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Use Playgrounds to:
Test Prompts in an easy-to-use interactive environment before deploying to production.
Run the same prompt across multiple models simultaneously and compare outputs directly.
Try existing use cases and prompts against new models without touching your production configuration.
Adjust temperature, top-p, max tokens, and other parameters to tune model behavior.
Provide feedback on responses to create curated datasets for future fine-tuning.

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Create a Playground

Head to the AI Studio, choose a Project, and use the + button to select Playground. The following modal opens:
Create playground modal with Title field, Model selector, and Path selector set to Default Project.

Give the Playground a title, set a Path, and select a model. Everything can be modified later.

After which, the Playground can be configured:
Configuring a Playground

Configure model, parameters, and prompt template in the Playground.

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Layout

The Playground is split into two panels:
  • Left panel: Parameters, Prompt template, Knowledge Bases, and Tools configuration.
  • Right panel: Chat and generation area where responses appear.
The top-right toolbar contains Add model, Variables, and Blocks. Use the Logs tab to view call logs for this Playground. See Logs for details.

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Parameters

The Parameters block at the top of the left panel controls the model and its settings. Click the chevron to collapse or expand it. Available parameters include: Model, Max Tokens, Temperature, Top P, Top K, and Response Format. To change the model, click the model name to open the list of available models.
See which models are available in the AI Gateway.
In the Playground, you can test all available models through the Orq.ai API key without setting up your own API keys.
When selecting a model, the block automatically updates with all corresponding parameters for that model.

When selecting a model, the block automatically updates with all corresponding parameters for that model.

The Max Tokens parameter is especially important: make sure the model has enough tokens allocated for the expected output.
To learn more about the most common model parameters, see Model Parameters.

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Prompt Template

Define the prompt in the Prompt template block. Use the Import prompt button to load an existing prompt from your project. Use {{variable_key}} syntax in the prompt message to define variables. The Variables button in the top toolbar lists all variables defined in the current prompt and lets you set their values before generating.
To learn how to set up your Prompt and Messages, see Creating a Prompt.

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Knowledge Bases

Attach a Knowledge Base to the Playground using the Add Knowledge Base button in the Knowledge Bases section. The Knowledge Base content is included in the prompt context when generating.

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Tools

Add tools to the Playground using the Add Tool or Import Tool buttons in the Tools section. Tools extend what the model can do during generation.

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Generation

Once the prompt template is ready, click Generate to produce a response. Use Add message to append messages before generating. Use Clear chat to reset the conversation while keeping the prompt template.
Responses stream in real time. Continue the conversation by adding messages and generating new answers.

Responses stream in real time. Continue the conversation by adding messages and generating new answers.

Cost and token count for the latest generation are shown at the bottom-right of the panel.

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Image Generation

Image generation models create images from text descriptions. Select a model with an image tag in the model picker. Selecting an Image Generation Model
The image tag identifies models capable of generating images.

The image tag identifies models capable of generating images.

Configuring Parameters for Image Models Image generation models have different parameters compared to chat models. Parameters vary per model and affect the generated output.
Example parameters for the DALL-E 3 model.

Example parameters for the DALL-E 3 model.

Generating Images Use image models in the Playground like any other model. Generated images appear as regular messages and can be viewed fullscreen.
Example of image generation using Leonardo AI.

Example of image generation using Leonardo AI.

Use Cases
  • Creative Content: Generate artwork, illustrations, and visual content for marketing materials
  • Product Design: Create mockups and visual prototypes based on descriptions
  • Content Creation: Generate images for blogs, social media, and presentations
  • Concept Visualization: Turn abstract ideas into visual representations
Best Practices
  • Be Specific: Provide detailed descriptions for better results
  • Style Guidelines: Include artistic style, mood, and visual elements in the prompt
  • Parameter Tuning: Experiment with model-specific parameters to achieve desired output quality
  • Iterative Refinement: Use generated images as starting points for further refinement

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Vision

Vision models analyze and interpret images. Select a model with a vision tag in the model picker.
The vision label identifies models that can interpret images.

The vision label identifies models that can interpret images.

To include an image as input, click the image icon at the top-right of the message. Share a link or upload a file to pass to the model.
An example use case using a vision model for insurance claims processing.

An example use case using a vision model.

To send images or files to a model via the API in production, see Attach Files in Deployments.
Use Cases
  • Document Processing: Extract text and information from scanned documents and forms
  • Visual Quality Control: Analyze product images for defects or compliance
  • Content Moderation: Automatically review images for inappropriate content
  • Medical Imaging: Analyze medical scans and diagnostic images (with appropriate models)
  • Insurance Claims: Process damage assessment photos and documentation
Best Practices
  • Image Quality: Ensure images are clear and well-lit for best analysis results
  • Specific Questions: Ask focused questions about the information to extract or understand
  • Context Provision: Provide context about what the image represents for better interpretation
  • Multiple Angles: For complex analysis, consider providing multiple views of the same subject

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Comparing Multiple Models

Click Add model in the top toolbar to add a second model block. Each model gets its own block, allowing side-by-side comparison with the same prompt.

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Copying and Duplicating Models

Use the menu at the top-right of any model block to:
  • Copy Prompt Template: copy the template to one or all other model blocks.
  • Duplicate Block: create a copy of the block including its configuration.

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Blocks

Use the Blocks button in the top toolbar to toggle which model blocks are visible or delete blocks you no longer need.
Use the Blocks menu to view all models in your Playground, toggle visibility, and delete blocks.

Use the Blocks menu to view all models in your Playground, toggle visibility, and delete blocks.