Everything in CAP / Java
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WerkbankWerkbankA local desktop workspace for AI conversations, attached files and generated HTML Spaces, run by a goose agent and offering a catalog of SAP MCP connectors and ABAP, CAP and UI5 skills.independent, umbrella
Local desktop workspace for AI conversations with SAP connectors
xflights-javaxflights-javaThe Java twin of capire/xflights: a CAP Java service managing Airlines, Airports and Flights master data, with its client package xflights-data pulled into a consuming app through Maven.sap official, cap
CAP Java reuse package for Airlines, Airports and Flights data
xtravels-javaxtravels-javaThe Java twin of xtravels: a Spring Boot travel-booking application built on master data from xflights-java, which CAP mocks automatically unless a hybrid profile connects a running instance.sap official, cap
CAP Java travel-booking app built on xflights-java master data
Understanding Fuzzy Search in SAP Fiori ApplicationsUnderstanding Fuzzy Search in SAP Fiori ApplicationsExplains SAP HANA Enterprise Search's fuzzy, relevance-ranked matching behind Fiori's global search bar, its exact-match Search Query Syntax operators, and how a CAP CDS project on @sap/cds tunes the gap between them with @cds.search and @Search.fuzzinessThreshold, shown on a Contracts entity's contractNumber field. Raising the threshold to 0.95 narrows that field to near-exact matches for structured identifiers such as contract numbers, while an unset field keeps HANA's default (~80%) fuzziness for broader free-text discovery.Ruchi5, published 2026-07-27
Unlocking Tabular Foundation Models: From Experimentation to ProductionUnlocking Tabular Foundation Models: From Experimentation to ProductionA Devtoberfest 2026 session (AI-41) on taking tabular prediction from a playground to a deployment. It sets tabular foundation models against a model trained per use case and against language models reading rows as text, explains in-context learning as examples plus the rows whose target column is missing, and tries SAP RPT 1.6 on a train-delay dataset in the RPT playground, including the column and row importance it returns with the prediction. The same prediction is then rebuilt on SAP AI Core, where the tabular orchestration service plays the part the orchestration service plays for language models: a data destination, a table artifact with its CSN schema and a scenario configuration registered once at design time, after which a predict call passes only the query rows, the scenario configuration and a context-selection strategy. The last demo runs those same calls in natural language through the aicore-skills plugin in a coding agent, and one of them only resolves once the agent is told which scenario configuration to use.SAP Developers, published 2026-10-15
What a Second Document AI Workshop Taught Me About GovernanceWhat a Second Document AI Workshop Taught Me About GovernanceFrom questions raised at a second SAP Document AI workshop: the retention period for extracted data is a setting in the service's administration rather than a fixed property, with the source file deleted after processing and the decommissioning period for the extracted data configured to the customer's own policy. It also draws a boundary readers kept merging: Document AI extracts across languages but does not translate, so turning a document into a reviewer's own language is a separate step, pointing on BTP at SAP Translation Hub.Nicolas_BacaStorni, published 2026-08-25
What an AI infra engineer sees when opening SAP's AI stack (1/3): the model gatewayWhat an AI infra engineer sees when opening SAP's AI stack (1/3): the model gatewayA first look at SAP AI Core's Generative AI Hub from someone who builds gateways outside SAP for a living: the orchestration service harmonizes provider calls onto one API (a model name string switches providers, and SAP Note 3437766 carries the current model list, token rates and deprecation dates), runs a fixed, non-reorderable module pipeline — templating, masking through SAP Data Privacy Integration, grounding, content filtering, then the model call — and retries down an ordered fallback list whose entries can each carry their own model and rules. It places @sap-ai-sdk/orchestration among the official JavaScript, Java and Python SDKs, and notes SAP's own LiteLLM provider as a way to put a different gateway in front of it.amishkush, published 2026-09-30
What's in Daniel Hutzel's brain?What's in Daniel Hutzel's brain?A Devtoberfest 2026 session in the building-apps track, in which Daniel Hutzel and DJ Adams work through what the CAP team is building for agents. A bookshop gets an MCP endpoint beside its OData one from a single annotation, with the plugin writing the coding agent's configuration itself; in the xt-travels sample five services that know nothing about each other are served over MCP and an agent does the orchestration the hand-built UI and its value helps used to do. Hutzel then annotates a service as an agent so the ReAct loop and the choice of model move into the CAP service, and finally drops MCP for a skill that teaches the agent CQL instead, which is where the edges to Serve your application over MCP, Agent tooling and Agent guidance come from. The mechanism under all of it, a plugin file in the package root and event handlers that can be added to any CAP service, is the edge to Plugin authoring.published 2026-10-02
