OpenAI
Integrate OpenAI models through the Adaline Proxy to automatically capture telemetry — requests, responses, token usage, latency, and costs — with minimal code changes.Supported Models
Chat Models| Model | Description |
|---|---|
gpt-5.3-codex | Latest Codex model |
gpt-5.2-pro | Latest flagship model |
gpt-5.2 | High capability next-gen model |
gpt-5.2-codex | GPT-5.2 Codex |
chatgpt-5.2 | ChatGPT 5.2 |
gpt-5.2-chat-latest | GPT-5.2 chat latest snapshot |
gpt-5.1 | Next-gen model |
gpt-5 | GPT-5 series base |
gpt-5-mini | Compact GPT-5 |
gpt-5-nano | Ultra-compact GPT-5 |
gpt-5-chat-latest | GPT-5 chat latest snapshot |
gpt-4.1 | Improved GPT-4 with enhanced reasoning |
gpt-4.1-mini | Compact GPT-4.1 |
gpt-4.1-nano | Ultra-compact GPT-4.1 |
gpt-4o | Multimodal with vision support |
gpt-4o-2024-08-06 | GPT-4o August 2024 snapshot |
gpt-4o-2024-05-13 | GPT-4o May 2024 snapshot |
chatgpt-4o-latest | ChatGPT-4o latest snapshot |
gpt-4o-mini | Fast and cost-effective multimodal |
gpt-4o-mini-2024-07-18 | GPT-4o Mini July 2024 snapshot |
gpt-4-turbo | High capability with 128k context |
gpt-4-turbo-2024-04-09 | GPT-4 Turbo April 2024 snapshot |
gpt-4-turbo-preview | GPT-4 Turbo preview |
gpt-4 | Original GPT-4 model |
gpt-4-0613 | GPT-4 June 2023 snapshot |
gpt-4-0125-preview | GPT-4 January 2024 preview |
gpt-4-1106-preview | GPT-4 November 2023 preview |
gpt-3.5-turbo | Fast and cost-effective |
gpt-3.5-turbo-0125 | GPT-3.5 Turbo January 2024 snapshot |
gpt-3.5-turbo-1106 | GPT-3.5 Turbo November 2023 snapshot |
o4-mini | Latest compact reasoning model |
o4-mini-2025-04-16 | O4 Mini April 2025 snapshot |
o3 | Advanced reasoning model |
o3-2025-04-16 | O3 April 2025 snapshot |
o3-mini | Compact reasoning model |
o3-mini-2025-01-31 | O3 Mini January 2025 snapshot |
o1 | Reasoning model for complex tasks |
o1-2024-12-17 | O1 December 2024 snapshot |
| Model | Description |
|---|---|
text-embedding-3-large | Highest quality embeddings |
text-embedding-3-small | Balanced quality and cost |
text-embedding-ada-002 | Legacy embedding model |
Proxy Base URL
https://gateway.adaline.ai/v1/openai/
Prerequisites
- An OpenAI API key
- An Adaline API key, project ID, and prompt ID
Chat Completions
Complete Chat
from openai import OpenAI
client = OpenAI(
api_key="your-openai-api-key",
base_url="https://gateway.adaline.ai/v1/openai/"
)
headers = {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id"
}
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is machine learning?"}
],
extra_headers=headers
)
print(response.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "your-openai-api-key",
baseURL: "https://gateway.adaline.ai/v1/openai/",
});
const response = await client.chat.completions.create(
{
model: "gpt-4o",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "What is machine learning?" },
],
},
{
headers: {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id",
},
}
);
console.log(response.choices[0].message.content);
Stream Chat
from openai import OpenAI
client = OpenAI(
api_key="your-openai-api-key",
base_url="https://gateway.adaline.ai/v1/openai/"
)
headers = {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id"
}
stream = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain quantum computing in simple terms."}
],
stream=True,
stream_options={"include_usage": True},
extra_headers=headers
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="")
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "your-openai-api-key",
baseURL: "https://gateway.adaline.ai/v1/openai/",
});
const stream = await client.chat.completions.create(
{
model: "gpt-4o",
messages: [
{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: "Explain quantum computing in simple terms." },
],
stream: true,
stream_options: { include_usage: true },
},
{
headers: {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id",
},
}
);
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content;
if (content) process.stdout.write(content);
}
Embeddings
from openai import OpenAI
client = OpenAI(
api_key="your-openai-api-key",
base_url="https://gateway.adaline.ai/v1/openai/"
)
headers = {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id"
}
response = client.embeddings.create(
model="text-embedding-3-small",
input="The quick brown fox jumps over the lazy dog",
extra_headers=headers
)
embedding = response.data[0].embedding
print(f"Embedding dimension: {len(embedding)}")
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "your-openai-api-key",
baseURL: "https://gateway.adaline.ai/v1/openai/",
});
const response = await client.embeddings.create(
{
model: "text-embedding-3-small",
input: "The quick brown fox jumps over the lazy dog",
},
{
headers: {
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id",
},
}
);
console.log(`Embedding dimension: ${response.data[0].embedding.length}`);
Optional Headers
Customize tracing behavior with optional headers:headers = {
# Required
"adaline-api-key": "your-adaline-api-key",
"adaline-project-id": "your-project-id",
"adaline-prompt-id": "your-prompt-id",
# Optional
"adaline-trace-name": "openai-chat-completion",
"adaline-trace-session-id": "user-session-123",
"adaline-span-name": "gpt-4o-call",
"adaline-trace-tags": '["production", "chat"]',
"adaline-trace-attributes": '{"create": {"userId": "user-123"}}',
}
Next Steps
- Multi-Step Workflows — RAG pipelines, multi-step generation, and conversational agents
- Headers Reference — Complete header documentation
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