OpenAI and OpenAI-compatible providers

OpenAIProvider talks to the OpenAI API (or an Azure OpenAI / Foundry resource through AzureOpenAIEndpoint, see deployments) with the Responses protocol by default, or Chat Completions with OpenAIApi.ChatCompletions. OpenAICompatibleProvider speaks Chat Completions to any server that implements it. Both implement chat, streaming, embeddings, token counting (OpenAI only) and the Batch API. Streaming and non-streaming calls build equal Messages.

What the Responses codec does

• Stateless. store: false is always sent (OpenAIOptions.Store changes it). For reasoning models include: reasoning.encrypted_content is added so reasoning items can be replayed on the next turn. Reasoning items are replayed verbatim from ReasoningPart.Data when their provider is openai; other providers' reasoning is dropped.
• Usage. InputTokens is the API's input_tokens minus cached and cache-write tokens, so the counters never overlap. Counters: cacheReadInputTokens, cacheCreationInputTokens, cacheCreation30mInputTokens and cacheCreation12hInputTokens (subsets of the cache-write counter), reasoningTokens (subset of output), toolCalls.<tool> (web_search, file_search, code_interpreter, image_generation, mcp) and image-generation token counters. The catalog declares the cache-write subsets with pricing.subsetOf.
• Tools. Function tools become function items; free-text "custom" tools are HostedToolDefinition("custom") and arrive as tool calls with {"input": text}. Hosted tools (web_search, file_search, code_interpreter, image_generation, mcp) come back as HostedToolCallPart; an output item the codec does not know is kept as a ProviderPart.
• Caching. The cache key goes to prompt_cache_key (64 characters at most). A TTL goes to prompt_cache_options.ttl (30m or 12h) on models whose catalog entry has the property promptCacheOptions, otherwise to prompt_cache_retention: "24h" for a TTL of an hour or more. Turning caching off cannot be asked of the API and is reported as a warning.
• Refused, not sent: stop sequences on Responses (use Chat Completions), reasoning efforts a model does not list, tools or structured output on models whose entry says no. Stripped with a warning: temperature/top_p on models that take none, reasoning settings on non-reasoning models, token budgets for reasoning.
• Warnings. RequestAdjuster runs once per request; its notices, plus the codec's own, are on ChatResponse.Warnings. Streaming and embeddings calls apply the same adjustments but have no channel for the notices yet.

Pricing in the shipped catalog

Service tiers are pricingMultipliers (flex 0.5, priority where the published ratio is clean), batch is the batch multiplier 0.5, and the long-context rate (above 272K input tokens) is a tier with multipliers. Web and file search calls are per-1000 items. Code-interpreter container sessions are not priced yet. Prices carry asOf 2026-11-05 and the pricing page as source.

Compatible-server presets

A preset supplies the base URL, the key's environment variable and the quirks recorded as catalog properties. Presets accept any model name. Presets for servers on the local machine (local: true) are priced at zero.

Base URLs come from each vendor's documentation. The quirks for Mistral and DeepSeek, the vLLM default port and reasoning-field names are recorded from the docs only partly and are to be checked against live servers; the recorded fixtures for the presets are written from the references, so they pin the request each preset sends and how its answers decode, not the server's behaviour.

Registering the catalog

OpenAICatalog.Register() adds the files to CatalogLoader's shipped list so a default catalog loads them; OpenAICatalog.Shipped() returns the layer directly for tests and custom catalogs.