[gtokman]

Resolves #360.

ToolExecutionDelegate.pendingMessages(in:) is asked after each round of tool calls, before the model's next request. Someone can steer a long response while it runs. The policy around it (an inbox, an acknowledgment, what interrupts the final text) stays in the app. The default adds nothing.

Following your notes on the issue:

• It returns [Prompt], so a message can carry images.
• Every provider whose tool loop continues after a round asks, through shared code. That's OpenAI (Chat Completions and Responses), Open Responses, Gemini, MLX and llama.cpp, plus Anthropic's and Ollama's streaming loops. Their nonstreaming responses make a single request. SystemLanguageModel doesn't ask, since Foundation Models runs its own tool loop, and the method's documentation says so.
• Steering doesn't reset the tool-round limit.
• Each message's transcript entry is built once and sent in the same form. The entry is built by pendingPrompts (Shared/PendingMessages.swift). Each provider sends it with the same conversion it replays a transcript's prompts with, pulled into one function where that was inline, as Replay OpenAI tool calls as plain, stable JSON #325 does for tool calls. A request made now and the replay of it on a later turn match, so a prompt cache still matches.
• Failure is documented. Once handed over, the messages are the response's. If it fails, they follow the session's transcriptErrorHandlingPolicy like its other entries, and they aren't handed back.
• Messages still pending when a response ends without another round stay with the app, to send as the next prompt.

Tests

• OpenAI, streaming and not: the message follows the tool output, is in the transcript as a prompt, and is byte-for-byte the same in flight and when the next turn replays it.
• OpenAI image: a message can carry an image.
• OpenAI round limit: steering doesn't reset it.
• Anthropic and Ollama: their streaming loops.
• Chat Completions, Responses, Open Responses and Gemini: one parameterized test.
• Not covered offline: MLX and llama.cpp build with their traits, but their steering paths need a local model to test.

The full suite has the same failures as main here: the 13 tests that need live services.

This touches some of the files #375 does, and the two branches merge cleanly in either order.

🤖 Generated with Claude Code

https://claude.ai/code/session_01B4WBsc1Jp8fGufe89MhQFB

[mattt]

Thanks, @gtokman. This follows what we discussed on #360, and returning [Prompt] works out nicely.

Two non-blocking notes:

• The description says the message is byte-for-byte the same in flight and on replay, but the test compares decoded dictionaries. Either is fine with me; the test and the description should just agree.
• The round-limit test could also check that the error's transcript entries include the steering prompt.