# Search and Question Answering

## Search Settings

Configure search behavior and context expansion:

```yaml
search:
  limit: 5                     # Default number of results to return
  max_context_chars: 5000     # Maximum characters in expanded context
```

- **limit**: Default number of search results to return when no limit is specified. Used by CLI, MCP server, and QA. Default: 5
- **max_context_chars**: Hard limit on total characters in expanded content. Default: 5000.

Context expansion is automatic and section-aware. For structured documents (with section headers), expansion includes the entire section containing the match. For sections that exceed the budget or are too small (e.g., a title+authors area), expansion grows outward item-by-item from the match center, skipping noise labels (page headers, page footers, table of contents). This naturally crosses into adjacent sections until the budget is filled. Picture and table matches are exempt: they return their enclosing section as-is and never cross section boundaries. For unstructured documents, expansion grows outward item-by-item. Results without `doc_item_refs` (e.g., custom chunks passed to `import_document`) pass through unexpanded.

!!! note "Reranking behavior"
    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`.

## Question Answering Configuration

Configure the RAG capability (used by `client.ask` and `haiku-rag ask`):

```yaml
qa:
  model:
    provider: ollama
    name: qwen3.8
    enable_thinking: true
    temperature: 0.3          # Default: 0.3
    vision: true              # Set false for text-only models
  max_searches: 5       # Maximum search units per question
```

- **model**: LLM configuration (see [Providers](providers.md#model-settings))
- **model.vision**: Set to `true` for vision-capable models (`qwen2.5vl`, `qwen3.6`, `gpt-4o`, `claude-sonnet`, …). The capability's `search` tool only attaches picture bytes (`BinaryContent`) to its `ToolReturn` when this is `true`, otherwise picture bytes are withheld. See [Pictures × embedder × QA model](processing.md#pictures-embedder-qa-model-how-the-pieces-compose) for the full matrix.
- **max_searches**: Maximum number of search units a capability can spend per question (default: 5). Up to three searches emitted in the same model response share one unit, so a model that rephrases its query in one response spends one unit. A search in a later response starts a new unit, as does each further group of three within one response. Shared by the RAG and analysis capabilities. Searches in one response also deduplicate their returns: evidence a sibling search already showed collapses to a reference line, and each picture attaches once per response.

!!! note "Thinking on vLLM"
    `enable_thinking` only applies to models with a pydantic-ai reasoning profile (o-series, gpt-5, gpt-oss). For other vLLM-served models such as Qwen3 or the Gemma family, the field is a silent no-op — set the chat template switch via [`extra_body`](providers.md#raw-provider-pass-through) instead.

## Analysis Configuration

Configure the analysis capability:

```yaml
analysis:
  model:
    provider: anthropic
    name: claude-sonnet-4-20250514
    temperature: 0.0        # Default: 0.0 (deterministic for code generation)
  code_timeout: 60.0      # Per call: compute stops, no read or search starts past it
  max_output_chars: 50000 # Truncate output after this many chars
  max_executions: 15      # Max execute_code calls per question
```

- **model**: LLM configuration (see [Providers](providers.md#model-settings)). When unset, falls back to `qa.model`.
- **code_timeout**: Seconds a single `execute_code` call has (default: 60). Past it the sandbox starts no further host call, a document read or an in-code `search()` / `list_documents()`; one already running finishes. Code that computes without host calls is killed by the worker watchdog at the same limit. `code_timeout * max_executions` is the cumulative ceiling across all calls in one question.
- **max_output_chars**: Truncate code output after this many characters (default: 50000)
- **max_executions**: Maximum `execute_code` calls per question before the capability is told to answer from what it has (default: 15)

See [Analysis capability](../capabilities/analysis.md) for usage details.