Comments (5)
AI: Your table E-commerce Customer Behavior - Sheet1 contains 350 rows and 11 columns. On average, each column has about 50 unique values. Watch out, there are 2 missing values in your data.
Here are some additional insights to enhance your understanding of the table.
- E-commerce behavior data by customers.
- Analyze customer satisfaction, spending habits, and purchase history.
- Identify correlations between customer demographics and spending.
Human: Analyze customer satisfaction, spending habits, and purchase history.
AI: ```json
{
"action": "PythonCodeBuilder",
"action_input": "calculate the average satisfaction level of each membership type",
}
[RESPONSE_BEGIN]
<code>
generate_continuous_elegant_python_code(history_dict)
</code>
<output>
[ERROR]: name 'generate_continuous_elegant_python_code' is not defined
</output>
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Observation: {
"success": "False",
"result": "[ERROR]: name 'generate_continuous_elegant_python_code' is not defined",
"intermediate_steps": "generate_continuous_elegant_python_code(history_dict)"
}
Thought:
Finished chain.
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It seems like the agent encounters some trouble with the format, and I thought it maybe due to the fact you used the gpt-3.5 instead of gpt-4 which are less intelligent when considering the instruction following, would you mind changing the LLM and see if it helps?
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This issue is stale because it has been open 3 days with no activity. Remove stale label or comment or this will be closed in 4 days.
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This issue was closed because it has been stalled for 4 days with no activity.
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