semvec/pypi-packages huggingface dataset:
graphrag-webui 1.2.0
A web interface for GraphRAG.
Requires Python: >=3.6

# GraphRAG WebUI

A web interface for [GraphRAG](https://github.com/microsoft/graphrag).

## Requirements

- Ubuntu 24
  - [Azure Virtual Machines](https://portal.azure.com/#browse/Microsoft.Compute%2FVirtualMachines)
- Docker & Docker Compose
  - [Install Docker Engine on Ubuntu](https://docs.docker.com/engine/install/ubuntu/)
- [Azure CLI](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli)

## Install Docker & Docker Compose

```bash
sudo apt update -y
sudo snap install docker
sudo apt install docker-compose -y
```

## Set Authentication (Optional)

If you want to set authentication, copy and set your config.yaml:

```bash
cp config.yaml.example config.yaml
```

## Start App

```bash
bash start.sh
```

When the applications are started, you will have access to 3 URLs:

- Management App: <http://localhost:9000/>
  - OR <http://{your-vm-ip}:9000/>
- API Documentation: <http://localhost:9002/docs>
  - OR <http://{your-vm-ip}:9002/docs>

## Update GraphRAG WebUI

```bash
bash update.sh
```

## Make App as system Service

If you want to make the app as your service, run:

```bash
bash service.sh
```

## Deploy to production environment

Before deploying the applications, run:

```bash
az login
```

### Deploy Test App

```bash
bash deploy_test.sh
```

### Deploy API

```bash
bash deploy_api.sh
```
llmperf 0.0.1
A CLI tool for LLM performance testing
Requires Python: >=3.6

# LLM Perf

`llmperf` is a benchmarking tool for stress testing self-hosted LLMs, Azure OpenAI, and OpenAI APIs. It provides efficient concurrent request management, detailed performance analysis, and helps developers optimize inference latency and throughput. With customizable test parameters, it is suitable for various LLM workload evaluation scenarios.

## 1. Config your env

Copy and set up the environment variables from `.env.example`.

```bash
cp .env.example .env
```

## 2. Launch your App

Copy and set up the environment variables.

```bash
./start.sh
```