mirror of
https://github.com/CJackHwang/ds2api.git
synced 2026-05-06 09:25:27 +08:00
Unify non-stream parsing with SSE parser
This commit is contained in:
CJACK.
161
routes/openai.py
161
routes/openai.py
@@ -453,107 +453,84 @@ IMPORTANT: If calling tools, output ONLY the JSON. The response must start with
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def collect_data():
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nonlocal result
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ptype = "text"
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current_fragment_type = "thinking" if thinking_enabled else "text"
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try:
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for raw_line in deepseek_resp.iter_lines():
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try:
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line = raw_line.decode("utf-8")
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except Exception as e:
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logger.warning(f"[chat_completions] 解码失败: {e}")
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if ptype == "thinking":
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think_list.append("解码失败，请稍候再试")
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else:
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text_list.append("解码失败，请稍候再试")
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chunk = parse_deepseek_sse_line(raw_line)
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if not chunk:
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continue
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if chunk.get("type") == "done":
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data_queue.put(None)
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break
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if not line:
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continue
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if line.startswith("data:"):
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data_str = line[5:].strip()
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if data_str == "[DONE]":
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data_queue.put(None)
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break
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try:
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chunk = json.loads(data_str)
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if "v" in chunk:
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v_value = chunk["v"]
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if "p" in chunk and chunk.get("p") == "response/search_status":
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continue
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if "p" in chunk and chunk.get("p") == "response/thinking_content":
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ptype = "thinking"
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elif "p" in chunk and chunk.get("p") == "response/content":
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ptype = "text"
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if isinstance(v_value, str):
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if search_enabled and v_value.startswith("[citation:"):
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continue
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if ptype == "thinking":
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think_list.append(v_value)
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else:
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text_list.append(v_value)
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elif isinstance(v_value, list):
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for item in v_value:
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if item.get("p") == "status" and item.get("v") == "FINISHED":
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final_reasoning = "".join(think_list)
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final_content = "".join(text_list)
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prompt_tokens = len(final_prompt) // 4
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reasoning_tokens = len(final_reasoning) // 4
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completion_tokens = len(final_content) // 4
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# 检测工具调用
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detected_tools = []
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finish_reason = "stop"
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if has_tools:
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detected_tools = parse_tool_calls(final_content, [{"name": t.get("function", t).get("name")} for t in tools_requested])
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if detected_tools:
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finish_reason = "tool_calls"
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# 构建 message 对象
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message_obj = {
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"role": "assistant",
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"content": final_content if not detected_tools else None,
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}
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# 只有启用思考模式时才包含 reasoning_content
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if thinking_enabled and final_reasoning:
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message_obj["reasoning_content"] = final_reasoning
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# 添加工具调用
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if detected_tools:
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tool_calls_data = format_openai_tool_calls(detected_tools)
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message_obj["tool_calls"] = tool_calls_data
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message_obj["content"] = None
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result = {
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"id": completion_id,
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"object": "chat.completion",
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"created": created_time,
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"model": model,
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"choices": [{
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"index": 0,
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"message": message_obj,
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"finish_reason": finish_reason,
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}],
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"usage": {
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"prompt_tokens": prompt_tokens,
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"completion_tokens": reasoning_tokens + completion_tokens,
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"total_tokens": prompt_tokens + reasoning_tokens + completion_tokens,
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"completion_tokens_details": {"reasoning_tokens": reasoning_tokens},
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},
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}
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data_queue.put("DONE")
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return
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except Exception as e:
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logger.warning(f"[collect_data] 无法解析: {data_str}, 错误: {e}")
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if ptype == "thinking":
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think_list.append("解析失败，请稍候再试")
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try:
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contents, is_finished, new_fragment_type = parse_sse_chunk_for_content(
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chunk, thinking_enabled, current_fragment_type
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)
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current_fragment_type = new_fragment_type
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if is_finished:
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final_reasoning = "".join(think_list)
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final_content = "".join(text_list)
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prompt_tokens = len(final_prompt) // 4
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reasoning_tokens = len(final_reasoning) // 4
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completion_tokens = len(final_content) // 4
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# 检测工具调用
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detected_tools = []
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finish_reason = "stop"
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if has_tools:
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detected_tools = parse_tool_calls(final_content, [{"name": t.get("function", t).get("name")} for t in tools_requested])
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if detected_tools:
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finish_reason = "tool_calls"
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# 构建 message 对象
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message_obj = {
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"role": "assistant",
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"content": final_content if not detected_tools else None,
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}
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# 只有启用思考模式时才包含 reasoning_content
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if thinking_enabled and final_reasoning:
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message_obj["reasoning_content"] = final_reasoning
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# 添加工具调用
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if detected_tools:
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tool_calls_data = format_openai_tool_calls(detected_tools)
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message_obj["tool_calls"] = tool_calls_data
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message_obj["content"] = None
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result = {
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"id": completion_id,
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"object": "chat.completion",
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"created": created_time,
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"model": model,
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"choices": [{
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"index": 0,
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"message": message_obj,
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"finish_reason": finish_reason,
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}],
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"usage": {
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"prompt_tokens": prompt_tokens,
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"completion_tokens": reasoning_tokens + completion_tokens,
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"total_tokens": prompt_tokens + reasoning_tokens + completion_tokens,
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"completion_tokens_details": {"reasoning_tokens": reasoning_tokens},
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},
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}
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data_queue.put("DONE")
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return
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for content_text, content_type in contents:
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if should_filter_citation(content_text, search_enabled):
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continue
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if content_type == "thinking":
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think_list.append(content_text)
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else:
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text_list.append("解析失败，请稍候再试")
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text_list.append(content_text)
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except Exception as e:
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logger.warning(f"[collect_data] 无法解析: {chunk}, 错误: {e}")
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text_list.append("解析失败，请稍候再试")
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data_queue.put(None)
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break
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except Exception as e:
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logger.warning(f"[collect_data] 错误: {e}")
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if ptype == "thinking":
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think_list.append("处理失败，请稍候再试")
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else:
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text_list.append("处理失败，请稍候再试")
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text_list.append("处理失败，请稍候再试")
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data_queue.put(None)
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finally:
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deepseek_resp.close()
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