# Amazon Product Extraction Pack
This LlamaPack provides an example of our Amazon product extraction pack.
It loads in a website URL, screenshots the page. Then we use OpenAI GPT-4V + prompt engineering to extract the screenshot into a structured JSON output.
Check out the [notebook here](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/amazon_product_extraction/product_extraction.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 AmazonProductExtractionPack --download-dir ./amazon_product_extraction_pack
```
You can then inspect the files at `./amazon_product_extraction_pack` and use them as a template for your own project.
## Code Usage
You can download the pack to a the `./amazon_product_extraction_pack` directory:
```python
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
AmazonProductExtractionPack = download_llama_pack(
"AmazonProductExtractionPack", "./amazon_product_extraction_pack"
)
```
From here, you can use the pack, or inspect and modify the pack in `./amazon_product_extraction_pack`.
Then, you can set up the pack like so:
```python
# create the pack
# get documents from any data loader
amazon_product_extraction_pack = SentenceWindowRetrieverPack(
amazon_product_page,
)
```
The `run()` function is a light wrapper around `program()`.
```python
response = amazon_product_extraction_pack.run()
display(response.dict())
```
You can also use modules individually.
```python
# get pydantic program
program = amazon_product_extraction_pack.openai_program
# get multi-modal LLM
mm_llm = amazon_product_extraction_pack.openai_mm_llm
```
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"description": "# Amazon Product Extraction Pack\n\nThis LlamaPack provides an example of our Amazon product extraction pack.\n\nIt loads in a website URL, screenshots the page. Then we use OpenAI GPT-4V + prompt engineering to extract the screenshot into a structured JSON output.\n\nCheck out the [notebook here](https://github.com/run-llama/llama-hub/blob/main/llama_hub/llama_packs/amazon_product_extraction/product_extraction.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 AmazonProductExtractionPack --download-dir ./amazon_product_extraction_pack\n```\n\nYou can then inspect the files at `./amazon_product_extraction_pack` and use them as a template for your own project.\n\n## Code Usage\n\nYou can download the pack to a the `./amazon_product_extraction_pack` directory:\n\n```python\nfrom llama_index.core.llama_pack import download_llama_pack\n\n# download and install dependencies\nAmazonProductExtractionPack = download_llama_pack(\n \"AmazonProductExtractionPack\", \"./amazon_product_extraction_pack\"\n)\n```\n\nFrom here, you can use the pack, or inspect and modify the pack in `./amazon_product_extraction_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\namazon_product_extraction_pack = SentenceWindowRetrieverPack(\n amazon_product_page,\n)\n```\n\nThe `run()` function is a light wrapper around `program()`.\n\n```python\nresponse = amazon_product_extraction_pack.run()\ndisplay(response.dict())\n```\n\nYou can also use modules individually.\n\n```python\n# get pydantic program\nprogram = amazon_product_extraction_pack.openai_program\n\n# get multi-modal LLM\nmm_llm = amazon_product_extraction_pack.openai_mm_llm\n```\n",
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