Pine
206 lines
7.1 KiB
Python
206 lines
7.1 KiB
Python
"""
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消息格式转换模块
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将 OpenAI Responses API 请求格式转换为 DeepSeek Chat Completions API 格式。
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"""
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def _clean_schema(obj):
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"""递归清除 JSON Schema 中 DeepSeek 不支持的字段"""
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if not isinstance(obj, dict):
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return obj
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cleaned = {}
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for k, v in obj.items():
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if k in ("additionalProperties", "strict"):
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continue
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if isinstance(v, dict):
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cleaned[k] = _clean_schema(v)
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elif isinstance(v, list):
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cleaned[k] = [_clean_schema(i) if isinstance(i, dict) else i for i in v]
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else:
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cleaned[k] = v
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return cleaned
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def _convert_tools(tools: list) -> list:
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"""将工具定义从 Responses API 格式转换为 Chat Completions API 格式"""
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result = []
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for tool in tools:
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if not isinstance(tool, dict):
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continue
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if tool.get("type") != "function":
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continue
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func = {
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"name": tool.get("name", ""),
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"description": tool.get("description", ""),
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}
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if "parameters" in tool:
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func["parameters"] = _clean_schema(tool["parameters"])
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result.append({"type": "function", "function": func})
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return result
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def _convert_tool_choice(tc):
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"""将 tool_choice 从 Responses API 格式转换为 Chat Completions 格式"""
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if tc is None:
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return "auto"
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if isinstance(tc, str):
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return tc
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if isinstance(tc, dict) and tc.get("type") == "function":
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return {"type": "function", "function": {"name": tc.get("name", "")}}
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return "auto"
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def extract_messages(data: dict):
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"""
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从 Responses API 请求中提取 messages 列表、tools 列表和 tool_choice。
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支持两种输入格式：
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- Responses API（input/instructions 字段）
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- Chat Completions API（messages 字段）
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Returns:
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(messages, tools, tool_choice)
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"""
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ROLE_MAP = {"developer": "system"}
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raw_tools = data.get("tools", [])
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tools = _convert_tools(raw_tools)
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tool_choice = _convert_tool_choice(data.get("tool_choice"))
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if "input" not in data:
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if "messages" in data:
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return data["messages"], tools, tool_choice
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return [], tools, tool_choice
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inp = data["input"]
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if isinstance(inp, str):
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messages = []
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if "instructions" in data and data["instructions"]:
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messages.append({"role": "system", "content": data["instructions"]})
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messages.append({"role": "user", "content": inp})
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return messages, tools, tool_choice
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if not isinstance(inp, list):
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return [], tools, tool_choice
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messages = []
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if "instructions" in data and data["instructions"]:
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messages.append({"role": "system", "content": data["instructions"]})
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pending_tool_calls = []
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pending_reasoning = ""
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def _flush_tool_calls():
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nonlocal pending_tool_calls, pending_reasoning
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if pending_tool_calls:
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msg = {
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"role": "assistant",
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"content": "",
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"tool_calls": pending_tool_calls,
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}
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if pending_reasoning:
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msg["reasoning_content"] = pending_reasoning
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messages.append(msg)
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pending_tool_calls = []
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pending_reasoning = ""
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for item in inp:
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if not isinstance(item, dict):
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continue
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item_type = item.get("type")
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if item_type == "message":
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_flush_tool_calls()
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role = item.get("role", "user")
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role = ROLE_MAP.get(role, role)
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content = item.get("content", "")
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if isinstance(content, list):
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texts = []
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tool_calls = []
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for c in content:
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if not isinstance(c, dict):
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continue
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c_type = c.get("type")
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if c_type in ("text", "input_text", "output_text"):
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t = c.get("text", "")
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if t.strip():
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texts.append(t)
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elif c_type == "tool_call":
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tool_calls.append({
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"id": c.get("id", ""),
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"type": "function",
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"function": {
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"name": c.get("name", ""),
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"arguments": c.get("arguments", ""),
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},
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})
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text_content = "\n".join(texts)
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if tool_calls:
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msg = {"role": role, "content": text_content or ""}
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msg["tool_calls"] = tool_calls
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if item.get("reasoning_content"):
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msg["reasoning_content"] = item["reasoning_content"]
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messages.append(msg)
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elif text_content:
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msg = {"role": role, "content": text_content}
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if item.get("reasoning_content"):
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msg["reasoning_content"] = item["reasoning_content"]
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messages.append(msg)
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elif isinstance(content, str) and content.strip():
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msg = {"role": role, "content": content.strip()}
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if item.get("reasoning_content"):
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msg["reasoning_content"] = item["reasoning_content"]
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messages.append(msg)
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elif item_type == "function_call":
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pending_tool_calls.append({
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"id": item.get("call_id", ""),
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"type": "function",
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"function": {
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"name": item.get("name", ""),
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"arguments": item.get("arguments", ""),
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},
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})
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if item.get("reasoning_content") and not pending_reasoning:
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pending_reasoning = item["reasoning_content"]
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elif item_type == "function_call_output":
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_flush_tool_calls()
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messages.append({
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"role": "tool",
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"tool_call_id": item.get("call_id", ""),
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"content": item.get("output", ""),
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})
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_flush_tool_calls()
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# ---- 重排消息：确保 tool 消息紧跟对应的 assistant 消息 ----
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reordered = []
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i = 0
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while i < len(messages):
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msg = messages[i]
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if msg.get("role") == "assistant" and msg.get("tool_calls"):
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expected_ids = {tc["id"] for tc in msg["tool_calls"]}
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tool_msgs = []
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non_tool_msgs = []
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j = i + 1
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while j < len(messages) and expected_ids:
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nxt = messages[j]
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if nxt.get("role") == "tool" and nxt.get("tool_call_id") in expected_ids:
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expected_ids.remove(nxt["tool_call_id"])
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tool_msgs.append(nxt)
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elif nxt.get("role") in ("system", "developer"):
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non_tool_msgs.append(nxt)
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else:
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break
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j += 1
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reordered.extend(non_tool_msgs)
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reordered.append(msg)
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reordered.extend(tool_msgs)
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i = j
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else:
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reordered.append(msg)
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i += 1
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return reordered, tools, tool_choice
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