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Zhongwei Li
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---
description: Query store with natural language RAG
argument-hint: prompt --store name
---
Query a Gemini File Search store with natural language using RAG (Retrieval-Augmented Generation).
## Usage
```bash
gemini-file-search-tool query "PROMPT" --store "STORE_NAME" [OPTIONS]
```
## Arguments
- `PROMPT`: Natural language query (required, positional)
- `--store NAME`: Store to query (required)
- `--query-model {flash|pro}`: Query model (default: flash)
- `--query-grounding-metadata`: Include source citations
- `--show-cost`: Show token usage and cost
- `-v/-vv/-vvv`: Verbosity levels
## Examples
```bash
# Basic query
gemini-file-search-tool query "What is DORA?" --store "papers"
# Query with citations and cost tracking
gemini-file-search-tool query "How does authentication work?" \
--store "codebase" --query-grounding-metadata --show-cost -v
# Query with Pro model
gemini-file-search-tool query "Explain the architecture" \
--store "docs" --query-model pro
```
## Output
Returns JSON with response_text, usage_metadata, grounding_metadata (if requested), and estimated_cost (if requested).