openrouter-openai-compat

Migrate from OpenAI to OpenRouter with minimal code changes. Use when switching to OpenRouter or maintaining dual compatibility. Triggers: 'openrouter openai compatible', 'openrouter drop-in', 'openai to openrouter', 'openrouter migration'.

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openrouter-pack Plugin
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openrouter-pack

Flagship+ skill pack for OpenRouter - 30 skills for multi-model routing, fallbacks, and LLM gateway mastery

saas packs v1.0.0
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Installation

This skill is included in the openrouter-pack plugin:

/plugin install openrouter-pack@claude-code-plugins-plus

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Instructions

OpenRouter OpenAI Compatibility

Overview

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

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 Direct OpenRouter ID
gpt-4o openai/gpt-4o
gpt-4o-mini openai/gpt-4o-mini
gpt-4-turbo openai/gpt-4-turbo
o1 openai/o1
o1-mini openai/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

Feature Status Notes
chat.completions.create Fully supported Main endpoint, all parameters
stream: true Fully supported SSE format identical to OpenAI
tools / tool_choice Supported OpenRouter transforms for non-OpenAI providers
responseformat: { type: "jsonobject" } Supported Basic JSON mode
responseformat: { type: "jsonschema" } Supported Strict schema mode
temperature, topp, maxtokens Supported Standard parameters
stop sequences Supported Array of stop strings
n (multiple completions) Supported Multiple choices

What Differs

Feature Difference Workaround
Model IDs Prefixed with provider/ Update model strings
organization param Not used Remove from client init
Embeddings Limited support Use direct provider or dedicated embedding service
Fine-tuned models Not directly accessible Use provider's fine-tuned model ID if hosted
logprobs Model-dependent Check model capabilities via /api/v1/models
Responses API Beta support Use /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"))

Error Handling

Issue Cause Fix
400 unsupported parameter Model doesn't support a parameter Conditionally set params based on model capabilities
Different response quality Non-OpenAI model handles prompt differently Adjust prompts per model family; test before switching
Missing organization OpenRouter ignores org-level auth Remove 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

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