With Adaline Proxy

Instrument your AI application with zero code changes by routing requests through the Adaline Proxy

Proxy is a hosted proxy service that automatically captures telemetry, traces, and spans from your AI applications.

Instead of calling AI provider APIs directly, your applications route requests through Adaline’s cloud infrastructure by simply modifying the baseUrl in your AI SDKs and adding required headers. This enables automatic observability without manual instrumentation.

Proxy is based on the open source Adaline Gateway project.

The flow

1. SDK Configuration — Update your AI SDK’s baseUrl to point to Proxy
2. Header Addition — Add required Adaline headers for authentication, project and prompt identification
3. Transparent Proxying — Proxy forwards your requests to the actual AI provider
4. Automatic Telemetry — Responses are captured and logged as traces and spans in your Adaline project and prompt
5. Original Response — Your application receives the exact same response it would from the provider

Benefits

• Minimal Code Changes — Works with existing AI SDK implementations by adding a couple of lines of code
• Automatic Observability — Captures traces and spans without manual logging
• Real-time Monitoring — Immediate visibility into AI application performance, including token usage and costs
• Continuous Evaluations — Setup one-click continuous AI evaluations for your AI applications
• Provider Agnostic — Supports all major AI providers
• Production Ready — Built for scale with high availability and security
• No Extra Costs — Proxy requests are billed as regular API Log requests to Adaline

Quick start

Python (OpenAI)

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("OPENAI_API_KEY"),
    base_url="https://gateway.adaline.ai/v1/openai/",
)

response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}],
    extra_headers={
        "adaline-api-key": os.getenv("ADALINE_API_KEY"),
        "adaline-project-id": os.getenv("ADALINE_PROJECT_ID"),
        "adaline-prompt-id": os.getenv("ADALINE_PROMPT_ID"),
        "adaline-trace-name": "my-workflow",
    },
)

TypeScript (OpenAI)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
  baseURL: "https://gateway.adaline.ai/v1/openai/",
  defaultHeaders: {
    "adaline-api-key": process.env.ADALINE_API_KEY,
    "adaline-project-id": process.env.ADALINE_PROJECT_ID,
    "adaline-prompt-id": process.env.ADALINE_PROMPT_ID,
  },
});

const response = await client.chat.completions.create({
  model: "gpt-4",
  messages: [{ role: "user", content: "Hello!" }],
});

Python (Anthropic)

import os
from anthropic import Anthropic

client = Anthropic(
    api_key=os.getenv("ANTHROPIC_API_KEY"),
    base_url="https://gateway.adaline.ai/v1/anthropic/",
    default_headers={
        "adaline-api-key": os.getenv("ADALINE_API_KEY"),
        "adaline-project-id": os.getenv("ADALINE_PROJECT_ID"),
        "adaline-prompt-id": os.getenv("ADALINE_PROMPT_ID"),
    },
)

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}],
)

Supported providers

Provider	Base URL
OpenAI	https://gateway.adaline.ai/v1/openai/
Anthropic	https://gateway.adaline.ai/v1/anthropic/
Google	https://gateway.adaline.ai/v1/google
Azure	https://gateway.adaline.ai/v1/azure/
Amazon Bedrock	https://gateway.adaline.ai/v1/bedrock/
Groq	https://gateway.adaline.ai/v1/groq/
Open Router	https://gateway.adaline.ai/v1/open-router/
Together AI	https://gateway.adaline.ai/v1/together-ai/
xAI	https://gateway.adaline.ai/v1/xai/
Vertex AI	https://gateway.adaline.ai/v1/vertex

Required headers

Header	Description
adaline-api-key	Your workspace API key
adaline-project-id	The project to log traces to
adaline-prompt-id	The prompt to associate spans with

Optional trace headers

Header	Description	Default
adaline-trace-name	Name for the trace	"Proxy"
adaline-trace-status	Trace status: success, failure, pending, unknown	Auto-detected
adaline-trace-reference-id	Custom ID to group multiple requests into one trace	Auto-generated
adaline-trace-session-id	Session ID to group related traces	—
adaline-trace-attributes	JSON array of attribute operations	—
adaline-trace-tags	JSON array of tag operations	—

Optional span headers

Header	Description
adaline-span-name	Name for the span
adaline-span-reference-id	Custom span ID
adaline-span-session-id	Session ID on the span
adaline-span-variables	JSON object of variable values for evaluation
adaline-span-attributes	Custom span attributes
adaline-span-tags	Span tags
adaline-span-run-evaluation	Set to "true" to trigger continuous evaluations
adaline-deployment-id	Deployment ID to associate with the span

For the full header specification with validation rules and detailed examples, see the Proxy Headers Reference.

Group requests into a single trace

Use the same adaline-trace-reference-id across multiple requests to group them under one trace:

import uuid

trace_id = str(uuid.uuid4())

# First request
embedding = client.embeddings.create(
    model="text-embedding-3-small",
    input="User query",
    extra_headers={
        "adaline-api-key": os.getenv("ADALINE_API_KEY"),
        "adaline-project-id": os.getenv("ADALINE_PROJECT_ID"),
        "adaline-prompt-id": os.getenv("ADALINE_PROMPT_ID"),
        "adaline-trace-reference-id": trace_id,
        "adaline-span-name": "query-embedding",
    },
)

# Second request — same trace
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "..."}],
    extra_headers={
        "adaline-api-key": os.getenv("ADALINE_API_KEY"),
        "adaline-project-id": os.getenv("ADALINE_PROJECT_ID"),
        "adaline-prompt-id": os.getenv("ADALINE_PROMPT_ID"),
        "adaline-trace-reference-id": trace_id,
        "adaline-span-name": "chat-completion",
    },
)

What gets captured automatically

When you route through the Proxy, Adaline automatically captures:

• Request and response payloads
• Token usage (input and output) and cost
• Latency
• Model and provider information
• Errors and status codes

Next steps

Proxy Headers Reference

Complete reference for all required and optional Proxy headers.

Advanced Usage

Session tracking, multi-step traces, and error patterns.

Setup Continuous Evaluations

Run automated quality checks on live production data.

Log Attachments

Attach custom attributes, tags, and variables.

Integrations

Browse all supported AI providers and frameworks.

Adaline Gateway (Open Source)

The open source project that powers Proxy.