[Feature Request] Native Knowledge Graph / GraphRAG support for built‑in knowledge base

### Self Checks

- [x] I have read the [Contributing Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) and [Language Policy](https://github.com/langgenius/dify/issues/1542).
- [x] I have searched for existing issues [search for existing issues](https://github.com/langgenius/dify/issues), including closed ones.
- [x] I confirm that I am using English to submit this report, otherwise it will be closed.
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### 1. Is this request related to a challenge you're experiencing? Tell me about your story.

### Self‑check
- [x] I have searched existing issues and discussions, no exactly matching feature request.

### Is your feature request related to a problem? Please describe.
Our team is currently using Dify for internal knowledge‑base applications.
The current built‑in knowledge base only supports vector/keyword hybrid retrieval.
When facing complex business documents, multi‑hop reasoning, entity‑relationship correlation questions, traditional vector‑based RAG often fails, and brings hallucinations.

Solutions like RAGFlow, KAG have native GraphRAG / knowledge‑graph enhanced RAG, while Dify does not have built‑in support.
We can integrate external GraphRAG services via workflow HTTP node or external‑knowledge‑base API, but this brings extra maintenance overhead, extra service deployment, and cannot reuse Dify’s existing document upload, parsing, citation, permission management.

### Describe the solution you'd like
I would like to ask: are there official plans to add native knowledge‑graph / GraphRAG capability inside Dify’s knowledge‑base pipeline?

Expected features:
1. Entity & relation extraction when importing documents inside Dify.
2. Hybrid retrieval: vector search + knowledge‑graph multi‑hop traversal.
3. Keep original citation capability, reuse Dify’s document management & permission.
4. Optional: support popular graph databases(Neo4j etc.) as backend.

### Describe alternatives you've considered
1. Call external GraphRAG service through workflow HTTP node, maintain another independent service.
2. Use Dify external knowledge‑base API to connect third‑party GraphRAG system.
Both options increase operation complexity for our production deployment.

### Additional context
Many enterprise scenarios require multi‑hop reasoning over business documents. This feature will greatly improve complex‑question answering quality.

### 2. Additional context or comments

_No response_

### 3. Can you help us with this feature?

- [ ] I am interested in contributing to this feature.

No source files, tests, or entry points are named. Start by reviewing Dify’s built-in knowledge-base pipeline and its document upload, parsing, citation, and permission flows; first establish acceptance criteria for entity and relation extraction, hybrid retrieval, and optional Neo4j support.

Written by the indexing model from the issue text.