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This commit is contained in:
Timothy Jaeryang Baek
2026-07-27 03:01:19 -04:00
parent 44f4f9dce4
commit 4c2d864b3f
1 changed files with 65 additions and 33 deletions
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backend/open_webui/utils/anthropic.py
+65 -33
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@@ -544,19 +544,37 @@ def convert_openai_to_anthropic_response(
)
# Usage
openai_usage = openai_response.get('usage', {})
openai_usage = openai_response.get('usage') or {}
cache_creation = openai_usage.get('cache_creation_input_tokens')
cache_read = openai_usage.get('cache_read_input_tokens')
prompt_details = openai_usage.get('prompt_tokens_details')
if cache_read is None and isinstance(prompt_details, dict):
cache_read = prompt_details.get('cached_tokens')
usage_input = openai_usage.get('input_tokens')
if usage_input is None:
prompt_tokens = openai_usage.get('prompt_tokens')
if prompt_tokens is not None:
usage_input = max(prompt_tokens - (cache_creation or 0) - (cache_read or 0), 0)
usage_output = openai_usage.get('output_tokens')
if usage_output is None:
usage_output = openai_usage.get('completion_tokens')
usage = {
'input_tokens': (
input_tokens
if input_tokens is not None
else openai_usage.get('input_tokens', openai_usage.get('prompt_tokens', 0))
),
'output_tokens': openai_usage.get('output_tokens', openai_usage.get('completion_tokens', 0)),
'input_tokens': usage_input if usage_input is not None else (input_tokens if input_tokens is not None else 0),
'output_tokens': usage_output if usage_output is not None else 0,
}
if 'cache_creation_input_tokens' in openai_usage:
usage['cache_creation_input_tokens'] = openai_usage['cache_creation_input_tokens']
if 'cache_read_input_tokens' in openai_usage:
usage['cache_read_input_tokens'] = openai_usage['cache_read_input_tokens']
if cache_creation is not None:
usage['cache_creation_input_tokens'] = cache_creation
if cache_read is not None:
usage['cache_read_input_tokens'] = cache_read
if isinstance(openai_usage.get('output_tokens_details'), dict):
usage['output_tokens_details'] = openai_usage['output_tokens_details']
if isinstance(openai_usage.get('server_tool_use'), dict):
usage['server_tool_use'] = openai_usage['server_tool_use']
if openai_usage.get('service_tier') is not None:
usage['service_tier'] = openai_usage['service_tier']
return {
'id': openai_response.get('id', f'msg_{_uuid.uuid4().hex[:24]}'),
@@ -592,23 +610,9 @@ async def openai_stream_to_anthropic_stream(openai_stream_generator, model: str
cache_read_input_tokens = None
output_tokens_details = None
server_tool_use = None
service_tier = None
stop_reason = 'end_turn'
def update_usage(usage_data: dict):
nonlocal input_tokens
nonlocal output_tokens
nonlocal cache_creation_input_tokens
nonlocal cache_read_input_tokens
nonlocal output_tokens_details
nonlocal server_tool_use
input_tokens = usage_data.get('input_tokens', usage_data.get('prompt_tokens', input_tokens))
output_tokens = usage_data.get('output_tokens', usage_data.get('completion_tokens', output_tokens))
cache_creation_input_tokens = usage_data.get('cache_creation_input_tokens', cache_creation_input_tokens)
cache_read_input_tokens = usage_data.get('cache_read_input_tokens', cache_read_input_tokens)
output_tokens_details = usage_data.get('output_tokens_details', output_tokens_details)
server_tool_use = usage_data.get('server_tool_use', server_tool_use)
# Track content blocks with a running index.
# Each text block or tool_use block gets its own index.
current_block_index = 0
@@ -663,21 +667,47 @@ async def openai_stream_to_anthropic_stream(openai_stream_generator, model: str
except (json.JSONDecodeError, TypeError):
continue
usage_data = data.get('usage')
if isinstance(usage_data, dict):
cache_creation = usage_data.get('cache_creation_input_tokens')
cache_read = usage_data.get('cache_read_input_tokens')
prompt_details = usage_data.get('prompt_tokens_details')
if cache_read is None and isinstance(prompt_details, dict):
cache_read = prompt_details.get('cached_tokens')
usage_input = usage_data.get('input_tokens')
if usage_input is None:
prompt_tokens = usage_data.get('prompt_tokens')
if prompt_tokens is not None:
usage_input = max(prompt_tokens - (cache_creation or 0) - (cache_read or 0), 0)
usage_output = usage_data.get('output_tokens')
if usage_output is None:
usage_output = usage_data.get('completion_tokens')
if usage_input is not None:
input_tokens = usage_input
if usage_output is not None:
output_tokens = usage_output
if cache_creation is not None:
cache_creation_input_tokens = cache_creation
if cache_read is not None:
cache_read_input_tokens = cache_read
if isinstance(usage_data.get('output_tokens_details'), dict):
output_tokens_details = usage_data['output_tokens_details']
if isinstance(usage_data.get('server_tool_use'), dict):
server_tool_use = usage_data['server_tool_use']
if usage_data.get('service_tier') is not None:
service_tier = usage_data['service_tier']
choices = data.get('choices', [])
if not choices:
# Check for usage in the final chunk
if data.get('usage'):
update_usage(data['usage'])
continue
delta = choices[0].get('delta', {})
finish_reason = choices[0].get('finish_reason')
message = choices[0].get('message') or {}
# Update usage if present
if data.get('usage'):
update_usage(data['usage'])
reasoning_content = (
delta.get('reasoning_content')
or delta.get('reasoning')
@@ -928,6 +958,8 @@ async def openai_stream_to_anthropic_stream(openai_stream_generator, model: str
usage['output_tokens_details'] = output_tokens_details
if server_tool_use is not None:
usage['server_tool_use'] = server_tool_use
if service_tier is not None:
usage['service_tier'] = service_tier
message_delta = {
'type': 'message_delta',