feat(data-process): 支持思维链输出类型

backend/app/modules/data_process/store.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import hashlib
 import json
+import re
 import uuid
 from collections.abc import Iterator, Sequence
 from contextlib import contextmanager
@@ -87,6 +88,31 @@ def _json_value(value: Any, default: Any) -> Any:
         return default
 
 
+def _task_output_type(task: dict[str, Any]) -> str:
+    config = _json_value(task.get("config"), {})
+    if not isinstance(config, dict):
+        return "standard"
+    return str(config.get("output_type") or config.get("outputType") or "standard")
+
+
+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*",
+        str(value or ""),
+        flags=re.IGNORECASE,
+    )
+    return bool(
+        match
+        and match.group("reasoning").strip()
+        and match.group("answer").strip()
+        and all(
+            tag not in part.lower()
+            for tag in ("<think", "</think")
+            for part in (match.group("reasoning"), match.group("answer"))
+        )
+    )
+
+
 def _preview_config_value(config: dict[str, Any], key: str, default: Any) -> Any:
     if key in config:
         return config[key]
@@ -1565,10 +1591,13 @@ class DataProcessStore:
                 raise ConflictError("data process result was modified by another request")
             merged = {**current, **values}
             quality = payload.get("quality_score") or {}
-            hard_valid = bool(
-                str(merged.get("instruction") or "").strip()
-                and str(merged.get("output") or "").strip()
+            instruction_valid = bool(str(merged.get("instruction") or "").strip())
+            output_valid = bool(str(merged.get("output") or "").strip())
+            reasoning_valid = (
+                _task_output_type(task) != "reasoning"
+                or _reasoning_output_is_valid(merged.get("output"))
             )
+            hard_valid = instruction_valid and output_valid and reasoning_valid
             quality_valid = bool(quality.get("is_valid", hard_valid))
             changed = any(
                 str(merged.get(field) or "")
@@ -1580,8 +1609,16 @@ class DataProcessStore:
             )
             values["status"] = status
             flags = quality.get("flags") if isinstance(quality, dict) else None
+            format_error = (
+                "思维链输出必须包含非空的 <think>...</think> 推理过程和最终答案"
+                if instruction_valid and output_valid and not reasoning_valid
+                else "Instruction 和 Output 不能为空"
+                if not instruction_valid or not output_valid
+                else None
+            )
             values["error"] = ", ".join(str(flag) for flag in flags or []) or (
-                "quality validation failed" if status == "invalid" else None
+                format_error
+                or ("quality validation failed" if status == "invalid" else None)
             )
             values["updated_at"] = utcnow()
             assignments = ", ".join(f"{key}=%s" for key in values)
@@ -1671,6 +1708,10 @@ class DataProcessStore:
                 if row["status"] == "invalid"
                 or not str(row.get("instruction") or "").strip()
                 or not str(row.get("output") or "").strip()
+                or (
+                    _task_output_type(task) == "reasoning"
+                    and not _reasoning_output_is_valid(row.get("output"))
+                )
             )
             if invalid_count:
                 raise InvalidStateError(f"task contains {invalid_count} invalid results")
@@ -1731,6 +1772,7 @@ class DataProcessStore:
                 "source": "data_process",
                 "storage_backend": "database",
                 "source_task_id": task_id,
+                "output_type": _task_output_type(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",