Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.
Here are some screenshots of the chatbot in action:
To enhance your development experience, you can add the Prompt Flow extension to Visual Studio Code. This extension provides a range of features to streamline your workflow, including syntax highlighting, code snippets, and integration with the Prompt Flow CLI.
- Open Visual Studio Code.
- Go to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side of the window or by pressing
Ctrl+Shift+X. - Search for "Prompt Flow" by Microsoft.
- Click the Install button for the Prompt Flow extension.
Once installed, you can start using the extension to improve your prompt engineering and development process.
For optimal performance and compatibility, it is recommended to use Python 3.9.
This project contains two main components: the Car Inspection Claim Agent and the Motor Insurance Claim Agent. Both agents are designed to assist users with their respective claims processes.
Car inspections that traditionally involve long wait times, manual paperwork, and back-and-forth coordination. But what if AI could make these seamless? That’s exactly what I’ve built! Buying or renewing car insurance? AI agent ensures the inspection process is quick and hassle-free, leveraging real-time image processing. Snap, submit, done!
Motor insurance claims can be a tedious process, involving multiple stakeholders and manual verification. But what if AI could make it seamless? That’s exactly what I’ve built! Imagine an AI agent that helps users raise a claim in real time, guiding them through the process effortlessly. No more endless calls — just a smooth, automated experience.
To deploy the prompt flow for this project, follow the detailed guide provided by Microsoft. You can find step-by-step instructions on how to deploy a flow at the following link: How to Deploy a Flow.
pf flow build --source . --output dist --format dockerdocker build dist -t <Image-Name>Before running the Docker image, ensure you set AOAI_CONNECTION_API_KEY environment variable.
docker run -e AOAI_CONNECTION_API_KEY=<Your-API-Key> <Image-Name>az login
az acr login --name <ACR-Name>docker tag <Image-Name>:latest <ACR-Name>.azurecr.io/<Image-Name>:latestdocker push <ACR-Name>.azurecr.io/<Image-Name>:latestFor more information, visit the Prompt Flow Documentation.