67 lines
2.9 KiB
Markdown
67 lines
2.9 KiB
Markdown
# Search and Question Answering
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## Search Settings
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Configure search behavior and context expansion:
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```yaml
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search:
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limit: 5 # Default number of results to return
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context_radius: 0 # DocItems before/after to include for text content
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max_context_items: 10 # Maximum items in expanded context
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max_context_chars: 10000 # Maximum characters in expanded context
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```
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- **limit**: Default number of search results to return when no limit is specified. Used by CLI, MCP server, QA, and research workflows. Default: 5
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- **context_radius**: For text content (paragraphs), includes N DocItems before and after. Set to 0 to disable expansion (default).
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- **max_context_items**: Limits how many document items (paragraphs, list items, etc.) can be included in expanded context. Default: 10.
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- **max_context_chars**: Hard limit on total characters in expanded content. Default: 10000.
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Structural content (tables, code blocks, lists) uses type-aware expansion that automatically includes the complete structure regardless of how it was chunked.
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!!! note "Reranking behavior"
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When a reranker is configured, search automatically retrieves 10x the requested limit, then reranks to return the final count. This improves result quality without requiring you to adjust `limit`.
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## Question Answering Configuration
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Configure the QA workflow:
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```yaml
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qa:
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model:
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provider: ollama
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name: gpt-oss
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enable_thinking: false
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max_sub_questions: 3 # Maximum sub-questions for deep QA
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max_iterations: 2 # Maximum search iterations per sub-question
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max_concurrency: 1 # Sub-questions processed in parallel
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```
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- **model**: LLM configuration (see [Providers](providers.md#model-settings))
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- **max_sub_questions**: For deep QA mode, maximum number of sub-questions to generate (default: 3)
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- **max_iterations**: Maximum search/evaluate cycles per sub-question (default: 2)
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- **max_concurrency**: Number of sub-questions to process in parallel (default: 1)
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Deep QA mode (`haiku-rag ask --deep`) decomposes complex questions into sub-questions, processes them in parallel batches, and synthesizes the results.
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## Research Configuration
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Configure the multi-agent research workflow:
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```yaml
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research:
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model:
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provider: "" # Empty to use qa settings
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name: "" # Empty to use qa model
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enable_thinking: false
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max_iterations: 3
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confidence_threshold: 0.8
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max_concurrency: 1
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```
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- **model**: LLM configuration. Leave provider/model empty to inherit from `qa` (see [Providers](providers.md#model-settings))
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- **max_iterations**: Maximum search/evaluate cycles (default: 3)
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- **confidence_threshold**: Stop when confidence score meets/exceeds this (default: 0.8)
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- **max_concurrency**: Sub-questions searched in parallel per iteration (default: 1)
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The research workflow plans sub-questions, searches in parallel batches, evaluates findings, and iterates until reaching the confidence threshold or max iterations.
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