promptflow

Introduction to Prompt Flow

Prompt Flow is a comprehensive suite of development tools geared towards simplifying the creation and deployment of AI applications that use large language models (LLMs). It supports users through every stage of development, from ideation and prototyping to testing, evaluation, production deployment, and monitoring. By focusing on prompt engineering, it aims to empower developers to produce applications of production quality.

Key Features of Prompt Flow

• Create and Develop Flows:

  • Developers can craft executable flows that integrate LLMs with various prompts, Python code, and other tools. This feature allows for easy debugging and iterative development, making it simple to trace interactions with LLMs.

• Evaluate Flow Quality and Performance:

  • The platform enables the evaluation of flows with large datasets, ensuring that developers can integrate these tests into their CI/CD systems for continuous quality assurance.

• Streamlined Production Cycle:

  • Deploying to a chosen serving platform is made straightforward, and there's an option to enhance collaboration with a team using the cloud version available in Azure AI.

Getting Started

To quickly begin using Prompt Flow, developers can utilize a pre-built development environment available via GitHub Codespaces. Alternatively, setting up locally is also possible with Python versions 3.9 to 3.11. Installation is simple using pip:

pip install promptflow promptflow-tools

Quick Start Guide

Build a Chatbot with Prompt Flow

1. Initialize the Flow:

   Start a new prompt flow from a chat template with:

   pf flow init --flow ./my_chatbot --type chat
   

2. Set Up API Key Connection:

   For OpenAI, establish a connection using a YAML file containing the necessary API key:

   pf connection create --file ./my_chatbot/openai.yaml --set api_key=<your_api_key> --name open_ai_connection
   

   For Azure OpenAI, use:

   pf connection create --file ./my_chatbot/azure_openai.yaml --set api_key=<your_api_key> api_base=<your_api_base> --name open_ai_connection
   

3. Interact with Your Chatbot:

   Test your chatbot by running:

   pf flow test --flow ./my_chatbot --interactive
   

   This command allows users to interact with the chatbot in real-time.

Ensuring High Quality from Prototype to Production

Prompt Flow emphasizes the importance of high-quality output from the prototype phase all the way to production. To achieve this, they recommend a comprehensive tutorial that guides developers through prompt tuning, batch testing, and evaluation.

Tutorials and Further Learning

The platform offers a range of tutorials, such as creating chat applications with integrated evaluation metrics. These resources help developers build robust applications efficiently.

Contribution and Community Engagement

Prompt Flow is an open project welcoming contributions and suggestions. Contributors need to agree to a Contributor License Agreement. The project also follows Microsoft's Open Source Code of Conduct, ensuring a safe and respectful environment for collaboration.

Conclusion

With Prompt Flow, developers have access to a well-rounded toolkit for building high-quality LLM-based applications. The capabilities to create, evaluate, and deploy flows make it a valuable asset for any developer looking to harness the power of AI systematically and efficiently.