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docs[patch]: AWS platform page update (#14160)
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The `AWS` platform page has many missed integrations.
- added missed integration references to the `AWS` platform page
- added/updated descriptions and links in the referenced notebooks
- renamed two notebook files. They have file names != page Title, which
generate unordered ToC.
- reroute the URLs for renamed files
- fixed `amazon_textract` notebook: removed failed cell outputs
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leo-gan authored Dec 3, 2023
1 parent 74d4154 commit 94bf733
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Showing 13 changed files with 1,160 additions and 1,067 deletions.
6 changes: 4 additions & 2 deletions docs/docs/guides/safety/amazon_comprehend_chain.ipynb
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"source": [
"# Amazon Comprehend Moderation Chain\n",
"\n",
"This notebook shows how to use [Amazon Comprehend](https://aws.amazon.com/comprehend/) to detect and handle `Personally Identifiable Information` (`PII`) and toxicity.\n",
">[Amazon Comprehend](https://aws.amazon.com/comprehend/) is a natural-language processing (NLP) service that uses machine learning to uncover valuable insights and connections in text.\n",
"\n",
"This notebook shows how to use `Amazon Comprehend` to detect and handle `Personally Identifiable Information` (`PII`) and toxicity.\n",
"\n",
"## Setting up"
]
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
"version": "3.10.12"
}
},
"nbformat": 4,
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12 changes: 10 additions & 2 deletions docs/docs/integrations/chat/bedrock.ipynb
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"source": [
"# Bedrock Chat\n",
"\n",
"[Amazon Bedrock](https://aws.amazon.com/bedrock/) is a fully managed service that makes FMs from leading AI startups and Amazon available via an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case"
">[Amazon Bedrock](https://aws.amazon.com/bedrock/) is a fully managed service that offers a choice of \n",
"> high-performing foundation models (FMs) from leading AI companies like `AI21 Labs`, `Anthropic`, `Cohere`, \n",
"> `Meta`, `Stability AI`, and `Amazon` via a single API, along with a broad set of capabilities you need to \n",
"> build generative AI applications with security, privacy, and responsible AI. Using `Amazon Bedrock`, \n",
"> you can easily experiment with and evaluate top FMs for your use case, privately customize them with \n",
"> your data using techniques such as fine-tuning and `Retrieval Augmented Generation` (`RAG`), and build \n",
"> agents that execute tasks using your enterprise systems and data sources. Since `Amazon Bedrock` is \n",
"> serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy \n",
"> generative AI capabilities into your applications using the AWS services you are already familiar with.\n"
]
},
{
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.9"
"version": "3.10.12"
}
},
"nbformat": 4,
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