fix(chatgpt): round-trip encrypted reasoning through /v1/messages

The chat bridge stored encrypted reasoning on reasoning_items, the Anthropic
adapter never read that field, stream chunks that only carried thinking
blocks were dropped, and the messages adapter stripped the signed blocks
before a chatgpt request could turn them back into reasoning items.

Co-authored-by: DDT <1786035110@qq.com>

litellm/completion_extras/litellm_responses_transformation/transformation.py

@@ -39,7 +39,7 @@ from litellm.litellm_core_utils.allowed_tools_tool_choice import (
     parse_chat_allowed_tools_tool_choice,
     responses_allowed_tools_tool_choice,
 )
-from litellm.litellm_core_utils.core_helpers import drops_unsupported_params
+from litellm.litellm_core_utils.core_helpers import as_str_mapping, drops_unsupported_params
 from litellm.litellm_core_utils.hidden_params import get_hidden_params, get_or_create_hidden_params
 from litellm.litellm_core_utils.prompt_templates.prompt_cache_breakpoint_utils import (
     prompt_cache_breakpoint_with_readable_mode,
@@ -48,6 +48,7 @@ from litellm.litellm_core_utils.prompt_templates.prompt_cache_breakpoint_utils i
 )
 from litellm.litellm_core_utils.prompt_templates.reasoning_utils import (
     responses_reasoning_items_from_thinking_blocks,
+    thinking_blocks_from_reasoning_items,
 )
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
 from litellm.llms.base_llm.bridges.completion_transformation import (
@@ -68,6 +69,8 @@ from litellm.responses.utils import (
 from litellm.types.llms.openai import (
     ChatCompletionAnnotation,
     ChatCompletionReasoningItem,
+    ChatCompletionRedactedThinkingBlock,
+    ChatCompletionThinkingBlock,
     ChatCompletionToolCallChunk,
     ChatCompletionToolCallFunctionChunk,
     ChatCompletionToolParamFunctionChunk,
@@ -76,7 +79,7 @@ from litellm.types.llms.openai import (
     ResponsesAPIResponse,
     ResponsesAPIStreamEvents,
 )
-from litellm.types.utils import GenericStreamingChunk, ModelResponseStream
+from litellm.types.utils import Delta, GenericStreamingChunk, ModelResponseStream, StreamingChoices
 
 if TYPE_CHECKING:
     from openai.types.responses import ResponseInputImageParam, ResponseOutputItem
@@ -481,6 +484,63 @@ def _as_chat_reasoning_items(
     return cast(list[ChatCompletionReasoningItem], list(reasoning_items))
 
 
+def _with_stream_block_index(
+    block: ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock,
+    index: int,
+) -> ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock:
+    if block["type"] == "redacted_thinking":
+        data: Final = block.get("data")
+        return ChatCompletionRedactedThinkingBlock(
+            type="redacted_thinking",
+            data=data if isinstance(data, str) else "",
+            index=index,
+        )
+    thinking: Final = block.get("thinking")
+    signature: Final = block.get("signature")
+    return ChatCompletionThinkingBlock(
+        type="thinking",
+        thinking=thinking if isinstance(thinking, str) else "",
+        signature=signature if isinstance(signature, str) else None,
+        index=index,
+    )
+
+
+def _reasoning_done_thinking_blocks(
+    item: Mapping[str, object],
+    output_index: object,
+) -> tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...]:
+    index: Final = output_index if isinstance(output_index, int) and not isinstance(output_index, bool) else 0
+    return tuple(_with_stream_block_index(block, index) for block in thinking_blocks_from_reasoning_items((item,)))
+
+
+def _reasoning_done_stream_chunk(chunk: Mapping[str, object]) -> ModelResponseStream | None:
+    event_type: Final = chunk.get("type")
+    event_name: Final = (
+        event_type.value
+        if isinstance(event_type, ResponsesAPIStreamEvents)
+        else event_type
+        if isinstance(event_type, str)
+        else None
+    )
+    if event_name != ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE:
+        return None
+    item: Final = as_str_mapping(chunk.get("item"))
+    if item is None or item.get("type") != "reasoning":
+        return None
+    signed_blocks: Final = _reasoning_done_thinking_blocks(item, chunk.get("output_index"))
+    if not signed_blocks:
+        return None
+    return ModelResponseStream(
+        choices=[
+            StreamingChoices(
+                index=0,
+                delta=Delta(thinking_blocks=list(signed_blocks)),
+                finish_reason=None,
+            )
+        ]
+    )
+
+
 def _shift_annotation(annotation: ChatCompletionAnnotation, offset: int) -> ChatCompletionAnnotation:
     shifted: Final = {
         key: value + offset if key in ("start_index", "end_index") and isinstance(value, int) else value
@@ -535,6 +595,7 @@ def _fold_choices_into_one(
         *chain.from_iterable(_message_reasoning_items(m) for m in messages),
         *trailing_reasoning_items,
     )
+    encrypted_thinking_blocks: Final = thinking_blocks_from_reasoning_items(reasoning_items)
     return Choices(
         message=Message(
             role=messages[0].role if messages else "assistant",
@@ -543,6 +604,7 @@ def _fold_choices_into_one(
             tool_calls=list(tool_calls) or None,
             reasoning_content=" ".join(value for value in reasoning_contents if value) or None,
             reasoning_items=_as_chat_reasoning_items(reasoning_items),
+            thinking_blocks=list(encrypted_thinking_blocks) or None,
             provider_specific_fields=_tool_search_provider_fields(tool_search_items),
         ),
         finish_reason="tool_calls" if tool_calls else "stop",
@@ -1436,10 +1498,12 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
             for summary_block in reasoning_item["summary"]
             if summary_block.get("text")
         )
+        encrypted_thinking_blocks: Final = thinking_blocks_from_reasoning_items(reasoning_items)
         message: Final = Message(
             content=None if tool_search_items else "",
             reasoning_content=reasoning_content if reasoning_content else None,
             reasoning_items=_as_chat_reasoning_items(reasoning_items),
+            thinking_blocks=list(encrypted_thinking_blocks) or None,
             provider_specific_fields=_tool_search_provider_fields(tool_search_items),
         )
         return Choices(message=message, finish_reason=finish_reason, index=0)
@@ -2248,7 +2312,6 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
                         )
                     ]
                 )
-
         elif event_type == "response.output_text.delta":
             # Content part added to output
             content_part = parsed_chunk.get("delta", None)
@@ -2365,9 +2428,12 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator):
         """
         verbose_logger.debug("Chat provider: transform_streaming_response called with chunk: %s", chunk)
         self._remember_served_service_tier(chunk)
+        reasoning_chunk: Final = _reasoning_done_stream_chunk(chunk)
         translated: Final = (
             self._empty_content_chunk()
             if self._is_text_delta_after_structured_answer(chunk)
+            else reasoning_chunk
+            if reasoning_chunk is not None
             else OpenAiResponsesToChatCompletionStreamIterator.translate_responses_chunk_to_openai_stream(
                 chunk,
                 tool_call_index_map=self._tool_call_index_map,

litellm/litellm_core_utils/prompt_templates/reasoning_utils.py

@@ -5,6 +5,7 @@ from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence
 from itertools import groupby
 from typing import Final, cast  # noqa: TID251  # Existing casts retained unchanged in this pure move
 
+from litellm.litellm_core_utils.core_helpers import as_str_mapping
 from litellm.types.llms.openai import (
     ChatCompletionReasoningItem,
     ChatCompletionReasoningSummaryTextBlock,
@@ -94,6 +95,87 @@ def encrypted_content_of_block(block: Mapping[str, object]) -> str | None:
     return encrypted_content_from_signature(_encrypted_reasoning_field(block))
 
 
+_REASONING_SUMMARY_SEPARATOR: Final = "\n\n"
+
+
+def _object_sequence(value: object) -> tuple[object, ...]:
+    if not isinstance(value, Sequence) or isinstance(value, (str, bytes)):
+        return ()
+    return tuple(value)
+
+
+def _iter_mappings(value: object) -> tuple[Mapping[str, object], ...]:
+    return tuple(mapping for item in _object_sequence(value) if (mapping := as_str_mapping(item)) is not None)
+
+
+def _reasoning_summary_part_text(part: object) -> str:
+    mapping: Final = as_str_mapping(part)
+    if mapping is not None:
+        text: Final = mapping.get("text")
+        return text if isinstance(text, str) else ""
+    text_attr: Final = getattr(part, "text", None)
+    return text_attr if isinstance(text_attr, str) else ""
+
+
+def _reasoning_item_summary_text(item: Mapping[str, object]) -> str:
+    parts: Final = tuple(_reasoning_summary_part_text(part) for part in _object_sequence(item.get("summary")))
+    return _REASONING_SUMMARY_SEPARATOR.join(part for part in parts if part)
+
+
+def thinking_block_from_reasoning_item(
+    item: object,
+) -> ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock | None:
+    """The chat thinking block that carries one Responses `reasoning` item back to an Anthropic client.
+
+    `encrypted_content` rides the same `litellm_encrypted_reasoning:` signature the Responses
+    adapter uses. A summary becomes thinking text. Bytes with no summary become `redacted_thinking`,
+    because an empty thinking string is not something the client can replay.
+    """
+    mapping: Final = as_str_mapping(item)
+    if mapping is None or mapping.get("type") not in (None, "reasoning"):
+        return None
+    encrypted_content: Final = mapping.get("encrypted_content")
+    if not isinstance(encrypted_content, str) or not encrypted_content:
+        return None
+    signature: Final = encrypted_reasoning_signature(encrypted_content)
+    text: Final = _reasoning_item_summary_text(mapping)
+    if not text:
+        return ChatCompletionRedactedThinkingBlock(type="redacted_thinking", data=signature)
+    return ChatCompletionThinkingBlock(type="thinking", thinking=text, signature=signature)
+
+
+def thinking_blocks_from_reasoning_items(
+    items: object,
+) -> tuple[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock, ...]:
+    return tuple(
+        block for item in _object_sequence(items) if (block := thinking_block_from_reasoning_item(item)) is not None
+    )
+
+
+def _block_encrypted_content(block: object) -> str | None:
+    mapping: Final = as_str_mapping(block)
+    if mapping is None:
+        return None
+    return encrypted_content_of_block(mapping)
+
+
+def thinking_blocks_with_encrypted_reasoning(
+    thinking_blocks: object,
+    reasoning_items: object,
+) -> tuple[Mapping[str, object], ...]:
+    """Thinking blocks already on the message, plus any encrypted reasoning item they do not already carry."""
+    direct: Final = _iter_mappings(thinking_blocks)
+    represented: Final = frozenset(
+        content for block in direct if (content := _block_encrypted_content(block)) is not None
+    )
+    extra: Final = tuple(
+        block
+        for block in thinking_blocks_from_reasoning_items(_iter_mappings(reasoning_items))
+        if _block_encrypted_content(block) not in represented
+    )
+    return (*extra, *direct)
+
+
 def is_encrypted_reasoning_block(block: object) -> bool:
     """A thinking or redacted_thinking block carrying Responses API encrypted reasoning.
 

litellm/litellm_core_utils/streaming_handler.py

@@ -1129,6 +1129,7 @@ class CustomStreamWrapper:
                 and model_response.choices[0].delta.role is not None
             )
             or (getattr(model_response.choices[0].delta, "reasoning_items", None) is not None)
+            or getattr(model_response.choices[0].delta, "thinking_blocks", None)
         ):
             return True
         else:

litellm/llms/anthropic/messages/adapters/streaming_iterator.py

@@ -27,8 +27,9 @@ import litellm
 from litellm._logging import verbose_logger
 from litellm._uuid import uuid
 from litellm.exceptions import ContextWindowExceededError, MidStreamFallbackError
-from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_items
+from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_items, attribute_or_none
 from litellm.litellm_core_utils.hidden_params import set_hidden_params
+from litellm.litellm_core_utils.prompt_templates.reasoning_utils import thinking_blocks_from_reasoning_items
 from litellm.llms.anthropic.messages.safeguards import StreamedSafeguardResults
 from litellm.llms.anthropic.messages.utils import anthropic_sse_frame
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
@@ -92,6 +93,10 @@ def _optional_attr(obj: object, name: str) -> object:
     return getattr(obj, name, None)
 
 
+def _delta_has_encrypted_reasoning(delta: object) -> bool:
+    return bool(thinking_blocks_from_reasoning_items(attribute_or_none(delta, "reasoning_items")))
+
+
 def _optional_attr_sequence(obj: object, name: str) -> Sequence[object]:
     value: Final = getattr(obj, name, None)
     return value if value else ()
@@ -1518,6 +1523,8 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper):
             for b in attribute_items(delta, "thinking_blocks")
         ):
             return False
+        if _delta_has_encrypted_reasoning(delta):
+            return False
         return True
 
     def _record_anthropic_stop_fields(self, delta: object) -> None:

litellm/llms/anthropic/messages/adapters/transformation.py

@@ -133,6 +133,7 @@ from litellm.litellm_core_utils.prompt_templates.prompt_cache_breakpoint_utils i
 )
 from litellm.litellm_core_utils.prompt_templates.reasoning_utils import (
     reasoning_content_from_thinking_blocks,
+    thinking_blocks_with_encrypted_reasoning,
 )
 from litellm.litellm_core_utils.prompt_templates.tool_call_json_repair import (
     parse_tool_call_arguments,
@@ -237,6 +238,19 @@ def target_supports_mid_conversation_system(model: str | None, custom_llm_provid
     return supports_mid_conversation_system(model=model, custom_llm_provider=custom_llm_provider)
 
 
+def _keeps_encrypted_reasoning_for_responses(model: str | None, custom_llm_provider: str | None) -> bool:
+    from litellm.responses.bridge_check import chat_completion_ends_in_responses_api
+
+    return chat_completion_ends_in_responses_api(model, custom_llm_provider)
+
+
+def _anthropic_thinking_blocks(source: object) -> tuple[Mapping[str, object], ...]:
+    return thinking_blocks_with_encrypted_reasoning(
+        getattr(source, "thinking_blocks", None),
+        getattr(source, "reasoning_items", None),
+    )
+
+
 def _chat_tool_param(function_chunk: ChatCompletionToolParamFunctionChunk, tool: object) -> ChatCompletionToolParam:
     eager_input_streaming: Final = eager_input_streaming_flag(tool)
     if eager_input_streaming is None:
@@ -505,7 +519,11 @@ class LiteLLMAnthropicMessagesAdapter:
         preserve_midturn_system: bool = False,
     ) -> list[AllMessageValues]:
         new_messages: Final[list[AllMessageValues]] = []
-        replayable_messages: Final = strip_encrypted_reasoning_blocks_from_anthropic_messages(messages)
+        replayable_messages: Final = (
+            messages
+            if _keeps_encrypted_reasoning_for_responses(model, custom_llm_provider)
+            else strip_encrypted_reasoning_blocks_from_anthropic_messages(messages)
+        )
         leading_count: Final = next(
             (i for i, m in enumerate(replayable_messages) if not is_system_role_message(m)),
             len(replayable_messages),
@@ -1443,9 +1461,9 @@ class LiteLLMAnthropicMessagesAdapter:
             for choice in choices
         ):
             new_content.extend(dict(_COMPACTION_BLOCK.validate_python(block)) for block in compaction_blocks)
-            # Handle thinking blocks first
-            if hasattr(choice.message, "thinking_blocks") and choice.message.thinking_blocks:
-                for thinking_block in choice.message.thinking_blocks:
+            signed_thinking_blocks = _anthropic_thinking_blocks(choice.message)
+            if signed_thinking_blocks:
+                for thinking_block in signed_thinking_blocks:
                     if thinking_block.get("type") == "thinking":
                         if is_empty_unsigned_thinking_block(thinking_block):
                             continue
@@ -1756,24 +1774,24 @@ class LiteLLMAnthropicMessagesAdapter:
                 choice.delta
             ) is not None:
                 return "text", TextBlock(type="text", text="")
-            elif isinstance(choice, StreamingChoices) and hasattr(choice.delta, "thinking_blocks"):
-                thinking_blocks = choice.delta.thinking_blocks or []
-                if len(thinking_blocks) > 0:
-                    thinking_block = thinking_blocks[0]
-                    if thinking_block["type"] == "redacted_thinking":
-                        return "redacted_thinking", ChatCompletionRedactedThinkingBlock(
-                            type="redacted_thinking", data=thinking_block.get("data") or ""
-                        )
-                    if thinking_block["type"] == "thinking":
-                        thinking = thinking_block.get("thinking") or ""
-                        signature = thinking_block.get("signature") or ""
+            elif isinstance(choice, StreamingChoices) and (thinking_blocks := _anthropic_thinking_blocks(choice.delta)):
+                thinking_block = thinking_blocks[0]
+                if thinking_block["type"] == "redacted_thinking":
+                    redacted_data = thinking_block.get("data")
+                    return "redacted_thinking", ChatCompletionRedactedThinkingBlock(
+                        type="redacted_thinking",
+                        data=redacted_data if isinstance(redacted_data, str) else "",
+                    )
+                if thinking_block["type"] == "thinking":
+                    thinking = thinking_block.get("thinking") or ""
+                    signature = thinking_block.get("signature") or ""
 
-                        assert isinstance(thinking, str)
-                        assert isinstance(signature, str)
+                    assert isinstance(thinking, str)
+                    assert isinstance(signature, str)
 
-                        return "thinking", ChatCompletionThinkingBlock(
-                            type="thinking", thinking=thinking if signature else "", signature=signature
-                        )
+                    return "thinking", ChatCompletionThinkingBlock(
+                        type="thinking", thinking=thinking if signature else "", signature=signature
+                    )
             # OpenAI-compatible reasoning backends (e.g. vLLM/SGLang reasoning
             # parsers) populate ``reasoning_content`` without ``thinking_blocks``.
             # ``Delta`` deletes the ``thinking_blocks`` attribute when unset, so the
@@ -1806,19 +1824,17 @@ class LiteLLMAnthropicMessagesAdapter:
                 for tool in choice.delta.tool_calls:
                     if tool.function is not None and tool.function.arguments is not None:
                         partial_json = (partial_json or "") + tool.function.arguments
-            elif isinstance(choice, StreamingChoices) and hasattr(choice.delta, "thinking_blocks"):
-                thinking_blocks = choice.delta.thinking_blocks or []
-                if len(thinking_blocks) > 0:
-                    for thinking_block in thinking_blocks:
-                        if thinking_block["type"] == "thinking":
-                            thinking = thinking_block.get("thinking") or ""
-                            signature = thinking_block.get("signature") or ""
+            elif isinstance(choice, StreamingChoices) and (thinking_blocks := _anthropic_thinking_blocks(choice.delta)):
+                for thinking_block in thinking_blocks:
+                    if thinking_block["type"] == "thinking":
+                        thinking = thinking_block.get("thinking") or ""
+                        signature = thinking_block.get("signature") or ""
 
-                            assert isinstance(thinking, str)
-                            assert isinstance(signature, str)
+                        assert isinstance(thinking, str)
+                        assert isinstance(signature, str)
 
-                            reasoning_content += thinking
-                            reasoning_signature += signature
+                        reasoning_content += thinking
+                        reasoning_signature += signature
             # Handle reasoning_content when thinking_blocks is not present
             # This handles providers like OpenRouter that return reasoning_content
             elif isinstance(choice, StreamingChoices) and hasattr(choice.delta, "reasoning_content"):

litellm/responses/bridge_check.py

@@ -4,7 +4,10 @@ from urllib.parse import urlsplit
 
 import litellm
 from litellm._logging import verbose_logger
-from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider
+from litellm.litellm_core_utils.get_llm_provider_logic import (
+    get_llm_provider,
+    resolve_model_and_provider_for_metadata,
+)
 from litellm.llms.azure_ai.chat.transformation import AzureAIGPT5Config
 from litellm.llms.azure_ai.common_utils import (
     azure_ai_supports_native_responses,
@@ -291,3 +294,23 @@ def responses_api_bridge_check(
         model = model.replace("responses/", "")
 
     return model_info, model
+
+
+def chat_completion_ends_in_responses_api(model: str | None, custom_llm_provider: str | None) -> bool:
+    """Whether chat completion for this model is served by a Responses API.
+
+    Encrypted reasoning can be replayed only there. A normal chat provider cannot
+    verify the block, so the messages adapter strips it. ``chatgpt`` and a
+    ``responses/`` model keep it.
+    """
+    if model is None and custom_llm_provider is None:
+        return False
+    try:
+        resolved_model, provider = resolve_model_and_provider_for_metadata(model or "", custom_llm_provider)
+    except Exception as error:  # noqa: BLE001  # unknown model names must not fail message translation
+        verbose_logger.debug("responses replay check failed for %s: %s", model, error)
+        return custom_llm_provider == LlmProviders.CHATGPT.value or (
+            isinstance(model, str) and (model == "chatgpt" or model.startswith("chatgpt/"))
+        )
+    model_info, _resolved = responses_api_bridge_check(model=resolved_model, custom_llm_provider=provider)
+    return model_info.get("mode") == "responses"

tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py

@@ -3837,6 +3837,165 @@ def test_reasoning_items_streaming_emitted_on_response_completed():
     assert ri["summary"][0]["text"] == summary_text
 
 
+def test_reasoning_output_item_done_emits_signed_thinking_blocks_the_stream_keeps():
+    """A chatgpt /v1/messages stream drops the reasoning item unless this delta carries thinking_blocks.
+
+    response.output_item.done is the only event that has encrypted_content. The chat delta has to
+    expose it as a signed thinking block, and that block alone has to count as stream content.
+    """
+    from unittest.mock import MagicMock
+
+    from litellm.completion_extras.litellm_responses_transformation.transformation import (
+        OpenAiResponsesToChatCompletionStreamIterator,
+    )
+    from litellm.litellm_core_utils.prompt_templates.common_utils import encrypted_reasoning_signature
+    from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper
+    from litellm.llms.anthropic.messages.adapters.transformation import LiteLLMAnthropicMessagesAdapter
+
+    encrypted: Final = "gAAAA_round_trip"
+    done: Final = {
+        "type": "response.output_item.done",
+        "output_index": 0,
+        "item": {
+            "type": "reasoning",
+            "id": "rs_done",
+            "encrypted_content": encrypted,
+            "summary": [],
+        },
+    }
+    result: Final = OpenAiResponsesToChatCompletionStreamIterator(
+        streaming_response=None, sync_stream=True
+    ).chunk_parser(done)
+    blocks: Final = result.choices[0].delta.thinking_blocks
+    assert blocks is not None
+    assert blocks[0]["type"] == "redacted_thinking"
+    assert blocks[0]["data"] == encrypted_reasoning_signature(encrypted)
+    assert blocks[0]["index"] == 0
+    assert getattr(result.choices[0].delta, "reasoning_content", None) in (None, "")
+
+    wrapper: Final = CustomStreamWrapper(
+        completion_stream=None,
+        model="chatgpt/gpt-6.1-sol",
+        logging_obj=MagicMock(),
+        custom_llm_provider="chatgpt",
+    )
+    assert wrapper.is_chunk_non_empty({}, result, {}) is True
+
+    block_type, start = LiteLLMAnthropicMessagesAdapter().translate_streaming_openai_chunk_to_anthropic_content_block(
+        choices=result.choices
+    )
+    assert block_type == "redacted_thinking"
+    assert start["data"] == encrypted_reasoning_signature(encrypted)
+
+
+def test_reasoning_output_item_done_with_summary_signs_the_thinking_text():
+    from litellm.completion_extras.litellm_responses_transformation.transformation import (
+        OpenAiResponsesToChatCompletionStreamIterator,
+    )
+    from litellm.litellm_core_utils.prompt_templates.common_utils import encrypted_reasoning_signature
+
+    encrypted: Final = "gAAAA_with_summary"
+    done: Final = {
+        "type": "response.output_item.done",
+        "output_index": 2,
+        "item": {
+            "type": "reasoning",
+            "id": "rs_sum",
+            "encrypted_content": encrypted,
+            "summary": [{"type": "summary_text", "text": "Oslo is colder."}],
+        },
+    }
+    result: Final = OpenAiResponsesToChatCompletionStreamIterator(
+        streaming_response=None, sync_stream=True
+    ).chunk_parser(done)
+    block: Final = result.choices[0].delta.thinking_blocks[0]
+    assert block["type"] == "thinking"
+    assert block["thinking"] == "Oslo is colder."
+    assert block["signature"] == encrypted_reasoning_signature(encrypted)
+    assert block["index"] == 2
+
+
+def test_reasoning_output_item_done_without_encrypted_content_stays_empty():
+    from litellm.completion_extras.litellm_responses_transformation.transformation import (
+        OpenAiResponsesToChatCompletionStreamIterator,
+    )
+
+    done: Final = {
+        "type": "response.output_item.done",
+        "output_index": 0,
+        "item": {
+            "type": "reasoning",
+            "id": "rs_plain",
+            "summary": [{"type": "summary_text", "text": "already streamed"}],
+        },
+    }
+    result: Final = OpenAiResponsesToChatCompletionStreamIterator(
+        streaming_response=None, sync_stream=True
+    ).chunk_parser(done)
+    assert getattr(result.choices[0].delta, "thinking_blocks", None) in (None, [])
+
+
+def test_transform_response_copies_encrypted_reasoning_onto_thinking_blocks():
+    from unittest.mock import Mock
+
+    from litellm.litellm_core_utils.prompt_templates.common_utils import encrypted_reasoning_signature
+    from litellm.types.llms.openai import ResponsesAPIResponse
+    from litellm.types.utils import ModelResponse, Usage
+
+    encrypted: Final = "gAAAA_non_stream"
+    reasoning: Final = ResponseReasoningItem(
+        id="rs_tool",
+        summary=[],
+        type="reasoning",
+        content=None,
+        encrypted_content=encrypted,
+        status=None,
+    )
+    function_call: Final = ResponseFunctionToolCall(
+        id="fc_1",
+        type="function_call",
+        status="completed",
+        arguments='{"city":"Oslo"}',
+        call_id="call_1",
+        name="get_weather",
+    )
+    raw: Final = ResponsesAPIResponse.model_construct(
+        id="resp_tool",
+        created_at=1,
+        error=None,
+        incomplete_details=None,
+        model="gpt-6.1-sol",
+        output=[reasoning, function_call],
+        status="completed",
+        usage=None,
+    )
+    model_response: Final = ModelResponse(
+        id="chatcmpl-tool",
+        created=1,
+        model=None,
+        object="chat.completion",
+        system_fingerprint=None,
+        choices=[],
+        usage=Usage(completion_tokens=0, prompt_tokens=0, total_tokens=0),
+    )
+    result: Final = LiteLLMResponsesTransformationHandler().transform_response(
+        model="gpt-6.1-sol",
+        raw_response=raw,
+        model_response=model_response,
+        logging_obj=Mock(),
+        request_data={"model": "gpt-6.1-sol"},
+        messages=[{"role": "user", "content": "Which city?"}],
+        optional_params={},
+        litellm_params={},
+        encoding=Mock(),
+    )
+    message: Final = result.choices[0].message
+    assert message.reasoning_items[0]["encrypted_content"] == encrypted
+    assert message.thinking_blocks[0]["type"] == "redacted_thinking"
+    assert message.thinking_blocks[0]["data"] == encrypted_reasoning_signature(encrypted)
+    assert message.tool_calls[0].function.name == "get_weather"
+
+
 def test_streaming_function_call_tool_id_for_degenerate_call_id():
     """In streaming, Bedrock Mantle's function_call event carries a unique ``id``
     (``fc_...``) and a non-unique, index-based ``call_id`` (``call_0``). For that

tests/unit/litellm_core_utils/test_streaming_handler.py

@@ -276,6 +276,37 @@ def test_is_chunk_non_empty(initialized_custom_stream_wrapper: CustomStreamWrapp
     )
 
 
+def test_is_chunk_non_empty_keeps_thinking_blocks_without_other_content(
+    initialized_custom_stream_wrapper: CustomStreamWrapper,
+):
+    """Encrypted reasoning arrives as thinking_blocks and nothing else, so that delta has to be yielded."""
+    chunk: Final = ModelResponseStream(
+        id="chunk-thinking",
+        object="chat.completion.chunk",
+        created=1,
+        model="chatgpt/gpt-6.1-sol",
+        choices=[
+            StreamingChoices(
+                index=0,
+                finish_reason=None,
+                delta=Delta(
+                    thinking_blocks=[
+                        {"type": "redacted_thinking", "data": "litellm_encrypted_reasoning:gAAAA"}
+                    ]
+                ),
+            )
+        ],
+    )
+    assert (
+        initialized_custom_stream_wrapper.is_chunk_non_empty(
+            completion_obj={},
+            model_response=chunk,
+            response_obj={},
+        )
+        is True
+    )
+
+
 def test_is_chunk_non_empty_with_annotations(
     initialized_custom_stream_wrapper: CustomStreamWrapper,
 ):

tests/unit/llms/anthropic/messages/adapters/test_anthropic_messages_adapters_transformation.py

@@ -563,6 +563,166 @@ def test_translate_anthropic_messages_to_openai_drops_bridge_encrypted_reasoning
     assert [b["signature"] for b in result[2]["thinking_blocks"]] == ["EqQBCkYIAxgCIkA_signed"]
 
 
+def test_chatgpt_messages_keep_encrypted_reasoning_and_replay_it():
+    """chatgpt /v1/messages ends in the Responses API, so the signed block has to survive into the next request."""
+    from litellm.completion_extras.litellm_responses_transformation.transformation import (
+        LiteLLMResponsesTransformationHandler,
+    )
+
+    summary_encrypted: Final = "gAAAA_summary"
+    bytes_encrypted: Final = "gAAAA_bytes"
+    messages: Final = [
+        AnthropicMessagesUserMessageParam(role="user", content="Which city is colder?"),
+        AnthopicMessagesAssistantMessageParam(
+            role="assistant",
+            content=[
+                {
+                    "type": "thinking",
+                    "thinking": "Oslo is colder.",
+                    "signature": encrypted_reasoning_signature(summary_encrypted),
+                },
+                {"type": "redacted_thinking", "data": encrypted_reasoning_signature(bytes_encrypted)},
+                {"type": "tool_use", "id": "call_1", "name": "get_weather", "input": {"city": "Oslo"}},
+            ],
+        ),
+        AnthropicMessagesUserMessageParam(
+            role="user",
+            content=[{"type": "tool_result", "tool_use_id": "call_1", "content": "-7 C"}],
+        ),
+    ]
+
+    kept: Final = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai(
+        messages=messages,
+        model="chatgpt/gpt-6.1-sol",
+        custom_llm_provider="chatgpt",
+    )
+    assistant: Final = kept[1]
+    assert [block["type"] for block in assistant["thinking_blocks"]] == ["thinking", "redacted_thinking"]
+    assert assistant["thinking_blocks"][0]["signature"] == encrypted_reasoning_signature(summary_encrypted)
+    assert assistant["thinking_blocks"][1]["data"] == encrypted_reasoning_signature(bytes_encrypted)
+
+    responses_input, _instructions = LiteLLMResponsesTransformationHandler().convert_chat_completion_messages_to_responses_api(
+        kept
+    )
+    reasoning: Final = tuple(item for item in responses_input if item.get("type") == "reasoning")
+    assert [item["encrypted_content"] for item in reasoning] == [summary_encrypted, bytes_encrypted]
+    types: Final = [item.get("type") for item in responses_input]
+    assert types.index("reasoning") < types.index("function_call")
+
+    stripped: Final = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai(
+        messages=messages,
+        model="gpt-4o",
+        custom_llm_provider="openai",
+    )
+    assert not stripped[1].get("thinking_blocks")
+
+    prefixed: Final = LiteLLMAnthropicMessagesAdapter().translate_anthropic_messages_to_openai(
+        messages=messages,
+        model="responses/gpt-5-mini",
+        custom_llm_provider="openai",
+    )
+    assert prefixed[1]["thinking_blocks"][1]["data"] == encrypted_reasoning_signature(bytes_encrypted)
+
+
+def test_translate_openai_reasoning_items_become_signed_thinking_blocks():
+    encrypted: Final = "gAAAA_outbound"
+    openai_choices: Final = [
+        Choices(
+            message=Message(
+                role="assistant",
+                content="Oslo.",
+                reasoning_items=[
+                    {
+                        "type": "reasoning",
+                        "id": "rs_1",
+                        "encrypted_content": encrypted,
+                        "summary": [{"type": "summary_text", "text": "Oslo is colder."}],
+                    }
+                ],
+                tool_calls=[
+                    ChatCompletionAssistantToolCall(
+                        id="call_1",
+                        type="function",
+                        function=Function(name="get_weather", arguments='{"city": "Oslo"}'),
+                    )
+                ],
+            )
+        )
+    ]
+
+    result: Final = LiteLLMAnthropicMessagesAdapter()._translate_openai_content_to_anthropic(choices=openai_choices)
+
+    assert result[0]["type"] == "thinking"
+    assert result[0]["thinking"] == "Oslo is colder."
+    assert result[0]["signature"] == encrypted_reasoning_signature(encrypted)
+    assert result[1]["type"] == "text"
+    assert result[2]["type"] == "tool_use"
+
+
+def test_translate_openai_reasoning_items_without_summary_become_redacted_thinking():
+    encrypted: Final = "gAAAA_bytes_only"
+    openai_choices: Final = [
+        Choices(
+            message=Message(
+                role="assistant",
+                content=None,
+                reasoning_items=[
+                    {"type": "reasoning", "id": "rs_1", "encrypted_content": encrypted, "summary": []}
+                ],
+            )
+        )
+    ]
+
+    result: Final = LiteLLMAnthropicMessagesAdapter()._translate_openai_content_to_anthropic(choices=openai_choices)
+
+    assert result == [
+        {"type": "redacted_thinking", "data": encrypted_reasoning_signature(encrypted)},
+    ]
+
+
+def test_translate_openai_reasoning_items_are_not_duplicated_when_thinking_blocks_already_carry_them():
+    encrypted: Final = "gAAAA_once"
+    signature: Final = encrypted_reasoning_signature(encrypted)
+    openai_choices: Final = [
+        Choices(
+            message=Message(
+                role="assistant",
+                content="Oslo.",
+                thinking_blocks=[{"type": "redacted_thinking", "data": signature}],
+                reasoning_items=[
+                    {"type": "reasoning", "id": "rs_1", "encrypted_content": encrypted, "summary": []}
+                ],
+            )
+        )
+    ]
+
+    result: Final = LiteLLMAnthropicMessagesAdapter()._translate_openai_content_to_anthropic(choices=openai_choices)
+
+    assert [block["type"] for block in result] == ["redacted_thinking", "text"]
+
+
+def test_streaming_chunk_with_only_reasoning_items_opens_a_signed_thinking_block():
+    encrypted: Final = "gAAAA_delta"
+    choices: Final = [
+        StreamingChoices(
+            finish_reason=None,
+            index=0,
+            delta=Delta(
+                reasoning_items=[
+                    {"type": "reasoning", "id": "rs_1", "encrypted_content": encrypted, "summary": []}
+                ]
+            ),
+        )
+    ]
+
+    block_type, start = LiteLLMAnthropicMessagesAdapter().translate_streaming_openai_chunk_to_anthropic_content_block(
+        choices=choices
+    )
+
+    assert block_type == "redacted_thinking"
+    assert start["data"] == encrypted_reasoning_signature(encrypted)
+
+
 def test_translate_anthropic_messages_to_openai_sets_reasoning_content():
     """Reasoning-aware chat providers read reasoning_content, so thinking text must land there.