Federico Mariani created CAMEL-22711:
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Summary: Spring AI integration components for Apache Camel (Chat,
Embeddings, Tools, Vector Store)
Key: CAMEL-22711
URL: https://issues.apache.org/jira/browse/CAMEL-22711
Project: Camel
Issue Type: New Feature
Reporter: Federico Mariani
Assignee: Federico Mariani
Create four new Camel components providing comprehensive [Spring
AI|https://docs.spring.io/spring-ai/reference/] integration for building
AI-powered integration patterns:
1. spring-ai-chat - LLM chat operations with:
- Multi-model support via Spring AI abstraction (OpenAI, Ollama, etc.)
- RAG with automatic VectorStore integration
- Conversation memory (message-based & vector-based)
- Function calling/tool integration
- Multimodal support (images, audio, documents)
- Structured output conversion (Bean, Map, List)
- SafeGuard content filtering
- Prompt templates
2. spring-ai-embeddings - Text embedding generation:
- Single text or batch processing
- Vector representations for semantic search
- Low-level component for direct embedding computation
3. spring-ai-tools - Function calling for agentic AI:
- Exposes Camel routes as LLM-callable functions/tools
- Tag-based tool organization and discovery
- Typed parameters with JSON schema validation
- Enables AI models to execute actions and retrieve data via Camel routes
4. spring-ai-vector-store - Vector database operations:
- ADD/DELETE/SIMILARITY_SEARCH operations
- Automatic embedding generation
- Metadata filtering
- Integrates with Spring AI VectorStore implementations
These components enable enterprise integration patterns with LLMs, supporting
chat applications, semantic search, RAG workflows, and autonomous AI agents
within Camel routes.
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