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350
adapters/openai_anthropic.py
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350
adapters/openai_anthropic.py
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"""OpenAI Chat Completions ↔ Anthropic Messages 格式转换
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请求方向: CC → Messages（Cursor 的 CC 请求转为 Anthropic 格式发给上游）
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响应方向: Messages → CC（上游 Anthropic 响应转为 CC 格式返回给 Cursor）
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包含非流式和流式两种转换。
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"""
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import json
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import uuid
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import logging
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from utils.tool_fixer import normalize_args, repair_str_replace_args, fix_anthropic_tool_use
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from utils.http import gen_id
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logger = logging.getLogger(__name__)
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# Anthropic stop_reason → OpenAI finish_reason
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_STOP_REASON_MAP = {
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'end_turn': 'stop',
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'max_tokens': 'length',
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'tool_use': 'tool_calls',
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'stop_sequence': 'stop',
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}
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# ═══════════════════════════════════════════════════════════
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# 请求转换: CC → Messages
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# ═══════════════════════════════════════════════════════════
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def cc_to_messages_request(payload):
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"""将 OpenAI CC 格式请求转换为 Anthropic Messages 格式"""
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messages = payload.get('messages', [])
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anthropic_msgs = []
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system_parts = []
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for msg in messages:
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role = msg.get('role', '')
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content = msg.get('content', '')
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# system 消息提取到顶层
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if role == 'system':
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system_parts.append(_flatten_text(content))
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continue
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anthropic_role = 'assistant' if role == 'assistant' else 'user'
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anthropic_content = _convert_content(msg)
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# assistant 的 tool_calls → tool_use content blocks
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if role == 'assistant' and 'tool_calls' in msg:
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blocks = _to_blocks(anthropic_content)
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for tc in msg['tool_calls']:
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func = tc.get('function', {})
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arguments = func.get('arguments', '{}')
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if isinstance(arguments, str):
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try:
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arguments = json.loads(arguments)
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except json.JSONDecodeError:
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arguments = {}
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blocks.append({
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'type': 'tool_use',
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'id': tc.get('id', f'toolu_{uuid.uuid4().hex[:24]}'),
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'name': func.get('name', ''),
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'input': arguments,
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})
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anthropic_content = blocks
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# tool 角色 → user + tool_result
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if role == 'tool':
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text = content if isinstance(content, str) else json.dumps(content)
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anthropic_content = [{
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'type': 'tool_result',
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'tool_use_id': msg.get('tool_call_id', ''),
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'content': text,
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}]
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anthropic_role = 'user'
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if not anthropic_content and anthropic_content != 0:
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continue
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anthropic_msgs.append({'role': anthropic_role, 'content': anthropic_content})
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# Anthropic 要求角色必须交替
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anthropic_msgs = _merge_same_role(anthropic_msgs)
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result = {
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'model': payload.get('model', 'claude-sonnet-4-20250514'),
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'messages': anthropic_msgs,
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'max_tokens': max(payload.get('max_tokens') or 8192, 8192),
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}
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if system_parts:
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result['system'] = '\n\n'.join(system_parts)
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if 'tools' in payload:
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result['tools'] = _convert_tools(payload['tools'])
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for key in ('temperature', 'top_p', 'stream'):
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if key in payload:
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result[key] = payload[key]
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return result
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# ═══════════════════════════════════════════════════════════
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# 非流式响应转换: Messages → CC
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# ═══════════════════════════════════════════════════════════
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def messages_to_cc_response(data, request_id=None):
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"""将 Anthropic Messages 响应转换为 OpenAI CC 格式"""
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request_id = request_id or gen_id('chatcmpl-')
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data = fix_anthropic_tool_use(data)
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content_text = ''
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reasoning = ''
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tool_calls = []
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for block in data.get('content', []):
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if not isinstance(block, dict):
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continue
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btype = block.get('type', '')
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if btype == 'text':
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content_text += block.get('text', '')
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elif btype == 'thinking':
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reasoning += block.get('thinking', '')
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elif btype == 'tool_use':
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args = block.get('input', {})
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if isinstance(args, dict):
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args = normalize_args(args)
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args = repair_str_replace_args(block.get('name', ''), args)
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tool_calls.append({
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'index': len(tool_calls),
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'id': block.get('id', f'toolu_{uuid.uuid4().hex[:24]}'),
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'type': 'function',
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'function': {
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'name': block.get('name', ''),
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'arguments': json.dumps(args, ensure_ascii=False) if isinstance(args, dict) else str(args),
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},
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})
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stop_reason = data.get('stop_reason', 'end_turn')
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message = {'role': 'assistant', 'content': content_text or None}
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if reasoning:
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message['reasoning_content'] = reasoning
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if tool_calls:
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message['tool_calls'] = tool_calls
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usage = data.get('usage', {})
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return {
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'id': request_id,
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'object': 'chat.completion',
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'model': data.get('model', 'claude'),
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'choices': [{
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'index': 0,
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'message': message,
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'finish_reason': _STOP_REASON_MAP.get(stop_reason, 'stop'),
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}],
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'usage': {
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'prompt_tokens': usage.get('input_tokens', 0),
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'completion_tokens': usage.get('output_tokens', 0),
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'total_tokens': usage.get('input_tokens', 0) + usage.get('output_tokens', 0),
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},
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}
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# ═══════════════════════════════════════════════════════════
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# 流式响应转换: Anthropic SSE → CC chunks
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# ═══════════════════════════════════════════════════════════
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class AnthropicStreamConverter:
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"""将 Anthropic SSE 事件逐个转换为 OpenAI CC 流式 chunk"""
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def __init__(self, request_id=None):
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self._id = request_id or gen_id('chatcmpl-')
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self._tool_index = -1
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self._input_tokens = 0
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self._output_tokens = 0
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def process_event(self, event_type, event_data):
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"""处理一个 Anthropic SSE 事件，返回 CC chunk JSON 字符串列表"""
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chunks = []
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if event_type == 'message_start':
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msg = event_data.get('message', {})
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self._input_tokens = msg.get('usage', {}).get('input_tokens', 0)
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chunk = self._make_chunk(delta={'role': 'assistant', 'content': ''})
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if msg.get('model'):
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chunk['model'] = msg['model']
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chunks.append(json.dumps(chunk))
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elif event_type == 'content_block_start':
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block = event_data.get('content_block', {})
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if block.get('type') == 'tool_use':
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self._tool_index += 1
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chunks.append(json.dumps(self._make_chunk(delta={
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'tool_calls': [{
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'index': self._tool_index,
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'id': block.get('id', f'toolu_{uuid.uuid4().hex[:24]}'),
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'type': 'function',
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'function': {'name': block.get('name', ''), 'arguments': ''},
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}]
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})))
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elif event_type == 'content_block_delta':
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delta = event_data.get('delta', {})
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dtype = delta.get('type', '')
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if dtype == 'text_delta' and delta.get('text'):
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chunks.append(json.dumps(self._make_chunk(
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delta={'content': delta['text']})))
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elif dtype == 'thinking_delta' and delta.get('thinking'):
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chunks.append(json.dumps(self._make_chunk(
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delta={'reasoning_content': delta['thinking']})))
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elif dtype == 'input_json_delta' and delta.get('partial_json'):
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chunks.append(json.dumps(self._make_chunk(delta={
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'tool_calls': [{
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'index': self._tool_index,
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'function': {'arguments': delta['partial_json']},
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}]
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})))
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elif event_type == 'message_delta':
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delta = event_data.get('delta', {})
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usage = event_data.get('usage', {})
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self._output_tokens = usage.get('output_tokens', 0)
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finish = _STOP_REASON_MAP.get(delta.get('stop_reason', ''), 'stop')
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chunk = self._make_chunk(delta={}, finish_reason=finish)
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chunk['usage'] = {
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'prompt_tokens': self._input_tokens,
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'completion_tokens': self._output_tokens,
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'total_tokens': self._input_tokens + self._output_tokens,
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}
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chunks.append(json.dumps(chunk))
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return chunks
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def _make_chunk(self, delta, finish_reason=None):
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choice = {'index': 0, 'delta': delta}
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if finish_reason:
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choice['finish_reason'] = finish_reason
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return {
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'id': self._id,
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'object': 'chat.completion.chunk',
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'model': 'claude',
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'choices': [choice],
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}
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# ═══════════════════════════════════════════════════════════
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# 内部辅助函数
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# ═══════════════════════════════════════════════════════════
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def _flatten_text(content):
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"""将 content 扁平化为纯文本"""
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts = []
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for p in content:
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if isinstance(p, str):
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parts.append(p)
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elif isinstance(p, dict) and p.get('type') == 'text':
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parts.append(p.get('text', ''))
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return '\n'.join(parts)
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return str(content)
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def _convert_content(msg):
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"""将 OpenAI 消息的 content 字段转为 Anthropic 格式"""
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content = msg.get('content', '')
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if content is None:
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return ''
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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blocks = []
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for part in content:
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if isinstance(part, str):
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blocks.append({'type': 'text', 'text': part})
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elif isinstance(part, dict):
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ptype = part.get('type', '')
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if ptype == 'text':
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blocks.append({'type': 'text', 'text': part.get('text', '')})
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elif ptype == 'image_url':
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blocks.append(_convert_image(part))
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elif ptype in ('tool_use', 'tool_result'):
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blocks.append(part)
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return blocks
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return str(content)
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def _convert_image(part):
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"""将 OpenAI image_url 格式转为 Anthropic image 格式"""
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url_data = part.get('image_url', {})
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url = url_data.get('url', '') if isinstance(url_data, dict) else str(url_data)
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if url.startswith('data:'):
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media_type, _, b64 = url.partition(';base64,')
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return {
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'type': 'image',
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'source': {
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'type': 'base64',
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'media_type': media_type.replace('data:', '') or 'image/png',
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'data': b64,
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},
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}
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return {'type': 'image', 'source': {'type': 'url', 'url': url}}
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def _convert_tools(tools):
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"""将 OpenAI tools 转为 Anthropic tools 格式（兼容 Cursor 扁平格式）"""
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result = []
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for tool in tools:
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if tool.get('type') == 'function' and 'function' in tool:
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func = tool['function']
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result.append({
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'name': func.get('name', ''),
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'description': func.get('description', ''),
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'input_schema': func.get('parameters', {'type': 'object', 'properties': {}}),
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})
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elif 'name' in tool and 'input_schema' in tool:
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result.append({
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'name': tool.get('name', ''),
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'description': tool.get('description', ''),
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'input_schema': tool.get('input_schema', {'type': 'object', 'properties': {}}),
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})
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return result
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def _to_blocks(content):
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"""将 content 统一转为 blocks 列表"""
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if isinstance(content, str):
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return [{'type': 'text', 'text': content}] if content else []
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if isinstance(content, list):
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return list(content)
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return [{'type': 'text', 'text': str(content)}] if content else []
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def _merge_same_role(messages):
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"""合并相邻同角色消息（Anthropic 要求角色必须交替）"""
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if not messages:
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return messages
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merged = [messages[0]]
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for msg in messages[1:]:
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if msg['role'] == merged[-1]['role']:
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prev = _to_blocks(merged[-1]['content'])
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curr = _to_blocks(msg['content'])
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merged[-1]['content'] = prev + curr
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else:
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merged.append(msg)
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return merged
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