OpenAI API

Use the OpenAI API via direct

curl

calls to access GPT models, DALL-E image generation, Whisper transcription, embeddings, and text-to-speech.

Official docs:

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

When to Use

Use this skill when you need to:

Chat completions with GPT-4o, GPT-4, or GPT-3.5 models
Image generation with DALL-E 3
Audio transcription with Whisper
Text-to-speech audio generation
Text embeddings for semantic search and RAG
Vision tasks (analyze images with GPT-4o)

Prerequisites

Sign up at OpenAI Platform and create an account
Go to API Keys and generate a new secret key
Add billing information and set usage limits

bash

export OPENAI_API_KEY="sk-..."

Pricing (as of 2025)

Model	Input (per 1M tokens)	Output (per 1M tokens)
GPT-4o	$2.50	$10.00
GPT-4o-mini	$0.15	$0.60
GPT-4 Turbo	$10.00	$30.00
text-embedding-3-small	$0.02	-
text-embedding-3-large	$0.13	-

Rate Limits

Rate limits vary by tier (based on usage history). Check your limits at Platform Settings.

Important: When using
$VAR
in a command that pipes to another command, wrap the command containing
$VAR
in
bash -c '...'
. Due to a Claude Code bug, environment variables are silently cleared when pipes are used directly.
bash
bash -c 'curl -s "https://api.example.com" -H "Authorization: Bearer $API_KEY"' | jq .

How to Use

All examples below assume you have

OPENAI_API_KEY

set.

Base URL:

https://api.openai.com/v1

1. Basic Chat Completion

Send a simple chat message:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [{"role": "user", "content": "Hello, who are you?"}]
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.choices[0].message.content'

Available models:

```
gpt-4o
```
: Latest flagship model (128K context)
```
gpt-4o-mini
```
: Fast and affordable (128K context)
```
gpt-4-turbo
```
: Previous generation (128K context)
```
gpt-3.5-turbo
```
: Legacy model (16K context)
```
o1
```
: Reasoning model for complex tasks
```
o1-mini
```
: Smaller reasoning model

2. Chat with System Prompt

Use a system message to set behavior:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [
    {"role": "system", "content": "You are a helpful assistant that responds in JSON format."},
    {"role": "user", "content": "List 3 programming languages with their main use cases."}
  ]
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.choices[0].message.content'

3. Streaming Response

Get real-time token-by-token output:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [{"role": "user", "content": "Write a haiku about programming."}],
  "stream": true
}

Then run:

bash

curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json

Streaming returns Server-Sent Events (SSE) with delta chunks.

4. JSON Mode

Force the model to return valid JSON:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [
    {"role": "system", "content": "Return JSON only."},
    {"role": "user", "content": "Give me info about Paris: name, country, population."}
  ],
  "response_format": {"type": "json_object"}
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.choices[0].message.content'

5. Vision (Image Analysis)

Analyze an image with GPT-4o:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [
    {
      "role": "user",
      "content": [
        {"type": "text", "text": "What is in this image?"},
        {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/Cat03.jpg/1200px-Cat03.jpg"}}
      ]
    }
  ],
  "max_tokens": 300
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.choices[0].message.content'

6. Function Calling (Tools)

Define functions the model can call:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [{"role": "user", "content": "What is the weather in Tokyo?"}],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get current weather for a location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {"type": "string", "description": "City name"}
          },
          "required": ["location"]
        }
      }
    }
  ]
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.choices[0].message.tool_calls'

7. Generate Embeddings

Create vector embeddings for text:

Write to

/tmp/openai_request.json

json

{
  "model": "text-embedding-3-small",
  "input": "The quick brown fox jumps over the lazy dog."
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/embeddings" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.data[0].embedding[:5]'

This extracts the first 5 dimensions of the embedding vector.

Embedding models:

```
text-embedding-3-small
```
: 1536 dimensions, fastest
```
text-embedding-3-large
```
: 3072 dimensions, most capable

8. Generate Image (DALL-E 3)

Create an image from text:

Write to

/tmp/openai_request.json

json

{
  "model": "dall-e-3",
  "prompt": "A white cat sitting on a windowsill, digital art",
  "n": 1,
  "size": "1024x1024"
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/images/generations" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.data[0].url'

Parameters:

```
size
```
:
```
1024x1024
```
,
```
1792x1024
```
, or
```
1024x1792
```
```
quality
```
:
```
standard
```
or
```
hd
```
```
style
```
:
```
vivid
```
or
```
natural
```

9. Audio Transcription (Whisper)

Transcribe audio to text:

bash

bash -c 'curl -s "https://api.openai.com/v1/audio/transcriptions" -H "Authorization: Bearer ${OPENAI_API_KEY}" -F "file=@audio.mp3" -F "model=whisper-1"' | jq '.text'

Supports: mp3, mp4, mpeg, mpga, m4a, wav, webm (max 25MB).

10. Text-to-Speech

Generate audio from text:

Write to

/tmp/openai_request.json

json

{
  "model": "tts-1",
  "input": "Hello! This is a test of OpenAI text to speech.",
  "voice": "alloy"
}

Then run:

bash

curl -s "https://api.openai.com/v1/audio/speech" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json --output speech.mp3

Voices:

alloy

echo

fable

onyx

nova

shimmer

Models:

tts-1

(fast),

tts-1-hd

(high quality)

11. List Available Models

Get all available models:

bash

bash -c 'curl -s "https://api.openai.com/v1/models" -H "Authorization: Bearer ${OPENAI_API_KEY}"' | jq -r '.data[].id' | sort | head -20

12. Check Token Usage

Extract usage from response:

Write to

/tmp/openai_request.json

json

{
  "model": "gpt-4o-mini",
  "messages": [{"role": "user", "content": "Hi!"}]
}

Then run:

bash

bash -c 'curl -s "https://api.openai.com/v1/chat/completions" -H "Content-Type: application/json" -H "Authorization: Bearer ${OPENAI_API_KEY}" -d @/tmp/openai_request.json' | jq '.usage'

This returns token counts for both input and output.

Response includes:

```
prompt_tokens
```
: Input token count
```
completion_tokens
```
: Output token count
```
total_tokens
```
: Sum of both

Guidelines

Choose the right model: Use
```
gpt-4o-mini
```
for most tasks,
```
gpt-4o
```
for complex reasoning,
```
o1
```
for advanced math/coding
Set max_tokens: Prevent runaway generation and control costs
Use streaming for long responses: Better UX for real-time applications
JSON mode requires system prompt: Include JSON instructions when using
```
response_format
```
Vision requires gpt-4o models: Only
```
gpt-4o
```
and
```
gpt-4o-mini
```
support image input
Batch similar requests: Use embeddings API batch input for efficiency
Monitor usage: Check dashboard regularly to avoid unexpected charges

openai

NPX Install

Tags

SKILL.md Content

OpenAI API

When to Use

Prerequisites

Pricing (as of 2025)

Rate Limits

How to Use

1. Basic Chat Completion

2. Chat with System Prompt

3. Streaming Response

4. JSON Mode

5. Vision (Image Analysis)

6. Function Calling (Tools)

7. Generate Embeddings

8. Generate Image (DALL-E 3)

9. Audio Transcription (Whisper)

10. Text-to-Speech

11. List Available Models

12. Check Token Usage

Guidelines