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Version: 3.17

ai-prompt-template

Description#

The ai-prompt-template Plugin supports pre-configuring prompt templates that only accept user inputs in designated template variables, in a "fill in the blank" fashion. It simplifies access to LLM providers, such as OpenAI and Anthropic, by letting you define reusable prompt structures.

Plugin Attributes#

NameTypeRequiredDefaultValid valuesDescription
templatesarrayTrueAn array of template objects.
templates.namestringTrueName of the template. When requesting the Route, the request should include the template name that corresponds to the configured template.
templates.templateobjectTrueTemplate specification.
templates.template.modelstringFalseName of the LLM model, such as gpt-4 or gpt-3.5. See your LLM provider API documentation for more available models.
templates.template.messagesarray[object]FalseTemplate message specification.
templates.template.messages.rolestringTrue[system, user, assistant]Role of the message.
templates.template.messages.contentstringTrueContent of the message (prompt). Use {{variable_name}} syntax to define template variables that will be filled from the request body.

Examples#

The following examples use OpenAI as the Upstream service provider. Before proceeding, create an OpenAI account and an API key. You can optionally save the key to an environment variable:

export OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

If you are working with other LLM providers, please refer to the provider's documentation to obtain an API key.

note

You can fetch the admin_key from config.yaml and save to an environment variable with the following command:

admin_key=$(yq '.deployment.admin.admin_key[0].key' conf/config.yaml | sed 's/"//g')

Configure a Template for Open Questions in Custom Complexity#

The following example demonstrates how to use the ai-prompt-template Plugin to configure a template that can be used to answer open questions and accepts user-specified response complexity.

The Route should now be available to respond to a variety of questions with different levels of user-specified complexity.

Send a POST request to the Route with a sample question and desired answer complexity in the request body:

curl "http://127.0.0.1:9080/openai-chat" -X POST \
  -H "Content-Type: application/json" \
  -d '{
    "template_name": "QnA with complexity",
    "complexity": "brief",
    "prompt": "quick sort"
  }'

You should receive a response similar to the following:

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Quick sort is a highly efficient sorting algorithm that uses a divide-and-conquer approach to arrange elements in a list or array in order. Here's a brief explanation:\n\n1. **Choose a Pivot**: Select an element from the list as a 'pivot'. Common methods include choosing the first element, the last element, the middle element, or a random element.\n\n2. **Partitioning**: Rearrange the elements in the list such that all elements less than the pivot are moved before it, and all elements greater than the pivot are moved after it. The pivot is now in its final position.\n\n3. **Recursively Apply**: Recursively apply the same process to the sub-lists of elements to the left and right of the pivot.\n\nThe base case of the recursion is lists of size zero or one, which are already sorted.\n\nQuick sort has an average-case time complexity of O(n log n), making it suitable for large datasets. However, its worst-case time complexity is O(n^2), which occurs when the smallest or largest element is always chosen as the pivot. This can be mitigated by using good pivot selection strategies or randomization.",
        "role": "assistant"
      }
    }
  ],
  "created": 1723194057,
  "id": "chatcmpl-9uFmTYN4tfwaXZjyOQwcp0t5law4x",
  "model": "gpt-4o-2024-05-13",
  "object": "chat.completion",
  "system_fingerprint": "fp_abc28019ad",
  "usage": {
    "completion_tokens": 234,
    "prompt_tokens": 18,
    "total_tokens": 252
  }
}

Configure Multiple Templates#

The following example demonstrates how you can configure multiple templates on the same Route. When requesting the Route, users will be able to pass custom inputs to different templates by specifying the template name.

The example continues with the last example. Update the Plugin with another template:

You should now be able to use both templates through the same Route.

Send a POST request to the Route and use the first template:

curl "http://127.0.0.1:9080/openai-chat" -X POST \
  -H "Content-Type: application/json" \
  -d '{
    "template_name": "QnA with complexity",
    "complexity": "brief",
    "prompt": "quick sort"
  }'

You should receive a response similar to the following:

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "Quick sort is a highly efficient sorting algorithm that uses a divide-and-conquer approach to arrange elements in a list or array in order. Here's a brief explanation:\n\n1. **Choose a Pivot**: Select an element from the list as a 'pivot'. Common methods include choosing the first element, the last element, the middle element, or a random element.\n\n2. **Partitioning**: Rearrange the elements in the list such that all elements less than the pivot are moved before it, and all elements greater than the pivot are moved after it. The pivot is now in its final position.\n\n3. **Recursively Apply**: Recursively apply the same process to the sub-lists of elements to the left and right of the pivot.\n\nThe base case of the recursion is lists of size zero or one, which are already sorted.\n\nQuick sort has an average-case time complexity of O(n log n), making it suitable for large datasets. However, its worst-case time complexity is O(n^2), which occurs when the smallest or largest element is always chosen as the pivot. This can be mitigated by using good pivot selection strategies or randomization.",
        "role": "assistant"
      }
    }
  ],
  ...
}

Send a POST request to the Route and use the second template:

curl "http://127.0.0.1:9080/openai-chat" -X POST \
  -H "Content-Type: application/json" \
  -d '{
    "template_name": "echo",
    "prompt": "hello APISIX"
  }'

You should receive a response similar to the following:

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "hello APISIX",
        "role": "assistant"
      }
    }
  ],
  ...
}