Jakarta Agentic AI: use released API 1.0.0-M1 and EE11 TCK branch - #8331
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luiseufrasio wants to merge 49 commits into
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Jakarta Agentic AI: use released API 1.0.0-M1 and EE11 TCK branch#8331luiseufrasio wants to merge 49 commits into
luiseufrasio wants to merge 49 commits into
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…r and agentic-ai-core)
…flowScopeContext, WorkflowScopeManager)
…ayara distribution
…jakarta-agentic-ai-1-0-tck-support-in-payara-server
…ery when @outcome failed
…croProfile Config Evolve the internal LlmBackend SPI to carry role-tagged conversation turns and an optional system prompt, and store assistant replies in LargeLanguageModelImpl so per-workflow conversational state is complete and providers receive a correctly alternating history. Add Ollama and Anthropic backends (raw java.net.http + JSON-B, no SDK) and an LlmBackendFactory that selects the provider from MicroProfile Config under payara.agentic.llm.*. The Anthropic backend marks the system prompt with cache_control for prompt caching across workflow phases. The no-op backend remains the default when no provider is configured. Wire the factory into AgenticAIExtension and add the microprofile-config-api dependency.
…generator quickstart: a minimal @agent that answers a question, exercising the @Trigger/@Decision/@Action/@outcome phases. Selects a small local Ollama model via MicroProfile Config and ships a CI-safe Arquillian IT that uses a stub LargeLanguageModel, so it runs without a live model. tutorial generator: an agent that writes a field-by-field guide for a Customer registration form (contract Azul Payara Server) and refines it through a chat loop, passing the current HTML plus the instruction each turn. Uses the Anthropic provider, ships a side-by-side form/guide UI, and a CI-safe IT with a stub model. Register both modules in the payara-samples reactor.
… configurable LLM backends) into the samples branch
… sample - Add VertexLlmBackend: authenticates via ADC (gcloud subprocess) or GOOGLE_ACCESS_TOKEN env var; builds the rawPredict endpoint URL handling the 'global' pseudo-region; sends anthropic_version in the request body as required by Vertex AI - Register 'vertex' provider in LlmBackendFactory; project-id and region fall back to the ANTHROPIC_VERTEX_PROJECT_ID / CLOUD_ML_REGION env vars - Switch sample config to vertex provider with claude-sonnet-4-6 model - Update system prompt to suppress the form-level title/intro in generated HTML - Redesign index.html with Azul brand tokens: navy header, white cards, Inter font, pill buttons (#0055cc), and chat bubbles styled after the brand Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
… chat - Redesign UI: form centred on the left; clicking a field slides in a contextual panel on the right showing only that field's AI explanation - Add POST /api/tutorial/refine-field endpoint: isolates one field's description, refines it via the agent, and merges the result back into the full guide JSON (other fields preserved) - Switch agent prompts and system prompt to return structured JSON (fieldName → plain-text explanation) instead of a free-form HTML fragment - Per-field chat history: each field keeps its own conversation thread, restored when the user switches between fields - Toast notification after generation guides the user to click a field - Guide panel styled to match the form card (white, clean border); removed metallic gradient - Graceful handling of non-JSON agent responses in the chat Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…-agentic-ai-on-payara-server
…erge Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
…nt-samples-with-jakarta-agentic-ai-on-payara-server
…ON_JSON The test requests TEXT_HTML and the store holds HTML; the wrong @produces annotation caused HTTP 406 on every CI run. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
…lAgent The stub checked for "Apply this change requested" but TutorialAgent sends "Apply this change to the explanations", so refine always returned GENERATED. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Rename local variable `html` to `content` in TutorialAgent.render() to avoid confusion with JSON output - Add Logger to TutorialResource and log caught exceptions in extractField and mergeField instead of silently discarding them - Add Javadoc to TutorialStore explaining why @ApplicationScoped + volatile is intentional (guide must persist across generate/refine requests) - Add refinesField IT test covering the /api/tutorial/refine-field endpoint Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
…to FISH-13709-create-agent-samples-with-jakarta-agentic-ai-on-payara-server
…/ai/agent/engine/ClassMethodOrder.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/ClassMethodOrder.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/extension/AgenticAIExtension.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…-jakarta-agentic-ai-1-0-tck-support-in-payara-server
StringBuffer is synchronized; StringBuilder is the correct choice for single-threaded local usage. Matcher.appendReplacement/appendTail accept StringBuilder since Java 9, and this project targets JDK 21. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…/ai/agent/cdi/WorkflowScopeContext.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/llm/AnthropicLlmBackend.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…/ai/agent/engine/WorkflowEngine.java Co-authored-by: Alfonso Valdez <alfonso.altamirano@payara.fish>
…-jakarta-agentic-ai-1-0-tck-support-in-payara-server
…ta-agentic-ai-1-0-tck-support-in-payara-server FISH-13708 implement jakarta agentic ai 1 0 tck support in payara server
…to FISH-13709-create-agent-samples-with-jakarta-agentic-ai-on-payara-server
…mples-with-jakarta-agentic-ai-on-payara-server FISH-13709 Add Jakarta Agentic AI samples (quickstart and tutorial generator)
…ntic-AI # Conflicts: # Jenkinsfile
Update the jakarta.agentic-ai-api dependency from 1.0.0-SNAPSHOT to the released 1.0.0-M1 version available on Maven Central. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Point the Jakarta Agentic AI TCK stage at the EE11 branch of the jakartaee-10-tck-runners repository. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Description
This PR brings the Jakarta Agentic AI integration branch up to date and switches the API dependency to a released version:
payara/maininto the branch.1.0.0-M1(available on Maven Central) instead of the1.0.0-SNAPSHOTversion.Jenkinsfileat theEE11branch of thejakartaee-10-tck-runnersrepository.Dependency
This PR depends on payara/jakartaee-10-tck-runners#213 and should be merged together with it.
Testing performed
CI / Jenkins pipeline (including the Jakarta Agentic AI TCK stage).