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docs: ai podcast guide part 2 (#653)
Co-authored-by: Tim Holm <[email protected]> Co-authored-by: David Moore <[email protected]>
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dictionary.txt

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preflight
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nav
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MacOS
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quantized
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[0-9]+px
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^.+[-:_]\w+$
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[a-z]+([A-Z0-9]|[A-Z0-9]\w+)
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([A-Z][a-z0-9]+)((\d)|([A-Z0-9][a-z0-9]+))*([A-Z])?
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([a-zA-Z0-9]+\.[a-zA-Z0-9]+)+
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^([0-9]+)
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^\d+B$
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\..+️

docs/guides/python/ai-podcast-part-1.mdx

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@main_api.post("/download-model")
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async def download_audio(ctx: HttpContext):
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model_id = ctx.req.query.get("model", audio_model_id)
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if isinstance(model_id, list):
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model_id = model_id[0]
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# asynchronously download the model
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await download_audio_model.publish({ "model_id": model_id })
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This will generate a nitric stack file called `test` which defines how we want to deploy a stack to AWS. We can update this stack file with settings to configure our batch service and the AWS Compute environment it will run in.
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```yaml title: nitric.test.yaml
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provider: nitric/aws@1.14.2
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provider: nitric/aws@1.15.4
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# The target aws region to deploy to
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# See available regions:
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# https://docs.aws.amazon.com/general/latest/gr/lambda-service.html
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## Next steps
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In part two of this guide we'll look at adding an LLM agent to our project to automatically generate scripts for our podcasts from small prompts.
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In [part two](./ai-podcast-part-2) of this guide we'll look at adding an LLM agent to our project to automatically generate scripts for our podcasts from small prompts.

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