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Revert "fix: strip empty text content blocks in /v1/messages endpoint" #23232

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Merged
Sameerlite merged 1 commit into from
Mar 10, 2026
Merged

Revert "fix: strip empty text content blocks in /v1/messages endpoint" #23232

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60 changes: 0 additions & 60 deletions litellm/llms/custom_httpx/llm_http_handler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -152,59 +152,6 @@
LiteLLMLoggingObj = Any


def _sanitize_anthropic_messages_empty_text_blocks(
messages: List[Dict],
) -> List[Dict]:
"""
Strip empty text content blocks from Anthropic-format messages.

Claude's API returns assistant messages with ``{"type": "text", "text": ""}``
alongside ``tool_use`` blocks, but rejects them when sent back in subsequent
requests. This helper removes those empty text blocks so the /v1/messages
native path doesn't forward them as-is.

- If a content list contains a mix of empty text blocks and other blocks
(e.g. tool_use), the empty text blocks are removed.
- If *all* blocks in a content list are empty text, the content is replaced
with a single non-empty placeholder to avoid sending an empty array.

Ref: https://github.com/BerriAI/litellm/issues/22930
"""
sanitized: List[Dict] = []
for message in messages:
content = message.get("content")
if not isinstance(content, list):
sanitized.append(message)
continue

filtered = [
block
for block in content
if not (
isinstance(block, dict)
and block.get("type") == "text"
and not block.get("text", "").strip()
)
]

if filtered == content:
# Nothing was removed — keep original message as-is.
sanitized.append(message)
elif filtered:
# Some empty text blocks removed, but other content remains.
new_message = message.copy()
new_message["content"] = filtered
sanitized.append(new_message)
else:
# All blocks were empty text blocks. Replace with a placeholder
# so we don't send an empty content array.
new_message = message.copy()
new_message["content"] = [{"type": "text", "text": "..."}]
sanitized.append(new_message)

return sanitized


class BaseLLMHTTPHandler:
async def _make_common_async_call(
self,
Comment on lines 152 to 157

@greptile-apps greptile-apps Bot Mar 10, 2026

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Revert re-introduces issue #22930

This revert removes the fix for a confirmed production bug: when Claude returns assistant messages with {"type": "text", "text": ""} alongside tool_use blocks during multi-turn agentic conversations, forwarding those messages back to the API fails with a 400 "text content blocks must be non-empty" error.

The root cause of the test breakage was a narrow, trivially-fixable bug in the sanitization function itself. test_bad_request_error_handling_streaming passes messages=["hi"] (a list containing a bare string, not a dict). The function iterated over messages and called message.get("content"), which raises AttributeError on a string, crashing before the request reached Anthropic's API.

The correct minimal fix would have been a single isinstance guard:

for message in messages:
    if not isinstance(message, dict):
        sanitized.append(message)
        continue
    content = message.get("content")
    ...

A full revert is too broad — it undoes a valid fix and re-exposes all users doing multi-turn tool-use conversations via /v1/messages to the original 400-error regression.

Expand Down Expand Up @@ -1958,13 +1905,6 @@ async def async_anthropic_messages_handler(
anthropic_messages_optional_request_params, path
)

# Sanitize empty text content blocks from messages before forwarding.
# Claude's API returns assistant messages with empty text blocks
# ({"type": "text", "text": ""}) alongside tool_use blocks, but rejects
# them when sent back. Strip these to prevent 400 errors.
# Ref: https://github.com/BerriAI/litellm/issues/22930
messages = _sanitize_anthropic_messages_empty_text_blocks(messages)

# Prepare request body
request_body = anthropic_messages_provider_config.transform_anthropic_messages_request(
model=model,
Expand Down
247 changes: 0 additions & 247 deletions tests/test_litellm/llms/anthropic/test_v1_messages_empty_text_sanitization.py
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