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add a section about debugging
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docs/concepts/debug.md

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---
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title: Debug
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description: Defang uses AI to help you debug your cloud applications.
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sidebar_position: 650
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---
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# Debug
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Defang includes an AI-driven tool to help you debug your cloud applications. The AI assistant will use your service logs as well as the files in your project to help you identify and resolve issues.
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:::warning
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The AI debugging assistant is currently in beta and is currently limited in its capabilities. We plan to expand the capabilities of the AI assistant in the future.
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:::

docs/concepts/ai.md renamed to docs/concepts/generate.md

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---
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title: AI
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description: How Defang uses AI to help you build and deploy your cloud applications.
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title: Generate
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description: Defang uses AI to help you generate a starting point for your cloud applications.
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sidebar_position: 100
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---
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# AI
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# Generate
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Defang includes an AI-driven assistant that translates natural language prompts to an outline for your project that you can then refine. The AI assistant is available through the [Defang CLI](../getting-started/installing.md).
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:::info
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The AI assistant is currently in beta and only supports a limited set of prompts. We plan to expand the capabilities of the AI assistant in the future.
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The AI assistant is currently in beta and only supports a limited set of prompts, varying in complexity. We plan to expand the capabilities of the AI assistant in the future.
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:::
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We are working on expanding the range of supported prompts and improving the accuracy of the AI assistant. If you have any feedback or suggestions, please let us know by [opening an issue](https://github.com/DefangLabs/defang/issues/new).
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```
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A simple api with a single route built on express
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```
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**An example of a more complex prompt**
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```
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A service that uses bullmq and redis. The compose file should also include a redis service. The code should setup a queue. It should also expose three endpoints with express: one to add a job to the queue, another to check how many tasks are in the queue, and a last one that runs on / which is just a healthcheck. The code should also include a worker that processes the queue by logging what's in each task. Use environment variables to configure the redis connection. No password.
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```

docs/intro.md

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- Support for [various types of applications](./use-cases/use-cases.md): Web services and APIs, mobile app backends, ML services, hosting LLMs, etc.
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- Support for your programming [language of choice](./samples.md): Node.js, Python, Golang, or anything else you can package in a Dockerfile.
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- Built-in [AI assistant](./concepts/ai.md) to go from natural language prompt to an outline project
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- Built-in AI assistant to go [from natural language prompt to an outline project](./concepts/generate.md)
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- Built-in AI assistant to help you [debug your cloud applications](./concepts/debug.md)
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- Automated [Dockerfile builds](./concepts/deployments.md)
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- Support for [pre-built Docker containers](./tutorials/deploy-container-using-the-cli.mdx), from public or private image registries
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- Ability to express your project configuration using a [Docker Compose YAML](./concepts/compose.md) file

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