OpenAI (Tech Preview) operation

The OpenAI (Tech Preview) connector Operations lets you discover and Invoke AI models on OpenAI. You can use it to generate content, create images, generate embeddings, or structured outputs.

Browsing

When you import an operation or browse objects, the connector presents the available object types based on the selected operation:

Generate Operation: Lists available sub-actions (Text, Images, Embeddings, Structured Output)

Each object type has corresponding request and response profiles that are imported during the browse process.

Generate operation

Use Generate operation to invoke OpenAI models for one-time content generation requests. This operation supports four sub-actions (object types):

Generate Text
Generate Image
Generate Embedding
Generate Structured Output

Generate text

Produces AI-generated text (answers, summaries, creative content, code, or responses) from text prompts using GPT models.

Before you begin

Ensure your OpenAI account has access to the desired model.
Prepare JSON that matches the text generation schema.
Choose an appropriate model (for example, gpt-4o, gpt-4o-mini, gpt-4-turbo, gpt-3.5-turbo, etc.)

Configure

Create a new Generate operation or click Import Operation.
Select Action Type: Generate Text.
Click Next to import Request and Response profiles.
Configure mapping for your input prompt and model selection.

Request Schema (GENERATE TEXT)

{
    "model": "gpt-4o-mini",
    "input": "Explain quantum computing in simple terms",
    "instructions": "You are a helpful science educator. Explain concepts clearly.",
    "temperature": 0.7,
    "max_output_tokens": 500,
    "top_p": 1.0
}

Response Schema (GENERATE TEXT)

{
    "id": "resp_abc123",
    "object": "response",
    "created_at": 1699000000,
    "model": "gpt-4o-mini",
    "status": "completed",
    "output": [
        {
            "type": "message",
            "role": "assistant",
            "content": [
                {
                    "type": "output_text",
                    "text": "Quantum computing is a type of computing that uses..."
                }
            ]
        }
    ],
    "usage": {
        "input_tokens": 25,
        "output_tokens": 150,
        "total_tokens": 175
    }
}

Generate image

Creates images from text prompts using OpenAI's image generation models.

Before you begin

Ensure your account has access to image generation models.
Choose an image-capable model (e.g., gpt-image-1, dall-e-2).
Prepare JSON that matches the image generation schema.

Configure

Create a new Generate operation or click Import Operation.
Select Action Type: Generate Image
Click Next to import Request and Response profiles.
Configure mapping for your image prompt and parameters.

Request Schema (GENERATE IMAGE)

{
    "prompt": "A futuristic city skyline at sunset with flying cars",
    "model": "gpt-image-1",
    "n": 1,
    "size": "1024x1024",
    "quality": "high",
    "output_format": "png",
    "background": "auto"
}

Response Schema (GENERATE IMAGE)

{
    "created": 1699000000,
    "data": [
        {
            "b64_json": "iVBORw0KGgoAAAANSUhEUgAA..."
        }
    ],
    "background": "opaque",
    "output_format": "png",
    "quality": "high",
    "size": "1024x1024",
    "usage": {
        "input_tokens": 50,
        "output_tokens": 1000,
        "total_tokens": 1050
    }
}

Generate embedding

Returns numerical vector embeddings for input text, useful for semantic search, clustering, and similarity comparisons.

Before you begin

Ensure your account has access to embedding models.
Choose an embedding model (for example, text-embedding-3-small, text-embedding-3-large, text-embedding-ada-002).
Prepare JSON that matches the embedding schema.

Configure

Create a new Generate operation or click Import Operation.
Select Action Type: Generate Embedding
Click Next to import Request and Response profiles.
Configure mapping for your input text.

Request Schema (GENERATE EMBEDDING)

{
    "model": "text-embedding-3-small",
    "input": ["The quick brown fox jumps over the lazy dog"],
    "encoding_format": "float",
    "dimensions": 1536
}

Response Schema (GENERATE EMBEDDING)

{
    "object": "embedding",
    "index": 0,
    "embedding": [
        -0.006929283,
        -0.005336422,
        0.024265893,
        ...
    ]
}

Generate structured output

Generates responses conforming to a user-defined JSON schema, ensuring consistent and parseable output formats.

Before you begin

Define your desired output JSON schema.
Prepare the complete text parameter JSON including format configuration.
Expected format:

	{
    "format": {
        "type": "json_schema",
        "name": "name of the schema",
        "Schema":{ 
		// Customer's schema
},
        "strict": true
    }
}

Choose a compatible model and input.

Configure

Create a new Generate operation or click Import Operation.
Select Action Type: Generate Structured Output
In the Text Parameter (JSON) field, paste your complete text parameter JSON.
Click Next to import dynamically generated Request and Response profiles.
Configure mapping for your model, input and other parameters

note

The text parameter with your schema is automatically injected by the connector based on your design-time configuration, therefore it is not required to be passed at runtime in the process.

Request Schema (GENERATE STRUCTURED OUTPUT)

{
    "model": "gpt-4o-mini",
    "input": [
        {
            "role": "user",
            "content": "Extract product information from: iPhone 15 Pro - $999, Electronics, Available now"
        }
    ],
    "instructions": "Extract structured product information from the text.",
    "temperature": 0
}

Response Schema (GENERATE STRUCTURED OUTPUT)

{
    "id": "resp_xyz789",
    "object": "response",
    "created_at": 1699000000,
    "model": "gpt-4o-mini",
    "status": "completed",
    "structured_output": [
       {
         "product_name": "iPhone 15 Pro",
         "price": 999,
         "category": "electronics",
         "in_stock": true
        }
                
    ],
    "usage": {
        "input_tokens": 50,
        "output_tokens": 30,
        "total_tokens": 80
    }
}

Generate operation import wizard

Step 1: Select operation type

In your Boomi process, add a connector step.
Select OpenAI (Tech Preview) connector.
Choose your configured connection.
Click Import Operation for a new operation.

Step 2: Select action type

For the Generate operation, select from:

Generate Text
Generate Images
Generate Embeddings
Generate Structured Output

Step 3: Configure structured output (if selected)

If Structured Output is selected, the Output Schema Format (JSON) field appears.
Paste your complete text parameter JSON with format and schema.
The connector validates the JSON structure.

Step 4: Import profiles

Click Next to proceed.
The connector imports Request and Response profiles.
For Structured Output, the Response profile is dynamically generated from your schema.
Review imported profiles and click Finish.

Troubleshooting

Operation issues

Empty response or Invalid model specified: Verify model ID is correct
Truncated response or max_tokens too low: Increase max_output_tokens
Schema validation fails or Invalid Structured Output schema: Verify JSON schema syntax
Unexpected format or Wrong object type selected: Re-import operation with correct type

Structured output issues

Text Parameter error or Missing or invalid JSON: Verify format includes type, name, schema
Schema not applied or Schema not saved at design time: Re-import operation with schema
Response not parsed or Invalid schema structure: Verify JSON Schema is valid

Archiving tab

See the topic Connector operation’s Archiving tab for more information.

Tracking tab

See the topic Connector operation’s Tracking tab for more information.

Caching tab

See the topic Connector operation’s Caching tab for more information.