name to Alfred Schmidt who lives in Frankfurt city. \\n SQL statement: \",\n\"textGenerationConfig\":{\n \"maxTokenCount\":4096,\n \"stopSequences\":[],\n \"temperature\":0,\n \"topP\":0.9\n }\n } ",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "amazon.titan-tg1-large",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": []
}
]
},
{
"name": "Image Generation",
"item": [
{
"name": "Character Design",
"event": [
{
"listen": "test",
"script": {
"exec": [
"var template = `",
"<img src=\"data:image/png;base64,{{response.artifacts.0.base64}}\" alt=\"Result Image\">",
"`;",
"",
"function constructVisualizerPayload() {",
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"}",
"",
"pm.visualizer.set(template, constructVisualizerPayload());"
],
"type": "text/javascript",
"packages": {}
}
}
],
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\n \"text_prompts\": [\n { \n \"text\": \"Character design of a robot warrior, concept art, contest winner, diverse medical cybersuits, Football armor, triade color scheme, black shirt underneath armor, in golden armor, clothes in military armor, high resolution render, octane \" \n }\n ],\n \"cfg_scale\":10,\n \"seed\":20,\n \"steps\":50\n}",
"options": {
"raw": {
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"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "stability.stable-diffusion-xl",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": []
}
]
},
{
"name": "Sentiment Analysis / Classification",
"item": [
{
"name": "Movie Review",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Review:This movie is so great and once again dazzles and delights us Is this movie review sentence negative or positive? \\n OPTIONS: -positive -negative \",\n\"textGenerationConfig\":{\n \"maxTokenCount\":4096,\n \"stopSequences\":[],\n \"temperature\":0,\n \"topP\":0.9\n }\n } ",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/:model_identifier/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
":model_identifier",
"invoke"
],
"variable": [
{
"key": "model_identifier",
"value": "amazon.titan-tg1-large",
"description": "Available text generation models under Amazon Bedrock have the following IDs:\n\n- amazon.titan-tg1-large\n- ai21.j2-grande-instruct\n- ai21.j2-jumbo-instruct\n- anthropic.claude-instant-v1\n- anthropic.claude-v1"
}
]
}
},
"response": []
}
]
},
{
"name": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-text-express-v1/invoke",
"request": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "*/*"
},
{
"key": "x-amzn-bedrock-save",
"value": "true"
},
{
"key": "Content-Type",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\"inputText\": \"Hello world\"} ",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/amazon.titan-tg1-large/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
"amazon.titan-tg1-large",
"invoke"
]
}
},
"response": []
},
{
"name": "https://bedrock-runtime.us-east-1.amazonaws.com/model/anthropic.claude-instant-v1/invoke",
"request": {
"method": "POST",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true"
},
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "modelId",
"value": "anthropic.claude-v2"
}
],
"body": {
"mode": "raw",
"raw": "{\"prompt\": \"\\n\\nHuman:story of two dogs\\n\\nAssistant:\"\r\n,\"max_tokens_to_sample\":100\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/anthropic.claude-v2/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
"anthropic.claude-v2",
"invoke"
]
}
},
"response": []
},
{
"name": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/stability.stable-diffusion-xl/invoke",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "x-amzn-bedrock-save",
"value": "true"
},
{
"key": "accept",
"value": "image/png"
}
],
"body": {
"mode": "raw",
"raw": "{\r\n \"text_prompts\": [\r\n { \r\n \"text\": \"Picture of a boy\" \r\n }\r\n ],\r\n \"cfg_scale\":10,\r\n \"seed\":20,\r\n \"steps\":50\r\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "https://bedrock-runtime.{{AWS_Region}}.amazonaws.com/model/stability.stable-diffusion-xl/invoke",
"protocol": "https",
"host": [
"bedrock-runtime",
"{{AWS_Region}}",
"amazonaws",
"com"
],
"path": [
"model",
"stability.stable-diffusion-xl",
"invoke"
]
}
},
"response": []
}
],
"description": "This collection includes usage examples for the following use cases:\n\n1. Embeddings\n2. Generation\n3. Summarization\n4. Question Answering\n5. Chat Bot\n6. Translate\n7. Generate SQL\n8. Image Generation\n9. Sentiment Analysis/Classification"
}
],
"auth": {
"type": "awsv4",
"awsv4": [
{
"key": "accessKey",
"value": "{{AccessKey}}",
"type": "string"
},
{
"key": "region",
"value": "{{AWS_Region}}",
"type": "string"
},
{
"key": "secretKey",
"value": "{{SecretKey}}",
"type": "string"
},
{
"key": "service",
"value": "bedrock",
"type": "string"
}
]
},
"event": [
{
"listen": "prerequest",
"script": {
"type": "text/javascript",
"exec": [
""
]
}
},
{
"listen": "test",
"script": {
"type": "text/javascript",
"exec": [
""
]
}
}
],
"variable": [
{
"key": "AccessKey",
"value": "ExampleAccessKey"
},
{
"key": "SecretKey",
"value": "ExampleSecretKey"
},
{
"key": "AWS_Region",
"value": "us-east-1",
"type": "string"
}
]
}
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