Universal API

Overview

Who is this for? Developers who want to use multiple AI providers through a single, consistent API interface without learning different schemas, request formats, or response structures for each provider.

What you'll achieve: Build applications using the familiar OpenAI API format while seamlessly accessing capabilities from dozens of AI providers, with automatic request/response translation and unified error handling.

The AI Proxy provides a Universal API that standardizes all provider interactions using the OpenAI API schema as the common interface, enabling you to switch between providers without changing your application code.

Key Benefits

Single API Schema

OpenAI Compatibility: Use the familiar OpenAI API format for all providers
Consistent Interface: Same request/response structure across all providers
Easy Migration: Switch providers without code changes
Reduced Complexity: Learn one API, use dozens of providers

Automatic Translation

Request Mapping: Converts OpenAI format to provider-specific formats
Response Unification: Transforms provider responses to OpenAI format
Error Standardization: Unified error codes and messages
Feature Mapping: Maps OpenAI features to provider equivalents

Provider Abstraction

Transparent Switching: Change providers without application changes
Feature Normalization: Consistent feature availability across providers
Capability Detection: Automatic feature support detection
Graceful Degradation: Handles unsupported features elegantly

How It Works

Request Flow

Client Request: Application sends OpenAI-format request
Schema Validation: Validates against OpenAI API schema
Provider Mapping: Translates to provider-specific format
Feature Mapping: Maps OpenAI features to provider capabilities
Request Execution: Sends translated request to provider
Response Translation: Converts provider response to OpenAI format
Unified Response: Returns standardized OpenAI-compatible response

Supported Endpoints

Chat Completions

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Text Completions

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Embeddings

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Audio Processing

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Image Generation

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Universal Request Format

Standard OpenAI Schema

All requests follow the OpenAI API specification:

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Provider-Agnostic Parameters

Common parameters that work across all providers:

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Enhanced Parameters

Additional parameters for advanced features:

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Response Unification

Standard Response Structure

All responses follow OpenAI format regardless of provider:

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Unified Error Format

Consistent error handling across all providers:

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Provider-Specific Extensions

Optional provider-specific data in unified format:

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Provider Mapping Examples

Anthropic Claude Mapping

How Claude requests/responses map to OpenAI format:

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Google AI (Gemini) Mapping

How Gemini requests/responses map to OpenAI format:

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Azure OpenAI Mapping

How Azure OpenAI integrates with the universal interface:

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Implementation Examples

Node.js Universal Client

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Python Universal Integration

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React Universal Hook

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Feature Compatibility Matrix

Core Features

Feature	OpenAI	Anthropic	Google AI	Groq	Cohere
Chat Completions	✅	✅	✅	✅	✅
Function Calling	✅	✅	✅	✅	✅
Streaming	✅	✅	✅	✅	✅
JSON Mode	✅	✅	✅	✅	✅
Vision	✅	✅	✅	❌	❌
System Messages	✅	✅	✅	✅	✅

Advanced Features

Feature	Support Level	Notes
Temperature	Universal	Automatically mapped across providers
Max Tokens	Universal	Converted to provider-specific limits
Stop Sequences	Universal	Mapped to provider stop mechanisms
Frequency Penalty	Partial	Where supported by provider
Presence Penalty	Partial	Where supported by provider
Logit Bias	Limited	OpenAI and compatible providers only

Migration Guide

From OpenAI Direct

Replace your OpenAI endpoint with the Universal API:

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From Provider-Specific APIs

Standardize multiple provider integrations:

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Gradual Migration Strategy

Step-by-step approach to adopting Universal API:

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Best Practices

Request Optimization

Use Standard Parameters: Stick to widely supported parameters
Test Across Providers: Validate functionality with multiple providers
Handle Feature Gaps: Check for unsupported features gracefully
Monitor Performance: Track response times across providers

Error Handling Strategy

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Provider Selection

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Performance Monitoring

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Advanced Configuration

Provider Routing Rules

Configure how requests route to providers:

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Feature Fallbacks

Handle unsupported features gracefully:

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Custom Mappings

Define custom parameter mappings:

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Schema Validation

Request Validation

All requests are validated against OpenAI schema:

Parameter Types: Ensure correct data types
Required Fields: Validate mandatory parameters
Value Ranges: Check parameter constraints
Format Validation: Validate structured parameters

Response Validation

Responses are standardized and validated:

Structure Consistency: Ensure consistent response format
Data Type Safety: Guarantee correct data types
Field Completeness: Include all required fields
Error Consistency: Standardized error reporting

Development Tools

OpenAPI Specification

Complete OpenAI-compatible API specification:

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SDKs and Libraries

Official SDKs that work with Universal API:

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Testing and Validation

Tools for testing Universal API integration:

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Enterprise Features

Custom Provider Integration

Add custom providers to Universal API:

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Request/Response Transformation

Custom transformation rules:

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Compliance and Governance

Enterprise governance features:

Audit Logging: Track all API interactions
Access Control: Fine-grained permission management
Data Residency: Control data location and processing
Compliance Reporting: Generate compliance reports

Troubleshooting

Common Issues

Parameter Not Supported
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Response Format Differences
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Feature Compatibility Issues
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Debugging Tools

Request Inspector: View translated requests
Response Analyzer: Compare provider responses
Compatibility Checker: Test feature support
Performance Profiler: Analyze response times

Performance Considerations

Translation Overhead

Minimal Latency: Translation adds <5ms overhead
Caching: Request/response templates cached
Optimization: Efficient mapping algorithms
Monitoring: Track translation performance

Scaling Considerations

Horizontal Scaling: Distribute translation load
Caching Strategy: Cache common translations
Connection Pooling: Optimize provider connections
Load Balancing: Balance requests across providers

Next Steps

Provider Integration: Learn about individual provider capabilities
Authentication: Set up provider authentication
Rate Limiting: Understand rate limit handling
Monitoring: Monitor Universal API performance