Network Management Research Group H. Chen Internet-Draft Red Hat Intended status: Informational L. Jalil Expires: 12 April 2026 Verizon N. Cocker Red Hat 20 October 2025 Multi-Provider Extensions for Agentic AI Inference APIs draft-chen-nmrg-multi-provider-inference-api-00 Abstract This document specifies extensions for multi-provider distributed AI inference using the widely-adopted OpenAI Responses API as the reference interface standard. These extensions enable provider diversity, load balancing, failover, and capability negotiation in distributed inference environments while maintaining full backward compatibility with existing implementations. The extensions do not require changes to standard API usage patterns or existing client applications. By treating the OpenAI Responses API as a de facto standard interface (similar to how HTTP serves as a standard protocol), these extensions provide an optional enhancement layer for multi-provider orchestration, intelligent routing, and distributed inference capabilities. The approach preserves the familiar API interface that developers already know and use, while enabling seamless integration across multiple AI inference providers without vendor lock-in. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at https://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." This Internet-Draft will expire on 12 April 2026. Chen, et al. Expires 12 April 2026 [Page 1] Internet-Draft Multi-Provider Inference API October 2025 Copyright Notice Copyright (c) 2025 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (https://trustee.ietf.org/ license-info) in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 2. Conventions and Terminology . . . . . . . . . . . . . . . . . 4 3. Problem Statement . . . . . . . . . . . . . . . . . . . . . . 4 4. Design Principles . . . . . . . . . . . . . . . . . . . . . . 5 5. Auto-Selection Parameters for Vendor Neutrality . . . . . . . 5 Vendor-Neutral Parameter Mapping . . . . . . . . . . . . . . . 5 Auto-Model Selection Criteria . . . . . . . . . . . . . . . . . 6 Auto-Tool Selection Framework . . . . . . . . . . . . . . . . . 7 Auto-Reasoning Capability Mapping . . . . . . . . . . . . . . . 7 Auto Parameters and Header Synchronization . . . . . . . . . . 10 6. Extension Headers . . . . . . . . . . . . . . . . . . . . . . 11 Request Headers . . . . . . . . . . . . . . . . . . . . . . . . 11 Response Headers . . . . . . . . . . . . . . . . . . . . . . . 12 7. Multi-Provider Orchestration with Responses API . . . . . . . 15 Auto-Model Selection with Responses API . . . . . . . . . . . . 15 Auto-Tool Selection with Provider Mapping . . . . . . . . . . . 16 Vendor-Neutral Parameters with Auto-Selection . . . . . . . . . 18 8. Streaming and Auto-Selection Compatibility . . . . . . . . . 20 Streaming with Auto-Model Selection . . . . . . . . . . . . . . 20 Auto-Tool Selection with Responses API . . . . . . . . . . . . 21 9. Performance-Based Auto-Selection . . . . . . . . . . . . . . 23 Latency-Optimized Auto-Selection . . . . . . . . . . . . . . . 23 Quality vs Speed Trade-off . . . . . . . . . . . . . . . . . . 24 10. Multi-Turn Failover with Persistent Tracking . . . . . . . . 25 Seamless Failover Example . . . . . . . . . . . . . . . . . . . 26 11. Security-Aware Auto-Selection . . . . . . . . . . . . . . . . 29 HIPAA-Compliant Auto-Selection . . . . . . . . . . . . . . . . 29 Multi-Tier Security with Data Segregation . . . . . . . . . . . 31 12. Advanced Failover and Performance Degradation . . . . . . . . 32 Cascading Failover with Quality Adjustment . . . . . . . . . . 33 13. Workflow State Management and Branching . . . . . . . . . . . 35 Workflow Branching Example . . . . . . . . . . . . . . . . . . 36 14. Implementation Architecture . . . . . . . . . . . . . . . . . 40 Router Components . . . . . . . . . . . . . . . . . . . . . . . 41 15. Backward Compatibility Guarantees . . . . . . . . . . . . . . 41 Chen, et al. Expires 12 April 2026 [Page 2] Internet-Draft Multi-Provider Inference API October 2025 16. Security Considerations . . . . . . . . . . . . . . . . . . . 42 17. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 42 18. Normative References . . . . . . . . . . . . . . . . . . . . 42 19. Informative References . . . . . . . . . . . . . . . . . . . 43 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . 43 Implementation Examples . . . . . . . . . . . . . . . . . . . . . 43 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 43 1. Introduction The OpenAI Responses API [OPENAI-RESPONSES-API] has emerged as a de facto standard interface for agentic AI applications, with widespread adoption across the industry. Many providers now offer compatible endpoints, creating a rich ecosystem of inference services. This document treats the OpenAI Responses API as a reference standard interface (analogous to how HTTP serves as a standard protocol), rather than as a vendor-specific implementation. However, applications that want to leverage multiple providers face significant challenges in orchestrating distributed inference, handling provider failures, and optimizing resource utilization across heterogeneous environments. This document specifies vendor-neutral extensions that enable multi- provider AI inference orchestration while maintaining the familiar API interface. The extensions allow applications to leverage the best models and tools from multiple providers without vendor lock-in. The approach uses "auto" parameters and extension headers to enable intelligent provider selection, capability mapping, and distributed inference coordination. The extensions are designed as optional HTTP headers and response fields that enhance the reference API with multi-provider capabilities while ensuring that existing applications continue to work unchanged. The key principle is compatibility-first: any application that works with the reference API interface will continue to work with these extensions, while applications that choose to use the extensions gain access to advanced multi-provider features like intelligent routing, automatic failover, and distributed load balancing. The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here. Chen, et al. Expires 12 April 2026 [Page 3] Internet-Draft Multi-Provider Inference API October 2025 2. Conventions and Terminology OpenAI Responses API: The reference API specification for agentic AI inference [OPENAI-RESPONSES-API], designed for hackathon-friendly rapid prototyping and widely adopted across the industry as a de facto standard. Multi-Provider Router: A service that extends the reference API with multi-provider orchestration capabilities while maintaining full compatibility. Provider Pool: A collection of compatible inference services that can be orchestrated by the multi-provider router. Multi-Vendor Compatibility: The ability to seamlessly integrate and route requests across multiple AI inference providers while maintaining a consistent interface. Extension Headers: Optional HTTP/HTTPS headers that provide multi- provider functionality without affecting standard API behavior. Distributed Inference: The orchestration of AI inference requests across multiple providers to achieve better performance, reliability, and resource utilization. Transport Protocol: All API endpoints support both HTTP and HTTPS protocols. HTTPS SHOULD be used for production deployments to ensure confidentiality and integrity of inference requests and responses. 3. Problem Statement While the OpenAI API provides an excellent standard interface for AI inference, several challenges arise when deploying at scale across multiple providers: 1. *Provider Lock-in:* Applications typically connect to a single provider, creating dependency on that provider's availability, pricing, and capabilities. 2. *Limited Failover:* When a provider experiences issues, applications have no automatic mechanism to failover to alternative providers while maintaining session continuity. 3. *Suboptimal Resource Utilization:* Different providers excel in different scenarios (cost, latency, specialized models), but applications cannot easily leverage these strengths dynamically. Chen, et al. Expires 12 April 2026 [Page 4] Internet-Draft Multi-Provider Inference API October 2025 4. *Operational Complexity:* Managing multiple provider connections, API keys, and routing logic adds significant complexity to application development and operations. 5. *Inconsistent Capabilities:* While providers offer OpenAI- compatible APIs, they may have different model names, capabilities, and limitations that applications must handle manually. These extensions address these challenges while preserving the simplicity and familiarity of the OpenAI API that developers rely on. 4. Design Principles The extensions are designed according to the following principles: 1. *Multi-Vendor Support:* Enable seamless integration across multiple AI inference providers without vendor lock-in. Applications can leverage the best capabilities from different providers within a unified interface. 2. *Opt-in Enhancement:* Multi-provider features are enabled only when clients explicitly request them through extension headers. Default behavior remains unchanged. 3. *Transparent Operation:* When multi-provider features are enabled, the complexity of provider orchestration is hidden from the client. Responses maintain standard OpenAI API format. 4. *Graceful Degradation:* If multi-provider features are unavailable or fail, the system falls back to standard single-provider behavior. 5. *Standard Compliance:* All extensions use standard HTTP mechanisms and do not require proprietary protocols or non-standard API modifications. 5. Auto-Selection Parameters for Vendor Neutrality The OpenAI Responses API supports several parameters that benefit from vendor-neutral "auto" values, enabling seamless multi-provider orchestration. The following parameters are enhanced with auto- selection capabilities: Vendor-Neutral Parameter Mapping Key Responses API parameters that require provider-specific mapping: Chen, et al. Expires 12 April 2026 [Page 5] Internet-Draft Multi-Provider Inference API October 2025 +=======================+===================+=====================+ | Parameter | Auto Value | Router Behavior | +=======================+===================+=====================+ | model | "auto" | Maps to optimal | | | | provider-specific | | | | model based on task | +-----------------------+-------------------+---------------------+ | tools | "auto" | Selects appropriate | | | | tools from | | | | provider's | | | | available toolkit | +-----------------------+-------------------+---------------------+ | tool_choice | "auto" | Lets provider | | | | decide when to use | | | | tools based on | | | | context | +-----------------------+-------------------+---------------------+ | reasoning | "auto" | Maps to reasoning- | | | | capable models or | | | | simulates reasoning | | | | for multi-vendor | | | | compatibility | +-----------------------+-------------------+---------------------+ | max_completion_tokens | "auto" | Calculates optimal | | | | token limit based | | | | on task complexity | +-----------------------+-------------------+---------------------+ | response_format | provider-adaptive | Adapts format | | | | requirements to | | | | provider | | | | capabilities | +-----------------------+-------------------+---------------------+ Table 1: Vendor-Neutral Parameters Auto-Model Selection Criteria When model is set to "auto", the router uses these criteria for selection: 1. *Task Classification:* Analyzes the request to determine task type (reasoning, coding, creative, analytical, etc.) 2. *Provider Capabilities:* Matches task requirements to provider strengths and available models 3. *Performance Requirements:* Considers latency, cost, and quality constraints from extension headers Chen, et al. Expires 12 April 2026 [Page 6] Internet-Draft Multi-Provider Inference API October 2025 4. *Context Awareness:* Maintains conversation context and provider affinity when beneficial Auto-Tool Selection Framework When tools is set to "auto", the router implements intelligent tool selection: 1. *Tool Category Mapping:* Maps generic tool categories (web-search, code-execution, image-generation) to provider-specific tools 2. *Capability Discovery:* Dynamically discovers available tools from each provider and their capabilities 3. *Context-Aware Selection:* Chooses tools based on conversation context and task requirements 4. *Cross-Provider Orchestration:* Coordinates tool usage across multiple providers when beneficial Auto-Reasoning Capability Mapping When reasoning is set to "auto", the router intelligently handles providers with different reasoning capabilities: 1. *Native Reasoning Models:* Routes to providers with dedicated reasoning models (o1, o1-mini, etc.) 2. *Reasoning-Enhanced Models:* Uses models optimized for logical thinking and step-by-step analysis 3. *Simulated Reasoning:* For providers without native reasoning, implements reasoning through structured prompting and chain-of- thought techniques 4. *Fallback Strategies:* Gracefully degrades to best-available reasoning approximation when native reasoning is unavailable # Auto-reasoning with mixed providers POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: reasoning-optimized X-AI-Routing-Strategy: capability-first { Chen, et al. Expires 12 April 2026 [Page 7] Internet-Draft Multi-Provider Inference API October 2025 "model": "auto", "messages": [ { "role": "user", "content": "Solve: If 3x+7=22, what is x?" } ] } # Router selects provider with native reasoning capability HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: openai-reasoning X-AI-Model-Mapped: o1-preview X-AI-Auto-Selection: { "reasoning_capability": "native", "provider_selection": { "primary_choice": { "provider": "openai-reasoning", "model": "o1-preview", "reasoning_type": "native_model", "confidence": 0.98 }, "alternatives_considered": [ { "provider": "anthropic", "model": "claude-3-5-sonnet", "reasoning_type": "enhanced", "confidence": 0.85, "reason_not_selected": "native_available" }, { "provider": "local", "model": "llama-3-8b", "reasoning_type": "sim_cot", "confidence": 0.65, "reason_not_selected": "lower_capability" } ] } } { "id": "resp-reasoning-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ Chen, et al. Expires 12 April 2026 [Page 8] Internet-Draft Multi-Provider Inference API October 2025 { "message": { "role": "assistant", "content": "x=5. Reasoning: 3x+7=22->3x=15->x=5" } ] } ] } Figure 1 *Fallback to Simulated Reasoning Example:* # Same request when native reasoning providers are unavailable POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: reasoning-optimized X-AI-Provider-Pool: anthropic,cohere,local-models { "model": "auto", "messages": [ { "role": "user", "content": "Solve: If 3x+7=22, what is x?" } ] } # Router falls back to simulated reasoning HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: anthropic-enhanced X-AI-Model-Mapped: claude-3-5-sonnet X-AI-Auto-Selection: { "reasoning_capability": "simulated", "fallback_strategy": { "native_reasoning_available": false, "selected_approach": "enhanced_chain_of_thought", "prompt_enhancement": "added_reasoning_structure", "confidence": 0.87 }, "reasoning_simulation": { "technique": "structured_step_by_step", Chen, et al. Expires 12 April 2026 [Page 9] Internet-Draft Multi-Provider Inference API October 2025 "verification_added": true, "explanation_enhanced": true } } { "id": "resp-reasoning-002", "object": "response", "created": 1699123500, "model": "auto", "choices": [ { "message": { "role": "assistant", "content": "Step-by-step: 3x+7=22->3x=15->x=5" } ] } ] } Figure 2 Auto Parameters and Header Synchronization Auto parameters in the request body are the primary mechanism for enabling multi-vendor capabilities. Extension headers provide supplementary information to assist the router in making optimal decisions: *Primary Control:* Auto parameters ("model": "auto", "tools": "auto", "reasoning": "auto") trigger multi-vendor selection. *Decision Assistance:* Headers provide hints, constraints, and preferences to guide the auto-selection process. *Synchronization Rules:* 1. If auto parameter is NOT "auto" but headers suggest multi- provider behavior, the router SHOULD honor the explicit parameter value and ignore conflicting headers. 2. If auto parameter is "auto" but X-AI-Multi-Provider is "disabled", the router MUST treat the parameter as a regular non-auto value and route to a single default provider. Chen, et al. Expires 12 April 2026 [Page 10] Internet-Draft Multi-Provider Inference API October 2025 3. If auto parameter is "auto" and X-AI-Multi-Provider is "enabled" (or absent but other multi-provider headers are present), the router SHOULD use headers as decision assistance. 4. If headers contain conflicting information (e.g., X-AI-Routing- Strategy: "cost" but X-AI-Quality-Threshold: 0.95), the router SHOULD prioritize explicit constraints (quality threshold) over optimization strategies (cost). 6. Extension Headers The multi-provider extensions are implemented through optional HTTP headers that clients can include in standard OpenAI Responses API requests. These headers provide hints and preferences for auto- selection and multi-provider orchestration. Request Headers The following headers can be included in requests to enable multi- provider features: +===========================+==================+==================+ | Header | Values | Description | +===========================+==================+==================+ | X-AI-Multi-Provider | enabled | | Enable multi- | | | disabled | provider | | | | orchestration | | | | (master switch) | +---------------------------+------------------+------------------+ | X-AI-Provider-Pool | CSV of provider | Constrain auto- | | | IDs | selection to | | | | specific | | | | providers | +---------------------------+------------------+------------------+ | X-AI-Routing-Strategy | cost | latency | | Optimization | | | quality | | strategy for | | | capability-first | auto-parameter | | | | decisions | +---------------------------+------------------+------------------+ | X-AI-Task-Hint | reasoning | | Task type hint | | | coding | | to assist model | | | creative | | auto-selection | | | analytical | | | | | multimodal | | +---------------------------+------------------+------------------+ | X-AI-Tool-Categories | CSV of tool | Preferred tool | | | categories | categories to | | | | assist tools | Chen, et al. Expires 12 April 2026 [Page 11] Internet-Draft Multi-Provider Inference API October 2025 | | | auto-selection | +---------------------------+------------------+------------------+ | X-AI-Reasoning-Preference | native | | Reasoning | | | enhanced | | approach | | | simulated | preference to | | | | assist reasoning | | | | auto-selection | +---------------------------+------------------+------------------+ | X-AI-Quality-Threshold | 0.0 - 1.0 | Minimum quality | | | | threshold for | | | | auto-selected | | | | providers | +---------------------------+------------------+------------------+ | X-AI-Max-Latency | milliseconds | Maximum | | | | acceptable | | | | latency for | | | | auto-selected | | | | providers | +---------------------------+------------------+------------------+ | X-AI-Cost-Limit | USD per request | Maximum cost | | | | limit for auto- | | | | selected | | | | providers | +---------------------------+------------------+------------------+ | X-AI-Failover-Policy | none | | Failover | | | automatic | | behavior when | | | manual | auto-selected | | | | providers fail | +---------------------------+------------------+------------------+ Table 2: Multi-Provider Assistance Headers Response Headers When multi-provider features are active, responses include additional headers providing transparency into the routing decisions: Chen, et al. Expires 12 April 2026 [Page 12] Internet-Draft Multi-Provider Inference API October 2025 +==============================+==============================+ | Header | Description | +==============================+==============================+ | X-AI-Provider-Used | ID of the provider selected | | | by auto-routing | +------------------------------+------------------------------+ | X-AI-Model-Mapped | Provider-specific model | | | mapped from "auto" | +------------------------------+------------------------------+ | X-AI-Auto-Selection | JSON object with auto- | | | selection decisions | +------------------------------+------------------------------+ | X-AI-Tool-Mapping | JSON object showing tool | | | category to provider mapping | +------------------------------+------------------------------+ | X-AI-Auto-Decisions | JSON object with all auto- | | | parameter resolutions | +------------------------------+------------------------------+ | X-AI-Alternatives-Considered | JSON array of alternative | | | providers/models considered | +------------------------------+------------------------------+ | X-AI-Selection-Confidence | Confidence score (0.0 - 1.0) | | | for auto-selection | +------------------------------+------------------------------+ Table 3: Auto-Selection Response Headers *Synchronization Examples:* _Example 1: Proper Sync (Headers Assist Auto Parameters)_ POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: reasoning X-AI-Reasoning-Preference: native X-AI-Quality-Threshold: 0.9 { "model": "auto", "reasoning": "auto", "messages": [{"role": "user", "content": "Solve complex math"}] } # Router behavior: Uses auto parameters with header guidance # Selects native reasoning model with quality >= 0.9 Chen, et al. Expires 12 April 2026 [Page 13] Internet-Draft Multi-Provider Inference API October 2025 Figure 3 _Example 2: Conflict Resolution (Explicit Parameter Wins)_ POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: reasoning { "model": "gpt-4", "reasoning": "auto", "messages": [{"role": "user", "content": "Solve complex math"}] } # Router behavior: Honors explicit "gpt-4" model selection # Only applies auto-reasoning since reasoning="auto" # Ignores task hint for model selection Figure 4 _Example 3: Multi-Provider Disabled Override_ POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: disabled X-AI-Task-Hint: reasoning { "model": "auto", "tools": "auto", "messages": [{"role": "user", "content": "Help with coding"}] } # Router behavior: Treats "auto" as regular values # Routes to single default provider # Ignores all multi-provider headers Figure 5 Chen, et al. Expires 12 April 2026 [Page 14] Internet-Draft Multi-Provider Inference API October 2025 7. Multi-Provider Orchestration with Responses API The following examples demonstrate how the extensions work with OpenAI's Responses API while providing multi-provider capabilities through auto-model and auto-tool selection. Auto-Model Selection with Responses API Using the OpenAI Responses API with auto-model selection for vendor- neutral multi-provider routing: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: reasoning X-AI-Routing-Strategy: balanced { "model": "auto", "messages": [ { "role": "user", "content": "Solve: integral of x*sin(x^2)" } ], "response_format": { "type": "text" }, "tools": "auto", "max_completion_tokens": 500 } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: provider-anthropic X-AI-Model-Mapped: claude-3-5-sonnet X-AI-Auto-Selection: { "model_selection": { "requested": "auto", "criteria": "reasoning", "selected": "claude-3-5-sonnet", "reason": "best_math_reasoning" }, "tool_selection": { "available_tools": ["calculator", "wolfram", "python"], "selected": "python", Chen, et al. Expires 12 April 2026 [Page 15] Internet-Draft Multi-Provider Inference API October 2025 "reason": "symbolic_math" } } { "id": "resp-abc123", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "I'll solve using substitution...", "tool_calls": [ { "id": "call_python_123", "type": "function", "function": { "name": "python_calculator", "arguments": "{\"code\": \"import sympy as sp...\"}" } }, "finish_reason": "stop" }, "finish_reason": "tool_calls" } ], "usage": { "prompt_tokens": 25, "completion_tokens": 150, "total_tokens": 175 } } Figure 6 Auto-Tool Selection with Provider Mapping The router automatically maps generic tool requests to provider- specific implementations while maintaining Responses API compatibility: Chen, et al. Expires 12 April 2026 [Page 16] Internet-Draft Multi-Provider Inference API October 2025 POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: coding X-AI-Provider-Pool: openai,anthropic,cohere X-AI-Tool-Categories: web-scraping,data-viz { "model": "auto", "messages": [ { "role": "user", "content": "Create web scraper and visualize data" } ], "tools": "auto", "tool_choice": "auto", "response_format": { "type": "text" } } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: openai X-AI-Model-Mapped: gpt-4-turbo X-AI-Tool-Mapping: { "requested": "auto", "available_categories": ["web-scraping", "data-viz", "code-exec"], "provider_tools": { "openai": ["browser", "python", "dalle"], "anthropic": ["computer_use", "text_editor"], "cohere": ["web_search", "python_interpreter"] }, "selected_tools": [ { "category": "web-scraping", "provider_tool": "browser", "generic_name": "web_scraper" }, { "category": "data-viz", "provider_tool": "python", "generic_name": "data_visualizer" } ] Chen, et al. Expires 12 April 2026 [Page 17] Internet-Draft Multi-Provider Inference API October 2025 } { "id": "resp-def456", "object": "response", "created": 1699123500, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "I'll create a web scraper and visualize data.", "tool_calls": [ { "id": "call_browser_123", "type": "function", "function": { "name": "web_scraper", "arguments": "{\"url\": \"example.com\"}" } }, "finish_reason": "stop" }, "finish_reason": "tool_calls" } ], "usage": { "prompt_tokens": 18, "completion_tokens": 95, "total_tokens": 113 } } Figure 7 Vendor-Neutral Parameters with Auto-Selection The Responses API enables vendor-neutral parameter handling through auto-selection, allowing seamless provider switching: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: analytical X-AI-Tool-Categories: data-analysis,reporting Chen, et al. Expires 12 April 2026 [Page 18] Internet-Draft Multi-Provider Inference API October 2025 X-AI-Routing-Strategy: cost X-AI-Quality-Threshold: 0.85 { "model": "auto", "messages": [ { "role": "user", "content": "Analyze data and create summary" } ], "tools": "auto", "tool_choice": "auto", "response_format": { "type": "json_schema", "json_schema": { "name": "analysis_report", "schema": { "type": "object", "properties": { "summary": {"type": "string"}, "insights": {"type": "array"} } } } }, "max_completion_tokens": "auto" } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: cohere X-AI-Model-Mapped: command-r-plus X-AI-Auto-Decisions: { "model_selection": { "criteria": "cost-efficient + data-analysis", "alternatives": { "openai": {"model": "gpt-4o-mini", "cost": 0.15}, "anthropic": {"model": "haiku", "cost": 0.25}, "cohere": {"model": "command-r-plus", "cost": 0.08} }, "selected": "cohere", "reason": "best_cost_above_threshold" }, "tool_mapping": { "data": "cohere_connector", "report": "structured_output" }, Chen, et al. Expires 12 April 2026 [Page 19] Internet-Draft Multi-Provider Inference API October 2025 "token_optimization": { "requested": "auto", "calculated": 300, "basis": "task_complexity_analysis" } } { "id": "resp-ghi789", "object": "response", "created": 1699123600, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "{\"summary\": \"Analysis...\", \"data\": [...]}" }, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 150, "completion_tokens": 285, "total_tokens": 435 } } Figure 8 8. Streaming and Auto-Selection Compatibility The extensions maintain full compatibility with OpenAI Responses API streaming while providing auto-selection capabilities. Streaming with Auto-Model Selection Server-sent events streaming works with auto-model selection, with provider routing happening before stream initiation: Chen, et al. Expires 12 April 2026 [Page 20] Internet-Draft Multi-Provider Inference API October 2025 POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: creative X-AI-Routing-Strategy: latency { "model": "auto", "messages": [{"role": "user", "content": "Write a story"}], "stream": true, "max_completion_tokens": "auto" } HTTP/1.1 200 OK Content-Type: text/event-stream X-AI-Provider-Used: anthropic X-AI-Model-Mapped: claude-3-5-sonnet X-AI-Auto-Selection: {"criteria": "creative", "confidence": 0.92} data: {"id":"resp-stream1","object":"response.chunk",...} data: {"id":"resp-stream1","object":"response.chunk",...} data: [DONE] Figure 9 Auto-Tool Selection with Responses API Tool calling with auto-selection maps generic tool requests to provider-specific implementations seamlessly: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: multimodal X-AI-Tool-Categories: weather,web-search { "model": "auto", "messages": [ { "role": "user", "content": "What's the weather in Boston and latest news?" Chen, et al. Expires 12 April 2026 [Page 21] Internet-Draft Multi-Provider Inference API October 2025 } ], "tools": "auto", "tool_choice": "auto" } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: openai X-AI-Model-Mapped: gpt-4o X-AI-Tool-Mapping: { "weather": "openai_weather_tool", "web-search": "openai_browser_tool" } { "id": "resp-func123", "object": "response", "created": 1699123700, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "I'll get the weather and latest news for you.", "tool_calls": [ { "id": "call_weather_123", "type": "function", "function": { "name": "weather_lookup", "arguments": "{\"location\": \"Boston\"}" } }, { "id": "call_news_456", "type": "function", "function": { "name": "web_search", "arguments": "{\"query\": \"Boston latest news\"}" } }, "finish_reason": "stop" }, "finish_reason": "tool_calls" } ] Chen, et al. Expires 12 April 2026 [Page 22] Internet-Draft Multi-Provider Inference API October 2025 } Figure 10 9. Performance-Based Auto-Selection The OpenAI Responses API with auto-selection enables dynamic provider routing based on performance requirements and real-time characteristics. Latency-Optimized Auto-Selection Applications can specify performance requirements through extension headers while using standard Responses API calls: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: support X-AI-Routing-Strategy: latency X-AI-Max-Latency: 200 { "model": "auto", "messages": [ { "role": "user", "content": "Quick support response needed" } ], "max_completion_tokens": "auto", "response_format": {"type": "text"} } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: edge-provider-fast X-AI-Model-Mapped: fast-response-model X-AI-Auto-Selection: { "latency_achieved_ms": 180, "alternatives_rejected": [ {"provider": "cloud", "latency_ms": 350, "reason": "slow"}, {"provider": "premium", "latency_ms": 800, "reason": "limit"} ], "performance_tier": "edge-optimized" } Chen, et al. Expires 12 April 2026 [Page 23] Internet-Draft Multi-Provider Inference API October 2025 { "id": "resp-support-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "I can help you right away..." }, "finish_reason": "stop" } ] } Figure 11 Quality vs Speed Trade-off Auto-selection can balance quality and performance requirements: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: analytical X-AI-Quality-Threshold: 0.85 X-AI-Max-Latency: 2000 { "model": "auto", "messages": [ { "role": "user", "content": "Analyze legal document for compliance" } ], "max_completion_tokens": "auto" } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: premium-balanced X-AI-Model-Mapped: legal-analysis-model X-AI-Auto-Decisions: { Chen, et al. Expires 12 April 2026 [Page 24] Internet-Draft Multi-Provider Inference API October 2025 "quality_achieved": 0.92, "latency_ms": 1800, "tradeoffs": { "fastest": {"quality": 0.72, "rejected": "below_thresh"}, "highest_quality": {"latency_ms": 5000, "rejected": "too_slow"} }, "selection_rationale": "optimal_quality_within_latency_constraint" } { "id": "resp-legal-002", "object": "response", "created": 1699123500, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Based on my analysis of the document..." }, "finish_reason": "stop" } ] } Figure 12 10. Multi-Turn Failover with Persistent Tracking The extensions maintain conversation continuity during provider failures through persistent ID tracking and state preservation using standard OpenAI conversation patterns. Chen, et al. Expires 12 April 2026 [Page 25] Internet-Draft Multi-Provider Inference API October 2025 Client Router Provider A Provider B State Store | | | | | | Start | | | | | Conv | | | | |--------->| | | | | | Route + | | | | | Store | | | | |---------->| | | | | | | Store | | | | conv-001 | |<----------| | | | conv-001 | | | | |<---------| | | | | | | | | | Continue | | | | |--------->| | | | | | Route + | | | | | Load | | | | |---------->| | | | | X TIMEOUT | | | | | | | | | FAILOVER | | | | | Detect + | | Retrieve | | Retrieve | | conv-001 | | State | | | | | | | | | | Route B + | | | | | Full St | | | | |---------------------->| | | | | | Store | | | | conv-001 | |<----------------------| | | conv-001 | | | | | FAILOVER | | | | |<---------| | | | Figure 13: Multi-Turn Failover with OpenAI API Seamless Failover Example Multi-turn conversations maintain context automatically during failover: Chen, et al. Expires 12 April 2026 [Page 26] Internet-Draft Multi-Provider Inference API October 2025 # Turn 1: Initial request to Provider A POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: coding X-AI-Failover-Policy: automatic { "model": "auto", "messages": [ { "role": "user", "content": "Debug: def calc(x): return x/0" } ] } # Response from Provider A HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: provider-a X-AI-Model-Mapped: code-assistant-model X-AI-Conversation-ID: conv-debug-001 { "id": "resp-debug-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Division by zero error. Add error handling." }, "finish_reason": "stop" } ] } # Turn 2: Follow-up (Provider A fails, auto-failover to Provider B) POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json Chen, et al. Expires 12 April 2026 [Page 27] Internet-Draft Multi-Provider Inference API October 2025 X-AI-Multi-Provider: enabled X-AI-Task-Hint: coding X-AI-Failover-Policy: automatic { "model": "auto", "messages": [ { "role": "user", "content": "Debug Python: def calc(x): return x/0" }, { "role": "assistant", "content": "Division by zero error. Add error handling." }, { "role": "user", "content": "Show me the corrected code" } ] } # Auto-failover response from Provider B HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: provider-b X-AI-Model-Mapped: advanced-coder-model X-AI-Failover-Occurred: true X-AI-Auto-Selection: { "failover_reason": "provider_a_timeout", "failover_time_ms": 1200, "context_preserved": true, "conversation_continuity": "maintained" } { "id": "resp-debug-002", "object": "response", "created": 1699123500, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Here's the corrected code with error handling" }, "finish_reason": "stop" Chen, et al. Expires 12 April 2026 [Page 28] Internet-Draft Multi-Provider Inference API October 2025 } ] } Figure 14 11. Security-Aware Auto-Selection The extensions handle providers with different security requirements and compliance levels through security-aware auto-selection. Client Router Security Provider Pool | | Evaluator | | Request + | | | | Sec Reqs | | | |---------->| | | | | Evaluate | | | | Security | | | |----------->| | | | | Check | | | | Compliance | | | | Hi|Med|Lo | | | | | | |<-----------| | | | Security | | | | Matched | | | | | | | | Route to | | | | Compliant | | | |------------------------>| | | | | | |<------------------------| | Response +| | | | Sec Info | | | |<----------| | | Figure 15: Security-Aware Provider Selection HIPAA-Compliant Auto-Selection Medical data processing with strict compliance requirements: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: medical Chen, et al. Expires 12 April 2026 [Page 29] Internet-Draft Multi-Provider Inference API October 2025 X-AI-Security-Requirements: hipaa,pii X-AI-Data-Classification: sensitive-medical { "model": "auto", "messages": [ { "role": "user", "content": "Analyze patient symptoms for diagnosis" } ], "tools": "auto", "response_format": {"type": "text"} } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: healthcare-secure X-AI-Model-Mapped: medical-analysis-hipaa X-AI-Auto-Selection: { "security_compliance": { "hipaa": "certified", "soc2_type2": "verified", "encryption": "aes256_end_to_end", "data_residency": "us_only" }, "rejected_providers": [ {"provider": "public", "reason": "insufficient_hipaa"}, {"provider": "intl", "reason": "data_residency"} ] } { "id": "resp-medical-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Based on the symptom analysis..." }, "finish_reason": "stop" } ] } Chen, et al. Expires 12 April 2026 [Page 30] Internet-Draft Multi-Provider Inference API October 2025 Figure 16 Multi-Tier Security with Data Segregation Financial workflow with mixed sensitivity levels using auto- selection: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: financial X-AI-Security-Requirements: pci-dss,sovereignty X-AI-Data-Classification: financial-mixed { "model": "auto", "messages": [ { "role": "user", "content": "Generate financial report" } ], "tools": "auto", "response_format": { "type": "json_schema", "json_schema": { "name": "financial_report", "schema": { "type": "object", "properties": { "public_data": {"type": "object"}, "private_data": {"type": "object"} } } } } } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: multi-tier-financial X-AI-Model-Mapped: financial-segregation X-AI-Auto-Selection: { "strategy": "segregation", "allocation": { "public": {"provider": "public", "sec": "basic"}, Chen, et al. Expires 12 April 2026 [Page 31] Internet-Draft Multi-Provider Inference API October 2025 "pci": {"provider": "secure", "sec": "pci"}, "conf": {"provider": "private", "sec": "max"} }, "flow_controls": { "cross_tier": "prohibited", "aggregation": "secure_comp" } } { "id": "resp-financial-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "{\"public\": {...}, \"private\": {...}}" }, "finish_reason": "stop" } ] } Figure 17 12. Advanced Failover and Performance Degradation The extensions implement sophisticated failover strategies that handle performance degradation and cascading failures while maintaining OpenAI API compatibility. Chen, et al. Expires 12 April 2026 [Page 32] Internet-Draft Multi-Provider Inference API October 2025 Client Router Monitor Prov-A Prov-B Prov-C | | | | | | | Req | | | | | |----->| | | | | | | Mon | | | | | | Start| | | | | |----->| | | | | | | Check | | | | | | Health| | | | | |------>| | | | | | |Degrade| | | | |<------| | | | | | | | | | | Route| | | | | | to B | | | | | |--------------------->| | | | | | | | | | | Mon | | | | | | Prov B| | | | | |-------------->| | | | | | Overload | | | |<--------------| | | | | | | | | |GRACEFUL | | | | |DEGRADE | | | | |Route C | | | | |----------------------------->| | | | | | | | |<-----------------------------| | Resp | | | | | |<-----| | | | | Figure 18: Advanced Failover with Performance Monitoring Cascading Failover with Quality Adjustment Auto-selection with graceful degradation during system stress: POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: creative X-AI-Quality-Threshold: 0.8 X-AI-Failover-Policy: cascading { Chen, et al. Expires 12 April 2026 [Page 33] Internet-Draft Multi-Provider Inference API October 2025 "model": "auto", "messages": [ { "role": "user", "content": "Write comprehensive product documentation" } ], "max_completion_tokens": "auto" } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: provider-fast X-AI-Model-Mapped: efficient-writer-model X-AI-Auto-Selection: { "failover_cascade": { "primary_attempt": { "provider": "premium", "status": "degraded", "quality_estimate": 0.95, "response_time_ms": 8000, "decision": "too_slow" }, "secondary_attempt": { "provider": "balanced", "status": "overloaded", "queue_depth": 150, "decision": "capacity_exceeded" }, "tertiary_selection": { "provider": "fast", "status": "available", "quality_estimate": 0.82, "response_time_ms": 1200, "decision": "selected_with_quality_adjustment" } }, "quality_adjustment": { "target": 0.95, "achieved": 0.82, "mitigation": "post_processing_available" } } { "id": "resp-docs-001", "object": "response", "created": 1699123456, Chen, et al. Expires 12 April 2026 [Page 34] Internet-Draft Multi-Provider Inference API October 2025 "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "# Product Docs\n\nGuide..." }, "finish_reason": "stop" } ] } Figure 19 13. Workflow State Management and Branching Complex workflows can branch and merge while maintaining conversation state through standard OpenAI message arrays and extension headers. Chen, et al. Expires 12 April 2026 [Page 35] Internet-Draft Multi-Provider Inference API October 2025 Initial Request | v +-------------+ | Base | | Analysis | | Provider A | | conv-001 | +------+------+ | | State: base | +-------+--------+ | | v v +-----------+ +-----------+ | Marketing | | Product | | Prov B | | Prov C | | conv-mkt | | conv-prod | +-----+-----+ +-----+-----+ | | | Inherits | Inherits | Base State | Base State | | +-------+--------+ | v +-------------+ | Final Report| | Provider D | | conv-final | +-------------+ | | Merges v Final Report Figure 20: Workflow Branching with State Inheritance Workflow Branching Example Multi-branch workflow with state inheritance using conversation arrays: Chen, et al. Expires 12 April 2026 [Page 36] Internet-Draft Multi-Provider Inference API October 2025 # Initial workflow step POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: analytical { "model": "auto", "messages": [ { "role": "user", "content": "Analyze user behavior data" } ] } # Base analysis response HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: analytics-provider X-AI-Conversation-ID: conv-behavior-001 X-AI-Workflow-Step: base-analysis { "id": "resp-base-001", "object": "response", "created": 1699123456, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "Analysis complete. Found 3 segments..." }, "finish_reason": "stop" } ] } # Branch 1: Marketing insights POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled Chen, et al. Expires 12 April 2026 [Page 37] Internet-Draft Multi-Provider Inference API October 2025 X-AI-Task-Hint: marketing X-AI-Parent-Conversation: conv-behavior-001 X-AI-Workflow-Branch: marketing { "model": "auto", "messages": [ { "role": "user", "content": "Analyze user behavior data for insights" }, { "role": "assistant", "content": "Analysis complete. Found 3 segments..." }, { "role": "user", "content": "Generate marketing recommendations" } ] } # Branch 2: Product insights (parallel) POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: product X-AI-Parent-Conversation: conv-behavior-001 X-AI-Workflow-Branch: product { "model": "auto", "messages": [ { "role": "user", "content": "Analyze user behavior data for insights" }, { "role": "assistant", "content": "Analysis complete. Found 3 segments..." }, { "role": "user", "content": "Generate product improvements" } ] Chen, et al. Expires 12 April 2026 [Page 38] Internet-Draft Multi-Provider Inference API October 2025 } # Merge branches for final report POST /v1/responses HTTP/1.1 Host: multi-provider.example.com Authorization: Bearer sk-... Content-Type: application/json X-AI-Multi-Provider: enabled X-AI-Task-Hint: analytical X-AI-Merge-Branches: marketing,product { "model": "auto", "messages": [ { "role": "user", "content": "Create executive summary" } ], "tools": "auto", "response_format": { "type": "json_schema", "json_schema": { "name": "executive_summary", "schema": { "type": "object", "properties": { "marketing_insights": {"type": "array"}, "product_recommendations": {"type": "array"}, "combined_strategy": {"type": "string"} } } } } } HTTP/1.1 200 OK Content-Type: application/json X-AI-Provider-Used: report-generator X-AI-Model-Mapped: executive-summary-model X-AI-Auto-Selection: { "branches_merged": ["marketing", "product"], "context_integration": "complete", "workflow_completion": "success" } { "id": "resp-final-001", Chen, et al. Expires 12 April 2026 [Page 39] Internet-Draft Multi-Provider Inference API October 2025 "object": "response", "created": 1699123600, "model": "auto", "choices": [ { "index": 0, "message": { "role": "assistant", "content": "{\"insights\": [...], \"strategy\": \"...\"}" }, "finish_reason": "stop" } ] } Figure 21 14. Implementation Architecture The multi-provider extensions can be implemented as a proxy layer that sits between clients and provider endpoints, or as enhanced provider implementations that support multi-provider orchestration. Client Applications (Standard OpenAI API) | | HTTP/HTTPS v +------------------+ | Multi-Provider | | Router | | - Header parsing | | - Route decision | | - Failover logic | | - Response merge | +------------------+ | +----+----+----+ | | | | v v v v +------+ +------+ +------+ +------+ |OpenAI| |Azure | |Anthro| |Local | |API | |OpenAI| |Claude| |Model | +------+ +------+ +------+ +------+ Figure 22: Multi-Provider Router Architecture Chen, et al. Expires 12 April 2026 [Page 40] Internet-Draft Multi-Provider Inference API October 2025 Router Components The multi-provider router consists of several key components: 1. *Header Parser:* Extracts multi-provider preferences from request headers while preserving standard OpenAI API structure. 2. *Provider Registry:* Maintains information about available providers, their capabilities, current status, and performance metrics. 3. *Routing Engine:* Implements provider selection algorithms based on client preferences, provider capabilities, and real-time performance data. 4. *Request Translator:* Adapts requests to provider-specific requirements while maintaining OpenAI API compatibility. 5. *Response Normalizer:* Ensures all responses conform to standard OpenAI API format regardless of the underlying provider. 6. *Failover Manager:* Handles provider failures and implements retry logic with alternative providers. 15. Backward Compatibility Guarantees The extensions provide strong backward compatibility guarantees: 1. *API Compatibility:* All standard OpenAI API endpoints, request formats, and response formats remain unchanged. Existing applications work without modification. 2. *Default Behavior:* Requests without extension headers behave identically to standard OpenAI API calls, typically routing to a default provider. 3. *Error Handling:* Error responses maintain standard OpenAI API error format and codes, ensuring existing error handling logic continues to work. 4. *Authentication:* Standard OpenAI API authentication mechanisms (API keys, bearer tokens) are preserved and work unchanged. 5. *Rate Limiting:* Rate limiting headers and behavior remain compatible with OpenAI API standards. Chen, et al. Expires 12 April 2026 [Page 41] Internet-Draft Multi-Provider Inference API October 2025 16. Security Considerations Multi-provider routing introduces several security considerations: *Credential Management:* The router must securely manage credentials for multiple providers while ensuring that client credentials are not exposed to inappropriate providers. *Data Privacy:* Request data may be processed by different providers with varying privacy policies. The router should provide mechanisms to restrict certain providers based on data sensitivity. *Audit Logging:* Multi-provider routing decisions should be logged for security auditing and compliance purposes. *Provider Trust:* The router must validate provider certificates and ensure secure communication channels to all providers. 17. IANA Considerations This document requests registration of the following HTTP header fields in the "Message Headers" registry: Request Headers (Decision Assistance): - X-AI-Multi-Provider - X-AI-Provider-Pool - X-AI-Routing-Strategy - X-AI-Task-Hint - X-AI-Tool-Categories - X-AI-Reasoning-Preference - X-AI-Quality-Threshold - X-AI-Max-Latency - X-AI-Cost-Limit - X-AI-Failover-Policy Response Headers (Transparency): - X-AI-Provider-Used - X-AI-Model-Mapped - X-AI-Auto-Selection - X-AI-Tool-Mapping - X-AI-Auto-Decisions - X-AI-Failover-Occurred - X-AI-Selection-Confidence 18. Normative References Chen, et al. Expires 12 April 2026 [Page 42] Internet-Draft Multi-Provider Inference API October 2025 [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", RFC 2119, March 1997, . [RFC8174] Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC 2119 Key Words", RFC 8174, May 2017, . 19. Informative References [OPENAI-RESPONSES-API] OpenAI, "OpenAI Responses API Specification", 2025, . Acknowledgments The authors thank the OpenAI team for creating the foundational API standard that enables this ecosystem, and the broader AI community for adopting OpenAI-compatible interfaces that make multi-provider orchestration possible. Implementation Examples This document includes comprehensive implementation examples throughout the main sections demonstrating: - Auto-model selection with vendor-neutral routing (Section 4) - Auto-tool selection and provider mapping (Section 4) - Performance-based routing with latency and quality constraints (Section 6) - Security-aware provider selection for compliance (Section 7) - Multi-turn failover with persistent state tracking (Section 5) - Workflow branching and state inheritance patterns (Section 8) Each example includes complete HTTP/HTTPS request-response pairs showing both the standard OpenAI Responses API format and the optional multi-provider extension headers. The examples are designed to be hackathon-friendly and can be directly adapted for rapid prototyping and production deployment. Authors' Addresses Huamin Chen Red Hat Boston, MA 02210 United States of America Email: hchen@redhat.com Chen, et al. Expires 12 April 2026 [Page 43] Internet-Draft Multi-Provider Inference API October 2025 Luay Jalil Verizon Richardson, TX United States of America Email: luay.jalil@verizon.com Nabeel Cocker Red Hat New York, NY United States of America Email: ncocker@redhat.com Chen, et al. Expires 12 April 2026 [Page 44]