https://github.com/webmaxru/enterprompt
Enterprise Prompting Demo
https://github.com/webmaxru/enterprompt
azure azure-openai azureopenai chatgpt openai prompt-engineering
Last synced: 12 months ago
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Enterprise Prompting Demo
- Host: GitHub
- URL: https://github.com/webmaxru/enterprompt
- Owner: webmaxru
- License: mit
- Created: 2023-06-07T22:03:15.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2025-01-30T10:04:51.000Z (over 1 year ago)
- Last Synced: 2025-04-15T18:11:09.294Z (about 1 year ago)
- Topics: azure, azure-openai, azureopenai, chatgpt, openai, prompt-engineering
- Language: JavaScript
- Homepage: https://enterprise.promptengineering.rocks/
- Size: 2.18 MB
- Stars: 11
- Watchers: 2
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Enterprise Prompt Engineering - Your company's very own ChatGPT
This is an alternative app (frontend and backend) for the [ChatGPT + Enterprise data with Azure OpenAI and Cognitive Search](https://github.com/Azure-Samples/azure-search-openai-demo/) project.
### Web application (installable, offline-ready)
[EnterPrompt](https://enterprise.promptengineering.rocks/) - ChatGPT-powered bot which only uses your enterprise data
## Getting Started
### Frontend
First, run the development server:
```bash
cd app
npm install
npm run dev
```
Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.
### Backend
There are 2 options available:
- running API from external server (hosted demo). You can only use the data that is already there.
- locally. Then you can upload your own data and create your own flavor of assistant (and deploy it if you wish). Running locally requires Azure account - you can get one with $200 credit for free [here](https://aka.ms/free-azure-pass).
#### Running API from external server
Just rename `.env.external-api.local` to `.env.local` and you are good to go. You will use https://enterprise.promptengineering.rocks/api as a backend proxied via Rapid API to deal with CORS.
#### Running API locally
1. Install [Python 3+](https://www.python.org/downloads/), [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli), and [Azure Functions Core Tools](https://learn.microsoft.com/en-us/azure/azure-functions/functions-run-local?tabs=v4%2Cwindows%2Ccsharp%2Cportal%2Cbash#v2)
2. In your Azure account create a new resource group with the following services (free or lowest tier is fine):
- Azure OpenAI Service with 2 model deployments: text-davinci-003 and gpt-35-turbo
- Azure Cognitive Search service. Free tier is fine.
- Form Recognizer. Free tier is fine.
- Azure Storage
- Azure Static Web Apps (if you want to deploy your app later). Free tier is fine.
3. Prepare your data.
- Replace PDFs in the data folder with your own ones.
- Rename `scripts/.env.template` to `scripts/.env` and enter services names and keys from the previous step there.
- Run `./scripts/prepdocs.ps1` or `./scripts/prepdocs.sh` (depending on your OS). This script will upload your PDFs to Azure Storage (split into pages) and create a new index in Azure Cognitive Search.
4. In `app/api/` folder rename `local.settings.template.json` to `local.settings.json` and fill in the values there by the names, endpoints, keys from the first step.
5. Run `func start` in `app/api/` folder. This will start Azure Functions locally.
6. You might also want to fine-tune prompts, quickstarts, and suggestions in JSON files located in `app/api/promptengineering` and `app/promptengineering` folders.
You are fully ready to interact with your own assistant now!
## About
### Author
[Maxim Salnikov](https://twitter.com/webmaxru). Feel free to contact me if you have any questions about the project, PWA, Web Push, etc.
### License
This project is licensed under the terms of the MIT license.