OpenAI API Deprecation Notice: What You Need to Know

OpenAI recently announced the deprecation of several older API versions to ensure better performance, security, and feature consistency across their ecosystem. If you’re currently using older APIs, this guide will help you understand which APIs are affected, why this change is happening, and how to update your applications to continue functioning seamlessly.

Which APIs Are Being Deprecated?

The following API versions will no longer be supported after the announced cutoff date:

• GPT-3 API (v1):
  • Endpoints like davinci, curie, babbage, and ada are deprecated.
  • This includes fine-tuned GPT-3 models using these engines.
• Codex API:
  • Endpoints for code completion, such as code-davinci-002, are being sunsetted.
• Old Embedding Models:
  • Embedding models like text-similarity-davinci-001 and text-embedding-ada-001 are no longer available.

Why Are These APIs Being Deprecated?

1. Advancements in Model Capabilities:
   Newer models, such as GPT-4 and GPT-3.5, outperform older versions in quality, efficiency, and versatility. Consolidating APIs allows OpenAI to focus on maintaining state-of-the-art solutions.
2. Simplified Ecosystem:
   Deprecation reduces fragmentation in the ecosystem, making it easier for developers to integrate and maintain applications.
3. Improved Performance and Cost Efficiency:
   The new APIs offer better performance at similar or reduced costs, with enhanced features like longer context windows and more robust outputs.

What You Can Do to Update Your Applications

If your application relies on deprecated APIs, you’ll need to migrate to supported alternatives. OpenAI has provided migration pathways for the most common use cases. Follow these steps to ensure a smooth transition:

Still Supported APIs

1. GPT-4 API:
   • Use the gpt-4 or gpt-4-turbo models.
   • Suitable for advanced conversational AI and high-quality text generation.
2. GPT-3.5 API:
   • Use gpt-3.5-turbo for a cost-effective, high-performance solution.
3. New Embedding Models:
   • Migrate to text-embedding-ada-002 for generating embeddings.
4. Fine-Tuning API:
   • OpenAI supports fine-tuning on the gpt-3.5-turbo model.

Migration Guides and Examples

Example 1: Text Completion

If you’re using text-davinci-003 for text completion, switch to gpt-3.5-turbo or gpt-4:

Old Code:

response = openai.Completion.create(
    engine="text-davinci-003",
    prompt="Write a creative story about AI.",
    max_tokens=150
)
print(response.choices[0].text.strip())

New Code:

response = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=[{"role": "user", "content": "Write a creative story about AI."}],
    max_tokens=150
)
print(response['choices'][0]['message']['content'].strip())

Example 2: Embedding Generation

Replace the deprecated embedding model text-embedding-ada-001 with text-embedding-ada-002:

Old Code:

response = openai.Embedding.create(
    engine="text-embedding-ada-001",
    input="OpenAI's mission is to ensure that artificial intelligence benefits all of humanity."
)
print(response["data"])

New Code:

response = openai.Embedding.create(
    model="text-embedding-ada-002",
    input="OpenAI's mission is to ensure that artificial intelligence benefits all of humanity."
)
print(response["data"])

Example 3: Fine-Tuned Models

If you used a fine-tuned GPT-3 model, migrate to gpt-3.5-turbo fine-tuning:

Old Fine-Tuned Endpoint:

response = openai.Completion.create(
    model="your-fine-tuned-model-id",
    prompt="Explain the significance of OpenAI.",
    max_tokens=100
)
print(response.choices[0].text.strip())

New Fine-Tuned Endpoint:

response = openai.ChatCompletion.create(
    model="your-new-fine-tuned-model-id",
    messages=[{"role": "user", "content": "Explain the significance of OpenAI."}],
    max_tokens=100
)
print(response['choices'][0]['message']['content'].strip())

Testing Your Updated APIs

After making the migration, it’s essential to validate your changes:

1. Unit Tests: Write test cases to ensure outputs match expectations.
2. Performance Benchmarks: Compare latency and cost between old and new implementations.
3. Edge Cases: Test for robustness with diverse prompts and inputs.

Summary

The deprecation of older OpenAI APIs is an opportunity to upgrade to more capable, cost-effective, and future-proof solutions. By transitioning to supported models like gpt-4, gpt-3.5-turbo, and text-embedding-ada-002, you can maintain your application’s reliability while benefiting from the latest advancements in AI.

For further details, visit OpenAI’s official API documentation, the CookBook and the Migration Manual.