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Chat Playground Interface

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Overview

The Chat Playground provides an interactive environment to test different LLM models and fine-tune their parameters for optimal results.

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Interface Components

Choose from available models:
  • GPT-4 Turbo
  • Claude 3
  • Gemini Pro
  • Custom Models
Model Selection
Adjust model behavior:
  • Temperature
  • Max tokens
  • Top P
  • Frequency penalty
  • Presence penalty
Set the context and behavior instructions for the AI model

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Using the Playground

Select Model

  1. Choose your preferred model
  2. Review model capabilities
  3. Check credit consumption rate

Configure Settings

  1. Adjust temperature for creativity
  2. Set maximum response length
  3. Fine-tune other parameters

Test Prompts

  1. Enter your prompt
  2. View real-time responses
  3. Iterate and refine

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Features

Save Templates

Save successful prompts for future use

Export Results

Download conversations and settings

Share Sessions

Collaborate with team members

API Preview

View API calls for implementation

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Code Generation

# Example API call matching playground settings
from openai import OpenAI

client = OpenAI(
    api_key="your-api-key",
    base_url="https://api.gately.ai/v1"
)

response = client.chat.completions.create(
    model="gpt-4-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Tell me about AI."}
    ],
    temperature=0.7,
    max_tokens=150
)
The playground automatically generates API code based on your current settings and prompts.

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Tips & Best Practices

Start Simple

Begin with basic prompts and iterate

Compare Models

Test same prompt across models

Save Versions

Track successful configurations
Remember that playground usage consumes credits according to the selected model’s pricing.