Add VertexAI RAG retrieval tool implementation

[nktks]

• This PR adds Vertex AI RAG Engine tool https://google.github.io/adk-docs/tools/built-in-tools/#vertex-ai-rag-engine.
• This is based on adk-python implementation
  • However I omitted the implementation of functional tool implementation with google.cloud.aiplatform.v1.VertexRagService.RetrieveContexts call for Gemini 1.x support, because Gemini 1.x is already retired before adk-go had released. ref

[gemini-code-assist[bot]]

Summary of Changes

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This pull request integrates the Vertex AI RAG (Retrieval-Augmented Generation) Engine tool into the adk-go framework, enabling agents to perform Retrieval-Augmented Generation by querying specified RAG corpora. The changes introduce a new VertexAIRAG tool that configures LLM requests to utilize Vertex AI's built-in RAG capabilities, specifically for Gemini models. An accompanying example demonstrates its usage, and dedicated tests ensure its proper functioning.

Highlights

• Vertex AI RAG Tool Integration: Introduces the VertexAIRAG tool for Retrieval-Augmented Generation using Vertex AI, enabling agents to leverage external knowledge bases.
• Built-in RAG Support: The implementation specifically utilizes the built-in Vertex AI RAG tool for Gemini models, intentionally omitting older Gemini 1.x functional tool support due to its retirement.
• New Example for Usage: Adds a new example file, examples/tools/retrievaltool/main.go, which demonstrates how to configure and use the VertexAIRAG tool within an llmagent.
• Core Tool Implementation: Defines the VertexAIRAG struct and its ProcessRequest method in tool/retrievaltool/vertex_ai_rag.go, responsible for injecting the RAG configuration into LLM requests.
• Comprehensive Testing: Includes tool/retrievaltool/vertex_ai_rag_test.go to validate the correct integration and functionality of the VertexAIRAG tool, ensuring it properly modifies LLM requests.

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