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OpenAI

OpenAI provides a suite of powerful AI models for generating text, creating images, analyzing sentiment, and classifying text. These models can be used to enhance applications with advanced AI capabilities.

Generate text response

Generate a response using OpenAI's Chat Completion API based on input messages.

Fields

  • Model ID: Enter the ID of the model you'd like to use. Common models include 'gpt-4o', 'gpt-3.5-turbo'. Verify model compatibility with the API. This field is required and must not be empty.
  • Messages: The array of message objects that represents the conversation. Each message should contain a 'role' (system, user, etc.) and 'content'. This field is required and must be a valid JSON array.
  • Temperature: Sampling temperature. Between 0 and 2. Adjusts randomness; lower is more deterministic, higher is more diverse. This field is optional.
  • Max Completion Tokens: The maximum number of tokens to generate. Helps control output length and cost. This field is optional.

Output

The output is a generated text response based on the input messages and model parameters.

Generate an image

Creates an image based on a given prompt using OpenAI's DALL-E model.

Fields

  • Prompt: A text description of the desired image(s). The maximum length is 4000 characters for dall-e-3. Provide a clear and concise description of the image you want to generate. This field is required.
  • Model: The model to use for image generation. For dall-e-2, set 'dall-e-2'. This field is optional.
  • Number of Images: The number of images to generate. For dall-e-3, only 1 is supported. This field is optional.
  • Image Size: The size of the generated images. Must be one of 1024x1024, 1792x1024, or 1024x1792 for dall-e-3 models. This field is optional.

Output

The output is a generated image based on the provided prompt and model parameters.

Generate text response to image input

Generates a model response for a given chat conversation with image input.

Fields

  • AI Model Selection: Select the AI model you wish to use for image and text analysis. Depending on your needs, different models like 'gpt-4o' might be used. This field is required.
  • Text Query: Enter the text prompt or question that describes what you want to analyze or ask about the image. This field is required.
  • Image URL: Provide a direct URL to the image you want to analyze. Ensure the URL is accessible and points directly to an image file. This field is required.
  • Max Tokens: Set the maximum number of tokens for the AI to return in its response. A higher number means more detailed responses. This field is optional.

Output

The output is a text response generated by the model based on the image and text input.

Analyze text sentiment

Analyzes the sentiment of provided text using OpenAI's language model.

Fields

  • Model ID: The ID of the model you wish to use for sentiment analysis. GPT-3.5-turbo and GPT-4 are recommended for their accuracy in sentiment analysis. This field is required.
  • Text Content: The text content you want to analyze for sentiment. This can be a sentence, paragraph, or longer text. This field is required.
  • Temperature: Controls randomness in the analysis. Use lower values (0.1-0.3) for more consistent sentiment analysis results. This field is optional.

Output

The output is a sentiment classification of the text as POSITIVE, NEGATIVE, or NEUTRAL.

Classify text into custom categories

Precisely categorizes input text into user-defined categories using OpenAI's language models.

Fields

  • Model ID: The ID of the model to use. This field is required.
  • Classification Categories: Define your categories as a comma-separated list. Each category can optionally include a brief description in parentheses. This field is required.
  • Classification Instructions: Specific instructions for how to apply the categories. This field is optional.
  • Text to Classify: The text content to be classified into one of the specified categories. This field is required.
  • Temperature: Sampling temperature. Use 0.1-0.3 for consistent classification results, higher values for more variety. This field is optional.

Output

The output is the classification of the text into one of the specified categories.

Classify text into risk matrix levels

Classifies input text into risk levels based on a 3x3 matrix of impact and likelihood using OpenAI's language models.

Fields

  • Model ID: The ID of the model to use. This field is required.
  • Impact Levels: Define your impact levels as a comma-separated list. This field is required.
  • Likelihood Levels: Define your likelihood levels as a comma-separated list. This field is required.
  • Risk Matrix Instructions: Specific instructions for how to assess the risk matrix levels. This field is optional.
  • Text to Classify: The text content to be classified into one of the specified categories. This field is required.
  • Temperature: Sampling temperature. Use 0.1-0.3 for consistent classification results, higher values for more variety. This field is optional.

Output

The output is the classification of the text into a risk matrix level based on the specified impact and likelihood levels.