Using the Code Interpreter Tool
Leverage the Code Interpreter tool for data analysis, calculations, and dynamic code execution.
What Is Code Interpreter?
Code Interpreter is a tool that allows agents to write and execute Python code in real-time. When enabled, agents can:
- Analyze data from uploaded files
- Perform complex calculations
- Generate charts and visualizations
- Transform and process data
- Create files for you to download
When Code Interpreter Is Available
The Code Interpreter tool is available when:
- The agent you're using has Code Interpreter enabled
- Your administrator has configured Python execution environments
- You're asking questions that benefit from code execution
Note: Not all agents have Code Interpreter. If you need this capability, check with your administrator or select an agent that supports it.
How It Works
The Process
- You ask a question that requires computation or data analysis
- The agent writes Python code to address your request
- Code runs in a secure environment isolated from your system
- Results are returned in the conversation as text, tables, or images
Behind the Scenes
- Code executes in a containerized Python environment
- The agent has access to common data science libraries
- Uploaded files can be accessed by the code
- Generated files are made available for download
What You Can Do
Data Analysis
Upload spreadsheets or data files and ask questions:
- "What's the average sales by region in this file?"
- "Find correlations between columns A and B"
- "Show me the top 10 customers by revenue"
- "Calculate year-over-year growth rates"
Visualizations
Request charts and graphs from your data:
- "Create a bar chart of monthly sales"
- "Plot the trend line for quarterly revenue"
- "Make a pie chart showing market share"
- "Generate a scatter plot comparing price and quantity"
Calculations
Perform mathematical or statistical operations:
- "Calculate the compound interest on $10,000 at 5% for 10 years"
- "What's the standard deviation of these numbers?"
- "Solve this equation: 2x + 5 = 15"
- "Run a regression analysis on this dataset"
Data Transformation
Process and transform data:
- "Convert this CSV to JSON format"
- "Clean this data by removing duplicates"
- "Merge these two datasets by customer ID"
- "Pivot this data to show totals by category"
File Generation
Create new files from your data:
- "Export the results as a CSV file"
- "Save this chart as a PNG image"
- "Create a summary report of the analysis"
- "Generate a cleaned version of this dataset"
Example Prompts
Basic Analysis
"I've uploaded a CSV file with sales data. Can you summarize the key metrics including total revenue, number of transactions, and average order value?"
Visualization Request
"Using the uploaded data, create a line chart showing sales trends over the past 12 months with a trend line."
Complex Processing
"Compare the sales performance across all regions. Show the top 3 and bottom 3 performers, and calculate the percentage difference from the average."
Data Cleaning
"The uploaded file has some issues — there are duplicate rows and some missing values in the 'price' column. Clean the data and show me what was fixed."
Understanding the Output
Text Results
The agent explains findings in natural language:
- Summaries of calculations
- Interpretations of data
- Answers to your questions
Tables
Data results may appear as formatted tables:
- Column headers
- Organized rows of data
- Numerical results
Charts and Images
Visualizations appear directly in the conversation:
- Click to view full size
- Right-click to save
- Charts are PNG images by default
Generated Files
When the agent creates files:
- Download links appear in the response
- Click to download the file
- Files may be in various formats (CSV, XLSX, PNG, etc.)
Tips for Best Results
Provide Clear Data
- Use clean, well-formatted files
- Include clear column headers
- Remove unnecessary data before uploading
- Smaller, focused datasets process faster
Be Specific in Requests
Instead of: "Analyze this data" Try: "Calculate the monthly average and identify any months with values more than 2 standard deviations from the mean"
Request Specific Formats
- Specify chart types you want
- Ask for specific file formats for exports
- Request particular calculations or metrics
Build on Previous Results
- Reference earlier analysis in the conversation
- Ask follow-up questions
- Request modifications to previous outputs
Check the Results
- Verify calculations make sense
- Spot-check numbers against your source data
- Ask for explanations if results are unexpected
Limitations
What Code Interpreter Cannot Do
- Access the internet or external systems
- Run indefinitely (there are time limits)
- Access files outside what you've uploaded
- Install arbitrary packages
- Access your local computer
Size and Time Limits
- Very large files may take longer to process
- Complex operations may timeout
- Some requests may be too resource-intensive
Library Availability
Common libraries are available (pandas, numpy, matplotlib, etc.) but:
- Specialized libraries may not be installed
- Ask the agent what capabilities are available
Troubleshooting
Code Doesn't Run
- The agent may not have Code Interpreter enabled
- Try a different agent with code execution capability
- Rephrase your request to be more specific
Analysis Takes Too Long
- Try with a smaller sample of data
- Simplify your request
- Break complex analysis into steps
Results Are Incorrect
- Check your source data for issues
- Be more specific about what you want
- Ask the agent to explain its approach
- Try rephrasing your question
Chart Doesn't Generate
- Request a specific chart type
- Ensure the data is suitable for visualization
- Ask for a different visualization approach
Can't Download Generated File
- Wait for the response to fully complete
- Click the download link in the message
- Check your browser's downloads
- Try asking the agent to regenerate the file
Security and Privacy
- Code runs in an isolated environment
- Your uploaded data is processed by the agent
- Generated code is visible in some configurations
- Follow your organization's data policies
Related Topics
- Uploading Files to a Conversation — Get data into the conversation
- Downloading Files from a Conversation — Save generated outputs
- Using the Knowledge Tool — Search document content
- Viewing Agent Prompts — See how responses are generated