aded

DataCleanser

@@ -0,0 +1 @@
+Subproject commit 3e6e35f31acfb8a4a3df2a0310b429d1134626e2

README.md

@@ -1,6 +1,8 @@
 ---
-title: OpenEnv Data Cleaning Environment
-emoji: 🧼
+
+## title: OpenEnv Data Cleaning Environment
+emoji: 🧼  
+
 colorFrom: blue
 colorTo: green
 sdk: docker
@@ -12,7 +14,6 @@ tags:
   - openenv
   - data-cleaning
   - data-validation
----
 
 ## What this is
 
@@ -39,7 +40,7 @@ Agents must iteratively apply safe transformations (imputation, deduplication, n
 - **medium_001**: missing values + format inconsistencies + invalid ranges (employee table)
 - **hard_001**: missing values + duplicates + mixed date/currency formats + cross-field constraints + outliers (sales table)
 
-On `submit`, the grader returns a **score in \([0.0, 1.0]\)** in `info.grade.final_score`.
+On `submit`, the grader returns a **score in [0.0, 1.0]** in `info.grade.final_score`.
 
 ## Action space
 
@@ -144,15 +145,16 @@ docker exec -it $(docker ps -q --filter ancestor=datacleanser | head -n 1) \
 
 1. Create a Space → **SDK: Docker**
 2. Push these files to the Space repo:
-   - `Dockerfile`
-   - `.dockerignore`
-   - `requirements.txt`
-   - `app.py`
-   - `env/`, `agent/`, `data/` (optional; datasets are generated on startup)
-   - `README.md` (this file)
+  - `Dockerfile`
+  - `.dockerignore`
+  - `requirements.txt`
+  - `app.py`
+  - `env/`, `agent/`, `data/` (optional; datasets are generated on startup)
+  - `README.md` (this file)
 3. The Space will build and start automatically on port **7860**.
 
 ## Notes
 
 - The server generates datasets on startup (see `app.py` startup event).
 - For baseline agent runs (outside Spaces), set `OPENAI_API_KEY` and use `inference.py`.
+