# Test your prompt variants for chat with math This is a prompt tuning case with 3 prompt variants for math question answering. By utilizing this flow, in conjunction with the `evaluation/eval-chat-math` flow, you can quickly grasp the advantages of prompt tuning and experimentation with prompt flow. Here we provide a [video](https://www.youtube.com/watch?v=gcIe6nk2gA4) and a [tutorial]((../../../tutorials/flow-fine-tuning-evaluation/promptflow-quality-improvement.md)) for you to get started. Tools used in this flow: - `llm` tool - custom `python` Tool ## Prerequisites Install promptflow sdk and other dependencies in this folder: ```bash pip install -r requirements.txt ``` ## Getting started ### 1 Create connection for LLM tool to use Go to "Prompt flow" "Connections" tab. Click on "Create" button, select one of LLM tool supported connection types and fill in the configurations. Currently, there are two connection types supported by LLM tool: "AzureOpenAI" and "OpenAI". If you want to use "AzureOpenAI" connection type, you need to create an Azure OpenAI service first. Please refer to [Azure OpenAI Service](https://azure.microsoft.com/en-us/products/cognitive-services/openai-service/) for more details. If you want to use "OpenAI" connection type, you need to create an OpenAI account first. Please refer to [OpenAI](https://platform.openai.com/) for more details. ```bash # Override keys with --set to avoid yaml file changes pf connection create --file ../../../connections/azure_openai.yml --set api_key= api_base= --name open_ai_connection ``` Note in [flow.dag.yaml](flow.dag.yaml) we are using connection named `open_ai_connection`. ```bash # show registered connection pf connection show --name open_ai_connection ``` ### 2 Start chatting ```bash # run chat flow with default question in flow.dag.yaml pf flow test --flow . # run chat flow with new question pf flow test --flow . --inputs question="2+5=?" # start a interactive chat session in CLI pf flow test --flow . --interactive # start a interactive chat session in CLI with verbose info pf flow test --flow . --interactive --verbose