adding aws-simple-rag sample app

[zoharsan]

I confirm that this contribution is made under the terms of the license found in the root directory of this repository's source tree and that I have the authority necessary to make this contribution on behalf of its copyright owner.

[Copilot]

Pull Request Overview

This pull request introduces a new sample application demonstrating Retrieval Augmented Generation (RAG) using AWS Bedrock-hosted LLM models integrated with Vespa. The application showcases how to leverage AWS Bedrock's OpenAI-compatible chat completions API for generation while using Vespa's hybrid search capabilities (combining BM25 text search and vector similarity) for retrieval.

Key Changes:

• New sample application aws-simple-rag with configuration for AWS Bedrock LLM integration
• Hybrid search implementation combining text search (BM25) and vector similarity search using E5 embeddings
• Comprehensive documentation covering AWS Bedrock setup, Vespa deployment, and structured output generation

Reviewed Changes

Copilot reviewed 5 out of 7 changed files in this pull request and generated 11 comments.

Show a summary per file

File	Description
aws-simple-rag/services.xml	Configures Vespa services including E5 embedder component, AWS Bedrock OpenAI client with secret management, and RAGSearcher for generation
aws-simple-rag/schemas/passage.sd	Defines the passage document schema with text indexing, vector embeddings, and hybrid ranking profile
aws-simple-rag/README.md	Provides comprehensive setup instructions for AWS Bedrock configuration, Vespa deployment, and query examples including structured output
aws-simple-rag/.vespaignore	Specifies files to exclude from the Vespa application package
aws-simple-rag/ext/edit-app-access.png	Screenshot illustrating the secret access configuration in Vespa Cloud console
README.md	Adds reference to the new AWS Bedrock RAG sample application in the main repository index

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[Copilot]

The closeness(field, embedding) function appears to be using incorrect syntax. The closeness function typically takes the field name as a string or just the field name directly, not the literal word "field". This should likely be closeness(embedding) or the correct field reference.

Suggested change

	expression: 2 * closeness(field, embedding) + bm25(text) / 11
	}
	match-features: bm25(text) closeness(field, embedding)
	expression: 2 * closeness(embedding) + bm25(text) / 11
	}
	match-features: bm25(text) closeness(embedding)

[Copilot]

Inconsistent indentation: the field id block uses irregular spacing with 1 space before field while the field text block uses proper indentation. The opening brace is also on a different line than expected for the id field.

Suggested change

	field id type string {
	field id type string {

[Copilot]

Inconsistent indentation: the component definition uses 5 spaces while the rest of the file uses standard 2-space indentation. The component should align with other elements at the same level.

Suggested change

	<component id="e5_small" type="hugging-face-embedder">
	<transformer-model url="https://github.com/vespa-engine/sample-apps/raw/master/examples/model-exporting/model/e5-small-v2-int8.onnx"/>
	<tokenizer-model url="https://raw.githubusercontent.com/vespa-engine/sample-apps/master/examples/model-exporting/model/tokenizer.json"/>
	<prepend> <!-- E5 prompt instructions -->
	<query>query:</query>
	<document>passage:</document>
	</prepend>
	</component>
	<component id="e5_small" type="hugging-face-embedder">
	<transformer-model url="https://github.com/vespa-engine/sample-apps/raw/master/examples/model-exporting/model/e5-small-v2-int8.onnx"/>
	<tokenizer-model url="https://raw.githubusercontent.com/vespa-engine/sample-apps/master/examples/model-exporting/model/tokenizer.json"/>
	<prepend> <!-- E5 prompt instructions -->
	<query>query:</query>
	<document>passage:</document>
	</prepend>
	</component>

[Copilot]

Incorrect capitalization: "BedRock" should be "Bedrock" (lowercase 'r'). The official AWS product name is "Amazon Bedrock" not "BedRock".

Suggested change

	# Retrieval Augmented Generation (RAG) in Vespa using AWS BedRock models
	This sample application demonstrates an end-to-end Retrieval Augmented
	Generation application in Vespa, leveraging [AWS BedRock](https://aws.amazon.com/bedrock/) hosted models.
	# Retrieval Augmented Generation (RAG) in Vespa using AWS Bedrock models
	This sample application demonstrates an end-to-end Retrieval Augmented
	Generation application in Vespa, leveraging [AWS Bedrock](https://aws.amazon.com/bedrock/) hosted models.

[Copilot]

Incorrect capitalization: "BedRock" should be "Bedrock" (lowercase 'r'). The official AWS product name is "Amazon Bedrock" not "BedRock".

Suggested change

	# Retrieval Augmented Generation (RAG) in Vespa using AWS BedRock models
	This sample application demonstrates an end-to-end Retrieval Augmented
	Generation application in Vespa, leveraging [AWS BedRock](https://aws.amazon.com/bedrock/) hosted models.
	# Retrieval Augmented Generation (RAG) in Vespa using AWS Bedrock models
	This sample application demonstrates an end-to-end Retrieval Augmented
	Generation application in Vespa, leveraging [AWS Bedrock](https://aws.amazon.com/bedrock/) hosted models.

[Copilot]

Missing opening angle bracket in the vault attribute. The value should be vault="<my-vault-name>" instead of vault=">my-vault-name>" to match the pattern used for <my-secret-name>.

Suggested change

	<bedrock-api-key vault=">my-vault-name>" name="<my-secret-name>"/>
	<bedrock-api-key vault="<my-vault-name>" name="<my-secret-name>"/>

[Copilot]

Inconsistent indentation in the embedding field definition. The field content uses excessive indentation (12 spaces) instead of the standard 2 or 4 spaces used elsewhere in the schema.

Suggested change

	indexing: input text | embed e5_small | attribute | index
	attribute {
	distance-metric: angular
	}
	index {
	hnsw {
	max-links-per-node: 32
	neighbors-to-explore-at-insert: 100
	}
	}
	indexing: input text | embed e5_small | attribute | index
	attribute {
	distance-metric: angular
	}
	index {
	hnsw {
	max-links-per-node: 32
	neighbors-to-explore-at-insert: 100
	}
	}

[Copilot]

Inconsistent indentation in the rank-profile definition. Lines use 8 spaces for indentation instead of the standard 2 or 4 spaces used in the document field definitions.

Suggested change

	inputs {
	query(e) tensor<bfloat16>(x[384])
	}
	first-phase {
	expression: 2 * closeness(field, embedding) + bm25(text) / 11
	}
	match-features: bm25(text) closeness(field, embedding)
	}
	inputs {
	query(e) tensor<bfloat16>(x[384])
	}
	first-phase {
	expression: 2 * closeness(field, embedding) + bm25(text) / 11
	}
	match-features: bm25(text) closeness(field, embedding)
	}

[Copilot]

Extra space in the config name attribute. Should be name="ai.vespa.llm.clients.llm-client" instead of name = "ai.vespa.llm.clients.llm-client" to follow standard XML formatting conventions.

Suggested change

	<config name = "ai.vespa.llm.clients.llm-client">
	<config name="ai.vespa.llm.clients.llm-client">

[Copilot]

Incorrect capitalization: "BedRock" should be "Bedrock" (lowercase 'r'). The official AWS product name is "Amazon Bedrock" not "BedRock".