feat(server): add FastAPI server with all OpenEnv endpoints

server/app.py — uvicorn FastAPI app on port 7860:
POST /reset — start new episode, accepts optional {task_id} body,
defaults to task_1_basic_antipatterns
POST /step — submit Action, returns StepResult with Observation+Reward
GET /state — current EnvironmentState (non-destructive)
GET /tasks — list all tasks with descriptions and action schema
POST /grader — grade an action against active task without advancing
POST /baseline — runs inference.py subprocess and returns stdout
GET / — health check returning env name and available tasks
CORS middleware enabled for all origins (required for HF Space)

server/__init__.py

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+# server package

server/app.py

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+from fastapi import FastAPI, HTTPException, Request
+from fastapi.middleware.cors import CORSMiddleware
+import os
+import sys
+import json
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from env import SQLOptimEnv
+from models import Action, StepResult, EnvironmentState, Observation
+from tasks import get_task_list
+from graders import grade
+
+app = FastAPI(
+    title="SQL Query Optimization Environment",
+    description=(
+        "OpenEnv-compliant RL environment where AI agents learn to analyze, "
+        "diagnose, and optimize SQL queries across three difficulty levels."
+    ),
+    version="1.0.0",
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+env = SQLOptimEnv()
+
+
+@app.get("/")
+def root():
+    return {
+        "status": "ok",
+        "environment": "sql-optim-env",
+        "version": "1.0.0",
+        "tasks": [t["task_id"] for t in get_task_list()],
+    }
+
+
+@app.post("/reset", response_model=Observation)
+async def reset(request: Request):
+    """
+    Start a new episode. Optionally pass {"task_id": "..."} in the body.
+    Defaults to task_1_basic_antipatterns.
+    """
+    try:
+        body = await request.body()
+        task_id = "task_1_basic_antipatterns"
+        if body:
+            try:
+                data = json.loads(body)
+                task_id = data.get("task_id", task_id) or task_id
+            except Exception:
+                pass
+        obs = env.reset(task_id=task_id)
+        return obs
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.post("/step", response_model=StepResult)
+def step(action: Action):
+    """Take one action (submit SQL analysis + optimized query)."""
+    try:
+        result = env.step(action)
+        return result
+    except RuntimeError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+
+
+@app.get("/state", response_model=EnvironmentState)
+def state():
+    """Get current environment state without advancing the episode."""
+    return env.state()
+
+
+@app.get("/tasks")
+def tasks():
+    """List all available tasks with descriptions and action schema."""
+    return {"tasks": get_task_list()}
+
+
+@app.post("/grader")
+def grader(action: Action):
+    """Grade an action against the current task without advancing the episode."""
+    if env._task_data is None:
+        raise HTTPException(status_code=400, detail="No active episode. Call /reset first.")
+    reward = grade(env._task_data, action)
+    return reward
+
+
+@app.post("/baseline")
+def baseline():
+    """Run the baseline agent and return scores for all tasks."""
+    try:
+        import subprocess
+        result = subprocess.run(
+            ["python", "inference.py"],
+            capture_output=True, text=True, timeout=300,
+            cwd=os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+        )
+        return {
+            "stdout": result.stdout,
+            "stderr": result.stderr,
+            "returncode": result.returncode,
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Baseline failed: {str(e)}")
+
+
+
+def main():
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=7860)
+
+
+if __name__ == "__main__":
+    main()