fix(uvlock): fix uv lock file to pass pytest

.gitignore

@@ -210,4 +210,7 @@ marimo/_static/
 marimo/_lsp/
 __marimo__/
 
-logs/
+logs/
+
+data/*
+!data/README.md

apps/prepare-benchmark/common.py

@@ -18,7 +18,7 @@ class Task:
     metadata: MutableMapping[str, Any] = dataclasses.field(default_factory=dict)
 
     def to_json(self) -> bytes:
-        return json.dumps(dataclasses.asdict(self)).encode()
+        return json.dumps(dataclasses.asdict(self), ensure_ascii=False).encode()
 
     @classmethod
     def from_json(cls, b: bytes):

apps/prepare-benchmark/gen_browsecomp.py

@@ -30,7 +30,7 @@ def decrypt(ciphertext_b64: str, password: str) -> str:
     encrypted = base64.b64decode(ciphertext_b64)
     key = derive_key(password, len(encrypted))
     decrypted = bytes(a ^ b for a, b in zip(encrypted, key))
-    return decrypted.decode()
+    return decrypted.decode("utf-8")
 
 
 def gen_browsecomp_test(hf_token: str) -> Generator[Task, None, None]:
@@ -53,3 +53,26 @@ def gen_browsecomp_test(hf_token: str) -> Generator[Task, None, None]:
         )
         yield task
     return
+
+
+def gen_browsecomp_zh_test(hf_token: str) -> Generator[Task, None, None]:
+    dataset = load_dataset(
+        "PALIN2018/BrowseComp-ZH",
+        token=hf_token,
+        split="test",
+    )
+    for idx, x in enumerate(dataset):
+        metadata: MutableMapping = x
+        problem_encrypted = metadata.pop("Question")
+        answer_encrypted = metadata.pop("Answer")
+        canary = metadata.pop("canary")
+        metadata["Topic"] = decrypt(metadata["Topic"], canary)
+        task = Task(
+            task_id=str(idx),
+            task_question=decrypt(problem_encrypted, canary),
+            ground_truth=decrypt(answer_encrypted, canary),
+            file_path=None,
+            metadata=metadata,
+        )
+        yield task
+    return

apps/prepare-benchmark/gen_hle.py

@@ -0,0 +1,75 @@
+# SPDX-FileCopyrightText: 2025 MiromindAI
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import base64
+import pathlib
+from typing import Generator, MutableMapping
+
+from datasets import load_dataset
+
+from common import Task
+
+
+def save_image(image, data_dir: str, task_id: str) -> str:
+    if not image:
+        return None
+    # Ensure data_dir is absolute and resolved to avoid ugly .. in the path
+    data_dir_path = pathlib.Path(data_dir).resolve()
+    image_path = data_dir_path / "hle" / "images" / f"{task_id}.png"
+    image_path.parent.mkdir(parents=True, exist_ok=True)
+
+    # Handle different image formats
+    if isinstance(image, str):
+        # If it's a data URL, extract the base64 part
+        if image.startswith("data:"):
+            try:
+                header, b64data = image.split(",", 1)
+                image_data = base64.b64decode(b64data)
+                image_path.write_bytes(image_data)
+            except Exception as e:
+                raise ValueError(
+                    f"Cannot process image data:<class 'str'> (data URL): {e}"
+                )
+        else:
+            try:
+                image_data = base64.b64decode(image)
+                image_path.write_bytes(image_data)
+            except Exception as e:
+                raise ValueError(
+                    f"Cannot process image data:<class 'str'> (raw b64): {e}"
+                )
+    elif hasattr(image, "save"):
+        # If it's a PIL Image object
+        image.save(image_path)
+    else:
+        # Try to handle it as bytes directly
+        try:
+            image_path.write_bytes(image)
+        except Exception:
+            raise ValueError(f"Cannot process image data: {type(image)}")
+
+    return str(image_path)
+
+
+def gen_hle_test(hf_token: str, data_dir: str) -> Generator[Task, None, None]:
+    dataset = load_dataset("cais/hle", split="test", token=hf_token)
+    for x in dataset:
+        metadata: MutableMapping = x  # type: ignore
+        task_id = metadata.pop("id")
+        question = metadata.pop("question")
+        gt = metadata.pop("answer")
+        image = metadata.pop("image")  # base64 encoded image
+        image_uri = save_image(image, data_dir, task_id)
+        metadata.pop("image_preview")
+        metadata.pop("rationale_image")
+        task = Task(
+            task_id=task_id,
+            task_question=question,
+            ground_truth=gt,
+            file_path=image_uri,
+            metadata=metadata,
+        )
+        yield task
+
+    return

apps/prepare-benchmark/main.py

@@ -8,10 +8,11 @@
 import dotenv
 import fire
 
-from gen_browsecomp import gen_browsecomp_test
+from gen_browsecomp import gen_browsecomp_test, gen_browsecomp_zh_test
 from gen_frames import gen_frames_test
 from gen_gaia import gen_gaia_validation
 from gen_gaia_text_only import gen_gaia_text_only
+from gen_hle import gen_hle_test
 from gen_webwalkerqa import gen_webwalkerqa
 
 
@@ -23,6 +24,8 @@ class _Env:
         "frames-test",
         "webwalkerqa",
         "browsecomp-test",
+        "browsecomp-zh-test",
+        "hle",
     )
     meta_filename = "standardized_data.jsonl"
     data_dir: pathlib.Path
@@ -56,6 +59,13 @@ def gen():
                 for x in gen_browsecomp_test(env.hf_token):
                     yield x
 
+            return gen
+        case "browsecomp-zh-test":
+
+            def gen():
+                for x in gen_browsecomp_zh_test(env.hf_token):
+                    yield x
+
             return gen
         case "frames-test":
 
@@ -79,6 +89,13 @@ def gen():
                 for x in gen_webwalkerqa(env.hf_token):
                     yield x
 
+            return gen
+        case "hle":
+
+            def gen():
+                for x in gen_hle_test(env.hf_token, env.data_dir):
+                    yield x
+
             return gen
         case _:
             raise ValueError("not supported")

apps/prepare-benchmark/pyproject.toml

@@ -11,6 +11,7 @@ dependencies = [
     "fire>=0.7.0",
     "python-dotenv>=1.1.1",
     "requests>=2.32.4",
+    "Pillow",
 ]
 
 [dependency-groups]