---
title: "Experimental Package"
id: experimental-package
slug: "/experimental-package"
description: "Try out new experimental features with Haystack."
---

# Experimental Package

Try out new experimental features with Haystack.

The `haystack-experimental` package allows you to test new experimental features without committing to their official release. Its main goal is to gather user feedback and iterate on new features quickly.

Check out the `haystack-experimental` [GitHub repository](https://github.com/deepset-ai/haystack-experimental) for the latest catalog of available features, or take a look at our [Experiments API Reference](/reference).

### Installation

For simplicity, every release of `haystack-experimental` includes all the available experiments at that time. To install the latest features, run:

```shell
pip install -U haystack-experimental
```

:::info
The latest version of the experimental package is only tested against the latest version of Haystack. Compatibility with older versions of Haystack is not guaranteed.
:::

### Lifecycle

Each experimental feature has a default lifespan of 3 months starting from the date of the first non-pre-release build that includes it. Once it reaches the end of its lifespan, we will remove it from `haystack-experimental` and either:

- Merge the feature into Haystack and publish it with the next minor release,
- Release the feature as an integration, or
- Drop the feature.

### Usage

You can import the experimental new features like any other Haystack integration package:

```python
from haystack.dataclasses import ChatMessage
from haystack_experimental.components.generators import FoobarGenerator

c = FoobarGenerator()
c.run([ChatMessage.from_user("What's an experiment? Be brief.")])
```

Experiments can also override existing Haystack features. For example, you can opt into an experimental type of `Pipeline` by changing the usual import:

```python
## from haystack import Pipeline
from haystack_experimental import Pipeline

pipe = Pipeline()
## ...
pipe.run(...)
```

## Additional References

🧑‍🍳 Cookbooks:

- [Improving Retrieval with Auto-Merging and Hierarchical Document Retrieval](https://haystack.deepset.ai/cookbook/auto_merging_retriever)
- [Invoking APIs with OpenAPITool](https://haystack.deepset.ai/cookbook/openapitool)
- [Conversational RAG using Memory](https://haystack.deepset.ai/cookbook/conversational_rag_using_memory)
- [Evaluating RAG Pipelines with EvaluationHarness](https://haystack.deepset.ai/cookbook/rag_eval_harness)
- [Define & Run Tools](https://haystack.deepset.ai/cookbook/tools_support)
- [Newsletter Sending Agent with Experimental Haystack Tools](https://haystack.deepset.ai/cookbook/newsletter-agent)