Aws Sdk | Techlist.io

awsJun 9, 20263 min readCurated summary

Anthropic Claude Fable 5 on AWS: Mythos-class capabilities with built-in safeguards now available | Amazon Web Services

Claude Fable 5 is now available through Amazon Bedrock and Claude Platform on AWS, offering Mythos-level performance with safeguards for broader access. Anthropic highlights its ability to perform long-running tasks, analyze complex visual documents, and verify or improve its own work. Access requires specific data-sharing consent, and higher-risk requests may be routed to Claude Opus 4.8. ## Capabilities and Safeguards - Supports extended, asynchronous coding and knowledge-work tasks with minimal intervention. - Interprets diagrams, charts, tables, files, and PDFs for research, finance, legal, analytics, architecture, gaming, and software development. - Uses vision to compare implemented designs with intended goals. - Can update skills, create evaluation harnesses, and perform proactive self-verification. - Cybersecurity, biology, chemistry, and health prompts with elevated misuse risk may be handled by Opus 4.8 instead. - The unrestricted Claude Mythos 5 is limited to a small group of vetted customers. ## Accessing Fable 5 on Amazon Bedrock - Available through: - Anthropic’s Messages API using `bedrock-mantle` or `bedrock-runtime`. - AWS Invoke and Converse APIs through `bedrock-runtime`. - The Amazon Bedrock console Playground. - Model access is being expanded gradually across AWS accounts; customers can contact AWS Support for expedited access. ## Required Data Sharing - Users must opt into data sharing through the Data Retention API by setting `provider_data_share`. - No console interface is available for this setting at launch. - Anthropic requires: - 30-day retention of inputs and outputs. - Human review. - Data retention enables abuse detection across multiple interactions rather than isolated requests. - Example endpoints are provided for both `bedrock-mantle` and `bedrock-runtime`. ## SDK and API Usage - Install the Anthropic Python SDK with `pip install anthropic`. - The Messages API can be called through the Bedrock Mantle endpoint using model ID `anthropic.claude-fable-5`. - Boto3’s Converse API supports unified multi-model access through model ID `global.anthropic.claude-fable-5`. - Users can configure token limits and submit tasks such as designing a multi-region AWS architecture supporting 100,000 requests per second. ## Pricing and Routing - Requests routed to Opus 4.8 because of harmful content are charged at Opus rates. - If a conversation is blocked mid-request, initial tokens are charged at Fable rates and later tokens at Opus rates. - Pricing details are available on the Amazon Bedrock pricing page. Claude Fable 5 is best suited to ambitious, long-running workloads that benefit from advanced reasoning and document or visual understanding. Before using it, organizations should confirm account access, configure the required data-sharing settings, and evaluate whether the 30-day retention and human-review requirements fit their compliance policies.

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Aws Sdk Generative AI Python Amazon Bedrock+4

awsJun 5, 20262 min readCurated summary

Try the new console experience in Amazon Bedrock, optimized for Anthropic- and OpenAI-compatible APIs | Amazon Web Services

Amazon Bedrock introduces a refreshed console centered on the `bedrock-mantle` inference engine, which supports Anthropic Messages, OpenAI Responses, and OpenAI Chat Completions APIs. The experience is designed to streamline model discovery, evaluation, application development, and production setup for GPT, Claude, and open-weight models. It complements the existing console, which remains available for features such as Agents, Knowledge Bases, Guardrails, fine-tuning, and `bedrock-runtime` APIs. ## Model Catalog and Comparison - Browse supported models in a unified catalog. - Compare up to three models by: - Capabilities and modalities - Context window and token limits - Pricing and input/output costs - Service quotas - Regional availability - Use side-by-side evaluations with identical prompts to compare model responses. ## Project-Based Workflow - Create projects that organize model assignments, evaluations, API keys, and application setup. - The project dashboard displays: - Inference requests and errors over selected date ranges - Recently used models - Total token usage - Tokens per minute - Requests per minute - Tokens per inference request - These metrics can guide model selection, prompt optimization, and workload consistency. ## Application Setup and Live Documentation - The console provides project-specific setup instructions for Anthropic and OpenAI SDKs. - Developers can select an SDK, programming language, and authentication method. - It generates terminal commands, `.env` configuration, and sample requests for quick testing. - Live API documentation automatically inserts the project’s model ID, Region, `bedrock-mantle` endpoint, and API key reference. - Documentation updates automatically when project models or settings change. ## AI Coding Agent Integration - Projects can connect coding agents such as Claude Code, Cline, Codex, Cursor, and OpenCode. - Setup instructions cover: - Installing the selected agent - Using AWS IAM credentials or Bedrock API keys - Configuring environment variables - Routing agent requests through Bedrock ## Availability The new console is available in Regions offering `bedrock-mantle`, including locations in the United States, Asia Pacific, Europe, and South America. Users can access it through the existing Bedrock console by selecting **Try the Bedrock Mantle Console**, while the traditional console remains available for fully managed Bedrock capabilities. Developers building with Anthropic- or OpenAI-compatible APIs can use the new console to move from model evaluation to application testing and deployment with less manual configuration.

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Aws Sdk AI Agents Generative AI Amazon Bedrock+3

awsJun 1, 20263 min readCurated summary

Get started with OpenAI GPT-5.5, GPT-5.4 models, and Codex on Amazon Bedrock | Amazon Web Services

OpenAI GPT-5.5, GPT-5.4, and Codex are now generally available through Amazon Bedrock. GPT-5.5 targets the most demanding coding, reasoning, and agentic workloads, while GPT-5.4 emphasizes price-performance. Customers can access the models through the Responses API and use Codex across CLI, desktop, IDE, and Xcode integrations, with regional processing and token-based pricing. ## Model Access Through Amazon Bedrock - Models are served through Bedrock’s next-generation inference engine and the OpenAI Responses API. - GPT-5.5 is positioned for the hardest workloads; GPT-5.4 offers a balance of capability and cost. - Processing remains within the selected Bedrock Region, supporting data residency requirements. - Pricing is based on token usage, with no seat licenses or per-developer commitments. ## Calling GPT Models Programmatically - The OpenAI Python SDK can be configured with Bedrock’s OpenAI-compatible endpoint: - Install with `pip install -U openai`. - Set `OPENAI_BASE_URL`, `OPENAI_API_KEY`, and `BEDROCK_OPENAI_MODEL_ID`. - Applications can call `client.responses.create()` with: - Developer and user messages - Configurable reasoning effort - Output verbosity controls - The same endpoint can be called directly with `curl`. - The Responses API supports multi-turn state, hosted and function tools, tool orchestration, and background or long-running work. ## Using Codex with Bedrock - Codex is available through the Codex CLI, desktop app, VS Code, JetBrains, and Xcode integrations. - It supports: - A Bedrock API key via `AWS_BEARER_TOKEN_BEDROCK` - The AWS SDK credential chain as a fallback - Configure the model and Region in `~/.codex/config.toml`, for example: - Model: `openai.gpt-5.5` - Provider: `amazon-bedrock` - Region: `us-east-2` - Other supported model IDs include `openai.gpt-5.4`, `openai.gpt-oss-120b`, and `openai.gpt-oss-20b`. - Desktop and VS Code users can place environment variables in `~/.codex/.env`. - Applications must be restarted after configuration changes. ## Latency and Scaling Considerations - Actual latency depends on reasoning effort, response length, tool calls, background execution, Region, quotas, throttling, prompt size, and cache hits. - AWS recommends starting GPT-5.5 with medium reasoning effort. - GPT-5.4 should use an explicitly chosen effort level rather than relying on its default of `none`. - Bedrock’s inference engine is designed to provision capacity dynamically. - During demand spikes, requests may be queued instead of rejected. ## Regional Availability - GPT-5.5 is initially available in the US East (Ohio) Region. - GPT-5.4 is available in US East (Ohio) and US West (Oregon). - Additional Regions may be added over time. Teams needing advanced coding and reasoning capabilities can now use OpenAI models and Codex through Bedrock while retaining AWS authentication, regional processing, and usage-based pricing. Evaluate reasoning effort, latency, quotas, and regional availability before moving workloads into production.

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Aws Sdk Python Amazon Bedrock Curl+4