Reorganize community environments - Move lean_proof_env, router_env, and philosophical_rlaif_env.py to environments/community/ - Add comprehensive README for community environments - This organizes community-contributed environments into a dedicated community folder for better maintainability and discoverability

environments/community/router_env/engine/agents/calc_agent.py

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+import os
+import logging # Added logging
+from dotenv import load_dotenv
+from livekit.agents import JobContext, WorkerOptions, cli # Changed import
+from livekit.agents import mcp # Corrected import for mcp
+from livekit.agents.llm import ChatChunk, function_tool # Added function_tool for delegate_to_router_agent if it were defined here
+from livekit.agents.voice import Agent, AgentSession
+from livekit.plugins import deepgram, openai, silero
+# Removed: from mcp_client import MCPServerStdio
+# Removed: from mcp_client.agent_tools import MCPToolsIntegration
+from livekit.plugins.turn_detector.multilingual import MultilingualModel # Added from official example
+from livekit.agents import ChatContext, RunContext # Add ChatContext & RunContext import
+from typing import Optional, List # Add Optional & List import
+from livekit.agents import tts # Corrected import for tts module
+from livekit.agents.types import NOT_GIVEN # Corrected import for NOT_GIVEN
+from livekit.agents.utils.misc import is_given # Corrected import for is_given
+
+logger = logging.getLogger("agent-math-official") # Added logger
+
+mcp_script_path = os.path.abspath(os.path.join(
+    os.path.dirname(__file__), '..', 'tools', 'mcp', 'calc', 'calc_server.py'
+))
+
+class CalculatorAgent(Agent):
+    """A LiveKit agent that uses MCP tools from one or more MCP servers."""
+
+    def __init__(self, 
+                 chat_ctx: ChatContext,
+                 instructions: Optional[str] = None, 
+                 mcp_servers: Optional[list[mcp.MCPServer]] = None,
+                 tts: Optional[tts.TTS] = NOT_GIVEN,
+                 tools: Optional[List[function_tool]] = None): # Added tools parameter
+        
+        final_instructions = instructions if instructions is not None else \
+            """
+                You are a specialist Math assistant. Your expertise is in solving mathematical problems, 
+                performing calculations, arithmetic, and answering questions about numbers.
+                You have two calculation tools: 'multiply' and 'add'.
+                When your current math task is complete, or if the user asks for something not related to math,
+                you MUST use the 'delegate_to_router_agent' tool to return to the main assistant.
+            """
+        
+        # Combine passed tools with any class-defined tools if necessary (none here for now)
+        all_tools = tools if tools is not None else []
+
+        super().__init__(
+            instructions=final_instructions, 
+            chat_ctx=chat_ctx,
+            allow_interruptions=True,
+            mcp_servers=[
+                mcp.MCPServerStdio(
+                    command="python",
+                    args=[mcp_script_path],
+                )
+                # MODIFIED: Removed chat_ctx=chat_ctx argument
+            ],
+            tools=all_tools # Pass the tools to the parent Agent class
+        )
+        # MCP tools are automatically integrated by AgentSession if mcp_servers is configured.
+        # No need for MCPToolsIntegration or manually adding tools here.
+
+    async def llm_node(self, chat_ctx, tools, model_settings):
+        """Override the llm_node to say a message when a tool call is detected."""
+        tool_call_detected = False
+
+        async for chunk in super().llm_node(chat_ctx, tools, model_settings):
+            if isinstance(chunk, ChatChunk) and chunk.delta and chunk.delta.tool_calls and not tool_call_detected:
+                tool_call_detected = True
+                # Example: if self.tts: self.session.say("Working on the math problem.")
+                # Currently, Math agent does not say anything here.
+            yield chunk
+
+    async def on_enter(self):
+        # when the agent is added to the session, we'll initiate the conversation by
+        # using the LLM to generate a reply
+        self.session.generate_reply()
+
+async def entrypoint(ctx: JobContext):
+    """Main entrypoint for the LiveKit agent application."""
+    await ctx.connect() # Connect earlier as in official example
+
+    # Directly configure AgentSession with mcp_servers
+    session = AgentSession(
+        vad=silero.VAD.load(), # Redundant if agent has it, but official example does this
+        stt=deepgram.STT(model="nova-2", language="en-US"), # Consistent with agent
+        llm=openai.LLM(model="gpt-4o"), # Consistent with agent
+        tts=openai.TTS(voice="alloy"), # Consistent with agent
+        turn_detection=MultilingualModel(), # Consistent with agent
+    )
+
+    # Instantiate the agent
+    agent = CalculatorAgent(chat_ctx=session._chat_ctx)
+
+    await session.start(agent=agent, room=ctx.room)
+
+if __name__ == "__main__":
+    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))