# Auto Merging Retriever Pack
This LlamaPack provides an example of our auto-merging retriever.
This specific template shows the e2e process of building this. It loads
a document, builds a hierarchical node graph (with bigger parent nodes and smaller
child nodes).
Check out the [notebook here](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/auto_merging_retriever/auto_merging_retriever.ipynb).
## CLI Usage
You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:
```bash
llamaindex-cli download-llamapack AutoMergingRetrieverPack --download-dir ./auto_merging_retriever_pack
```
You can then inspect the files at `./auto_merging_retriever_pack` and use them as a template for your own project.
## Code Usage
You can download the pack to a the `./auto_merging_retriever_pack` directory:
```python
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
AutoMergingRetrieverPack = download_llama_pack(
"AutoMergingRetrieverPack", "./auto_merging_retriever_pack"
)
```
From here, you can use the pack, or inspect and modify the pack in `./auto_merging_retriever_pack`.
Then, you can set up the pack like so:
```python
# create the pack
# get documents from any data loader
auto_merging_retriever_pack = AutoMergingRetrieverPack(
documents,
)
```
The `run()` function is a light wrapper around `query_engine.query()`.
```python
response = auto_merging_retriever_pack.run(
"Tell me about what the author did growing up."
)
```
You can also use modules individually.
```python
# get the node parser
node_parser = auto_merging_retriever_pack.node_parser
# get the retriever
retriever = auto_merging_retriever_pack.retriever
# get the query engine
query_engine = auto_merging_retriever_pack.query_engine
```
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"description": "# Auto Merging Retriever Pack\n\nThis LlamaPack provides an example of our auto-merging retriever.\n\nThis specific template shows the e2e process of building this. It loads\na document, builds a hierarchical node graph (with bigger parent nodes and smaller\nchild nodes).\n\nCheck out the [notebook here](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/auto_merging_retriever/auto_merging_retriever.ipynb).\n\n## CLI Usage\n\nYou can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:\n\n```bash\nllamaindex-cli download-llamapack AutoMergingRetrieverPack --download-dir ./auto_merging_retriever_pack\n```\n\nYou can then inspect the files at `./auto_merging_retriever_pack` and use them as a template for your own project.\n\n## Code Usage\n\nYou can download the pack to a the `./auto_merging_retriever_pack` directory:\n\n```python\nfrom llama_index.core.llama_pack import download_llama_pack\n\n# download and install dependencies\nAutoMergingRetrieverPack = download_llama_pack(\n \"AutoMergingRetrieverPack\", \"./auto_merging_retriever_pack\"\n)\n```\n\nFrom here, you can use the pack, or inspect and modify the pack in `./auto_merging_retriever_pack`.\n\nThen, you can set up the pack like so:\n\n```python\n# create the pack\n# get documents from any data loader\nauto_merging_retriever_pack = AutoMergingRetrieverPack(\n documents,\n)\n```\n\nThe `run()` function is a light wrapper around `query_engine.query()`.\n\n```python\nresponse = auto_merging_retriever_pack.run(\n \"Tell me about what the author did growing up.\"\n)\n```\n\nYou can also use modules individually.\n\n```python\n# get the node parser\nnode_parser = auto_merging_retriever_pack.node_parser\n\n# get the retriever\nretriever = auto_merging_retriever_pack.retriever\n\n# get the query engine\nquery_engine = auto_merging_retriever_pack.query_engine\n```\n",
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