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Update llm-tool.md
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articles/machine-learning/prompt-flow/tools-reference/llm-tool.md

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# LLM tool
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The large language model (LLM) tool in prompt flow enables you to take advantage of widely used large language models like [OpenAI](https://platform.openai.com/) or [Azure OpenAI Service](../../../cognitive-services/openai/overview.md) for natural language processing.
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The large language model (LLM) tool in prompt flow enables you to take advantage of widely used large language models like [OpenAI](https://platform.openai.com/), [Azure OpenAI Service](../../../cognitive-services/openai/overview.md), or any language model supported by the [Azure AI model inference API](https://aka.ms/azureai/modelinference) for natural language processing.
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Prompt flow provides a few different large language model APIs:
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- [Completion](https://platform.openai.com/docs/api-reference/completions): OpenAI's completion models generate text based on provided prompts.
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- [Chat](https://platform.openai.com/docs/api-reference/chat): OpenAI's chat models facilitate interactive conversations with text-based inputs and responses.
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- [Chat](https://platform.openai.com/docs/api-reference/chat): OpenAI's chat models and the [Azure AI](https://aka.ms/azureai/modelinference) chat models facilitate interactive conversations with text-based inputs and responses.
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> [!NOTE]
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> We removed the `embedding` option from the LLM tool API setting. You can use an embedding API with the [embedding tool](embedding-tool.md).
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- Create Azure OpenAI resources with [these instructions](../../../ai-services/openai/how-to/create-resource.md).
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- **Models deployed to Serverless API endpoints**
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- Select the model from the catalog you are interested in [and deploy it with a serverless API endpoint](../../how-to-deploy-models-serverless.md).
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- To use models deployed to serverless API endpoints supported by the [Azure AI model inference API](https://aka.ms/azureai/modelinference), like Mistral, Cohere, Meta Llama, or Microsoft family of models (among others), you need to [create a connection in your project to your endpoint](../../how-to-connect-models-serverless.md?#create-a-serverless-api-endpoint-connection).
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## Connections
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Set up connections to provisioned resources in prompt flow.
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| OpenAI | Required | Required | - | - |
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| Azure OpenAI - API key| Required | Required | Required | Required |
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| Azure OpenAI - Microsoft Entra ID| Required | - | - | Required |
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| Serverless model | Requred | Required | - | - |
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> [!TIP]
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> - To use Microsoft Entra ID auth type for Azure OpenAI connection, you need assign either the `Cognitive Services OpenAI User` or `Cognitive Services OpenAI Contributor role` to user or user assigned managed identity.
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| Name | Type | Description | Required |
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|------------------------|-------------|------------------------------------------------------------------------------------------------|----------|
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| prompt | string | Text prompt that the language model uses for a response. | Yes |
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| model, deployment_name | string | Language model to use. | Yes |
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| model, deployment_name | string | Language model to use. This parameter is not required if the model is deployed to a serverless API endpoint. | Yes* |
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| max\_tokens | integer | Maximum number of tokens to generate in the response. Default is inf. | No |
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| temperature | float | Randomness of the generated text. Default is 1. | No |
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| stop | list | Stopping sequence for the generated text. Default is null. | No |
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## Use the LLM tool
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1. Set up and select the connections to OpenAI resources.
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1. Set up and select the connections to OpenAI resources or to a serverless API endpoint.
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1. Configure the large language model API and its parameters.
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1. Prepare the prompt with [guidance](prompt-tool.md#write-a-prompt).

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