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AI for AWS Documentation

awsdocsgpt.com

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Re: AI for AWS Documentation

#51

Post by KRAKRISMOTT »

scarface_74 wrote: post #39
sovietmudkipz wrote: post #31

This is exactly the kind of software that people should be making. Even if this one is bad, the concept is very sound. I want to have a specialist AI that is trained to help me learn how to use the software. 100% what should be happening. General AI should know how to do stuff too but having an specialist AI implies that the company/group of people/person is making sure to tune the model. Just an IMO.

Why? You can ask the same questions to ChatGPT and get the same or better answers. I also know from personal experience with ChatGPT, that you can use it to: - convert Python/boto3 to any language that has an AWS SDK - convert CloudFormation to Terraform or the CDK - write scripts that use the SDK You will get the occasional hallucination.

ChatGPT is not up to date unless you start using the plugins. This sort of indexing is based on vector databases and various intermediate prompting. If you want to get technical, the academic term is "Retrieval Augmented Generation".

Re: AI for AWS Documentation

#52

Post by klysm »

scarface_74 wrote: post #41
WrtCdEvrydy wrote: post #38

Earlier quoted context omitted.

> Inexperienced folks won’t know better. I've seen answers like this in Stack Overflow before. Technically correct, but basically broken in every other way: cybersecurity's future is gonna be interesting.

One of my pet peeves about almost every answer on Stack Overflow is that the answer always starts with client=boto3.client( , access-key,secret-key) There is never a reason to include those last two parameters. It’s always a security risk no matter how you do it.

This is great example, and I think it’s a smaller version of the same problem.

Re: AI for AWS Documentation

#53

Post by stan_kirdey »

I am building something similar, it has documentation from azure, aws, and lots of slack/discord threads of software projects are also searchable, check it out https://www.kwq.ai

it even gets real time indexing from slack of aws deep java library, and from discord of deepset haystack project

Re: AI for AWS Documentation

#54

Post by 8note »

scarface_74 wrote: post #40
CSDude wrote: post #12

Well, I'll pass. Prompt: how to connect a lambda function to an RDS instance and query it safely? 1. Configure your RDS instance for outbound connections to AWS Lambda. This step involves ensuring that your DB instance is in a public subnet on your VPC and that the instance's "PubliclyAccessible" property is set to true.

Asking the same question to Chatgpt To connect a Lambda function to an RDS (Relational Database Service) instance and query it safely, you can follow these general steps: 1. Configure your Lambda function's execution role: Ensure that your Lambda function has the necessary permissions to access the RDS instance. The role should include the `AWSLambdaVPCAccessExecutionRole` and the appropriate RDS permissions. 2. Plac…

This all looks about right, but how would somebody without aws experience be able to validate it without making a mess?

Re: AI for AWS Documentation

#55

Post by jgalt212 »

is AWS designed to take all my money?

No, AWS is not designed to take all your money. AWS offers a variety of payment options and cost-saving measures to help you manage your expenses effectively. ...

Re: AI for AWS Documentation

#56

Post by scarface_74 »

8note wrote: post #54
scarface_74 wrote: post #40

Earlier quoted context omitted.

Asking the same question to Chatgpt To connect a Lambda function to an RDS (Relational Database Service) instance and query it safely, you can follow these general steps: 1. Configure your Lambda function's execution role: Ensure that your Lambda function has the necessary permissions to access the RDS instance. The role should include the `AWSLambdaVPCAccessExecutionRole` and the appropriate RDS permissions. 2. Plac…

This all looks about right, but how would somebody without aws experience be able to validate it without making a mess?

Keep going down the rabbit hole…

“I’m a beginner. Walk me through step $n”

Re: AI for AWS Documentation

#57

Post by istjohn »

71a54xd wrote: post #37

I've been using GPT4 for this since the beginning - ironically a large majority of AWS documentation has been machine generated since 2018. Circa 2019 the entire exlixir API for AWS was machine generated. Asking GPT4 is also consistently less of a headache than asking the devops guy and getting a 20min explanation for a simple question.

You need to add something like "You give clear and succinct answers to questions" to the beginning of your prompts to the devops guy.

Re: AI for AWS Documentation

#58

Post by underlines »

RAG is very difficult to do right. I am experimenting with various RAG projects from [1]. The main problems are:

- Chunking can interfer with context boundaries

- Content vectors can differ vastly from question vectors, for this you have to use hypothetical embeddings (they generate artificial questions and store them)

- Instead of saving just one embedding per text-chuck you should store various (text chunk, hypothetical embedding questions, meta data)

- RAG will miserably fail with requests like "summarize the whole document"

- to my knowledge, openAI embeddings aren't performing well, use a embedding that is optimized for question answering or information retrieval and supports multi language. SOTA textual embedding models can be found on the MTEB Leaderboard [2]. Also look into instructorEmbeddings

- the LLM used for the Q&A using your context should be fine-tuned for this task. There are several open (source?) LLMs based on openllama and others, that are fine tuned for information retrieval. They hallucinate less and are sticking to the context given.

1 https://github.com/underlines/awesome-marketing-datascience/...

2 https://github.com/embeddings-benchmark/mteb

Re: AI for AWS Documentation

#59

Post by zgluck »

I asked it:

"how do I avoid high NAT gateway bills when an ECS service keeps downloading the same image over and over?"

It offered three replies. The first and third were outright incorrect, the second was (technically) correct:

https://i.imgur.com/la98cxC.png

Also: I'm assuming you haven't actually secured a license to use the AWS logo.

Re: AI for AWS Documentation

#60

Post by darkteflon »

underlines wrote: post #58

RAG is very difficult to do right. I am experimenting with various RAG projects from [1]. The main problems are: - Chunking can interfer with context boundaries - Content vectors can differ vastly from question vectors, for this you have to use hypothetical embeddings (they generate artificial questions and store them) - Instead of saving just one embedding per text-chuck you should store various (text chunk, hypothe…

This comment was very helpful for me, thanks.

I’ve been working with RAG for months, too, and it’s vanishingly rare to see anything but toy examples in the wild. This is a solid, concise list of where the dragons are.

Any idea where all the RAG practitioners hang out and trade war stories? Is there a forum or Discord or something?

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