fix:dataset viewer

README.md

@@ -1,18 +1,24 @@
----
-license: mit
----
+---
+license: mit
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: metadata.parquet
+---
 
 # AVGen-Bench Generated Videos Data Card
 
 ## Overview
 
-This data card describes the generated audio-video outputs stored directly in the repository root by model directory.
+This data card describes the generated audio-video outputs stored directly in the repository root by model directory.
 
 The collection is intended for **benchmarking and qualitative/quantitative evaluation** of text-to-audio-video (T2AV) systems. It is not a training dataset. Each item is a model-generated video produced from a prompt defined in `prompts/*.json`.
 
-Code repository: https://github.com/microsoft/AVGen-Bench
-
-For Hugging Face Hub compatibility, the repository includes a root-level `metadata.parquet` file so the Dataset Viewer can expose each video as a structured row with prompt metadata instead of treating the repo as an unindexed file dump.
+Code repository: https://github.com/microsoft/AVGen-Bench
+
+For Hugging Face Hub compatibility, the repository includes a root-level `metadata.parquet` file so the Dataset Viewer can expose each video as a structured row with prompt metadata instead of treating the repo as an unindexed file dump.
+The relative video path is stored as a plain string column (`video_path`) rather than a media-typed `file_name` column, which avoids current Dataset Viewer post-processing failures on video rows.
 
 ## What This Dataset Contains
 
@@ -25,28 +31,28 @@ The dataset is organized by:
 A typical top-level structure is:
 
 ```text
-AVGen-Bench/
-├── Kling_2.6/
-├── LTX-2/
-├── LTX-2.3/
-├── MOVA_360p_Emu3.5/
-├── MOVA_360p_NanoBanana_2/
-├── Ovi_11/
-├── Seedance_1.5_pro/
-├── Sora_2/
-├── Veo_3.1_fast/
-├── Veo_3.1_quality/
-├── Wan_2.2_HunyuanVideo-Foley/
-├── Wan_2.6/
-├── metadata.parquet
-├── prompts/
-└── reference_image/   # optional, depending on generation pipeline
+AVGen-Bench/
+├── Kling_2.6/
+├── LTX-2/
+├── LTX-2.3/
+├── MOVA_360p_Emu3.5/
+├── MOVA_360p_NanoBanana_2/
+├── Ovi_11/
+├── Seedance_1.5_pro/
+├── Sora_2/
+├── Veo_3.1_fast/
+├── Veo_3.1_quality/
+├── Wan_2.2_HunyuanVideo-Foley/
+├── Wan_2.6/
+├── metadata.parquet
+├── prompts/
+└── reference_image/   # optional, depending on generation pipeline
 ```
 
 Within each model directory, videos are grouped by category, for example:
 
 ```text
-Veo_3.1_fast/
+Veo_3.1_fast/
 ├── ads/
 ├── animals/
 ├── asmr/
@@ -92,7 +98,7 @@ Each generated item is typically:
 
 - A single `.mp4` file
 - Containing model-generated video and, when supported by the model/pipeline, synthesized audio
-- Stored under `<model>/<category>/`
+- Stored under `<model>/<category>/`
 
 The filename is usually derived from prompt content after sanitization. Exact naming may vary by generation script or provider wrapper.
 In the standard export pipeline, the filename is derived from the prompt's `content` field using the following logic:
@@ -111,18 +117,18 @@ def safe_filename(name: str, max_len: int = 180) -> str:
 
 So the expected output path pattern is:
 
-```text
-<model>/<category>/<safe_filename(content)>.mp4
-```
-
-For Dataset Viewer indexing, `metadata.parquet` stores one row per exported video with:
-
-- `file_name`: relative path to the `.mp4`
-- `model`: model directory name
-- `category`: benchmark category
-- `content`: prompt short name
-- `prompt`: full generation prompt
-- `prompt_id`: index inside `prompts/<category>.json`
+```text
+<model>/<category>/<safe_filename(content)>.mp4
+```
+
+For Dataset Viewer indexing, `metadata.parquet` stores one row per exported video with:
+
+- `video_path`: relative path to the `.mp4` stored as a plain string
+- `model`: model directory name
+- `category`: benchmark category
+- `content`: prompt short name
+- `prompt`: full generation prompt
+- `prompt_id`: index inside `prompts/<category>.json`
 
 ## How The Data Was Produced
 

metadata.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:236f73fb879f176c4999a60838f53d1dae7a8904b070344d60802f58ecb449c9
-size 112572
+oid sha256:3e7d3f7dafd4392ae31e2ec656c4ccfb435a1f6ef234c1252e1db30fde3b57a2
+size 112574

scripts/build_hf_metadata.py

@@ -69,7 +69,7 @@ def build_rows(repo_root: Path) -> list[dict[str, object]]:
 
         rows.append(
             {
-                "file_name": rel_path,
+                "video_path": rel_path,
                 "model": model,
                 "category": category,
                 "content": prompt_record["content"] if prompt_record else filename,