- treceId       (YO4R743DHIHgk6pR/vdFKA==)

## Step 0
- attributes.input.value                        ({\"log_entry\": \"ActionStep(agent_memory=None, tool_calls=None, start_time=1738150784.891076, end_time=None, step_number=0, error=None, duration=None, llm_output=None, observations=None, observations_images=None, action_output=)

## LiteLLMModel.__call__
- attributes.input.mime_type                    (application/json)
- attributes.input.value                        ({\"messages\": [{\"role\": \"system\", \"content\": [{\"type\": \"text\", \"text\": \"You are an expert assi.....)
- attributes.llm.invocation_parameters          ({"max_tokens": 4096})
- attributes.llm.input_messages.0.message.role  (system)
- attributes.lm.input_messages.1.message.role   (user)
- attributes.llm.token_count.prompt             (1026)
- attributes.llm.token_count.completion         (53)
- attributes.llm.model_name                     (ollama/llama3.1)
- attributes.llm.token_count.total              (1079)
- attributes.llm.output_messages.0.message.role  (assistant)
- attributes.llm.output_messages.0.message.content (```py\n# Thought: We need the length of the b....)
- attributes.output.mime_type                   (application/json)
- attributes.output.value                       ({\"role\": \"assistant\", \"content\": \"```py\\n# Thought: We need the lengt...)

## CodeAgent.run
- attributes.input.value                        ({\"task\": \"How many seconds would it take for a leopard at ....)
- attributes.smolagents.max_steps               (6)
- attributes.smolagents.tools_names             (final_answer)
- attributes.llm.token_count.prompt             (7182)
- attributes.llm.token_count.completion         (1657)
- attributes.llm.token_count.total              (8839)
- attributes.output.value                       ("## Step 1: Understand the problem\nThe problem asks us to calculate how many seco...)