langchain/templates/intel-rag-xeon/intel_rag_xeon.ipynb
lvliang-intel 0175906437
templates: add RAG template for Intel Xeon Scalable Processors (#18424)
**Description:**
This template utilizes Chroma and TGI (Text Generation Inference) to
execute RAG on the Intel Xeon Scalable Processors. It serves as a
demonstration for users, illustrating the deployment of the RAG service
on the Intel Xeon Scalable Processors and showcasing the resulting
performance enhancements.

**Issue:**
None

**Dependencies:**
The template contains the poetry project requirements to run this
template.
CPU TGI batching is WIP.

**Twitter handle:**
None

---------

Signed-off-by: lvliang-intel <liang1.lv@intel.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-29 14:37:32 -07:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "681a5d1e",
"metadata": {},
"source": [
"## Connect to RAG App\n",
"\n",
"Assuming you are already running this server:\n",
"```bash\n",
"langserve start\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d774be2a",
"metadata": {},
"outputs": [],
"source": [
"from langserve.client import RemoteRunnable\n",
"\n",
"gaudi_rag = RemoteRunnable(\"http://localhost:8000/intel-rag-xeon\")\n",
"\n",
"print(gaudi_rag.invoke(\"What was Nike's revenue in 2023?\"))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "07ae0005",
"metadata": {},
"outputs": [],
"source": [
"print(gaudi_rag.invoke(\"How many employees work at Nike?\"))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}