fix(space): install only what the server imports, and declare the right port

Dockerfile

@@ -6,8 +6,8 @@ RUN apt-get update && apt-get install -y \
     gcc \
     && rm -rf /var/lib/apt/lists/*
 
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+COPY requirements-serve.txt .
+RUN pip install --no-cache-dir -r requirements-serve.txt
 
 COPY . .
 

README.md

@@ -4,10 +4,12 @@ emoji: 🗄️
 colorFrom: indigo
 colorTo: blue
 sdk: docker
-app_file: server/app.py
+app_port: 7860
 pinned: false
 tags:
   - openenv
+  - agent-environment
+  - rl-environment
   - sql
   - world-modeling
   - llm-training

requirements-serve.txt

@@ -0,0 +1,7 @@
+# What the environment server actually imports. Installed into the Space image.
+# Kept as its own file, and included by requirements.txt below, so the two
+# cannot drift: the image and the full install share one definition of these.
+fastapi==0.115.0
+uvicorn[standard]==0.30.6
+pydantic==2.8.2
+duckdb>=0.10.0

requirements.txt

@@ -1,12 +1,16 @@
-fastapi==0.115.0
-uvicorn[standard]==0.30.6
-pydantic==2.8.2
+# Serving dependencies, shared with the Space image. One definition, included
+# rather than repeated.
+-r requirements-serve.txt
+
+# Client and evaluation scripts (inference.py, baseline_runner.py).
 openai>=1.0.0
 pyyaml==6.0.2
 requests==2.32.3
 openenv-core>=0.2.0
-duckdb>=0.10.0
-# Training dependencies
+
+# Training only (train.py, scripts/ablation.py). Deliberately absent from the
+# Space image: no served module imports any of these, and installing torch into
+# the image took minutes and gigabytes for code the server never runs.
 trl>=0.8.0
 transformers>=4.40.0
 torch>=2.1.0