fix(all): version 0.8

[andylau-55]

1. Index extraction and retrieval are core capabilities of knowledge base applications. KAG v0.8 has upgraded its architecture to support configurable management of index construction and retrieval. Each index type is equipped with its own extractor (Extractor) and retriever (Retriever), managed through the IndexManager.
2. KAG comes with built-in foundational index types such as KnowledgeUnit (an enhanced version of graph triples), Outline, Summary, Chunk, AtomicQuery, and Table, along with their corresponding extractors and retrievers. During the knowledge base construction phase, the platform invokes the appropriate extractor based on the index types selected by the user to perform index extraction. In the application phase, based on the knowledge bases associated with the application, the platform automatically calls the corresponding retriever to complete the recall of graph/chunk/doc data and integrates with the KAG-Solver pipeline to enable reasoning and question-answering.
3. Developers can extend the IndexManager to implement or combine custom extractors and retrievers. After packaging KAG with these custom components and replacing the corresponding installation package in the openspg-server image, users can select the custom index types on the product page during knowledge base construction. This enables seamless integration of custom index types with the product.
4. This release offers three methods to integrate KAG into business systems: HttpAPI, MCP Protocol, and Frontend Page Embedding.The KAG HttpAPI provides two types of interfaces: recall and reasoning & Q&A. Developers can choose to use KAG as a retrieval source or as a complete reasoning and Q&A capability.The KAG MCP Protocol offers interfaces for reasoning and Q&A, which can be embedded into agent applications like Cursor.In this release, the reasoning and Q&A functionality has been upgraded to an independent page, allowing developers to embed this page into their business systems.
5. This release addresses several community concerns, including response latency, streaming output stability, model configuration management, and task scheduling reliability. We greatly appreciate the community's support and patience with KAG.

[github-actions]

license-eye has checked 1705 files.

Valid	Invalid	Ignored	Fixed
1677	5	23	0

Click to see the invalid file list

• cloudext/interface/graph-store/src/main/java/com/antgroup/openspg/cloudext/interfaces/graphstore/util/TypeChecker.java
• server/biz/common/src/main/java/com/antgroup/openspg/server/biz/common/AppManager.java
• server/biz/common/src/main/java/com/antgroup/openspg/server/biz/common/util/RegexPattern.java
• server/common/model/src/main/java/com/antgroup/openspg/server/common/model/app/App.java
• server/common/service/src/main/java/com/antgroup/openspg/server/common/service/app/AppRepository.java

Use this command to fix any missing license headers

```bash

docker run -it --rm -v $(pwd):/github/workspace apache/skywalking-eyes header fix

</details>

[xionghuaidong]

LGTM

[northmachine]

LGTM