[Feature Request]: Add Query Process Tracing (Show Subgraph Usage per Query) for LightRAG

[Huahuatii]

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Feature Request Description

Hello, I think LightRAG is a great project. However, when using it myself, I often find it difficult to understand which knowledge from the graph is being used in queries. Although we can see what knowledge is retrieved during debugging, this still isn't convenient enough.

Therefore, I'd like to propose adding query process tracing functionality to LightRAG that can record and visualize the actual nodes (entities) and edges (relationships) used during queries, and export GraphML and HTML files for analysis and debugging. This feature would help developers better understand how the LightRAG system works during queries by:

1. Helping optimize parameter values like top_k, max_token_for_text_unit, etc.
2. Providing intuitive understanding of which knowledge is actually retrieved and used during queries
3. Helping identify problem areas when query results are unsatisfactory

My current proposal is to:

• Add optional parameters to queryparam to control whether to generate this graph (without affecting any existing functionality)
• Add functionality to kg_query to save the graph used in queries
  - Implement visualization based on either graph_visual_with_html.py or a custom visualization solution
• Provide an example in the examples directory

I'm willing to contribute code for this feature and can assist with documentation writing.

### Additional Context

The complete graph：

The graph used during queries：

[Huahuatii]

Thanks for moving this to a discussion!

I've implemented a solution that now enables direct visualization of subgraph information for each query through the frontend. The feature includes optional controls that maintain full backward compatibility with existing functionality.

Implementation details:

1. Enhanced operate.py to collect subgraph data
2. Modified query_routes.py API to accept parameters for subgraph visibility control
3. Added frontend rendering logic for the subgraph visualization

Current implementation:
you can use 1 to control subplot zoom details, 2 to show/hide subplots, and 3 to generate/not generate subplots.

If everyone thinks this idea is good, I’ll continue optimizing the front-end display further.

Looking forward to your feedback—feel free to discuss!

[panacorn]

Yeah, It's gonna be great to clearly understand what going on during the processing big data

If everyone thinks this idea is good, I’ll continue optimizing the front-end display further.

Looking forward to your feedback—feel free to discuss!