OpenRouter Support¶

ToolUniverse now includes full support for OpenRouter, allowing you to access a wide variety of LLM models from multiple providers through a single, unified API.

Overview¶

OpenRouter provides access to models from:

OpenAI (GPT-5)
Anthropic (Claude Sonnet 4.5)
Google (Gemini 2.5 Flash, Gemini 2.5 Pro)
And many more!

Configuration¶

Environment Variables¶

To use OpenRouter, set the following environment variables:

# Required
export OPENROUTER_API_KEY="your_openrouter_api_key_here"

# Optional - for usage tracking and attribution
export OPENROUTER_SITE_URL="https://your-site.com"
export OPENROUTER_SITE_NAME="Your Application Name"

Getting an API Key¶

Visit OpenRouter
Sign up for an account
Navigate to the API Keys section
Generate a new API key
Copy and set it as the OPENROUTER_API_KEY environment variable

Using OpenRouter with AgenticTool¶

Basic Configuration¶

Configure an AgenticTool to use OpenRouter:

from tooluniverse import ToolUniverse

# Example tool configuration using OpenRouter
tool_config = {
    "name": "OpenRouter_Summarizer",
    "description": "Summarize text using OpenRouter models",
    "type": "AgenticTool",
    "prompt": "Summarize the following text:\n{text}",
    "input_arguments": ["text"],
    "parameter": {
        "type": "object",
        "properties": {
            "text": {
                "type": "string",
                "description": "The text to summarize",
                "required": True
            }
        },
        "required": ["text"]
    },
    "configs": {
        "api_type": "OPENROUTER",
        "model_id": "openai/gpt-5",
        "temperature": 0.7,
        "return_json": False
    }
}

# Initialize ToolUniverse and register the tool
tu = ToolUniverse()
tu.register_tool_from_config(tool_config)

# Use the tool
result = tu.execute_tool("OpenRouter_Summarizer", {
    "text": "Your long text here..."
})

Using OpenRouter with ToolFinderLLM¶

Configure ToolFinderLLM to use OpenRouter models:

from tooluniverse import ToolUniverse

# Create ToolUniverse instance
tu = ToolUniverse()

# Configure ToolFinderLLM with OpenRouter
tool_finder_config = {
    "type": "ToolFinderLLM",
    "name": "Tool_Finder_OpenRouter",
    "description": "Find tools using OpenRouter LLMs",
    "configs": {
        "api_type": "OPENROUTER",
        "model_id": "anthropic/claude-sonnet-4.5",
        "temperature": 0.1,
        "max_new_tokens": 4096,
        "return_json": True,
        "exclude_tools": ["Tool_RAG", "Tool_Finder", "Finish"]
    }
}

# Register and use
tu.register_tool_from_config(tool_finder_config)
result = tu.execute_tool("Tool_Finder_OpenRouter", {
    "description": "tools for protein analysis",
    "limit": 5
})

Fallback Configuration¶

OpenRouter is included in the default fallback chain. If the primary API fails, the system will automatically try OpenRouter:

# Default fallback chain (in order):
# 1. CHATGPT (Azure OpenAI)
# 2. OPENROUTER (with openai/gpt-5)
# 3. GEMINI (Google Gemini)

# You can customize the fallback chain with environment variable:
import os
import json

custom_chain = [
    {"api_type": "OPENROUTER", "model_id": "anthropic/claude-sonnet-4.5"},
    {"api_type": "OPENROUTER", "model_id": "openai/gpt-5"},
    {"api_type": "GEMINI", "model_id": "gemini-2.5-flash"}
]

os.environ["AGENTIC_TOOL_FALLBACK_CHAIN"] = json.dumps(custom_chain)

Advanced Configuration¶

Custom Model Limits¶

Override default token limits for specific models:

import os
import json

custom_limits = {
    "openai/gpt-5": {
        "max_output": 32000,  # Custom limit
        "context_window": 1048576
    },
    "anthropic/claude-sonnet-4.5": {
        "max_output": 4096,
        "context_window": 200000
    }
}

os.environ["OPENROUTER_DEFAULT_MODEL_LIMITS"] = json.dumps(custom_limits)