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  1. README.md +88 -17
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README.md CHANGED
@@ -47,7 +47,7 @@ configs:
47
 
48
  # cua-lite/GUIOdyssey
49
 
50
- cua-lite preprocessed version of GUIOdyssey (hflqf88888/GUIOdyssey). A long-horizon cross-app Android mobile dataset of 8,334 task trajectories over ~128k screenshots. Produces two cohorts: navigation (multi-step agent episodes) and understanding (per-step screen captioning from the source `description` annotations).
51
 
52
  ## Origin
53
 
@@ -65,45 +65,114 @@ ds = load_dataset("cua-lite/GUIOdyssey")
65
  ds = load_dataset("cua-lite/GUIOdyssey", "mobile.understanding")
66
  ```
67
 
68
- You can also filter by `metadata.platform` / `metadata.task_type` /
69
- `metadata.others.*` after loading; every row carries a rich `metadata`
70
- struct (see schema below).
71
 
72
  ## Schema
73
 
74
- Each row has these columns:
75
 
76
  | column | type | notes |
77
  |---|---|---|
78
  | `images` | list[Image] | embedded PNG/JPEG bytes; HF viewer renders thumbnails |
79
- | `messages` | list[struct] | OpenAI-style turns with `role` + structured `content` |
80
- | `metadata` | struct | `{platform, task_type, extra_tool_schemas, valid_actions, others{...}}` |
 
81
 
82
  Coordinate values in `messages` are normalized to `[0, 1000]` integers.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
83
 
84
  **Image-dedup (`grounding.*` / `understanding` cohorts).** These cohorts are
85
  single-image-per-row and many rows share the same screenshot, so to avoid
86
  re-embedding identical image bytes once per instruction they are stored
87
  *folded*: one row per unique screenshot (image embedded once), carrying an
88
  extra **`_folded`** column — a JSON string with the authoritative list of
89
- `{messages, metadata}` members for that screenshot. The row's top-level
90
- `messages` is the members concatenated for viewer convenience. `use`
91
- cohorts are not folded. **Use `lite.data.hf.download` to consume this repo**
92
- it unfolds automatically back to one row per instruction; reading the parquet
93
- directly yields the folded form.
 
94
 
95
  ## Layout
96
 
97
  ```
98
- <platform>/<task_type>/<split>/shard-NNNNN-of-NNNNN.parquet # single-variant cohort
99
- <platform>/<task_type>/<split>/<variant>/shard-NNNNN-of-NNNNN.parquet # multi-variant cohort
100
  ```
101
 
102
- - `platform` ∈ {desktop, mobile, web}
103
  - `task_type` ∈ {understanding, grounding.action, grounding.point, grounding.bbox, use} — used verbatim as the dir component
104
- - HF config names are `<platform>.<task_type>` (e.g. `mobile.grounding.action`). The agent registry lookup key in code is `<agent>@<platform>@<task_type>` (e.g. `qwen3_vl@mobile@grounding.action`); only this user-facing token uses `.` between platform and task_type, because `@` triggers a 403 on the dataset-viewer's signed image URLs.
105
  - HF split names stay `train` / `validation` (the `datasets` library blacklists `<>:/\|?*` in split names; everything else is fine in config_name)
106
- - `validation` is an in-distribution held-out slice (never used in training); `test` is reserved for out-of-distribution benchmark datasets
107
 
108
  ## Stats
109
 
@@ -135,6 +204,8 @@ form directly with `--image-root=$CUA_LITE_DATASETS_ROOT`.
135
 
136
  Source `info` coordinates are already normalized to [0, 1000] (per the upstream README) and are used directly — they are NOT device pixels.
137
 
 
 
138
  ## License & citation
139
 
140
  See original dataset (hflqf88888/GUIOdyssey).
 
47
 
48
  # cua-lite/GUIOdyssey
49
 
50
+ cua-lite preprocessed version of GUIOdyssey (hflqf88888/GUIOdyssey). A long-horizon cross-app Android mobile dataset of 8,334 task trajectories over ~128k screenshots. Produces two cohorts: use (multi-step agent episodes) and understanding (per-step screen captioning from the source `description` annotations).
51
 
52
  ## Origin
53
 
 
65
  ds = load_dataset("cua-lite/GUIOdyssey", "mobile.understanding")
66
  ```
67
 
68
+ After loading, parse `metadata` as JSON before filtering by `metadata_kind`,
69
+ `dims`, or `others.*`; every row carries a rich metadata object inside that JSON
70
+ string (see schema below). CUA rows use `dims == [platform, task_type]`.
71
 
72
  ## Schema
73
 
74
+ Published parquet columns:
75
 
76
  | column | type | notes |
77
  |---|---|---|
78
  | `images` | list[Image] | embedded PNG/JPEG bytes; HF viewer renders thumbnails |
79
+ | `messages` | string (JSON array) | parse as JSON to OpenAI-style turns with `role`, structured `content`, nested `tool_calls`, and `role:"tool"` results |
80
+ | `metadata` | string (JSON object) | parse as JSON to fields `metadata_kind`, `dims`, `extra_tool_schemas`, CUA-only `valid_actions`, and `others` |
81
+ | `_folded` | string (JSON array, optional) | folded grounding/understanding rows only; authoritative per-instruction `messages` / `metadata` members |
82
 
83
  Coordinate values in `messages` are normalized to `[0, 1000]` integers.
84
+ The JSON examples below show the decoded shape, not the raw string cell.
85
+
86
+ `metadata.extra_tool_schemas[*]` uses the nested Chat Completions function-tool
87
+ declaration shape:
88
+
89
+ ```json
90
+ {
91
+ "metadata_kind": "cua",
92
+ "dims": ["desktop", "use"],
93
+ "extra_tool_schemas": [
94
+ {
95
+ "type": "function",
96
+ "function": {
97
+ "name": "bash",
98
+ "description": "Run a shell command.",
99
+ "parameters": {
100
+ "type": "object",
101
+ "properties": {"cmd": {"type": "string"}},
102
+ "required": ["cmd"]
103
+ }
104
+ }
105
+ }
106
+ ],
107
+ "valid_actions": ["click", "type"],
108
+ "others": {}
109
+ }
110
+ ```
111
+
112
+ `messages[].tool_calls[*]` uses the matching nested invocation shape. Tool
113
+ results pair `tool_calls[].id` with `role:"tool"` `tool_call_id`:
114
+
115
+ ```json
116
+ [
117
+ {
118
+ "role": "user",
119
+ "content": [
120
+ {"type": "image", "index": 0},
121
+ {"type": "text", "text": "Click the OK button."}
122
+ ]
123
+ },
124
+ {
125
+ "role": "assistant",
126
+ "tool_calls": [
127
+ {
128
+ "id": "call_0000",
129
+ "type": "function",
130
+ "function": {
131
+ "name": "computer",
132
+ "arguments": {
133
+ "actions": [
134
+ {"action": "click", "coordinate": [640, 400]},
135
+ {"action": "type", "text": "hello"}
136
+ ]
137
+ }
138
+ }
139
+ }
140
+ ]
141
+ },
142
+ {
143
+ "role": "tool",
144
+ "tool_call_id": "call_0000",
145
+ "content": [
146
+ {"type": "image", "index": 1},
147
+ {"type": "text", "text": "clicked; typed"}
148
+ ]
149
+ }
150
+ ]
151
+ ```
152
 
153
  **Image-dedup (`grounding.*` / `understanding` cohorts).** These cohorts are
154
  single-image-per-row and many rows share the same screenshot, so to avoid
155
  re-embedding identical image bytes once per instruction they are stored
156
  *folded*: one row per unique screenshot (image embedded once), carrying an
157
  extra **`_folded`** column — a JSON string with the authoritative list of
158
+ per-instruction members for that screenshot. Each member's `messages` and
159
+ `metadata` values are the same opaque JSON strings described above. The row's
160
+ top-level `messages` is a JSON string containing the members concatenated for
161
+ viewer convenience. `use` cohorts are not folded. **Use
162
+ `lite.data.hf.download` to consume this repo** — it unfolds automatically back
163
+ to one row per instruction; reading the parquet directly yields the folded form.
164
 
165
  ## Layout
166
 
167
  ```
168
+ <platform>/<task_type>/<split>/<variant>/shard-NNNNN-of-NNNNN.parquet
 
169
  ```
170
 
171
+ - `platform` ∈ {desktop, browser, mobile}
172
  - `task_type` ∈ {understanding, grounding.action, grounding.point, grounding.bbox, use} — used verbatim as the dir component
173
+ - HF config names are `<platform>.<task_type>` by default (e.g. `mobile.grounding.action`) — UNLESS the dataset was staged with `--config-names`, which sets verbatim, explicitly-chosen config names (see the `configs:` block above for the authoritative list). The agent registry lookup key in code is `<agent>@<platform>@<task_type>` (e.g. `qwen3_vl@mobile@grounding.action`); only this user-facing token uses `.` between platform and task_type, because `@` triggers a 403 on the dataset-viewer's signed image URLs.
174
  - HF split names stay `train` / `validation` (the `datasets` library blacklists `<>:/\|?*` in split names; everything else is fine in config_name)
175
+ - `validation` is an in-distribution held-out slice: no validation **sample** also appears in `train` — content-identical rows (same `images` + same `messages`, differing only in their ids) are co-located into one split, so upstream re-publishing one sample under two ids cannot straddle the split. It is *not* disjoint in **images**: one screenshot legitimately backs many distinct samples, and only whole samples are co-located, so the same picture can appear on both sides. `test` is reserved for out-of-distribution benchmark datasets
176
 
177
  ## Stats
178
 
 
204
 
205
  Source `info` coordinates are already normalized to [0, 1000] (per the upstream README) and are used directly — they are NOT device pixels.
206
 
207
+ split: content-identical rows co-located, then hash_split on metadata.others.id with val_frac=0.02, seed=42, val_cap=2000 per (metadata.dims[0], metadata.dims[1], variant) (an upstream split label, where the source ships one, wins over the hash). A cap-bound carve depends on source iteration order and these parameters do not reproduce it; content co-location may make the final physical validation row count differ from the cap.
208
+
209
  ## License & citation
210
 
211
  See original dataset (hflqf88888/GUIOdyssey).
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