Code Interpreter Agent

Execution Flow & Architecture

Process Flow Diagram

Workflow Explanation

1. Input Detection: Detects if input is natural language (generates code) or raw code (executes as-is). Identifies language (Python default, or JS/TS/R/Java)

2. Code Preparation: Adds imports, installs packages dynamically, includes error handling and save commands for artifacts

3. Secure Execution: Runs in sandbox. On error: analyzes -> modifies -> re-executes (max 5 attempts). Blocks dangerous operations

4. Result Formatting: Returns final code only (hides iterations), formatted results, and embedded artifacts

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Detailed Mechanisms

Code Execution Mechanism

How Code is Executed:

1. Agent calls the E2B Sandbox Tool with parameters:

   • code: The Python/JS/TS/R/Java code to execute

   • language: Target programming language (default: Python)

   • timeout: Maximum execution time in seconds (default: 30s, max: 300s)

   • additional_packages: Optional packages to install before execution

2. Sandbox Initialization: E2B Cloud Sandbox creates isolated environment with specified language runtime

3. Package Installation: Installs required packages dynamically within the sandbox

4. Code Execution: Runs code in isolated environment with resource monitoring

5. Result Collection & Response: Captures execution details and returns structured response:

   {
     "status": "success/error",
     "code": "executed code",
     "stdout": "standard output",
     "stderr": "standard error",
     "error": "error message if any",
     "duration_ms": "execution time",
     "artifacts": ["generated files"]
   }

Language Support

1. Supported Languages: Python (default), JavaScript, TypeScript, R, Java

2. Extensible: Additional languages can be installed dynamically based on user requirements or query needs

Security Mechanisms

Layer	Protection
Execution Boundaries	Isolated sandbox; no system commands; max 5 iterations; reject eval/exec
Resource Protection	Memory monitoring; computation limits; output truncation
Code Validation	Block harmful operations; sanitize errors; prevent system info exposure

Iterative Error Recovery

1. Error Detection: Captures exceptions, syntax errors, runtime failures

2. Error Analysis: Parses messages, identifies root causes

3. Code Modification: Adjusts imports, fixes syntax, installs packages

4. Re-execution: Runs modified code (max 5 attempts)

5. Clean Presentation: Only final successful code shown to users

Example: Missing matplotlib -> agent installs it automatically -> re-executes -> user sees only working result.

Artifacts

1. Visualization Generation: Charts, graphs, plots, heatmaps saved as PNG/JPG/SVG and embedded in markdown

2. File Generation: CSV exports, JSON data, reports, processed files

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Sample Code

Using Code Interpreter Agent via SDK

from glaip_sdk import Client

client = Client()

agent = client.agents.find_agents("code_interpreter_agent")[0]
print(agent.run("Generate 5x5 chessboard"))

Output:

Executed Code:

import matplotlib.pyplot as plt
import numpy as np

# Create a 5x5 chessboard pattern
chessboard = np.zeros((5, 5))
chessboard[1::2, ::2] = 1
chessboard[::2, 1::2] = 1

plt.figure(figsize=(5, 5))
plt.imshow(chessboard, cmap='gray', interpolation='nearest')
plt.xticks([])
plt.yticks([])
plt.title('5x5 Chessboard')
plt.savefig('/tmp/output/chessboard_5x5.png', bbox_inches='tight', dpi=300)
plt.close()

Output: Example execution returns a generated chessboard image artifact plus summary text.