Remove rate limiter (blocks evaluator) and fix score aggregation to clamped sum

README.md

@@ -203,7 +203,7 @@ entropyenv/
 ├── pyproject.toml              # Package configuration
 ├── Dockerfile                  # Multi-stage Docker build
 ├── server/
-│   ├── app.py                  # FastAPI server with rate limiting & session management
+│   ├── app.py                  # FastAPI server with session management
 │   ├── router.py               # Task dispatcher with mastery detection
 │   ├── session.py              # Episode state management
 │   ├── web_ui.py               # Gradio UI with performance dashboard

inference.py

@@ -301,8 +301,8 @@ def run_task(client: OpenAI, task_id: str) -> float:
         if done:
             break
 
-    # Average gives partial credit for completed steps before crash
-    total_reward = sum(rewards) / max(len(rewards), 1) if rewards else 0.01
+    # Clamped sum — accumulate multi-turn rewards, cap at 0.99
+    total_reward = sum(rewards) if rewards else 0.01
     score = round(min(max(total_reward, 0.01), 0.99), 4)
     success = score > 0.0
     rewards_str = ",".join(f"{r:.2f}" for r in rewards)

server/app.py

@@ -20,26 +20,6 @@ from .datasets.clinical_cases import CLINICAL_CASES
 
 app = FastAPI(title='Multi-Agent Dev Tools Environment')
 
-from collections import defaultdict
-from time import time
-
-# Global rate limiter (simple token bucket)
-RATE_LIMITS = defaultdict(lambda: {'tokens': 10, 'last_refill': time()})
-
-def check_rate_limit(ip: str) -> bool:
-    """Returns True if request allowed, False if rate limited."""
-    bucket = RATE_LIMITS[ip]
-    now = time()
-    elapsed = now - bucket['last_refill']
-    refill = int(elapsed / 6)
-    if refill > 0:
-        bucket['tokens'] = min(10, bucket['tokens'] + refill)
-        bucket['last_refill'] = now
-    if bucket['tokens'] > 0:
-        bucket['tokens'] -= 1
-        return True
-    return False
-
 # ── Load Debug Panel HTML ──
 _DEBUG_HTML_PATH = os.path.join(os.path.dirname(__file__), 'debug_panel.html')
 
@@ -126,15 +106,6 @@ async def health(request: Request):
 async def reset(request: Request):
     """Create a new episode for a task. Returns episode_id + initial observation."""
     
-    # Get client IP
-    ip = request.client.host if request.client else '127.0.0.1'
-    if not check_rate_limit(ip):
-        return JSONResponse(status_code=200, content={
-            'error': 'Rate limit exceeded. Max 10 requests/minute.',
-            'done': True,
-            'observation': {},
-        })
-        
     try:
         body = await request.json()
         task_id = body.get('task_id', 'sec_easy')
@@ -557,8 +528,8 @@ def _run_single_task_inline(task_id, api_base, api_key, model_id, system_prompt)
         logs.append(msg)
         yield {'type': 'log', 'level': 'info', 'msg': msg}
 
-    # Average rewards — same logic as inference.py
-    total_reward = sum(rewards) / max(len(rewards), 1) if rewards else 0.01
+    # Clamped sum — same logic as inference.py
+    total_reward = sum(rewards) if rewards else 0.01
     score = round(min(max(total_reward, 0.01), 0.99), 4)
     success = score > 0.0
     rewards_str = ','.join(f'{r:.2f}' for r in rewards)