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---
title: "Query"
id: experimental-query-api
description: "Components for query processing and expansion."
slug: "/experimental-query-api"
---
<a id="haystack_experimental.components.query.query_expander"></a>
## Module haystack\_experimental.components.query.query\_expander
<a id="haystack_experimental.components.query.query_expander.QueryExpander"></a>
### QueryExpander
A component that returns a list of semantically similar queries to improve retrieval recall in RAG systems.
The component uses a chat generator to expand queries. The chat generator is expected to return a JSON response
with the following structure:
### Usage example
```json
{"queries": ["expanded query 1", "expanded query 2", "expanded query 3"]}
```
```python
from haystack.components.generators.chat.openai import OpenAIChatGenerator
from haystack_experimental.components.query import QueryExpander
expander = QueryExpander(
chat_generator=OpenAIChatGenerator(model="gpt-4.1-mini"),
n_expansions=3
)
result = expander.run(query="green energy sources")
print(result["queries"])
# Output: ['alternative query 1', 'alternative query 2', 'alternative query 3', 'green energy sources']
# Note: Up to 3 additional queries + 1 original query (if include_original_query=True)
# To control total number of queries:
expander = QueryExpander(n_expansions=2, include_original_query=True) # Up to 3 total
# or
expander = QueryExpander(n_expansions=3, include_original_query=False) # Exactly 3 total
```
<a id="haystack_experimental.components.query.query_expander.QueryExpander.__init__"></a>
#### QueryExpander.\_\_init\_\_
```python
def __init__(*,
chat_generator: Optional[ChatGenerator] = None,
prompt_template: Optional[str] = None,
n_expansions: int = 4,
include_original_query: bool = True)
```
Initialize the QueryExpander component.
**Arguments**:
- `chat_generator`: The chat generator component to use for query expansion.
If None, a default OpenAIChatGenerator with gpt-4.1-mini model is used.
- `prompt_template`: Custom [PromptBuilder](https://docs.haystack.deepset.ai/docs/promptbuilder)
template for query expansion. The template should instruct the LLM to return a JSON response with the
structure: `{"queries": ["query1", "query2", "query3"]}`. The template should include 'query' and
'n_expansions' variables.
- `n_expansions`: Number of alternative queries to generate (default: 4).
- `include_original_query`: Whether to include the original query in the output.
<a id="haystack_experimental.components.query.query_expander.QueryExpander.to_dict"></a>
#### QueryExpander.to\_dict
```python
def to_dict() -> Dict[str, Any]
```
Serializes the component to a dictionary.
**Returns**:
Dictionary with serialized data.
<a id="haystack_experimental.components.query.query_expander.QueryExpander.from_dict"></a>
#### QueryExpander.from\_dict
```python
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "QueryExpander"
```
Deserializes the component from a dictionary.
**Arguments**:
- `data`: Dictionary with serialized data.
**Returns**:
Deserialized component.
<a id="haystack_experimental.components.query.query_expander.QueryExpander.run"></a>
#### QueryExpander.run
```python
@component.output_types(queries=List[str])
def run(query: str,
n_expansions: Optional[int] = None) -> Dict[str, List[str]]
```
Expand the input query into multiple semantically similar queries.
The language of the original query is preserved in the expanded queries.
**Arguments**:
- `query`: The original query to expand.
- `n_expansions`: Number of additional queries to generate (not including the original).
If None, uses the value from initialization. Can be 0 to generate no additional queries.
**Raises**:
- `ValueError`: If n_expansions is not positive (less than or equal to 0).
- `RuntimeError`: If the component is not warmed up and the chat generator does not support warm up.
**Returns**:
Dictionary with "queries" key containing the list of expanded queries.
If include_original_query=True, the original query will be included in addition
to the n_expansions alternative queries.
<a id="haystack_experimental.components.query.query_expander.QueryExpander.warm_up"></a>
#### QueryExpander.warm\_up
```python
def warm_up()
```
Warm up the underlying LLM if it supports it.