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OpenAI Workflows

OpenAI LLM Response

This workflow demonstrates how to use the OpenAI LLM SDK to generate a response to a user's message.

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Note
  • Make sure that you have the OPENAI_API_KEY environment variable set in preferences.
  • Make sure that the output mode in the Text Node is set to LLM Content.
  • The exact index to access the response from a non-reasoning OpenAI response is ['output'][0]['content'][0]['text']. This is the value that you need to pass to the query with index node.

OpenAI Vision Response

This workflow demonstrates how to use the OpenAI to generate a response to a user's message to use the vision capabilities of an LLM.

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Note
  • Make sure that you have the OPENAI_API_KEY environment variable set in preferences.
  • Make sure that the output mode in the Text and Image Nodes is set to LLM Content.
  • The exact index to access the response from a non-reasoning OpenAI response is ['output'][0]['content'][0]['text']. This is the value that you need to pass to the query with index node.

OpenAI Response with Schema

This workflow demonstrates how to use the OpenAI to generate a response to a user's message with a schema.

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Note
  • Make sure that you have the OPENAI_API_KEY environment variable set in preferences.
  • Make sure that the output mode in the Text Node is set to LLM Content.
  • The exact index to access the response from a non-reasoning OpenAI response is ['parsed_output']. This is the value that you need to pass to the query with index node.

OpenAI Vision Response with Schema

This workflow demonstrates how to use the OpenAI to generate a response to a user's message with a schema.

Download Workflow

Note
  • Make sure that you have the OPENAI_API_KEY environment variable set in preferences.
  • Make sure that the output mode in the Text and Image Nodes is set to LLM Content.
  • The exact index to access the response from a non-reasoning OpenAI response is ['parsed_output']. This is the value that you need to pass to the query with index node.