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This commit is contained in:
Timothy Jaeryang Baek
2026-06-17 00:36:34 +02:00
parent 9ccda6715c
commit caedcbae49
1 changed files with 98 additions and 53 deletions
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backend/open_webui/utils/anthropic.py
+98 -53
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@@ -89,6 +89,26 @@ async def get_anthropic_models(url: str, key: str, user: UserModel = None) -> di
############################## ##############################
def _copy_cache_control(source: dict, target: dict) -> dict:
if isinstance(source, dict) and 'cache_control' in source:
target['cache_control'] = source['cache_control']
return target
def _has_cache_control(blocks: list) -> bool:
return any(isinstance(block, dict) and 'cache_control' in block for block in blocks)
def _finalize_openai_content(blocks: list) -> str | list:
if not blocks:
return ''
if len(blocks) == 1 and blocks[0].get('type') == 'text' and not _has_cache_control(blocks):
return blocks[0].get('text', '')
return blocks
def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict: def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
""" """
Convert an Anthropic Messages API request to OpenAI Chat Completions format. Convert an Anthropic Messages API request to OpenAI Chat Completions format.
@@ -112,14 +132,21 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
if isinstance(system, str): if isinstance(system, str):
messages.append({'role': 'system', 'content': system}) messages.append({'role': 'system', 'content': system})
elif isinstance(system, list): elif isinstance(system, list):
# Anthropic supports system as list of content blocks openai_content = []
text_parts = []
for block in system: for block in system:
if isinstance(block, dict) and block.get('type') == 'text': if isinstance(block, dict) and block.get('type') == 'text':
text_parts.append(block.get('text', '')) openai_content.append(
_copy_cache_control(
block,
{
'type': 'text',
'text': block.get('text', ''),
},
)
)
elif isinstance(block, str): elif isinstance(block, str):
text_parts.append(block) openai_content.append({'type': 'text', 'text': block})
messages.append({'role': 'system', 'content': '\n'.join(text_parts)}) messages.append({'role': 'system', 'content': _finalize_openai_content(openai_content)})
# Convert messages # Convert messages
for msg in anthropic_payload.get('messages', []): for msg in anthropic_payload.get('messages', []):
@@ -138,10 +165,13 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
if block_type == 'text': if block_type == 'text':
openai_content.append( openai_content.append(
{ _copy_cache_control(
'type': 'text', block,
'text': block.get('text', ''), {
} 'type': 'text',
'text': block.get('text', ''),
},
)
) )
elif block_type == 'image': elif block_type == 'image':
source = block.get('source', {}) source = block.get('source', {})
@@ -149,19 +179,25 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
media_type = source.get('media_type', 'image/png') media_type = source.get('media_type', 'image/png')
data = source.get('data', '') data = source.get('data', '')
openai_content.append( openai_content.append(
{ _copy_cache_control(
'type': 'image_url', block,
'image_url': { {
'url': f'data:{media_type};base64,{data}', 'type': 'image_url',
'image_url': {
'url': f'data:{media_type};base64,{data}',
},
}, },
} )
) )
elif source.get('type') == 'url': elif source.get('type') == 'url':
openai_content.append( openai_content.append(
{ _copy_cache_control(
'type': 'image_url', block,
'image_url': {'url': source.get('url', '')}, {
} 'type': 'image_url',
'image_url': {'url': source.get('url', '')},
},
)
) )
elif block_type == 'tool_use': elif block_type == 'tool_use':
tool_calls.append( tool_calls.append(
@@ -196,10 +232,13 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
if content_type == 'text': if content_type == 'text':
converted_parts.append( converted_parts.append(
{ _copy_cache_control(
'type': 'text', content_block,
'text': content_block.get('text', ''), {
} 'type': 'text',
'text': content_block.get('text', ''),
},
)
) )
elif content_type == 'image': elif content_type == 'image':
source = content_block.get('source', {}) source = content_block.get('source', {})
@@ -207,21 +246,27 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
media_type = source.get('media_type', 'image/png') media_type = source.get('media_type', 'image/png')
data = source.get('data', '') data = source.get('data', '')
converted_parts.append( converted_parts.append(
{ _copy_cache_control(
'type': 'image_url', content_block,
'image_url': { {
'url': f'data:{media_type};base64,{data}', 'type': 'image_url',
'image_url': {
'url': f'data:{media_type};base64,{data}',
},
}, },
} )
) )
elif source.get('type') == 'url': elif source.get('type') == 'url':
converted_parts.append( converted_parts.append(
{ _copy_cache_control(
'type': 'image_url', content_block,
'image_url': { {
'url': source.get('url', ''), 'type': 'image_url',
'image_url': {
'url': source.get('url', ''),
},
}, },
} )
) )
elif content_type == 'document': elif content_type == 'document':
# Documents have no direct OpenAI equivalent; # Documents have no direct OpenAI equivalent;
@@ -254,7 +299,9 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
converted_parts.append({'type': 'text', 'text': search_text}) converted_parts.append({'type': 'text', 'text': search_text})
# Flatten to string when only text parts are present # Flatten to string when only text parts are present
if all(part.get('type') == 'text' for part in converted_parts): if all(part.get('type') == 'text' for part in converted_parts) and not _has_cache_control(
converted_parts
):
tool_content = '\n'.join(part.get('text', '') for part in converted_parts) tool_content = '\n'.join(part.get('text', '') for part in converted_parts)
elif converted_parts: elif converted_parts:
tool_content = converted_parts tool_content = converted_parts
@@ -287,21 +334,13 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
# Assistant message with tool calls # Assistant message with tool calls
msg_dict = {'role': role} msg_dict = {'role': role}
if openai_content: if openai_content:
# If there's only text, flatten it msg_dict['content'] = _finalize_openai_content(openai_content)
if len(openai_content) == 1 and openai_content[0]['type'] == 'text':
msg_dict['content'] = openai_content[0]['text']
else:
msg_dict['content'] = openai_content
else: else:
msg_dict['content'] = '' msg_dict['content'] = ''
msg_dict['tool_calls'] = tool_calls msg_dict['tool_calls'] = tool_calls
messages.append(msg_dict) messages.append(msg_dict)
elif openai_content: elif openai_content:
# If there's only a single text block, flatten it to a string messages.append({'role': role, 'content': _finalize_openai_content(openai_content)})
if len(openai_content) == 1 and openai_content[0]['type'] == 'text':
messages.append({'role': role, 'content': openai_content[0]['text']})
else:
messages.append({'role': role, 'content': openai_content})
else: else:
messages.append({'role': role, 'content': str(content) if content else ''}) messages.append({'role': role, 'content': str(content) if content else ''})
@@ -312,7 +351,7 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
openai_payload['max_tokens'] = anthropic_payload['max_tokens'] openai_payload['max_tokens'] = anthropic_payload['max_tokens']
# Common parameters # Common parameters
for param in ('temperature', 'top_p', 'stop_sequences', 'stream'): for param in ('temperature', 'top_p', 'top_k', 'stop_sequences', 'stream', 'metadata', 'service_tier'):
if param in anthropic_payload: if param in anthropic_payload:
if param == 'stop_sequences': if param == 'stop_sequences':
openai_payload['stop'] = anthropic_payload[param] openai_payload['stop'] = anthropic_payload[param]
@@ -324,14 +363,17 @@ def convert_anthropic_to_openai_payload(anthropic_payload: dict) -> dict:
openai_tools = [] openai_tools = []
for tool in anthropic_payload['tools']: for tool in anthropic_payload['tools']:
openai_tools.append( openai_tools.append(
{ _copy_cache_control(
'type': 'function', tool,
'function': { {
'name': tool.get('name', ''), 'type': 'function',
'description': tool.get('description', ''), 'function': {
'parameters': tool.get('input_schema', {}), 'name': tool.get('name', ''),
'description': tool.get('description', ''),
'parameters': tool.get('input_schema', {}),
},
}, },
} )
) )
openai_payload['tools'] = openai_tools openai_payload['tools'] = openai_tools
@@ -382,7 +424,7 @@ def convert_openai_to_anthropic_response(openai_response: dict, model: str = '')
content.append({'type': 'text', 'text': message_content}) content.append({'type': 'text', 'text': message_content})
# Tool calls -> tool_use blocks # Tool calls -> tool_use blocks
tool_calls = message.get('tool_calls', []) tool_calls = message.get('tool_calls') or []
for tool_call in tool_calls: for tool_call in tool_calls:
function = tool_call.get('function', {}) function = tool_call.get('function', {})
try: try:
@@ -404,6 +446,10 @@ def convert_openai_to_anthropic_response(openai_response: dict, model: str = '')
'input_tokens': openai_usage.get('prompt_tokens', 0), 'input_tokens': openai_usage.get('prompt_tokens', 0),
'output_tokens': openai_usage.get('completion_tokens', 0), 'output_tokens': openai_usage.get('completion_tokens', 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']
return { return {
'id': openai_response.get('id', f'msg_{_uuid.uuid4().hex[:24]}'), 'id': openai_response.get('id', f'msg_{_uuid.uuid4().hex[:24]}'),
@@ -703,4 +749,3 @@ async def openai_stream_to_anthropic_stream(openai_stream_generator, model: str
# Emit message_stop # Emit message_stop
yield f'event: message_stop\ndata: {json.dumps({"type": "message_stop"})}\n\n'.encode() yield f'event: message_stop\ndata: {json.dumps({"type": "message_stop"})}\n\n'.encode()