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Given a prompt ID, variable values, and optionally any hyperparameters, this API returns a JSON object containing the raw prompt template.
Note: Unlike inference requests, Prompt Render API calls are processed through Portkey’s Control Plane services.
Here’s how you can take the output from the render API and use it for making a separate LLM call. We’ll take example of OpenAI SDKs, but you can use it simlarly for any other frameworks like Langchain etc. as well.
from portkey_ai import Portkey
from openai import OpenAI

# Retrieving the Prompt from Portkey

portkey = Portkey(
  api_key="PORTKEY_API_KEY"
)

render_response = portkey.prompts.render(
  prompt_id="PROMPT_ID",
  variables={ "movie":"Dune 2" }
)

PROMPT_TEMPLATE = render_response.data

# Making a Call to OpenAI with the Retrieved Prompt

openai = OpenAI(
    api_key = "OPENAI_API_KEY",
    base_url = "https://api.portkey.ai/v1",
    default_headers = {
      'x-portkey-provider': 'openai',
      'x-portkey-api-key': 'PORTKEY_API_KEY',
      'Content-Type': 'application/json',
    }
)

chat_complete = openai.chat.completions.create(**PROMPT_TEMPLATE)

print(chat_complete.choices[0].message.content)