# LLaVA Completion Pack
This LlamaPack creates the LLaVA multimodal model, and runs its `complete` endpoint to execute queries.
## CLI Usage
You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:
```bash
llamaindex-cli download-llamapack LlavaCompletionPack --download-dir ./llava_pack
```
You can then inspect the files at `./llava_pack` and use them as a template for your own project!
## Code Usage
You can download the pack to a `./llava_pack` directory:
```python
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
LlavaCompletionPack = download_llama_pack(
"LlavaCompletionPack", "./llava_pack"
)
```
From here, you can use the pack, or inspect and modify the pack in `./llava_pack`.
Then, you can set up the pack like so:
```python
# create the pack
llava_pack = LlavaCompletionPack(image_url="./images/image1.jpg")
```
The `run()` function is a light wrapper around `llm.complete()`.
```python
response = llava_pack.run(
"What dinner can I cook based on the picture of the food in the fridge?"
)
```
You can also use modules individually.
```python
# call the llm.complete()
llm = llava_pack.llm
response = llm.complete("query_str")
```
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"description": "# LLaVA Completion Pack\n\nThis LlamaPack creates the LLaVA multimodal model, and runs its `complete` endpoint to execute queries.\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 LlavaCompletionPack --download-dir ./llava_pack\n```\n\nYou can then inspect the files at `./llava_pack` and use them as a template for your own project!\n\n## Code Usage\n\nYou can download the pack to a `./llava_pack` directory:\n\n```python\nfrom llama_index.core.llama_pack import download_llama_pack\n\n# download and install dependencies\nLlavaCompletionPack = download_llama_pack(\n \"LlavaCompletionPack\", \"./llava_pack\"\n)\n```\n\nFrom here, you can use the pack, or inspect and modify the pack in `./llava_pack`.\n\nThen, you can set up the pack like so:\n\n```python\n# create the pack\nllava_pack = LlavaCompletionPack(image_url=\"./images/image1.jpg\")\n```\n\nThe `run()` function is a light wrapper around `llm.complete()`.\n\n```python\nresponse = llava_pack.run(\n \"What dinner can I cook based on the picture of the food in the fridge?\"\n)\n```\n\nYou can also use modules individually.\n\n```python\n# call the llm.complete()\nllm = llava_pack.llm\nresponse = llm.complete(\"query_str\")\n```\n",
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