Fix formatting issues in community environments - Applied black, isort, trailing whitespace, and end-of-file fixes - Remaining flake8 issues (unused imports, line length) noted for future cleanup

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

@@ -1,50 +1,70 @@
+import logging  # Added logging
 import os
-import logging # Added logging
+from typing import List, Optional  # Add Optional & List import
+
 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 import mcp  # Corrected import for mcp
+from livekit.agents import tts  # Corrected import for tts module
+from livekit.agents import (  # Changed import; Add ChatContext & RunContext import
+    ChatContext,
+    JobContext,
+    RunContext,
+    WorkerOptions,
+    cli,
+)
+from livekit.agents.llm import (  # Added function_tool for delegate_to_router_agent if it were defined here
+    ChatChunk,
+    function_tool,
+)
+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
 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
+from livekit.plugins.turn_detector.multilingual import (  # Added from official example
+    MultilingualModel,
+)
 
-logger = logging.getLogger("agent-math-official") # Added logger
+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"
+    )
+)
 
-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, 
+    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, 
+            instructions=final_instructions,
             chat_ctx=chat_ctx,
             allow_interruptions=True,
             mcp_servers=[
@@ -54,7 +74,7 @@ class CalculatorAgent(Agent):
                 )
                 # MODIFIED: Removed chat_ctx=chat_ctx argument
             ],
-            tools=all_tools # Pass the tools to the parent Agent class
+            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.
@@ -64,7 +84,12 @@ class CalculatorAgent(Agent):
         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:
+            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.
@@ -75,17 +100,18 @@ class CalculatorAgent(Agent):
         # 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
+    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
+        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
@@ -93,5 +119,6 @@ async def entrypoint(ctx: JobContext):
 
     await session.start(agent=agent, room=ctx.room)
 
+
 if __name__ == "__main__":
-    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
+    cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))