remove lmnr dependency

agent/core/agent_loop.py

@@ -9,7 +9,6 @@ import os
 
 from litellm import ChatCompletionMessageToolCall, Message, acompletion
 from litellm.exceptions import ContextWindowExceededError
-from lmnr import observe
 
 from agent.config import Config
 from agent.core.session import Event, OpType, Session
@@ -233,7 +232,6 @@ class Handlers:
         logger.info("Abandoned %d pending approval tool(s)", len(tool_calls))
 
     @staticmethod
-    @observe(name="run_agent")
     async def run_agent(
         session: Session, text: str, max_iterations: int = 300
     ) -> str | None:
@@ -241,12 +239,6 @@ class Handlers:
         Handle user input (like user_input_or_turn in codex.rs:1291)
         Returns the final assistant response content, if any.
         """
-        # Set session ID for this trace
-        if hasattr(session, "session_id"):
-            from lmnr import Laminar
-
-            Laminar.set_trace_session_id(session_id=session.session_id)
-
         # Clear any stale cancellation flag from a previous run
         session.reset_cancel()
 
@@ -843,7 +835,6 @@ async def process_submission(session: Session, submission) -> bool:
     return True
 
 
-@observe(name="submission_loop")
 async def submission_loop(
     submission_queue: asyncio.Queue,
     event_queue: asyncio.Queue,

agent/core/tools.py

@@ -12,7 +12,6 @@ logger = logging.getLogger(__name__)
 
 from fastmcp import Client
 from fastmcp.exceptions import ToolError
-from lmnr import observe
 from mcp.types import EmbeddedResource, ImageContent, TextContent
 
 from agent.config import MCPServerConfig
@@ -226,7 +225,6 @@ class ToolRouter:
             await self.mcp_client.__aexit__(exc_type, exc, tb)
             self._mcp_initialized = False
 
-    @observe(name="call_tool")
     async def call_tool(
         self,
         tool_name: str,

agent/main.py

@@ -10,7 +10,6 @@ from pathlib import Path
 from typing import Any, Optional
 
 import litellm
-from lmnr import Laminar, LaminarLiteLLMCallback
 from prompt_toolkit import PromptSession
 
 from agent.config import load_config
@@ -41,15 +40,6 @@ def _safe_get_args(arguments: dict) -> dict:
     return args if isinstance(args, dict) else {}
 
 
-lmnr_api_key = os.environ.get("LMNR_API_KEY")
-if lmnr_api_key:
-    try:
-        Laminar.initialize(project_api_key=lmnr_api_key)
-        litellm.callbacks = [LaminarLiteLLMCallback()]
-        print("Laminar initialized")
-    except Exception as e:
-        print(f"Failed to initialize Laminar: {e}")
-
 
 @dataclass
 class Operation:

eval/hf_agent_connector.py

@@ -5,7 +5,6 @@ import sys
 from pathlib import Path
 from typing import Any
 
-from lmnr import observe
 
 from agent.config import Config, load_config
 from agent.core.agent_loop import Handlers
@@ -40,7 +39,6 @@ class AgentResponseGenerator:
         """Expose the agent model name for downstream logging."""
         return self.config.model_name
 
-    @observe(name="eval_run")
     async def run(self, prompt: str) -> str:
         """
         Execute the agent loop for a single prompt and return the assistant reply.

eval/solvers.py

@@ -14,7 +14,6 @@ import litellm
 from inspect_ai.model import ChatMessageAssistant, ModelOutput
 from inspect_ai.solver import Solver, solver
 from inspect_ai.solver._task_state import TaskState
-from lmnr import Laminar, LaminarLiteLLMCallback
 
 from eval.hf_agent_connector import AgentResponseGenerator
 
@@ -39,10 +38,6 @@ def hf_agent(
     config_path: str = "agent/config_mcp_example.json",
     max_iterations: int = 10,
 ) -> Solver:
-    # init lmnr for observability
-    Laminar.initialize(project_api_key=os.environ.get("LMNR_API_KEY"))
-    litellm.callbacks = [LaminarLiteLLMCallback()]
-    print("✅ Laminar initialized")
 
     runner = AgentResponseGenerator(
         config_path=config_path,

pyproject.toml

@@ -18,7 +18,6 @@ agent = [
     "litellm>=1.0.0",
     "huggingface-hub>=1.0.1",
     "fastmcp>=2.4.0",
-    "lmnr>=0.7.23",  # Note: Using base package to avoid torch/transformers from [all] extra
     "prompt-toolkit>=3.0.0",
     "thefuzz>=0.22.1",
     "nbconvert>=7.16.6",