Playgrounds

LLM Playground

Chat with Skytells-hosted large language models — configure system prompts, adjust parameters, iterate on outputs, and compare model responses without writing code.

The LLM Playground is Skytells' interactive environment for large language models — text, code, reasoning, and instruction-following models. It provides a conversational chat interface with a system prompt editor, model selector, and parameter controls, giving you everything you need to iterate on prompts and evaluate model behavior before integrating into production.

Accessing the LLM Playground

In the Skytells Console, go to AI → Playgrounds → LLM Playground in the left sidebar.


Playground layout

The LLM Playground has three primary panels: the Model & Settings panel on the left, the Chat panel in the center, and the System Prompt panel on the right.

Model selector

At the top of the settings panel, a dropdown lets you choose which language model to use. Available models include Skytells-hosted LLMs as well as compatible third-party models. The model is applied to all subsequent chat turns.

When you change the model, the conversation history is retained so you can compare how different models respond to the same messages.

System prompt

The system prompt field appears in the right panel. Type instructions here that shape the model's behavior throughout the entire conversation — persona, output format, constraints, tone, and so on.

Examples:

You are a concise technical writer. Always respond in plain text with no markdown.
You are a senior software engineer with expertise in TypeScript and distributed systems.
Answer technical questions precisely and always include code examples.
You are a product manager assistant. Help the user write PRDs, meeting notes, and feature specs.

Changes to the system prompt take effect on the next message you send. They do not retroactively rewrite existing turns in the conversation.

Chat panel

The chat panel is the main interaction area. Type a message in the input box at the bottom and press Enter (or the send button) to submit. The model's response streams in real time.

Each message turn shows:

  • Your message on the right
  • The model's response on the left, with a copy button

Use the Regenerate (↻) button to rerun the last message without the model's previous response, useful for exploring different outputs to the same input.

Parameter controls

Below the model selector, a set of parameter sliders and inputs let you adjust generation behavior:

ParameterDescriptionRange
TemperatureControls output randomness. Higher values produce more creative and varied outputs; lower values produce more deterministic and predictable outputs.0 – 2 (default: 1)
Max tokensMaximum number of tokens the model will generate in a single response.Model-dependent
Top PNucleus sampling threshold. Restricts generation to tokens whose cumulative probability is within the top P.0 – 1 (default: 1)
Frequency penaltyPenalizes tokens that have already appeared in the output, reducing repetition.–2 – 2 (default: 0)
Presence penaltyPenalizes tokens that have appeared anywhere in the context, encouraging the model to explore new topics.–2 – 2 (default: 0)

For most use cases, start with defaults. Increase Temperature (0.7–1.2) for creative tasks and decrease it (0.0–0.3) for factual, code generation, or structured output tasks.


Working with the LLM Playground

Testing a prompt from scratch

Select a model

Open the model dropdown at the top of the settings panel and select the language model you want to test. If you are unsure which to start with, use the default — typically the latest GPT or Skytells instruction-following model.

Write a system prompt (optional)

In the system prompt panel on the right, type the persona or behavioral instructions for the model. Leave blank to use the model's default behavior.

Type your first message

Click the chat input at the bottom of the chat panel and type your message. Press Enter to send.

Review the response

The response streams in. If it is not what you expected:

  • Adjust the system prompt to be more specific.
  • Reduce Temperature for more focused responses.
  • Click Regenerate to get a different output for the same message.

Iterate

Continue the conversation, refine your prompt, or switch models to compare outputs.

Comparing models

To compare the same conversation across multiple models:

  1. Complete a conversation with one model.
  2. Open the model selector and choose a different model.
  3. The conversation history is retained. Send the same message again to see how the new model responds.
  4. You can also clear the conversation and paste the same prompt fresh.

Getting production code

Once you've validated your prompt and parameters, implement your integration using the Inference API and the TypeScript or Python SDK.

The Skytells Inference API is OpenAI-compatible — any client built for the OpenAI API works with a Skytells API key.


Clearing and resetting

  • Clear conversation — Removes all messages from the current session and starts fresh. Does not change the model or parameters.
  • Reset parameters — Returns all sliders (temperature, top-p, etc.) to their defaults for the selected model.
  • Change system prompt — Takes effect on the next message sent. No need to clear the conversation.

LLM Playground vs. Inference Playground

FeatureInference PlaygroundLLM Playground
Model typesImage, video, audio, musicText, code, reasoning, multimodal LLMs
InterfaceSchema-driven formChat interface
System promptYes
OutputImage/Video/Audio previewText response
Code generationNode.js, Python, HTTP snippetsManual from API reference
Prediction trackingYes, in Predictions historyNo (uses Inference API, not Predictions API)
StreamingNot applicableYes, responses stream in real time

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