Data Foundation Model extensions, including the extension of the Product Model, to support additional use cases.
The initial use case extends the Software Components table specifically to support firmware.
Instantiates the following tables:
- Software Component Model [cmdb_sw_component_model]
- Discovered SW Component Model [cmdb_discv_sw_component_model]
- Software Component Installation [cmdb_sw_component_install]
Added the following:
MCP Function (cmdb_ci_function_mcp)
The MCP Function class represents an MCP (Model Context Protocol) server, which serves as an intermediary connecting AI models with tools and data.
- The new MCP server URL (mcp_url) attribute stores the URL for the MCP server.
- The new MCP Digital Asset (alm_mcp_digital_asset) asset class represents the digital asset.
- The new MCP Product Model (cmdb_mcp_product_model) product model represents the product model.
AWS Bedrock AI Agent (cmdb_ci_aws_bedrock_ai_agent)
Amazon Bedrock is a fully managed service for building generative AI applications using foundation models from leading AI companies. Amazon Bedrock offers model customization, Retrieval Augmented Generation, and task-executing agents. Serverless and secure, Amazon Bedrock integrates with AWS services to streamline development without infrastructure management.
AWS SageMaker (cmdb_ci_aws_sagemaker_agent)
Amazon SageMaker's next generation unifies data, analytics, and AI with a single studio to integrate model development, generative AI, and SQL analytics.
Azure AI Agent (cmdb_ci_azure_ai_agent)
Customizable AI agents built in Azure AI Foundry, automating complex enterprise workflows. The agents integrate seamlessly with enterprise tools, leverage advanced models, and ensure secure, production-ready performance with robust governance.
Azure AI Foundry (cmdb_ci_azure_ai_foundry)
A platform for building generative AI applications and agents, offering unified tools, APIs, and models from providers like OpenAI and Mistral. Azure AI Foundry supports secure, scalable deployment with responsible AI practices.
Azure AI Project (cmdb_ci_azure_ai_project)
A environment for secure, isolated environments within Azure AI Foundry for AI applications. Projects enable collaboration, data isolation, and experimentation with models and tools to create customized AI solutions efficiently.
Updated the following:
Updated the AI Function (cmdb_ci_function_ai) class:
- Made the class independent.
- Added two attributes to capture A2A:
- Well-Known URI (well_known_uri): Stores the well-known URL. This is currently used for the A2A server’s well-known location.
- Card (card): Stores card information. This is currently used to store agent card information from the A2A server.
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