This node establishes a connection with an Azure OpenAI Chat Model. After successfully authenticating using the Azure OpenAI Authenticator node, enter the deployment name of the model you want to use. You can find the models on the Azure AI Studio at 'Management - Deployments'.
Note that chat models can also be used as LLMs because they are actually a subcategory of LLMs that are optimized for chat-like applications.
The name of the deployed model to use. Find the deployed models on the Azure AI Studio.
The maximum number of tokens to generate.
The token count of your prompt plus max_tokens cannot exceed the model's context length.
Sampling temperature to use, between 0.0 and 2.0. Higher values means the model will take more risks. Try 0.9 for more creative applications, and 0 for ones with a well-defined answer. It is generally recommend altering this or top_p but not both.
How many chat completion choices to generate for each input message. This parameter generates many completions and can quickly consume your token quota.
An alternative to sampling with temperature, where the model considers the results of the tokens (words) with top_p probability mass. Hence, 0.1 means only the tokens comprising the top 10% probability mass are considered.
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