AI & ML2025-01-25

OpenAI API

Access powerful language models including GPT-4, GPT-3.5, and embedding models for AI applications.

https://platform.openai.com/docs/api-reference

OpenAI API

The OpenAI API provides access to state-of-the-art language models for a wide range of natural language processing tasks.

Key Features

Chat Completions

  • GPT-4 and GPT-4 Turbo for advanced reasoning
  • GPT-3.5 Turbo for fast, cost-effective responses
  • Function calling for structured outputs
  • Streaming responses

Embeddings

  • text-embedding-3-small and text-embedding-3-large
  • Semantic search and clustering
  • RAG (Retrieval Augmented Generation) applications

Additional Capabilities

  • Vision (image understanding)
  • Audio transcription (Whisper)
  • Text-to-speech
  • Fine-tuning custom models

Pricing

Models are priced per token:

  • GPT-4 Turbo: $0.01/1K input tokens, $0.03/1K output tokens
  • GPT-3.5 Turbo: $0.0005/1K input tokens, $0.0015/1K output tokens
  • Embeddings: $0.00002/1K tokens (text-embedding-3-small)

Getting Started

from openai import OpenAI

client = OpenAI(api_key="your-api-key")

response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Explain Bayesian statistics simply."}
    ]
)

print(response.choices[0].message.content)

Use Cases

  • Chatbots: Customer support, virtual assistants
  • Content Generation: Articles, summaries, translations
  • Code Assistance: Code generation, debugging, explanation
  • Data Analysis: Extract insights from text data
  • Education: Tutoring, personalized learning

Best Practices

  1. Prompt Engineering: Craft clear, specific prompts
  2. Temperature Control: Lower for factual, higher for creative
  3. Token Management: Monitor usage to control costs
  4. Error Handling: Implement retry logic for rate limits
  5. Security: Never expose API keys in client-side code

Resources