OpenRouter OpenAI Compatibility

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'Migrate from OpenAI to OpenRouter with minimal code changes. Use when

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OpenRouter OpenAI CompatibilityStart free

What this skill tells your AI

The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/openrouter-openai-compat/SKILL.md and read by ahel’s review.

Overview

OpenRouter implements the OpenAI Chat Completions API specification (/v1/chat/completions). Existing OpenAI SDK code works with OpenRouter by changing two values: base_url and api_key. This gives you access to 400+ models from all providers through the same SDK interface.

Prerequisites

  • An existing OpenAI SDK integration to migrate — Python or TypeScript code calling chat.completions.create
  • An OpenRouter API key exported as OPENROUTER_API_KEY — see the openrouter-install-auth skill for setup
  • Python 3.8+ with the openai package, or Node.js 18+ with the openai npm package — the same SDK you already use, no new dependency
  • Optionally keep OPENAI_API_KEY exported too, so the Dual-Provider Pattern can switch back to direct OpenAI

Instructions

  1. Apply The Two-Line Migration: point base_url at https://openrouter.ai/api/v1 and swap api_key to OPENROUTER_API_KEY; optionally add the HTTP-Referer / X-Title headers for app attribution.
  2. Prefix every model string per Model ID Mapping — gpt-4o becomes openai/gpt-4o, o1 becomes openai/o1 — and try a non-OpenAI model (anthropic/claude-3.5-sonnet) through the same client.
  3. Confirm your feature usage against What Works Identically (streaming, tools, JSON mode, stop, n) and adjust per What Differs — remove the organization param, plan around limited embeddings, and check logprobs support per model via /api/v1/models.
  4. Layer in OpenRouter-Only Features through extra_body: ordered fallback model lists with "route": "fallback", provider preferences with sort: "price", or the plugins: [{"id": "web"}] web-search plugin.
  5. Keep the migration reversible with the Dual-Provider Pattern — create_client() switches between direct OpenAI and OpenRouter off the LLM_PROVIDER environment variable.

The Two-Line Migration

Python (Before)

from openai import OpenAI

client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])  # OpenAI direct
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Hello"}],
)

Python (After)

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",              # Changed
    api_key=os.environ["OPENROUTER_API_KEY"],              # Changed
    default_headers={
        "HTTP-Referer": "https://your-app.com",            # Added (optional)
        "X-Title": "Your App",                             # Added (optional)
    },
)
response = client.chat.completions.create(
    model="openai/gpt-4o",  # Prefix with provider namespace
    messages=[{"role": "user", "content": "Hello"}],
)

TypeScript (After)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://openrouter.ai/api/v1",
  apiKey: process.env.OPENROUTER_API_KEY,
  defaultHeaders: { "HTTP-Referer": "https://your-app.com", "X-Title": "Your App" },
});

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

Model ID Mapping

OpenAI DirectOpenRouter ID
gpt-4oopenai/gpt-4o
gpt-4o-miniopenai/gpt-4o-mini
gpt-4-turboopenai/gpt-4-turbo
o1openai/o1
o1-miniopenai/o1-mini

You also gain access to non-OpenAI models through the same SDK:

# Same client, any provider
response = client.chat.completions.create(
    model="anthropic/claude-3.5-sonnet",  # Anthropic
    messages=[{"role": "user", "content": "Hello"}],
)

response = client.chat.completions.create(
    model="google/gemini-2.0-flash",  # Google
    messages=[{"role": "user", "content": "Hello"}],
)

What Works Identically

FeatureStatusNotes
chat.completions.createFully supportedMain endpoint, all parameters
stream: trueFully supportedSSE format identical to OpenAI
tools / tool_choiceSupportedOpenRouter transforms for non-OpenAI providers
response_format: { type: "json_object" }SupportedBasic JSON mode
response_format: { type: "json_schema" }SupportedStrict schema mode
temperature, top_p, max_tokensSupportedStandard parameters
stop sequencesSupportedArray of stop strings
n (multiple completions)SupportedMultiple choices

What Differs

FeatureDifferenceWorkaround
Model IDsPrefixed with provider/Update model strings
organization paramNot usedRemove from client init
EmbeddingsLimited supportUse direct provider or dedicated embedding service
Fine-tuned modelsNot directly accessibleUse provider's fine-tuned model ID if hosted
logprobsModel-dependentCheck model capabilities via /api/v1/models
Responses APIBeta supportUse /api/v1/responses endpoint

OpenRouter-Only Features

These are available through the same SDK but are unique to OpenRouter:

# Model fallbacks (try models in order)
response = client.chat.completions.create(
    model="anthropic/claude-3.5-sonnet",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "models": [
            "anthropic/claude-3.5-sonnet",
            "openai/gpt-4o",
            "google/gemini-2.0-flash",
        ],
        "route": "fallback",
    },
)

# Provider preferences
response = client.chat.completions.create(
    model="anthropic/claude-3.5-sonnet",
    messages=[{"role": "user", "content": "Hello"}],
    extra_body={
        "provider": {
            "order": ["anthropic"],             # Prefer Anthropic direct
            "allow_fallbacks": True,
            "sort": "price",                    # Cheapest first
        },
    },
)

# Plugins (web search, response healing)
response = client.chat.completions.create(
    model="openai/gpt-4o",
    messages=[{"role": "user", "content": "What happened today?"}],
    extra_body={
        "plugins": [{"id": "web"}],  # Enable real-time web search
    },
)

Dual-Provider Pattern

import os
from openai import OpenAI

def create_client(provider: str = "openrouter") -> OpenAI:
    if provider == "openai":
        return OpenAI(api_key=os.environ["OPENAI_API_KEY"])
    return OpenAI(
        base_url="https://openrouter.ai/api/v1",
        api_key=os.environ["OPENROUTER_API_KEY"],
        default_headers={"HTTP-Referer": "https://your-app.com"},
    )

# Switch providers without changing application code
client = create_client(os.environ.get("LLM_PROVIDER", "openrouter"))

Output

  • Standard OpenAI-SDK ChatCompletion objects — choices[0].message.content, usage token counts, and model reporting the provider-prefixed ID that actually served the request
  • The identical code path returning completions from non-OpenAI models (Claude, Gemini) with only the model string changed
  • A provider-switchable client from create_client() — flipping LLM_PROVIDER moves traffic between direct OpenAI and OpenRouter with zero application-code changes

Examples

After the two-line change, the untouched OpenAI SDK call round-trips through OpenRouter:

client = OpenAI(base_url="https://openrouter.ai/api/v1",
                api_key=os.environ["OPENROUTER_API_KEY"])
response = client.chat.completions.create(
    model="openai/gpt-3.5-turbo",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
    max_tokens=100,
)
print(response.choices[0].message.content)  # The capital of France is Paris.
print(response.model)                        # openai/gpt-3.5-turbo

Swap the model string to anthropic/claude-3.5-sonnet and the same code returns Claude's answer — that swap is the entire multi-provider story. More worked examples: references/examples.md.

Error Handling

IssueCauseFix
400 unsupported parameterModel doesn't support a parameterConditionally set params based on model capabilities
Different response qualityNon-OpenAI model handles prompt differentlyAdjust prompts per model family; test before switching
Missing organizationOpenRouter ignores org-level authRemove organization from client init

Enterprise Considerations

  • Use environment variables to switch between direct OpenAI and OpenRouter without code changes
  • Test your full prompt suite across providers before migrating production traffic
  • Monitor response quality and latency after migration; some prompts may need tuning
  • OpenRouter normalizes the API across providers, but subtle behavioral differences exist between model families
  • Use extra_body for OpenRouter-specific features (provider preferences, plugins, fallbacks)

References

Signals

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Last commit
Oct 2026

ahel review

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Item type
skill
Key
openrouter-openai-compat
Source
github.com/jeremylongshore/tons-of-skills-marketplace