This helps give the model context for new user queries. Select the number of past messages to include in each new API request. Try adjusting temperature or Top P but not both. Increasing Top P lets the model choose from tokens with both high and low likelihood. Lowering Top P narrows the model’s token selection to likelier tokens. Similar to temperature, this controls randomness but uses a different method. One token is roughly four characters for typical English text. The API supports a maximum of 4096 tokens shared between the prompt (including system message, examples, message history, and user query) and the model's response. Set a limit on the number of tokens per model response. Increasing the temperature results in more unexpected or creative responses. Lowering the temperature means that the model produces more repetitive and deterministic responses. For ChatGPT, you need to use the gpt-35-turbo model.Ĭontrols randomness. Your deployment name that is associated with a specific model. Select the Clear chat button to delete the current conversation history. Selecting the Send button sends the entered text to the completions API and the results are returned back to the text box. You can then take this code and write an application to complete the same task you're currently performing with the playground. You can describe the assistant's personality, tell it what it should and shouldn't answer, and tell it how to format responses.Īdd few-shot examples allows you to provide conversational examples that are used by the model for in-context learning.Īt any time while using the ChatGPT playground you can select View code to see Python, curl, and json code samples pre-populated based on your current chat session and settings selections. System messages give the model instructions about how it should behave and any context it should reference when generating a response. You can use the Assistant setup dropdown to select a few pre-loaded System message examples to get started. From this page, you can quickly iterate and experiment with the capabilities. Start exploring OpenAI capabilities with a no-code approach through the Azure OpenAI Studio ChatGPT playground. During or after the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.įrom the Azure OpenAI Studio landing page, select ChatGPT playground (Preview) Navigate to Azure OpenAI Studio at and sign-in with credentials that have access to your OpenAI resource. For more information about model deployment, see the resource deployment guide. This model is currently available in East US and South Central US. Open an issue on this repo to contact us if you have an issue.Īn Azure OpenAI Service resource with the gpt-35-turbo model deployed. You can apply for access to Azure OpenAI by completing the form at. An Azure subscription - Create one for free.Īccess granted to Azure OpenAI in the desired Azure subscription.Ĭurrently, access to this service is granted only by application.
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