Page Comparison

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models: {
  "GPT-4 Turbo": {
    provider: "openai",
    model: "gpt-4-1106-preview",
    apiKey: "sk-....."
  },
  "GPT-3.5 Turbo": {
    provider: "openai",
    model: "gpt-3.5-turbo-1106",
    apiKey: "sk-....."
  },
  "Gemini Pro": {
    provider: "google",
    model: "gemini-pro",
    apiKey: "AI......"
  },
  "Azure OpenAI GPT-3.5": {
    provider: "azure",
    model: "azure-gpt-35-0613",
    resource: "profound-openai",
    apiKey: "......",
    apiVersion: "2023-07-01-preview"
  },  
  "Mistral Medium with Streaming": {
    provider: "mistral",
    model: "mistral-medium",
    stream: true,
    apiKey: "......"
  },
  "Mistral 7B via Anyscale": {
    endpoint: "https://api.endpoints.anyscale.com/v1",
    apiFormat: "completion",
    model: "mistralai/Mistral-7B-Instruct-v0.1",
    apiKey: "esecret_......"
  },
  "Llama 2 70B": {
    endpoint: "https://myserver",
    apiFormat: "completion",
    model: "Llama-2-70b-chat-hf-function-calling-v2",
    apiKey: "esecret_......"
  }
}

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Use this property to specify a custom endpoint or API URL. This may be necessary for custom, open-source, and/or inhouse models.

resource

For Azure OpenAI, you can specify the the resource name in place of the full endpoint.

apiFormat

Use this property to override the default format of how the data is exchanged with the model. Providers may support different formats. For example, OpenAI offers “completion” and “assistant” API.

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This property contains the API key or secret key associated with the respective model. These keys are used for authentication when making requests to the API.

apiVersion

The API you’re using may require a version. Use this property to set the appropriate API version.

stream

Set this Boolean property to true to indicate that you want the model API to stream its output as it is generated rather than sending the output all at once. Beware that some model API may not have this capability.

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1. Go to https://portal.azure.com and sign in.

2. Search and select the Azure OpenAI service.

3. Click Create a resource and follow the steps to create the resource.

4. Go to the resource you created and select Keys and Endpoint and copy .

   1. Copy those items into your config.js file as endpoint and apiKey properties of your model.

   2. Alternatively, instead of the endpoint property, you can also set the resource property based on the resource name you chose. With this property set, the endpoint will be constructed automatically.

   3. Set the provider property to

   “openai”

   1. “azure”.

5. Go to Manage Deployments.

6. Select Create Deployment.

7. Select desired model and model version; then give it a name. Supply this name as the model property in your config.js file. Ensure the model and version you select supports function calling. It may take a few minutes before the model is fully deployed and you are ready to try it.

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