Upload server/app.py with huggingface_hub

server/app.py

@@ -19,6 +19,62 @@ from openenv.core.env_server.http_server import create_app
 
 load_dotenv(os.path.join(os.path.dirname(__file__), "..", ".env"))
 
+# Override the generic Quick Start with gym-specific content
+import openenv.core.env_server.web_interface as _wi  # noqa: E402
+
+_wi.DEFAULT_QUICK_START_MARKDOWN = """
+### How to use this environment
+
+Use the **Playground** (right panel) to interact. Enter a **Tool Name** and **Arguments Json**, then click **Step**.
+
+#### 1. Start a game
+
+| Step | Tool Name | Arguments Json |
+|------|-----------|---------------|
+| Reset | Click **Reset** | — |
+| List scenarios | `list_scenarios` | `{}` |
+| Load a game | `load_scenario` | `{"scenario_id": "directional_trap_8x8"}` |
+
+#### 2. Explore the board
+
+| Tool Name | Arguments Json | What it does |
+|-----------|---------------|--------------|
+| `get_board_view` | `{}` | See the board (SVG) |
+| `get_status` | `{}` | Score, flags, progress |
+| `reveal_cell` | `{"row": 0, "col": 0}` | Uncover a cell (costs 1 step) |
+| `inspect_region` | `{"row": 3, "col": 3, "radius": 1}` | Peek without revealing |
+| `recall_log` | `{}` | Review all signals found |
+
+#### 3. Flag hazards & submit
+
+| Tool Name | Arguments Json | What it does |
+|-----------|---------------|--------------|
+| `flag_cell` | `{"row": 1, "col": 1}` | Mark as hazardous |
+| `unflag_cell` | `{"row": 1, "col": 1}` | Remove flag |
+| `submit_solution` | `{"flagged_positions": "[[0,1],[2,3]]"}` | Submit answer (ends game) |
+
+#### Available scenarios
+
+`ambiguous_cluster_10x10` · `directional_trap_8x8` · `partial_intel_9x9` · `cascading_deduction_11x11` · `safe_zone_identification_9x9` · `flash_fade_minefield_7x7` · `delayed_recall_keys_8x8` · `fog_labyrinth_10x10` · `fog_key_hunt_8x8` · `decoy_minefield_8x10`
+
+#### Connect from Python
+
+```python
+from visual_memory import VisualMemoryAction, VisualMemoryEnv
+
+with VisualMemoryEnv.from_env("<SPACE_ID>") as env:
+    obs = env.reset()
+    obs = await env.step(VisualMemoryAction(
+        tool_name="load_scenario",
+        arguments_json='{"scenario_id": "directional_trap_8x8"}'
+    ))
+```
+
+Or connect directly: `VisualMemoryEnv(base_url="http://localhost:8000")`
+
+For more information, see the [OpenEnv documentation](https://meta-pytorch.org/OpenEnv/).
+"""
+
 try:
     from visual_memory.models import VisualMemoryAction, VisualMemoryObservation
     from visual_memory.server.memory_environment import MemoryEnvironment