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Clone the repository:
git clone https://github.com/yourusername/your-repo-name.git cd your-repo-name -
Install Poetry(if not already installed):
pip install poetry
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Create a virtual environment:
poetry shell
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Install the dependencies:
poetry install
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[Placeholder] (add in your next installation step here):
[Placeholder]
To create our Amazon Bedrock Knowledge base we will:
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Go to the Amazon Bedrock Service homepage within the AWS console and on the left-hand side we will select "Knowledge bases" under the "Orchestration" drop down
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We will then click on "Create knowledge base"
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In the Knowledge base details section, you can optionally change the default name and provide a description for your knowledge base.In the IAM permissions section, choose an AWS Identity and Access Management (IAM) role that provides Amazon Bedrock permission to access other AWS services. You can let Amazon Bedrock create the service role or choose a custom role that you have created. Optionally, add tags to your knowledge base. Select Next.
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On the Set up data source page, provide the information for the data source to use for the knowledge base: Optionally, change the default Data source name. Provide the S3 URI of the object containing the files for the data source that you prepared. Select Next.
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In the Embeddings model section, choose a supported embeddings model to convert your data into vector embeddings for the knowledge base. In the Vector database section, choose Quick create a new vector store and select Next
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On the Review and create page, check the configuration and details of your knowledge base. Choose Edit in any section that you need to modify. When you are satisfied, select Create knowledge base.
