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feat(data-process): 增加可配置思维链生成

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This commit is contained in:
caoxiaozhu
2026-07-27 14:41:38 +08:00
parent 97cdb5cc68
commit f97245b814
12 changed files with 224 additions and 29 deletions
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3
backend/app/api/v1/endpoints/data_process.py
View File

@@ -566,6 +566,9 @@ def _run_generation(
config, "generation_prompt", "generationPrompt", ""
),
"output_type": output_type,
"reasoning_detail": _value(
config, "reasoning_detail", "reasoningDetail", "normal"
),
"max_tokens": _value(config, "max_tokens", "maxTokens", 1024),
"json_mode": _value(config, "json_mode", "jsonMode", False),
}

31
backend/app/modules/data_process/generation.py
View File

@@ -25,6 +25,12 @@ class ModelGenerationError(ValueError):
OUTPUT_TYPE_STANDARD = "standard"
OUTPUT_TYPE_REASONING = "reasoning"
SUPPORTED_OUTPUT_TYPES = {OUTPUT_TYPE_STANDARD, OUTPUT_TYPE_REASONING}
REASONING_DETAIL_NORMAL = "normal"
REASONING_DETAIL_DETAILED = "detailed"
SUPPORTED_REASONING_DETAILS = {
REASONING_DETAIL_NORMAL,
REASONING_DETAIL_DETAILED,
}
def chat_completions_url(value: str) -> str:
@@ -122,19 +128,32 @@ def _prompt_messages(
start_index: int,
total_count: int,
output_type: str,
reasoning_detail: str,
) -> list[dict[str, str]]:
end_index = start_index + count - 1
if output_type == OUTPUT_TYPE_REASONING:
schema = '{"items":[{"instruction":"...","input":"...","reasoning":"...","answer":"..."}]}'
detail_rule = (
"推理详细程度为“详细”：完整展开问题条件、来源依据、中间计算或推导，"
"并在得出答案前核对结论；每一步都必须能从来源内容中验证。"
if reasoning_detail == REASONING_DETAIL_DETAILED
else
"推理详细程度为“普通”：只保留得出答案所需的关键依据和必要步骤，"
"避免冗长复述、套话和无依据扩展。"
)
output_rule = (
"你正在生成用于训练推理模型的思维链数据，而不是普通问答数据。"
"instruction、reasoning 和 answer 均不得为空；reasoning 必须是基于来源内容、"
"可核对且简洁的推理步骤，answer 只写最终答案。"
f"可核对的推理过程，answer 只写最终答案。{detail_rule}"
"这是思维链输出模式，即使其他提示语要求省略分析，也不得省略 reasoning。"
"不要自行添加 <think> 标签，系统会在保存时统一组装。"
)
else:
schema = '{"items":[{"instruction":"...","input":"...","output":"..."}]}'
output_rule = "instruction 和 output 不得为空，不要输出分析过程。"
output_rule = (
"你正在生成标准监督微调问答数据。instruction 和 output 不得为空；"
"output 只写最终答案，禁止输出分析、推理过程或 <think> 标签。"
)
schema_instruction = (
f"必须只返回 JSON 对象，格式为 {schema}；items 必须包含 {count} 条。"
f"这是总计 {total_count} 条中的第 {start_index}-{end_index} 条，"
@@ -176,6 +195,13 @@ def generate_model_records(
output_type = str(config.get("output_type") or OUTPUT_TYPE_STANDARD).strip().lower()
if output_type not in SUPPORTED_OUTPUT_TYPES:
raise ModelGenerationError(f"output_type must be one of {sorted(SUPPORTED_OUTPUT_TYPES)}")
reasoning_detail = str(
config.get("reasoning_detail") or REASONING_DETAIL_NORMAL
).strip().lower()
if reasoning_detail not in SUPPORTED_REASONING_DETAILS:
raise ModelGenerationError(
f"reasoning_detail must be one of {sorted(SUPPORTED_REASONING_DETAILS)}"
)
endpoint = chat_completions_url(str(model.get("api_url") or ""))
model_name = str(model.get("online_model_name") or model.get("name") or "").strip()
if not model_name:
@@ -217,6 +243,7 @@ def generate_model_records(
start_index=batch_start,
total_count=qa_pairs_per_item,
output_type=output_type,
reasoning_detail=reasoning_detail,
),
"temperature": temperature,
"max_tokens": max_tokens,

12
backend/app/modules/data_process/store.py
View File

@@ -95,6 +95,17 @@ def _task_output_type(task: dict[str, Any]) -> str:
return str(config.get("output_type") or config.get("outputType") or "standard")
def _task_reasoning_detail(task: dict[str, Any]) -> str:
config = _json_value(task.get("config"), {})
if not isinstance(config, dict):
return "normal"
return str(
config.get("reasoning_detail")
or config.get("reasoningDetail")
or "normal"
)
def _reasoning_output_is_valid(value: Any) -> bool:
match = re.fullmatch(
r"\s*<think>\s*(?P<reasoning>[\s\S]*?)\s*</think>\s*(?P<answer>[\s\S]+?)\s*",
@@ -1773,6 +1784,7 @@ class DataProcessStore:
"storage_backend": "database",
"source_task_id": task_id,
"output_type": _task_output_type(task),
"reasoning_detail": _task_reasoning_detail(task),
"source_file_ids": [item["id"] for item in self._source_ids(conn, task_id)],
"source_result_ids": source_result_ids,
"format": payload.get("format") or "alpaca_jsonl",

59
backend/tests/test_data_process_generation.py
View File

@@ -33,6 +33,8 @@ def test_generate_model_records_uses_prompt_auth_and_stable_split() -> None:
assert payload["model"] == "qwen-plus"
assert payload["response_format"] == {"type": "json_object"}
assert "客户反馈页面加载慢" in payload["messages"][1]["content"]
assert "你正在生成标准监督微调问答数据" in payload["messages"][0]["content"]
assert "禁止输出分析、推理过程" in payload["messages"][0]["content"]
return httpx.Response(
200,
json={
@@ -91,6 +93,8 @@ def test_generate_model_records_builds_reasoning_output_with_think_tags() -> Non
payload = json.loads(request.content)
system_prompt = payload["messages"][0]["content"]
assert '"reasoning":"...","answer":"..."' in system_prompt
assert "你正在生成用于训练推理模型的思维链数据" in system_prompt
assert "推理详细程度为“普通”" in system_prompt
assert "系统会在保存时统一组装" in system_prompt
content = "<think>模型接口自己的分析</think>" + json.dumps(
{
@@ -126,6 +130,49 @@ def test_generate_model_records_builds_reasoning_output_with_think_tags() -> Non
)
def test_generate_model_records_uses_detailed_reasoning_instruction() -> None:
def handler(request: httpx.Request) -> httpx.Response:
system_prompt = json.loads(request.content)["messages"][0]["content"]
assert "推理详细程度为“详细”" in system_prompt
assert "完整展开问题条件、来源依据、中间计算或推导" in system_prompt
return httpx.Response(
200,
json={
"choices": [
{
"message": {
"content": json.dumps(
{
"items": [
{
"instruction": "计算报销总额",
"reasoning": "条件为交通费 30 元和餐费 20 元。分别核对后相加，30 + 20 = 50。",
"answer": "报销总额为 50 元。",
}
]
},
ensure_ascii=False,
)
}
}
]
},
)
records = generate_model_records(
[{"id": "preview-detailed", "edited_content": "交通费 30 元，餐费 20 元"}],
model={"name": "model", "api_url": "https://model.example/v1"},
config={"output_type": "reasoning", "reasoning_detail": "detailed"},
task_id="task-detailed",
split={"train": 100, "validation": 0, "test": 0},
qa_pairs_per_item=1,
client=httpx.Client(transport=httpx.MockTransport(handler)),
)
assert records[0]["status"] == "valid"
assert "分别核对后相加" in records[0]["output"]
def test_generate_model_records_marks_reasoning_without_reasoning_field_invalid() -> None:
response = {
"choices": [
@@ -392,3 +439,15 @@ def test_generate_model_records_rejects_unknown_output_type() -> None:
split={"train": 100, "validation": 0, "test": 0},
qa_pairs_per_item=1,
)
def test_generate_model_records_rejects_unknown_reasoning_detail() -> None:
with pytest.raises(ModelGenerationError, match="reasoning_detail"):
generate_model_records(
[],
model={"name": "model", "api_url": "https://model.example/v1"},
config={"output_type": "reasoning", "reasoning_detail": "verbose"},
task_id="task-invalid-reasoning-detail",
split={"train": 100, "validation": 0, "test": 0},
qa_pairs_per_item=1,
)