kodeagent.agents.csv_agent.CSVAnalysisAgent#

class kodeagent.agents.csv_agent.CSVAnalysisAgent(name: str = 'CSV Analyst', model_name: str = 'gemini/gemini-2.0-flash-lite', **kwargs: Any)[source]#

An agent specializing in discovering patterns and insights from CSV data.

Examples

Using a local file:

agent = CSVAnalysisAgent()
# Pass the file path (or URL) directly as a task file
async for response in agent.run(task, files=['/path/to/data.csv']):
    pass

Using a URL:

agent = CSVAnalysisAgent()
async for response in agent.run(task, files=['https://example.com/data.csv']):
    pass

Initialize the CSVAnalysisAgent.

Parameters:

name – Name of the agent.
model_name – The LLM model to use.
**kwargs – Additional arguments passed to ReActAgent.

__init__(name: str = 'CSV Analyst', model_name: str = 'gemini/gemini-2.0-flash-lite', **kwargs: Any) → None[source]#

Initialize the CSVAnalysisAgent.

Parameters:

name – Name of the agent.
model_name – The LLM model to use.
**kwargs – Additional arguments passed to ReActAgent.

Methods

`__init__`([name, model_name])	Initialize the CSVAnalysisAgent.
`add_output_file`(path)	Record a file generated during task execution.
`add_to_history`(message)	Add a chat message to the agent's message history.
`clear_history`()	Clear the agent's message history.
`get_history`()	Get a formatted string of the agent's message history, excluding the system prompt
`get_system_prompt_content`()	Return the formatted system prompt string for this agent.
`get_tools_description`([tools])	Generate a description of all the tools available to the agent.
`get_usage_metrics`()	Get raw usage metrics as a dictionary.
`get_usage_report`([include_breakdown])	Get a formatted report of LLM usage for the current/last task.
`init_history`()	Initialize the agent's message history with the system prompt.
`normalize_content`(content)	Convert message content to a readable string for Observer.
`parse_text_response`(text)	Parse text-based response when structured output fails.
`post_run`()	Perform cleanup after the main run loop.
`pre_run`()	Pre-run hook to auto-load CSV files and yield initialization logs.
`response`(rtype, value[, channel, metadata])	Prepare a response to be sent by the agent.
`run`(task[, files, task_id, max_iterations, ...])	Solve a task using ReAct's TAO loop (or CodeAct's TCO loop).
`salvage_response`()	When an agent fails to find an answer, salvage what information could be gathered.

Attributes

`HISTORY_TRUNCATE_CHARS`
`artifacts`	Returns the list of output files generated during task execution.
`current_plan`	Returns the current plan for the task.
`current_trace`
`description`
`filter_tools_for_task`
`final_answer_found`
`max_iterations`
`max_retries`
`msg_idx_of_new_task`
`name`
`persona`
`planner`
`purpose`	Describe the name, purpose of, and tools available to an agent.
`system_prompt`
`task`
`tracing_type`
`work_dir`
`model_name`
`tools`
`litellm_params`
`id`
`tool_name_to_func`
`tool_names`
`chat_history`
`usage_tracker`
`tracer_manager`
`observer`
`is_visual_model`
`task_output_files`

kodeagent.agents.csv_agent.CSVAnalysisAgent#

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