| Feat/issue clarify graph example (#410)
* feat(issue-clarify-graph-example): add issue clarify graph example for booking workflow
- Create Maven project for issue clarify graph example with dependencies on Spring Boot and Alibaba AI starters
- Configure application.yml with server port and DashScope API details
- Add prompt template for slot extraction in clarify_prompt.st with detailed JSON schema and extraction rules
- Provide extensive flight booking customer knowledge base in custome_knowledge.md
- Implement DashScopeConfig to instantiate DashScopeApi and DocumentRetriever beans using API key and index name
- Develop GraphConfig to assemble issue clarify workflow graph with intent recognition, RAG retrieval,
slot extraction, user wait, and order placement nodes with async edges and state key strategies
- Introduce GraphController REST API for booking workflow allowing session initialization, multi-turn dialogue,
and human interaction loop with state persistence in memory saver via compiled graph execution
* feat(nodes): add AI-driven intent, clarification, knowledge, order, and retrieval nodes
- Introduce ClarifyNode for slot parameter clarification via chat prompts
- Add ClarifyWaitNode for async waiting and interruption handling in flows
- Implement IntentNode to classify user intent into booking or knowledge categories
- Create KnowledgeReplyNode to generate replies based on ticket knowledge base
- Add OrderNode simulating ticket booking with order ID and confirmation message
- Develop RagNode to retrieve and filter relevant documents for knowledge querying | 5 个月前 |