Add OpenAI 2048 example and fix agent loop

Author: jdchawla29

examples/openai_2048.py

@@ -0,0 +1,127 @@
+#!/usr/bin/env python3
+"""
+OpenAI Chat Agent playing Text 2048
+
+This example demonstrates using the OpenAIChatAgent with the text-2048 environment.
+It shows how to:
+- Initialize an OpenAI client with the openai_chat agent
+- Configure the text-2048 environment
+- Run the agent to play the game
+
+Requirements:
+- pip install openai
+- export OPENAI_API_KEY="your-api-key"  # Or set OPENAI_BASE_URL for custom endpoints
+
+Environment Variables:
+- OPENAI_BASE_URL: Custom OpenAI-compatible API endpoint (optional)
+- OPENAI_API_KEY: API key for authentication
+"""
+
+import asyncio
+import os
+from openai import AsyncOpenAI
+import hud
+from hud.agents.openai_chat_generic import GenericOpenAIChatAgent
+from hud.clients import MCPClient
+from hud.datasets import Task
+
+from hud.agents.misc import ResponseAgent
+
+
+async def main():
+    # Initialize OpenAI client with environment variables
+    base_url = os.getenv("OPENAI_BASE_URL")  # Optional custom endpoint
+    api_key = os.getenv("OPENAI_API_KEY", "EMPTY")  # Default to "EMPTY" for local servers
+    
+    openai_client = AsyncOpenAI(
+        base_url=base_url,  # None will use default OpenAI endpoint
+        api_key=api_key,
+    )
+    
+    # Configure the text-2048 environment
+    mcp_config = {
+        "local": {
+            "command": "docker",
+            "args": ["run", "--rm", "-i", "hudevals/hud-text-2048:latest"]
+        }
+    }
+    
+    # Define the task with game setup and evaluation
+    task = Task(
+        prompt="""Play the 2048 game strategically. 
+        
+        Tips for high scores:
+        - Keep your highest tile in a corner (preferably bottom-right)
+        - Build tiles in descending order from that corner
+        - Avoid moving up unless absolutely necessary
+        - Try to keep tiles of similar values adjacent
+        
+        Use the 'move' tool with directions: up, down, left, or right.
+        Aim for the highest possible score!""",
+        mcp_config=mcp_config,
+        setup_tool={"name": "setup","arguments": {"name": "board", "arguments": {"board_size": 4}},}, # type: ignore
+        evaluate_tool={"name": "evaluate", "arguments": {"name": "max_number", "arguments": {}}}, # type: ignore
+    )
+
+    # Initialize MCP client
+    client = MCPClient(mcp_config=task.mcp_config)
+    
+    # Create OpenAI agent with the text-2048 game tools
+    agent = GenericOpenAIChatAgent(
+        mcp_client=client,
+        openai_client=openai_client,
+        model_name="Qwen/Qwen2.5-3B-Instruct",
+        allowed_tools=["move"],
+        parallel_tool_calls=False,
+        response_agent=ResponseAgent(),
+        system_prompt="""You are an expert 2048 game player. 
+        Make strategic moves to achieve the highest score possible.
+        Always analyze the board state before making a move.""",
+    )
+
+    agent.metadata = {}
+
+    # Run the game with tracing
+    with hud.trace("OpenAI 2048 Game"):
+        try:
+            print("🎮 Starting 2048 game with OpenAI agent...")
+            print(f"🤖 Model: {agent.model_name}")
+            print("="*50)
+            
+            # Run the task with unlimited steps (game ends when no moves available)
+            result = await agent.run(task, max_steps=-1)
+            
+            # Display results
+            print("="*50)
+            print(f"✅ Game completed!")
+            print(f"🏆 Final Score/Max Tile: {result.reward}")
+            if result.info:
+                print(f"📊 Game Stats: {result.info}")
+
+            # Display conversation history
+            print("🗣️ Conversation History:")
+            for i, msg in enumerate(agent.conversation_history):
+                print(f"  {i+1} : {msg}")
+                print("-"*30)
+
+        except Exception as e:
+            print(f"❌ Error during game: {e}")
+        finally:
+            await client.shutdown()
+
+
+if __name__ == "__main__":
+    # Check for API configuration
+    if not os.getenv("OPENAI_API_KEY") and not os.getenv("OPENAI_BASE_URL"):
+        print("⚠️  Please configure OpenAI API access:")
+        print("   For OpenAI API: export OPENAI_API_KEY='your-api-key'")
+        print("   For local/custom endpoints: export OPENAI_BASE_URL='your-custom-endpoint'")
+        exit(1)
+    
+    # Display configuration
+    if os.getenv("OPENAI_BASE_URL"):
+        print(f"🔗 Using endpoint: {os.getenv('OPENAI_BASE_URL')}")
+    else:
+        print("🔗 Using default OpenAI API endpoint")
+    
+    asyncio.run(main())

hud/agents/misc/response_agent.py

@@ -54,7 +54,7 @@ async def determine_response(self, agent_message: str) -> ResponseType:
         """
         try:
             response = await self.client.chat.completions.create(
-                model="gpt-4o",
+                model="gpt-5-nano",
                 messages=[
                     {"role": "system", "content": self.system_prompt},
                     {

hud/agents/openai_chat_generic.py

@@ -21,6 +21,7 @@
 
 import mcp.types as types
 
+from hud import instrument
 from hud.types import AgentResponse, MCPToolCall, MCPToolResult
 
 from .base import MCPAgent
@@ -52,6 +53,7 @@ def __init__(
         self.model_name = model_name
         self.parallel_tool_calls = parallel_tool_calls
         self.logprobs = logprobs
+        self.conversation_history = []
 
     @staticmethod
     def _oai_to_mcp(tool_call: Any) -> MCPToolCall:  # type: ignore[valid-type]
@@ -64,9 +66,7 @@ def _oai_to_mcp(tool_call: Any) -> MCPToolCall:  # type: ignore[valid-type]
 
     async def get_system_messages(self) -> list[Any]:
         """Get system messages for OpenAI."""
-        return [
-            {"role": "system", "content": self.system_prompt},
-        ]
+        return [{"role": "system", "content": self.system_prompt}]
 
     async def format_blocks(self, blocks: list[types.ContentBlock]) -> list[Any]:
         """Format blocks for OpenAI."""
@@ -96,8 +96,14 @@ def get_tool_schemas(self) -> list[dict]:
             openai_tools.append(openai_tool)
         return openai_tools
 
+    @instrument(
+        span_type="agent",
+        record_args=False,
+        record_result=True,
+    )
     async def get_response(self, messages: list[Any]) -> AgentResponse:
         """Send chat request to OpenAI and convert the response."""
+        
         # Convert MCP tool schemas to OpenAI format
         mcp_schemas = self.get_tool_schemas()
 
@@ -111,6 +117,19 @@ async def get_response(self, messages: list[Any]) -> AgentResponse:
 
         choice = response.choices[0]
         msg = choice.message
+        
+        assistant_msg: dict[str, Any] = {"role": "assistant"}
+        
+        if msg.content:
+            assistant_msg["content"] = msg.content
+        
+        if msg.tool_calls:
+            assistant_msg["tool_calls"] = msg.tool_calls
+        
+        messages.append(assistant_msg)
+
+        # Store the complete conversation history
+        self.conversation_history = messages.copy()
 
         tool_calls = []
         if msg.tool_calls:
@@ -144,11 +163,10 @@ async def format_tool_results(
                     for c in res.content
                     if hasattr(c, "text")
                 )
-            rendered.append(
-                {
-                    "role": "tool",
-                    "tool_call_id": call.id,
-                    "content": content or "",  # Ensure content is never None
-                }
-            )
+            tool_msg = {
+                "role": "tool",
+                "tool_call_id": call.id,
+                "content": content or "",  # Ensure content is never None
+            }
+            rendered.append(tool_msg)
         return rendered