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TODO.md

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Import fixtures follow-up TODO

Failing new cases

  • openai-responses-function-call-output-input
  • openai-responses-image-attachments
  • openai-responses-image-generation-call
  • openai-responses-mixed-input-order
  • openai-responses-mixed-output-order
  • openai-responses-real-world-tool-loop
  • openai-responses-reasoning-blocks
  • openai-responses-reasoning-only-output
  • openai-responses-web-search

Work items

  • Loosen importer pre-check for Responses item arrays

    • Current gap: has_message_structure rejects arrays that do not have role or nested message.role.
    • Goal: allow Responses-only arrays (reasoning, function_call_output, web_search_call, etc.) to reach typed OpenAI conversion logic.
    • Acceptance: mixed/output-only Responses fixtures are not dropped at import pre-check.

  • Handle raw string span input as user messages

    • Current gap: string-valued span.input is ignored.
    • Goal: map string input to Message::User with string content.
    • Acceptance: string-input fixtures (for example image generation and web search) include the expected leading user message.

  • Expand lenient text-type parsing for content blocks

    • Current gap: lenient parser only accepts type: "text".
    • Goal: also accept OpenAI Responses block types input_text and output_text.
    • Acceptance: fixtures containing these block types parse into expected user/assistant text messages.

  • Add typed compatibility for callId aliasing

    • Current gap: some fixtures use callId while generated OpenAI types expect call_id.
    • Goal: normalize or alias callId at import boundary before typed conversion.
    • Acceptance: tool call and tool result linkage is preserved for both call_id and callId.

  • Add typed compatibility for function_call_result

    • Current gap: fixtures include type: "function_call_result" which is not represented in generated enums.
    • Goal: normalize this to the canonical supported shape before conversion, without raw fallback parsing.
    • Acceptance: output/input-order and tool-loop fixtures parse tool result messages correctly.

  • Add typed compatibility for non-string tool output payloads

    • Current gap: fixtures include object-valued output, while generated OpenAI types model output as string.
    • Goal: normalize object payloads to canonical representation for strict typed conversion.
    • Acceptance: function/tool-result fixtures preserve structured output content in imported tool messages.

  • Decide and implement reasoning message aggregation behavior

    • Current gap: reasoning output items become standalone assistant messages; some fixtures expect reasoning merged with adjacent assistant text.
    • Goal: define canonical import behavior for reasoning-plus-message sequences and implement consistently.
    • Acceptance: openai-responses-reasoning-blocks and openai-responses-reasoning-only-output match expected message counts and roles.

  • Re-run and verify fixture suite after each fix

    • Command: cargo test -p lingua --test import_fixtures -- --nocapture
    • Process: update one behavior at a time and confirm no regressions in previously passing fixtures.