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fix(openai_cli): 完善 Responses API 响应格式，对齐 CLI 客户端协议要求

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- 流式事件添加 sequence_number 递增序号
- output_text 内容补充 annotations 空数组
- 补充 content_part.added/done 和 function_call_arguments.done 事件
- 非流式响应回显原始请求字段（instructions/tools/reasoning 等）
- 补充 input_tokens_details/output_tokens_details 用量明细
- 响应结构添加 background/error/incomplete_details 等缺失字段
This commit is contained in:
fawney19
2026-02-19 22:43:04 +08:00
parent 5629edf487
commit d7f0a555c0
1 changed files with 146 additions and 12 deletions
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158
src/core/api_format/conversion/normalizers/openai_cli.py
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@@ -300,7 +300,7 @@ class OpenAICliNormalizer(FormatNormalizer):
"id": f"msg_{internal.id or 'stream'}",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": text}],
"content": [{"type": "output_text", "text": text, "annotations": []}],
}
)
@@ -329,7 +329,7 @@ class OpenAICliNormalizer(FormatNormalizer):
"id": f"msg_{internal.id or 'stream'}",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": ""}],
"content": [{"type": "output_text", "text": "", "annotations": []}],
}
)
@@ -339,20 +339,56 @@ class OpenAICliNormalizer(FormatNormalizer):
"output_tokens": usage.output_tokens,
"total_tokens": usage.total_tokens or (usage.input_tokens + usage.output_tokens),
}
# input_tokens_details（cached_tokens）
if usage.cache_read_tokens:
usage_obj["input_tokens_details"] = {"cached_tokens": usage.cache_read_tokens}
# output_tokens_details（reasoning_tokens）— 从原始 usage 中恢复
raw_usage = (usage.extra.get("openai_cli") or {}).get("usage") or {}
if isinstance(raw_usage, dict):
output_details = raw_usage.get("output_tokens_details")
if isinstance(output_details, dict) and output_details.get("reasoning_tokens"):
usage_obj["output_tokens_details"] = {
"reasoning_tokens": int(output_details["reasoning_tokens"]),
}
# 优先使用用户请求的原始模型名，回退到上游返回的模型名
model_name = requested_model if requested_model else (internal.model or "")
return {
result: dict[str, Any] = {
"id": internal.id or "resp",
"object": "response",
"created": int(time.time()),
"model": model_name,
"created_at": int(time.time()),
"status": "completed",
"model": model_name,
"output": output_items,
"usage": usage_obj,
"background": False,
"error": None,
"incomplete_details": None,
}
# 回显原始请求字段（CLI 客户端可能依赖这些字段做状态管理）
openai_cli_extra = internal.extra.get("openai_cli", {})
for key in (
"instructions",
"max_output_tokens",
"temperature",
"top_p",
"tool_choice",
"tools",
"store",
"metadata",
"previous_response_id",
"reasoning",
"truncation",
"service_tier",
"parallel_tool_calls",
):
if key in openai_cli_extra and key not in result:
result[key] = openai_cli_extra[key]
return result
# =========================
# Stream conversion
# =========================
@@ -639,19 +675,34 @@ class OpenAICliNormalizer(FormatNormalizer):
ss.setdefault("text_started", False)
ss.setdefault("next_output_index", 0)
ss.setdefault("sent_in_progress", False)
ss.setdefault("seq", 0)
response_obj = {
"id": state.message_id,
"object": "response",
"created": int(time.time()),
"created_at": int(time.time()),
"model": state.model,
"status": "in_progress",
"background": False,
"error": None,
"output": [],
}
out.append({"type": "response.created", "response": response_obj})
out.append(
{
"type": "response.created",
"sequence_number": self._next_seq(ss),
"response": response_obj,
}
)
# OpenAI Responses API 常见的 in_progress 事件（可选，最佳努力）
if not ss.get("sent_in_progress"):
ss["sent_in_progress"] = True
out.append({"type": "response.in_progress", "response": response_obj})
out.append(
{
"type": "response.in_progress",
"sequence_number": self._next_seq(ss),
"response": response_obj,
}
)
return out
def _emit_content_block_start(
@@ -684,6 +735,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.output_item.added",
"sequence_number": self._next_seq(ss),
"output_index": output_index,
"item": {
"type": "function_call",
@@ -710,6 +762,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.function_call_arguments.delta",
"sequence_number": self._next_seq(ss),
"delta": event.input_delta,
"item_id": tool_id,
"output_index": output_index,
@@ -729,9 +782,21 @@ class OpenAICliNormalizer(FormatNormalizer):
tool_calls = ss.get("tool_calls", {})
entry = tool_calls.get(tool_id, {})
output_index = ss.get("tool_output_index", {}).get(tool_id, event.block_index)
# function_call_arguments.done
out.append(
{
"type": "response.function_call_arguments.done",
"sequence_number": self._next_seq(ss),
"item_id": tool_id,
"output_index": output_index,
"arguments": entry.get("args") or "",
}
)
# output_item.done
out.append(
{
"type": "response.output_item.done",
"sequence_number": self._next_seq(ss),
"output_index": output_index,
"item": {
"type": "function_call",
@@ -771,6 +836,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.output_item.added",
"sequence_number": self._next_seq(ss),
"output_index": reasoning_output_index,
"item": {
"type": "reasoning",
@@ -783,6 +849,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.reasoning_summary_part.added",
"sequence_number": self._next_seq(ss),
"item_id": reasoning_id,
"output_index": reasoning_output_index,
"summary_index": 0,
@@ -793,6 +860,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.reasoning_summary_text.delta",
"sequence_number": self._next_seq(ss),
"item_id": ss.get("reasoning_id", ""),
"output_index": ss.get("reasoning_output_index", 0),
"summary_index": 0,
@@ -813,6 +881,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.output_item.added",
"sequence_number": self._next_seq(ss),
"output_index": output_index,
"item": {
"type": "message",
@@ -823,9 +892,25 @@ class OpenAICliNormalizer(FormatNormalizer):
},
}
)
# content_part.added
out.append(
{
"type": "response.content_part.added",
"sequence_number": self._next_seq(ss),
"output_index": output_index,
"content_index": 0,
"part": {"type": "output_text", "text": "", "annotations": []},
}
)
ss["text_started"] = True
ss["collected_text"] = str(ss.get("collected_text") or "") + event.text_delta
out.append({"type": "response.output_text.delta", "delta": event.text_delta})
out.append(
{
"type": "response.output_text.delta",
"sequence_number": self._next_seq(ss),
"delta": event.text_delta,
}
)
return out
def _emit_message_stop(
@@ -842,6 +927,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.reasoning_summary_text.done",
"sequence_number": self._next_seq(ss),
"item_id": reasoning_id,
"output_index": reasoning_output_index,
"summary_index": 0,
@@ -851,6 +937,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.reasoning_summary_part.done",
"sequence_number": self._next_seq(ss),
"item_id": reasoning_id,
"output_index": reasoning_output_index,
"summary_index": 0,
@@ -860,6 +947,7 @@ class OpenAICliNormalizer(FormatNormalizer):
out.append(
{
"type": "response.output_item.done",
"sequence_number": self._next_seq(ss),
"output_index": reasoning_output_index,
"item": {
"type": "reasoning",
@@ -875,15 +963,36 @@ class OpenAICliNormalizer(FormatNormalizer):
"id": message_id,
"role": "assistant",
"status": "completed",
"content": ([{"type": "output_text", "text": final_text}] if final_text else []),
"content": (
[{"type": "output_text", "text": final_text, "annotations": []}]
if final_text
else []
),
}
if ss.get("text_started"):
out.append({"type": "response.output_text.done", "text": final_text})
out.append(
{
"type": "response.output_text.done",
"sequence_number": self._next_seq(ss),
"text": final_text,
}
)
# content_part.done
out.append(
{
"type": "response.content_part.done",
"sequence_number": self._next_seq(ss),
"output_index": ss.get("message_output_index") or 0,
"content_index": 0,
"part": {"type": "output_text", "text": final_text, "annotations": []},
}
)
if ss.get("message_output_started"):
output_index = ss.get("message_output_index") or 0
out.append(
{
"type": "response.output_item.done",
"sequence_number": self._next_seq(ss),
"output_index": output_index,
"item": message_item,
}
@@ -896,6 +1005,8 @@ class OpenAICliNormalizer(FormatNormalizer):
if final_text:
final_content.append(TextBlock(text=final_text))
# 传递 extra 以便 response_from_internal 能回显请求字段
resp_extra = state.extra.get("openai_cli_request_extra") or {}
response_obj = self.response_from_internal(
InternalResponse(
id=state.message_id or "resp",
@@ -903,13 +1014,20 @@ class OpenAICliNormalizer(FormatNormalizer):
content=final_content,
stop_reason=event.stop_reason or StopReason.END_TURN,
usage=event.usage or UsageInfo(),
extra={"openai_cli": resp_extra} if resp_extra else {},
)
)
# 将工具调用添加到 output（最佳努力）
output_items = self._build_final_output_items(message_item, ss)
if output_items:
response_obj["output"] = output_items
out.append({"type": "response.completed", "response": response_obj})
out.append(
{
"type": "response.completed",
"sequence_number": self._next_seq(ss),
"response": response_obj,
}
)
return out
def _build_final_output_items(
@@ -967,6 +1085,7 @@ class OpenAICliNormalizer(FormatNormalizer):
) -> list[dict[str, Any]]:
err_payload = self.error_from_internal(event.error)
err_payload["type"] = "response.failed"
err_payload["sequence_number"] = self._next_seq(ss)
return [err_payload]
# =========================
@@ -1007,6 +1126,13 @@ class OpenAICliNormalizer(FormatNormalizer):
# Helpers
# =========================
@staticmethod
def _next_seq(ss: dict[str, Any]) -> int:
"""递增并返回下一个 sequence_number"""
seq = int(ss.get("seq") or 0) + 1
ss["seq"] = seq
return seq
def _unwrap_response_object(self, response: dict[str, Any]) -> dict[str, Any]:
if not isinstance(response, dict):
return {}
@@ -1094,10 +1220,18 @@ class OpenAICliNormalizer(FormatNormalizer):
input_tokens = int(usage.get("input_tokens") or 0)
output_tokens = int(usage.get("output_tokens") or 0)
total_tokens = int(usage.get("total_tokens") or (input_tokens + output_tokens))
# input_tokens_details.cached_tokens
cache_read_tokens = 0
input_details = usage.get("input_tokens_details")
if isinstance(input_details, dict):
cache_read_tokens = int(input_details.get("cached_tokens") or 0)
return UsageInfo(
input_tokens=input_tokens,
output_tokens=output_tokens,
total_tokens=total_tokens,
cache_read_tokens=cache_read_tokens,
extra={"openai_cli": {"usage": usage}},
)