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dictionary.txt

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docs/guides/python/serverless-ai-api.mdx

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# Build a Serverless AI-Powered Python API
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**TL;DR:** _In this tutorial, you'll learn how to build and deploy a **serverless** backend in Python that integrates an **AI** text summarization feature - all using the open-source Nitric framework. We'll go from setting up a Nitric project, writing an API endpoint that calls an AI service, testing it locally (with a slick built-in dashboard), to deploying it on the cloud. No prior cloud knowledge or tedious infrastructure configs required._
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**TL;DR:** _In this tutorial, you'll learn how to build and deploy a **serverless** backend in Python that integrates an **AI** text summarization feature - all using the open-source Nitric framework. We'll go from setting up a Nitric project, writing an API endpoint that calls an AI service, testing it locally (with a slick built-in dashboard), to deploying it on the cloud. No prior cloud knowledge or tedious infrastructure configuration required._
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Modern backend development is exciting and fast-moving - **serverless architectures** and **AI integrations** are among 2025's hottest trends. Yet, if you're a Python developer with minimal cloud experience, diving into these topics can feel daunting. This guide is here to help. We'll leverage **Nitric**, a cloud-agnostic framework that abstracts away the cloud complexity, letting you focus on code, not servers or YAML config. By the end, you'll have a working **Python API** that takes in text and returns an AI-generated summary, deployed on a cloud provider.
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