优化标注代码，修复图片训练处理问题

backend/app/engines/vision_engine.py

@@ -80,11 +80,25 @@ class VisionEngine(BaseEngine):
     async def preprocess_dataset(
         self, dataset_path: str, output_path: str, **kwargs: Any
     ) -> str:
-        """图像数据集预处理（提取 image_path + label）。"""
-        from app.preprocessors import preprocess_file
-
-        processed = preprocess_file(dataset_path, output_path, "sft", "raw")
-        logger.info(f"Preprocessed {len(processed)} vision samples")
+        """图像数据集预处理：直接透传 image_path + label，不做文本模板转换。"""
+        data = []
+        with open(dataset_path, "r", encoding="utf-8") as f:
+            for line in f:
+                line = line.strip()
+                if line:
+                    try:
+                        data.append(json.loads(line))
+                    except json.JSONDecodeError:
+                        continue
+
+        # 写入输出（保留 image_path / label 等字段原样）
+        output_p = Path(output_path)
+        output_p.parent.mkdir(parents=True, exist_ok=True)
+        with open(output_path, "w", encoding="utf-8") as f:
+            for item in data:
+                f.write(json.dumps(item, ensure_ascii=False) + "\n")
+
+        logger.info(f"Preprocessed {len(data)} vision samples")
         return output_path
 
     async def train(

backend/app/services/annotation_platform_service.py

@@ -5,9 +5,10 @@
 功能：列出项目、获取项目详情、数据集导出与下载。
 """
 
+import asyncio
 import hashlib
 import hmac
-import secrets
+import json
 import time
 import uuid
 from datetime import datetime
@@ -45,7 +46,7 @@ def _build_token_headers() -> dict[str, str]:
     """构建获取 Token 的 HMAC-SHA256 签名请求头。"""
     app_id, app_secret = _get_credentials()
     timestamp = str(int(time.time()))
-    nonce = uuid.uuid4().hex  # 使用 uuid4 保证每次唯一，16+ 位随机字符串
+    nonce = uuid.uuid4().hex
     message = app_id + timestamp + nonce
     signature = hmac.new(
         key=app_secret.encode("utf-8"),
@@ -71,11 +72,7 @@ def _is_token_valid() -> bool:
 
 
 async def _refresh_token() -> str:
-    """使用 Bearer Token 刷新 Access Token。
-
-    POST /api/v1/open/auth/refresh
-    比重新签名更高效，仅在 Token 存在但即将过期时调用。
-    """
+    """使用 Bearer Token 刷新 Access Token。"""
     old_token = _token_cache.get("access_token", "")
     base_url = _get_base_url()
 
@@ -92,20 +89,13 @@ async def _refresh_token() -> str:
 
     data = body.get("data", {})
     _token_cache["access_token"] = data["access_token"]
-    _token_cache["expires_in"] = data.get("expires_in", 7200)
     _token_cache["expires_at"] = time.time() + data.get("expires_in", 7200)
 
     return data["access_token"]
 
 
 async def get_token() -> str:
-    """获取 Access Token，带缓存和自动刷新。
-
-    优先级：
-    1. Token 有效 → 直接返回
-    2. Token 存在但快过期 → 调用 /auth/refresh 刷新
-    3. 无 Token → 调用 /auth/token 重新签名获取
-    """
+    """获取 Access Token，带缓存和自动刷新。"""
     if _is_token_valid():
         return _token_cache["access_token"]
 
@@ -129,13 +119,11 @@ async def get_token() -> str:
         resp.raise_for_status()
         body = resp.json()
 
-    # 标注平台返回 code: 0 表示成功
     if body.get("code") != 0:
         raise RuntimeError(f"获取标注平台 Token 失败: {body.get('message', body)}")
 
     data = body.get("data", {})
     _token_cache["access_token"] = data["access_token"]
-    _token_cache["expires_in"] = data.get("expires_in", 7200)
     _token_cache["expires_at"] = time.time() + data.get("expires_in", 7200)
 
     return data["access_token"]
@@ -149,10 +137,12 @@ def _auth_headers() -> dict[str, str]:
     }
 
 
-async def _request(method: str, path: str, raise_on_error: bool = True, **kwargs) -> dict[str, Any]:
+async def _request(
+    method: str, path: str, *, raise_on_error: bool = True, **kwargs
+) -> dict[str, Any]:
     """统一的业务请求方法，自动携带 Token。
 
-    raise_on_error=False 时，400 等错误不抛异常，返回原始响应体。
+    raise_on_error=False 时，HTTP 4xx/5xx 不抛异常，返回带 _error 标记的 dict。
     """
     await get_token()
     base_url = _get_base_url()
@@ -169,7 +159,7 @@ async def _request(method: str, path: str, raise_on_error: bool = True, **kwargs
             try:
                 body = resp.json()
             except Exception:
-                body = {"status_code": resp.status_code, "text": resp.text}
+                body = {"message": resp.text}
             return {"_error": True, "_status_code": resp.status_code, **body}
 
         resp.raise_for_status()
@@ -190,10 +180,7 @@ async def list_projects(
     project_type: str | None = None,
     status: str | None = None,
 ) -> dict[str, Any]:
-    """获取标注平台项目列表。
-
-    GET /api/v1/open/projects
-    """
+    """获取标注平台项目列表。"""
     params: dict[str, Any] = {"page": page, "page_size": page_size}
     if name:
         params["name"] = name
@@ -208,15 +195,71 @@ async def list_projects(
 # ---------- 项目详情 ----------
 
 async def get_project_detail(project_id: str) -> dict[str, Any]:
-    """获取项目详情。
-
-    GET /api/v1/open/projects/{project_id}
-    """
+    """获取项目详情。"""
     return await _request("GET", f"/api/v1/open/projects/{project_id}")
 
 
 # ---------- 数据集导出与下载 ----------
 
+# 文本项目和图片项目支持的导出格式（参考标注平台 API 文档）
+_TEXT_FORMATS = ["alpaca", "sharegpt"]
+_IMAGE_FORMATS = ["json", "csv", "coco"]
+
+
+async def _request_export(project_id: str, fmt: str) -> dict[str, Any] | None:
+    """请求导出并返回导出信息，格式不兼容或失败时返回 None。"""
+    data = await _request(
+        "POST",
+        f"/api/v1/open/projects/{project_id}/datasets/download",
+        raise_on_error=False,
+        json={"format": fmt, "completed_only": True},
+    )
+
+    if data.get("_error"):
+        logger.info(f"导出格式 '{fmt}' 不可用: {data.get('message', data.get('detail', ''))}")
+        return None
+
+    if data.get("status") != "completed":
+        logger.info(f"导出格式 '{fmt}' 状态异常: {data.get('status')}")
+        return None
+
+    if not data.get("file_url"):
+        logger.info(f"导出格式 '{fmt}' 未返回下载链接")
+        return None
+
+    return data
+
+
+async def _download_file(download_token: str, max_retries: int = 3) -> bytes:
+    """通过 download_token 下载导出文件，带重试（标注平台可能需要时间生成文件）。"""
+    await get_token()
+    base_url = _get_base_url()
+    url = f"{base_url}/api/v1/open/datasets/downloads/{download_token}"
+
+    for attempt in range(max_retries):
+        async with httpx.AsyncClient(timeout=120) as client:
+            resp = await client.get(url, headers=_auth_headers(), follow_redirects=True)
+            resp.raise_for_status()
+            content = resp.content
+
+        if len(content) > 10:
+            return content
+
+        if attempt < max_retries - 1:
+            wait = 2 ** attempt  # 1, 2 秒
+            logger.info(f"文件尚未就绪 ({len(content)} bytes)，{wait}s 后重试...")
+            await asyncio.sleep(wait)
+
+    return content
+
+
+def _extract_download_token(file_url: str) -> str:
+    """从 file_url 中提取 download_token。"""
+    if "/datasets/downloads/" in file_url:
+        return file_url.split("/datasets/downloads/")[-1].strip("/")
+    return file_url.rstrip("/").split("/")[-1]
+
+
 async def import_project_dataset(
     project_id: str,
     project_name: str = "",
@@ -225,144 +268,58 @@ async def import_project_dataset(
     """导出并下载项目数据集，保存到本地并写入数据库。
 
     流程：
-    1. 查询项目详情获取 task_type
-    2. POST /api/v1/open/projects/{project_id}/datasets/download → 获取 file_url
-    3. GET /api/v1/open/datasets/downloads/{download_token} → 下载文件
-    4. 保存到 uploads 目录
-    5. 写入 DatasetRecord 数据库
+    1. 查询项目详情获取 project_type
+    2. 根据项目类型选择合适的导出格式，依次尝试
+    3. 下载文件并转换为 JSONL
+    4. 写入数据库
     """
-    # 1. 查询项目详情，获取 task_type 和 project_type
+    # 1. 查询项目类型，决定可用格式
     try:
-        project_detail = await get_project_detail(project_id)
-        task_type = project_detail.get("task_type", "")
-        project_type = project_detail.get("project_type", "text")
-        logger.info(f"Project {project_id}: task_type={task_type}, project_type={project_type}")
-    except Exception as e:
-        logger.warning(f"Failed to get project detail: {e}, using default formats")
-        task_type = ""
+        detail = await get_project_detail(project_id)
+        project_type = detail.get("project_type", "text")
+    except Exception:
         project_type = "text"
 
-    # 2. 根据项目类型选择导出格式
-    # 文本项目: alpaca / sharegpt
-    # 图片项目: json / csv / coco / yolo / pascal_voc
+    # 2. 构建格式尝试列表（用户指定的格式优先）
     if project_type == "text":
-        formats_to_try = ["alpaca", "sharegpt"]
+        formats_to_try = list(_TEXT_FORMATS)
     else:
-        formats_to_try = ["json", "csv", "coco"]
+        formats_to_try = list(_IMAGE_FORMATS)
 
-    # 如果用户指定了格式，优先使用
     if format and format not in formats_to_try:
         formats_to_try.insert(0, format)
 
+    # 3. 依次尝试各格式：请求导出 → 下载文件
     file_content = b""
-    file_name = ""
     total_exported = 0
     used_format = ""
-    last_error = ""
-
-    for try_format in formats_to_try:
-        # 请求导出
-        export_data = await _request(
-            "POST",
-            f"/api/v1/open/projects/{project_id}/datasets/download",
-            raise_on_error=False,
-            json={"format": try_format, "completed_only": True},
-        )
 
-        # 检查是否返回错误
-        if export_data.get("_error"):
-            status_code = export_data.get("_status_code", 0)
-            error_msg = export_data.get("message", export_data)
-            last_error = f"HTTP {status_code}: {error_msg}"
-            logger.warning(f"Format '{try_format}' failed: {last_error}, trying next...")
+    for fmt in formats_to_try:
+        export_data = await _request_export(project_id, fmt)
+        if not export_data:
             continue
 
-        logger.info(f"Annotation export response (format={try_format}): {export_data}")
-
-        file_url = export_data.get("file_url", "")
-        file_name = export_data.get("file_name", f"{project_id}_{try_format}.json")
         total_exported = export_data.get("total_exported", 0)
-        export_status = export_data.get("status", "completed")
-
-        # 检查导出状态
-        if export_status != "completed":
-            logger.warning(f"Export status={export_status} for format={try_format}, trying next...")
-            last_error = f"导出状态: {export_status}"
-            continue
-
-        if not file_url:
-            logger.warning(f"No file_url for format={try_format}, trying next...")
-            last_error = "未返回下载链接"
-            continue
-
-        # 从 file_url 中提取 download_token
-        if "/datasets/downloads/" in file_url:
-            download_token = file_url.split("/datasets/downloads/")[-1].strip("/")
-        else:
-            download_token = file_url.rstrip("/").split("/")[-1]
-
-        # 下载文件，带轮询（标注平台生成文件可能需要时间）
-        await get_token()
-        base_url = _get_base_url()
-        download_url = f"{base_url}/api/v1/open/datasets/downloads/{download_token}"
-
-        file_content = b""
-        max_retries = 4
-        for attempt in range(max_retries):
-            async with httpx.AsyncClient(timeout=120) as client:
-                resp = await client.get(
-                    download_url,
-                    headers=_auth_headers(),
-                    follow_redirects=False,
-                )
-                redirect_count = 0
-                while resp.is_redirect and redirect_count < 5:
-                    redirect_url = resp.next_request.url
-                    logger.info(f"Download redirect to: {redirect_url}")
-                    resp = await client.get(
-                        str(redirect_url),
-                        headers=_auth_headers(),
-                        follow_redirects=False,
-                    )
-                    redirect_count += 1
-                resp.raise_for_status()
-                file_content = resp.content
-
-            if len(file_content) > 10:
-                break
-
-            if attempt < max_retries - 1:
-                import asyncio
-                wait = 2 ** attempt  # 1, 2, 4 秒
-                logger.info(
-                    f"Download attempt {attempt + 1}/{max_retries} (format={try_format}): "
-                    f"file too small ({len(file_content)} bytes), retrying in {wait}s..."
-                )
-                await asyncio.sleep(wait)
-
-        logger.info(
-            f"Downloaded (format={try_format}): {len(file_content)} bytes, "
-            f"content_type={resp.headers.get('content-type', 'unknown')}"
-        )
+        download_token = _extract_download_token(export_data["file_url"])
+        file_content = await _download_file(download_token)
 
         if len(file_content) > 10:
-            used_format = try_format
+            used_format = fmt
+            logger.info(
+                f"标注平台导出成功: format={fmt}, {len(file_content)} bytes, "
+                f"total_exported={total_exported}"
+            )
             break
 
-        logger.warning(
-            f"Format '{try_format}' returned empty file ({len(file_content)} bytes), "
-            f"trying next format..."
-        )
-        last_error = f"格式 {try_format} 导出文件为空"
+        logger.info(f"格式 '{fmt}' 导出文件为空 ({len(file_content)} bytes)，尝试下一格式")
 
     if len(file_content) <= 10:
-        logger.warning(f"Annotation file content: {file_content!r}")
         raise RuntimeError(
-            f"标注平台导出文件为空（task_type={task_type}, 尝试了格式: {formats_to_try}），"
-            f"total_exported={total_exported}。最后错误: {last_error}"
+            f"标注平台所有导出格式均返回空文件（project_type={project_type}，"
+            f"尝试格式: {formats_to_try}），请检查标注平台该项目的数据是否支持导出"
         )
 
-    # 保存到 uploads 目录
+    # 4. 保存到 uploads 目录
     upload_dir = settings.uploads_dir
     upload_dir.mkdir(parents=True, exist_ok=True)
 
@@ -373,13 +330,11 @@ async def import_project_dataset(
 
     file_path.write_bytes(file_content)
 
-    # 统一转为 JSONL 格式
+    # 5. 转为 JSONL 格式
     jsonl_path = _convert_to_jsonl(file_path)
     record_count = _count_records(jsonl_path, "jsonl")
 
-    logger.info(f"Annotation file converted: {jsonl_path.name}, record_count={record_count}, format={used_format}")
-
-    # 6. 写入数据库（格式统一为 jsonl）
+    # 6. 写入数据库
     record_id = str(uuid.uuid4())
     record = DatasetRecord(
         id=record_id,
@@ -393,7 +348,7 @@ async def import_project_dataset(
         session.add(record)
         await session.commit()
 
-    logger.info(f"Imported dataset from annotation platform: {project_id} -> {jsonl_path.name} ({record_count} records)")
+    logger.info(f"Imported annotation dataset: {project_name} ({record_count} records, format={used_format})")
 
     return {
         "project_id": project_id,
@@ -407,8 +362,6 @@ async def import_project_dataset(
 
 def _convert_to_jsonl(file_path: Path) -> Path:
     """将 JSON/JSONL 文件统一转为 JSONL 格式。"""
-    import json as _json
-
     jsonl_path = file_path.with_suffix(".jsonl")
     with open(file_path, "r", encoding="utf-8") as f:
         content = f.read().strip()
@@ -418,46 +371,21 @@ def _convert_to_jsonl(file_path: Path) -> Path:
         return jsonl_path
 
     try:
-        # 尝试作为 JSON 解析
-        data = _json.loads(content)
-        if isinstance(data, list):
-            # JSON 数组
-            items = data
-        elif isinstance(data, dict):
-            # JSON 对象：查找嵌套的数组字段
-            items = None
-            for key in ("data", "items", "results", "records", "annotations", "samples"):
-                if key in data and isinstance(data[key], list):
-                    items = data[key]
-                    break
-            if items is None:
-                # 单个对象，包装为数组
-                items = [data]
-        else:
-            items = None
-
+        data = json.loads(content)
+        items = _extract_items(data)
         if items is not None:
             with open(jsonl_path, "w", encoding="utf-8") as out:
                 for item in items:
-                    out.write(_json.dumps(item, ensure_ascii=False) + "\n")
-            # 只有当原始文件与新文件不同时才删除（避免删除刚写入的文件）
+                    out.write(json.dumps(item, ensure_ascii=False) + "\n")
             if jsonl_path != file_path and file_path.exists():
                 file_path.unlink()
             return jsonl_path
-    except _json.JSONDecodeError:
+    except json.JSONDecodeError:
         pass
 
-    # 不是标准 JSON，可能是 JSONL，逐行验证
-    lines = content.split("\n")
-    valid_lines = []
-    for line in lines:
-        line = line.strip()
-        if line:
-            try:
-                _json.loads(line)
-                valid_lines.append(line)
-            except _json.JSONDecodeError:
-                continue  # 跳过无效行
+    # JSONL 逐行验证
+    valid_lines = [line.strip() for line in content.split("\n") if line.strip()]
+    valid_lines = [line for line in valid_lines if _is_valid_json(line)]
 
     with open(jsonl_path, "w", encoding="utf-8") as out:
         out.write("\n".join(valid_lines) + ("\n" if valid_lines else ""))
@@ -466,24 +394,28 @@ def _convert_to_jsonl(file_path: Path) -> Path:
     return jsonl_path
 
 
-def _detect_format(filename: str) -> str:
-    """根据文件名推断格式。"""
-    name = filename.lower()
-    if name.endswith(".jsonl"):
-        return "jsonl"
-    if name.endswith(".csv"):
-        return "csv"
-    if name.endswith(".parquet"):
-        return "parquet"
-    if name.endswith(".json"):
-        return "json"
-    return "json"
+def _extract_items(data) -> list | None:
+    """从 JSON 数据中提取记录列表。"""
+    if isinstance(data, list):
+        return data
+    if isinstance(data, dict):
+        for key in ("data", "items", "results", "records", "annotations", "samples"):
+            if key in data and isinstance(data[key], list):
+                return data[key]
+        return [data]
+    return None
+
+
+def _is_valid_json(s: str) -> bool:
+    try:
+        json.loads(s)
+        return True
+    except json.JSONDecodeError:
+        return False
 
 
 def _count_records(file_path: Path, fmt: str) -> int:
     """计算文件中的记录数。"""
-    import json
-
     if not file_path.exists():
         return 0
 
@@ -494,9 +426,7 @@ def _count_records(file_path: Path, fmt: str) -> int:
         elif fmt == "json":
             with open(file_path, "r", encoding="utf-8") as f:
                 data = json.load(f)
-            if isinstance(data, list):
-                return len(data)
-            return 1
+            return len(data) if isinstance(data, list) else 1
         elif fmt == "csv":
             import csv
             with open(file_path, "r", encoding="utf-8") as f:

result.txt

@@ -1,23 +1,30 @@
-2026-05-28 09:01:22 | INFO     | httpx | HTTP Request: POST http://192.168.92.61:8003/api/v1/open/auth/token "HTTP/1.1 200 OK"
-2026-05-28 09:01:22 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/projects?page=1&page_size=20 "HTTP/1.1 200 OK"
-INFO:     172.20.0.4:40246 - "GET /api/v1/annotation-platform/projects?page=1&page_size=20 HTTP/1.0" 200 OK
-2026-05-28 09:01:24 | INFO     | httpx | HTTP Request: POST http://192.168.92.61:8003/api/v1/open/projects/proj_2e8e2373469c/datasets/download "HTTP/1.1 200 OK"
-2026-05-28 09:01:24 | INFO     | peft-platform | Annotation export (completed_only=True): total_exported=4, file_url=/api/v1/open/datasets/downloads/dl_692c3a34d6fa, file_name=proj_2e8e2373469c_alpaca_20260528_090124.json
-2026-05-28 09:01:24 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:24 | INFO     | peft-platform | Download attempt 1/6: file too small (2 bytes), retrying in 1s...
-2026-05-28 09:01:25 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:25 | INFO     | peft-platform | Download attempt 2/6: file too small (2 bytes), retrying in 2s...
-INFO:     127.0.0.1:46024 - "GET /health HTTP/1.1" 200 OK
-2026-05-28 09:01:27 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:27 | INFO     | peft-platform | Download attempt 3/6: file too small (2 bytes), retrying in 4s...
-2026-05-28 09:01:31 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:31 | INFO     | peft-platform | Download attempt 4/6: file too small (2 bytes), retrying in 8s...
-2026-05-28 09:01:39 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:39 | INFO     | peft-platform | Download attempt 5/6: file too small (2 bytes), retrying in 16s...
-2026-05-28 09:01:55 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_692c3a34d6fa "HTTP/1.1 200 OK"
-2026-05-28 09:01:55 | WARNING  | peft-platform | Download failed after 6 attempts, file still empty
-2026-05-28 09:01:55 | INFO     | peft-platform | Downloaded annotation file: 2 bytes, content_type=application/json, redirects=0
-2026-05-28 09:01:55 | WARNING  | peft-platform | Annotation file content suspiciously small: b'[]'
-2026-05-28 09:01:55 | INFO     | peft-platform | Annotation file converted: eaacdd59_计算机实体标注_.jsonl, record_count=0
-2026-05-28 09:01:55 | INFO     | peft-platform | Imported dataset from annotation platform: proj_2e8e2373469c -> eaacdd59_计算机实体标注_.jsonl (0 records)
-INFO:     172.20.0.4:59282 - "POST /api/v1/annotation-platform/projects/proj_2e8e2373469c/import?project_name=%E8%AE%A1%E7%AE%97%E6%9C%BA%E5%AE%9E%E4%BD%93%E6%A0%87%E6%B3%A8%20&format=alpaca HTTP/1.0" 200 OK
+INFO:     127.0.0.1:52806 - "GET /health HTTP/1.1" 200 OK
+2026-05-28 09:09:24 | INFO     | httpx | HTTP Request: POST http://192.168.92.61:8003/api/v1/open/auth/token "HTTP/1.1 200 OK"
+2026-05-28 09:09:24 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/projects?page=1&page_size=20 "HTTP/1.1 200 OK"
+INFO:     172.20.0.4:34814 - "GET /api/v1/annotation-platform/projects?page=1&page_size=20 HTTP/1.0" 200 OK
+2026-05-28 09:09:25 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/projects/proj_2e8e2373469c "HTTP/1.1 200 OK"
+2026-05-28 09:09:25 | INFO     | peft-platform | Project proj_2e8e2373469c: task_type=ner, project_type=text
+2026-05-28 09:09:25 | INFO     | httpx | HTTP Request: POST http://192.168.92.61:8003/api/v1/open/projects/proj_2e8e2373469c/datasets/download "HTTP/1.1 200 OK"
+2026-05-28 09:09:25 | INFO     | peft-platform | Annotation export response (format=alpaca): {'project_id': 'proj_2e8e2373469c', 'format': 'alpaca', 'total_exported': 4, 'file_url': '/api/v1/open/datasets/downloads/dl_8477a8c1c9a0', 'file_name': 'proj_2e8e2373469c_alpaca_20260528_090925.json', 'file_size': 2, 'expires_at': '2026-05-28T11:09:25.720776Z', 'status': 'completed'}
+2026-05-28 09:09:25 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_8477a8c1c9a0 "HTTP/1.1 200 OK"
+2026-05-28 09:09:25 | INFO     | peft-platform | Download attempt 1/4 (format=alpaca): file too small (2 bytes), retrying in 1s...
+2026-05-28 09:09:26 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_8477a8c1c9a0 "HTTP/1.1 200 OK"
+2026-05-28 09:09:26 | INFO     | peft-platform | Download attempt 2/4 (format=alpaca): file too small (2 bytes), retrying in 2s...
+2026-05-28 09:09:28 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_8477a8c1c9a0 "HTTP/1.1 200 OK"
+2026-05-28 09:09:28 | INFO     | peft-platform | Download attempt 3/4 (format=alpaca): file too small (2 bytes), retrying in 4s...
+2026-05-28 09:09:32 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_8477a8c1c9a0 "HTTP/1.1 200 OK"
+2026-05-28 09:09:32 | INFO     | peft-platform | Downloaded (format=alpaca): 2 bytes, content_type=application/json
+2026-05-28 09:09:32 | WARNING  | peft-platform | Format 'alpaca' returned empty file (2 bytes), trying next format...
+2026-05-28 09:09:32 | INFO     | httpx | HTTP Request: POST http://192.168.92.61:8003/api/v1/open/projects/proj_2e8e2373469c/datasets/download "HTTP/1.1 200 OK"
+2026-05-28 09:09:32 | INFO     | peft-platform | Annotation export response (format=sharegpt): {'project_id': 'proj_2e8e2373469c', 'format': 'sharegpt', 'total_exported': 4, 'file_url': '/api/v1/open/datasets/downloads/dl_4bf4c529bde9', 'file_name': 'proj_2e8e2373469c_sharegpt_20260528_090932.json', 'file_size': 2, 'expires_at': '2026-05-28T11:09:32.845246Z', 'status': 'completed'}
+2026-05-28 09:09:32 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_4bf4c529bde9 "HTTP/1.1 200 OK"
+2026-05-28 09:09:32 | INFO     | peft-platform | Download attempt 1/4 (format=sharegpt): file too small (2 bytes), retrying in 1s...
+2026-05-28 09:09:33 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_4bf4c529bde9 "HTTP/1.1 200 OK"
+2026-05-28 09:09:33 | INFO     | peft-platform | Download attempt 2/4 (format=sharegpt): file too small (2 bytes), retrying in 2s...
+2026-05-28 09:09:35 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_4bf4c529bde9 "HTTP/1.1 200 OK"
+2026-05-28 09:09:35 | INFO     | peft-platform | Download attempt 3/4 (format=sharegpt): file too small (2 bytes), retrying in 4s...
+2026-05-28 09:09:39 | INFO     | httpx | HTTP Request: GET http://192.168.92.61:8003/api/v1/open/datasets/downloads/dl_4bf4c529bde9 "HTTP/1.1 200 OK"
+2026-05-28 09:09:39 | INFO     | peft-platform | Downloaded (format=sharegpt): 2 bytes, content_type=application/json
+2026-05-28 09:09:39 | WARNING  | peft-platform | Format 'sharegpt' returned empty file (2 bytes), trying next format...
+2026-05-28 09:09:39 | WARNING  | peft-platform | Annotation file content: b'[]'
+INFO:     172.20.0.4:41202 - "POST /api/v1/annotation-platform/projects/proj_2e8e2373469c/import?project_name=%E8%AE%A1%E7%AE%97%E6%9C%BA%E5%AE%9E%E4%BD%93%E6%A0%87%E6%B3%A8%20&format=alpaca HTTP/1.0" 502 Bad Gateway