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Documentation Index

Fetch the complete documentation index at: https://docs.orq.ai/llms.txt

Use this file to discover all available pages before exploring further.

Prompts store all configuration for interacting with a model: system instructions, messages, model selection, and parameters. A Prompt can be reused across Playgrounds, Experiments, Deployments, and Agents.

Use Cases

Use prompts as shared instructions so every team and application produces consistent, aligned outputs.
Package prompts as configurable building blocks that can be reused across products, workflows, and experiments.
Adjust behavior, tone, and structure by editing prompts instead of modifying application logic.
Roll out improvements, A/B test variations, and manage risk through prompt versioning and controlled updates.
Embed domain rules, policies, and structured outputs directly into prompts to align AI with business needs.

Create a Prompt

1

Navigate to a Project

Open a Project and click the + button at the top.
2

Select Prompt

Choose Prompt from the menu. The Prompt editor opens in AI Studio.
Standalone prompts are stored in the Project and can be reused across Playgrounds, Experiments, Agents, and Deployments.

Choose a Model

Select a model from the model picker at the top of the Prompt editor.
A model must be available through the AI Router to appear in the picker.

Model Parameters

Controls creativity and predictability. Higher values produce more diverse, surprising responses. Lower values produce more predictable output that sticks closely to learned patterns.
Sets the upper limit on tokens the model can produce in a single output. Prevents excessively long responses while ensuring enough room for a complete answer.
Narrows the model’s choices to the k most likely tokens at each generation step. Helps refine output to follow particular patterns or meet specific criteria.
Nucleus sampling. Selects a pool of likely words based on a probability threshold, balancing creativity with coherence.
Discourages the model from reusing the same words or phrases, encouraging richer and more varied language.
Discourages repeated topics or ideas rather than specific words. Higher values lead to more creative and diverse responses.

Messages

Select Add Message in the Prompt Template panel to add a message. Messages define the context the model receives before generating a response.

Roles

When adding a message, choose a role to define how the model interprets it:
RoleDescriptionExample
SystemA guideline or context for the language model, directing how it should interpret and respond to requests.”You are an expert botanist. Respond briefly to questions with one-line answers.”
UserAn actual query posed by the user.”Which plants thrive in shady environments?”
AssistantResponses to user queries by the language model.”Ferns, Hostas, and Hydrangeas are some plants that thrive in shady environments.”

Variables

Use {{variable_name}} syntax inside a message to declare a dynamic input. All declared inputs appear in the Inputs block at the top-right of the page, where default values can be set for testing.
In a Deployment, populate variables through the inputs field when invoking.

Prompt Generator

Select the Generate Prompt button next to the Role Selector to open the prompt generation assistant.
  • Select Copy to copy the generated prompt to the clipboard.
  • Select Apply to overwrite the current prompt with the generated one.

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
Configuring Parameters for Image ModelsImage generation models have different parameters compared to chat models. Parameters vary per model and affect the generated output.
Using Image Generation in PlaygroundUse image models in the Playground like any other model. Generated images appear as regular messages and can be viewed fullscreen.
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 your prompts
  • Parameter Tuning: Experiment with model-specific parameters to achieve desired output quality
  • Iterative Refinement: Use generated images as starting points for further refinement

Vision

Vision models analyze and interpret images. Select a model with a vision tag in the model picker.
To include an image as input in the Playground, click the image icon at the top-right of the message. Share a link or upload a file to pass to the model.
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 what you want 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

Fetch a Prompt

Retrieve a Prompt by its ID using the Retrieve a Prompt API.
curl --request GET \
     --url https://api.orq.ai/v2/prompts/PROMPT_ID \
     --header 'accept: application/json' \
     --header 'authorization: Bearer ORQ_API_KEY'

Prompt Snippets

Reference Prompt Snippets with {{snippet:key}} syntax. Inject reusable templates into prompts for modular configuration.