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RAG Knowledge Base

Drop your own neuroscience knowledge files here to improve LLM interpretations.

Supported formats

JSON files (*.json)

Each JSON file should be a flat object mapping region names to descriptions:

{
    "Amygdala (AMY)": "The amygdala processes threat detection and fear conditioning. It receives rapid subcortical visual input via the superior colliculus and pulvinar for fast threat assessment...",
    "Hippocampal Formation (HPF)": "The hippocampus is essential for episodic memory encoding and spatial navigation. Place cells in CA1 fire at specific locations..."
}

Region names do not need to match the Allen atlas names exactly -- the system uses semantic similarity (embedding search) to find the most relevant knowledge for any query.

Text files (*.txt)

Use ## Region Name headers to separate entries:

## Amygdala (AMY)
The amygdala processes threat detection and fear conditioning...

## Hippocampal Formation (HPF)
The hippocampus is essential for episodic memory encoding...

Partial coverage is fine

You do not need to cover every brain region. The system merges your files with a built-in fallback knowledge base (21 regions). For any region not covered by your files or the fallback, the LLM uses its own training knowledge.

Priority order:

  1. Your files in this directory (highest priority)
  2. Built-in fallback knowledge base (REGION_KNOWLEDGE in src/region_analyzer.py)
  3. LLM's own neuroscience training knowledge

Tips

  • More detail is better -- include connectivity, cell types, clinical relevance
  • Multiple JSON/TXT files are merged automatically
  • If two files define the same region, the last one loaded (alphabetical order) wins
  • Changes take effect on the next app startup (no need to rebuild anything)