# RAG Local CLI Pack
This LlamaPack implements a fully local version of our [RAG CLI](https://docs.llamaindex.ai/en/stable/use_cases/q_and_a/rag_cli.html),
with Mistral (through Ollama) and [BGE-M3](https://huggingface.co/BAAI/bge-m3).
## CLI Usage
You can download llamapacks directly using `llamaindex-cli`, which comes installed with the `llama-index` python package:
```bash
llamaindex-cli download-llamapack LocalRAGCLIPack --download-dir ./local_rag_cli_pack
```
You can then inspect the files at `./local_rag_cli_pack` and use them as a template for your own project!
## Code Usage
You can download the pack to a directory. **NOTE**: You must specify `skip_load=True` - the pack contains multiple files,
which makes it hard to load directly.
We will show you how to import the agent from these files!
```python
from llama_index.core.llama_pack import download_llama_pack
# download and install dependencies
download_llama_pack("LocalRAGCLIPack", "./local_rag_cli_pack", skip_load=True)
```
From here, you can use the pack. The most straightforward way is through the CLI. You can directly run base.py, or run the `setup_cli.sh` script.
```bash
cd local_rag_cli_pack
# option 1
python base.py rag -h
# option 2 - you may need sudo
# default name is lcli_local
sudo sh setup_cli.sh
lcli_local rag -h
```
You can also directly get modules from the pack.
```python
from local_rag_cli_pack.base import LocalRAGCLIPack
pack = LocalRAGCLIPack(
verbose=True, llm_model_name="mistral", embed_model_name="BAAI/bge-m3"
)
# will spin up the CLI
pack.run()
# get modules
rag_cli = pack.get_modules()["rag_cli"]
rag_cli.cli()
```
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"description": "# RAG Local CLI Pack\n\nThis LlamaPack implements a fully local version of our [RAG CLI](https://docs.llamaindex.ai/en/stable/use_cases/q_and_a/rag_cli.html),\nwith Mistral (through Ollama) and [BGE-M3](https://huggingface.co/BAAI/bge-m3).\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 LocalRAGCLIPack --download-dir ./local_rag_cli_pack\n```\n\nYou can then inspect the files at `./local_rag_cli_pack` and use them as a template for your own project!\n\n## Code Usage\n\nYou can download the pack to a directory. **NOTE**: You must specify `skip_load=True` - the pack contains multiple files,\nwhich makes it hard to load directly.\n\nWe will show you how to import the agent from these files!\n\n```python\nfrom llama_index.core.llama_pack import download_llama_pack\n\n# download and install dependencies\ndownload_llama_pack(\"LocalRAGCLIPack\", \"./local_rag_cli_pack\", skip_load=True)\n```\n\nFrom here, you can use the pack. The most straightforward way is through the CLI. You can directly run base.py, or run the `setup_cli.sh` script.\n\n```bash\ncd local_rag_cli_pack\n\n# option 1\npython base.py rag -h\n\n# option 2 - you may need sudo\n# default name is lcli_local\nsudo sh setup_cli.sh\nlcli_local rag -h\n\n```\n\nYou can also directly get modules from the pack.\n\n```python\nfrom local_rag_cli_pack.base import LocalRAGCLIPack\n\npack = LocalRAGCLIPack(\n verbose=True, llm_model_name=\"mistral\", embed_model_name=\"BAAI/bge-m3\"\n)\n# will spin up the CLI\npack.run()\n\n# get modules\nrag_cli = pack.get_modules()[\"rag_cli\"]\nrag_cli.cli()\n```\n",
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