Embedding
Text Embedding Ada 002
OpenAI Ada 002 January 1, 2022
A text embedding model that converts text into vector representations for various NLP tasks, producing 1536-dimensional embeddings.
What is it good for?
Primary Use Cases
Content Creation: Writing, editing, summarization, translation
Code Assistance: Programming help, debugging, code review
Best For
Business Applications: Customer service, content generation
Specifications & Pricing
Pricing
Input / 1M tk
$0.1000
Output / 1M tk
N/A
Est. cost in USD
💡 What does this cost in practice?
📖 300-page book:~200,000 tokens ≈ $0.0200
📄 Research paper:~15,000 tokens ≈ $0.0015
💬 Chat conversation:~1,000 tokens ≈ $0.0001
Priced per 1M input tokens; no output token pricing
Usage Guidance
How to Prompt This Model
✨ General Tips
🎯Be Specific: Detail the desired outcome, format, tone, and constraints.
🎭Set Context: Explain your role or the purpose (e.g., "Act as a helpful architect...").
📝Specify Format: Request bullet points, JSON, markdown, code blocks, etc.
🔄Iterate: Refine prompts based on responses. Don't expect perfection first try.
🚀 Best Practices for Text Embedding Ada 002
📋 Example Prompts
Content Creation Example
Write a professional email to a client explaining a project delay. The project is a website redesign, the delay is due to additional security requirements, and the new timeline is 2 weeks. Keep the tone apologetic but confident.