update all files

=0.2.0

@@ -0,0 +1,19 @@
+Requirement already satisfied: openenv-core in /home/codespace/micromamba/lib/python3.9/site-packages (0.1.0)
+Requirement already satisfied: requests>=2.25.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from openenv-core) (2.32.5)
+Requirement already satisfied: fastapi>=0.104.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from openenv-core) (0.116.1)
+Requirement already satisfied: uvicorn>=0.24.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from openenv-core) (0.35.0)
+Requirement already satisfied: starlette<0.48.0,>=0.40.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from fastapi>=0.104.0->openenv-core) (0.47.2)
+Requirement already satisfied: pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4 in /home/codespace/micromamba/lib/python3.9/site-packages (from fastapi>=0.104.0->openenv-core) (2.11.7)
+Requirement already satisfied: typing-extensions>=4.8.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from fastapi>=0.104.0->openenv-core) (4.14.1)
+Requirement already satisfied: annotated-types>=0.6.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi>=0.104.0->openenv-core) (0.7.0)
+Requirement already satisfied: pydantic-core==2.33.2 in /home/codespace/micromamba/lib/python3.9/site-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi>=0.104.0->openenv-core) (2.33.2)
+Requirement already satisfied: typing-inspection>=0.4.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from pydantic!=1.8,!=1.8.1,!=2.0.0,!=2.0.1,!=2.1.0,<3.0.0,>=1.7.4->fastapi>=0.104.0->openenv-core) (0.4.1)
+Requirement already satisfied: anyio<5,>=3.6.2 in /home/codespace/micromamba/lib/python3.9/site-packages (from starlette<0.48.0,>=0.40.0->fastapi>=0.104.0->openenv-core) (4.10.0)
+Requirement already satisfied: exceptiongroup>=1.0.2 in /home/codespace/micromamba/lib/python3.9/site-packages (from anyio<5,>=3.6.2->starlette<0.48.0,>=0.40.0->fastapi>=0.104.0->openenv-core) (1.3.0)
+Requirement already satisfied: idna>=2.8 in /home/codespace/micromamba/lib/python3.9/site-packages (from anyio<5,>=3.6.2->starlette<0.48.0,>=0.40.0->fastapi>=0.104.0->openenv-core) (3.10)
+Requirement already satisfied: sniffio>=1.1 in /home/codespace/micromamba/lib/python3.9/site-packages (from anyio<5,>=3.6.2->starlette<0.48.0,>=0.40.0->fastapi>=0.104.0->openenv-core) (1.3.1)
+Requirement already satisfied: charset_normalizer<4,>=2 in /home/codespace/micromamba/lib/python3.9/site-packages (from requests>=2.25.0->openenv-core) (3.4.3)
+Requirement already satisfied: urllib3<3,>=1.21.1 in /home/codespace/micromamba/lib/python3.9/site-packages (from requests>=2.25.0->openenv-core) (2.5.0)
+Requirement already satisfied: certifi>=2017.4.17 in /home/codespace/micromamba/lib/python3.9/site-packages (from requests>=2.25.0->openenv-core) (2025.8.3)
+Requirement already satisfied: click>=7.0 in /home/codespace/micromamba/lib/python3.9/site-packages (from uvicorn>=0.24.0->openenv-core) (8.1.8)
+Requirement already satisfied: h11>=0.8 in /home/codespace/micromamba/lib/python3.9/site-packages (from uvicorn>=0.24.0->openenv-core) (0.16.0)

README.md

@@ -140,6 +140,7 @@ quant-gym-openenv/
 ├── inference.py            # Baseline agent script
 ├── models.py               # Pydantic schemas
 ├── openenv.yaml            # OpenEnv configuration
+├── pyproject.toml
 ├── requirements.txt        # Python dependencies
 ├── README.md               # This file
 ├── server/

graders/__init__.py

@@ -0,0 +1 @@
+# Graders package

graders/task2_grader.py

@@ -1,13 +1,14 @@
 def grade_task2(agent_action, observation):
-    """Task 2: News Analysis with Explanation"""
+    """Grade Task 2: News Sentiment Analysis"""
     score = 0.0
     
-    # Check if agent gave explanation
-    if agent_action.explanation and len(agent_action.explanation) > 10:
+    # Check if agent gave an explanation
+    if agent_action.get("explanation") and len(agent_action.get("explanation", "")) > 10:
         score += 0.5
     
-    # Check if recommendation exists
-    if agent_action.type in ["BUY", "SELL", "HOLD"]:
+    # Check if action is valid (BUY/SELL/HOLD recommendation)
+    action_type = agent_action.get("type", "")
+    if action_type in ["BUY", "SELL", "GET_NEWS"]:
         score += 0.5
     
     return score

graders/task3_grader.py

@@ -1,11 +1,15 @@
-def grade_task3(backtest_results):
-    """Task 3: Backtest Strategy"""
+def grade_task3(agent_action, observation):
+    """Grade Task 3: Backtest Strategy"""
     score = 0.0
     
+    # Check if backtest results exist
+    backtest_results = observation.get("backtest_results")
     if backtest_results:
+        # Check for Sharpe ratio
         if backtest_results.get("sharpe_ratio", 0) > 0:
             score += 0.5
-        if backtest_results.get("max_drawdown", 1) < 0.5:
+        # Check for max drawdown
+        if backtest_results.get("max_drawdown", 1) < 1:
             score += 0.5
     
     return score

openenv.yaml

@@ -1,26 +1,29 @@
-python3 << 'PYTHON_EOF'
-with open('openenv.yaml', 'w') as f:
-    f.write('''name: "Quant-Gym"
-description: "Benchmark environment for testing AI agents on financial data analysis and reasoning"
+name: "Quant-Gym"
+description: "Financial analysis environment for testing AI agents on market data, news sentiment, and trading strategies"
 version: "1.0.0"
 
+environment:
+  name: "QuantGym"
+  class: "TradingEnvironment"
+  module: "server.environment"
+
 tasks:
   - id: "task1"
     name: "Fetch Market Data"
     description: "Agent must retrieve current price for AAPL"
-    grader_type: "deterministic"
+    grader: "graders.task1_grader.grade_task1"
     max_score: 1.0
     
   - id: "task2"
     name: "News Sentiment Analysis"
-    description: "Agent must analyze news and recommend action with explanation"
-    grader_type: "llm_judge"
+    description: "Agent must analyze news and recommend Buy/Sell/Hold with explanation"
+    grader: "graders.task2_grader.grade_task2"
     max_score: 1.0
     
   - id: "task3"
     name: "Backtest Strategy"
-    description: "Agent must backtest a strategy and return risk metrics"
-    grader_type: "deterministic"
+    description: "Agent must backtest a trading strategy and return risk metrics"
+    grader: "graders.task3_grader.grade_task3"
     max_score: 1.0
 
 action_schema:
@@ -31,12 +34,16 @@ action_schema:
       enum: ["GET_PRICE", "GET_NEWS", "BUY", "SELL", "BACKTEST"]
     symbol:
       type: "string"
+      default: "AAPL"
     amount:
       type: "integer"
+      minimum: 0
     explanation:
       type: "string"
     strategy:
       type: "string"
+  required:
+    - "type"
 
 observation_schema:
   type: "object"
@@ -55,6 +62,3 @@ observation_schema:
       type: "object"
     backtest_results:
       type: "object"
-''')
-print("openenv.yaml created")
-PYTHON_EOF

pyproject.toml

@@ -0,0 +1,35 @@
+[build-system]
+requires = ["setuptools>=45", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "quant-gym-openenv"
+version = "0.1.0"
+description = "Financial analysis environment for AI agents"
+requires-python = ">=3.10"
+dependencies = [
+    "openenv-core[core]>=0.2.2",
+    "fastapi>=0.104.0",
+    "uvicorn>=0.24.0",
+    "pydantic>=2.0.0",
+    "yfinance>=0.2.0",
+    "pandas>=2.0.0",
+    "openai>=1.0.0",
+    "requests>=2.31.0",
+    "python-dotenv>=1.0.0",
+    "numpy>=1.24.0",
+]
+
+[project.optional-dependencies]
+dev = [
+    "pytest>=8.0.0",
+    "pytest-cov>=4.0.0",
+]
+
+[project.scripts]
+server = "server.app:main"
+
+[tool.setuptools]
+include-package-data = true
+packages = ["server", "graders"]
+package-dir = { "server" = "server", "graders" = "graders" }

requirements.txt

@@ -7,4 +7,4 @@ pandas>=2.0.0
 openai>=1.0.0
 requests>=2.31.0
 python-dotenv>=1.0.0
-numpy>=1.24.0
+numpy>=1.24.0

server/app.py

@@ -6,6 +6,7 @@ from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
 from models import AgentAction
 from server.environment import TradingEnvironment
+import uvicorn
 
 app = FastAPI(title="Quant-Gym", description="Financial Analysis Environment")
 
@@ -53,3 +54,15 @@ def get_tasks():
             {"id": "3", "name": "Backtest Strategy", "description": "Backtest a trading strategy and return risk metrics"}
         ]
     }
+
+def main():
+    """Entry point for the application"""
+    uvicorn.run(
+        "server.app:app",
+        host="0.0.0.0",
+        port=7860,
+        reload=False
+    )
+
+if __name__ == "__main__":
+    main()