OpenAI Integration

The OpenAI integration provides direct access to OpenAI models through a unified interface. Configure once, use everywhere with enterprise-grade performance and the latest AI capabilities from OpenAI.

Integrating OpenAI

Simply enter your OpenAI API key once in the Platform Integrations section. This enables authorized users to access OpenAI models within the platform. Once integrated, models can be registered and used as any other python object on the platform.

# Example: Using a registered OpenAI model
result = openai_gpt4_model(text="Analyze this data", temperature=0.8)

Example of Models Supported

OpenAI provides access to state-of-the-art language models with different capabilities:

GPT-4o - Most advanced multimodal model with vision and reasoning capabilities
GPT-4 - Advanced reasoning and complex task completion
GPT-3.5 Turbo - Fast, efficient responses for most use cases
o1-preview, o1-mini - Latest reasoning models with enhanced problem-solving
Additional Models - Latest OpenAI variants with enhanced capabilities

Registering a New OpenAI Model

Navigate to New Model to begin registration. The registration form connects your OpenAI integration with custom model configurations.

Basic Information

Description: Document your model’s purpose, use cases, and limitations. For example: “GPT-4o optimized for content analysis and generation. Use for enterprise content processing with multimodal capabilities. Ideal for complex reasoning and creative tasks.”

Code Configuration

Alias: A unique identifier for your model (e.g., openai_gpt4_analyzer, content_generator). This becomes the variable name you’ll use in code.

Output Type: Define the return format:

• Map[String, String] - Key-value pairs for structured responses
• String - Simple text responses
• List - Array of items

Input Type: Select your implementation approach:

• API Based: Platform handles API calls automatically using your OpenAI integration
• Python Function: Custom function implementation with full control
• Custom: Advanced configurations for specialized use cases

Model Provider: Select “OpenAI” from your configured integrations.

Arguments Configuration

Define input parameters that your model will accept. Important: Variables declared here are automatically available in the Scoring Logic section.

Common argument patterns for OpenAI models:

Alias	Type	Optional	Default Value	Usage
text	String	No	N/A	Main input content
temperature	Numerical	Yes	0.7	Controls response creativity
max_tokens	Numerical	Yes	1500	Maximum response length
system_prompt	String	Yes	""	System instructions

Use + Add Argument to include additional parameters.

Scoring Logic Implementation

In the Scoring Logic section, you can directly reference any variable declared in the Arguments section. The platform automatically makes these available in your code.

# Arguments: text, temperature are automatically available
import os
from openai import OpenAI

# Direct initialization
client = OpenAI(
    api_key=os.getenv("OPENAI_API_KEY")
)

if text is None:
    return None

messages = [
    {"role": "system", "content": system_prompt if system_prompt else "You are a helpful assistant."},
    {"role": "user", "content": text}
]

completion = client.chat.completions.create(
    model="gpt-4o",
    messages=messages,
    max_tokens=int(max_tokens),
    temperature=float(temperature),
    top_p=0.95,
    frequency_penalty=0,
    presence_penalty=0
)

return {"output": completion.choices[0].message.content, "context": None}

Platform Integration Setup

Before registering models, configure your OpenAI credentials:

1. Navigate to Settings > Platform Integrations
2. Click on OpenAI
3. Enter your OpenAI API key
4. Test the connection

The platform creates environment variables automatically:

• OPENAI_API_KEY

Example Use Case: Content Analysis Model

An OpenAI GPT-4o model configured for enterprise content analysis demonstrates the complete workflow:

Arguments Configuration:

• text (String, required)
• temperature (Numerical, optional, default: “0.3”)
• max_tokens (Numerical, optional, default: “2000”)
• system_prompt (String, optional, default: “You are an expert content analyst.”)

Usage:

# Model becomes available as: content_analyzer
result = content_analyzer(
    text="Your content text here...",
    temperature=0.3,
    max_tokens=2000,
    system_prompt="Analyze this content for key themes, sentiment, and actionable insights."
)

Want to Learn More?

• Review OpenAI API documentation
• Check OpenAI model capabilities
• Monitor usage through OpenAI Dashboard
• Set up rate limiting and cost management