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Source channel @githubtrending · Post #15382 · Jan 1

#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples

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djangoproject

@djangoproject · Post #589 · 03/29/2018, 06:38 AM

http://books.agiliq.com/projects/django-api-polls-tutorial/en/latest/ Building #APIs with #Django and #Django_Rest_Framework(#DRF) Introductions Setup, Models and Admin A simple API with pure Django #Serializing and Deserializing Data Views and Generic Views More views and viewsets #Access_Control #Testing and Continuous Integeration Testing and Using API with Postman Documenting APIs (with Swagger and more)