> ## Documentation Index
> Fetch the complete documentation index at: https://docs.declaw.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent in Sandbox (Anthropic)

> Use Anthropic Claude to generate Python code and execute it securely inside a Declaw sandbox. The model runs on the host; only the generated code runs inside the isolated sandbox.

## What You'll Learn

* How to call the Anthropic Messages API and feed the response directly into a sandbox
* Structuring prompts to get code-only output (no markdown, no explanation)
* Sandbox-per-task isolation: fresh sandbox for each code generation request
* Demo mode: run the full workflow without an Anthropic API key

## Prerequisites

* Declaw running locally or in the cloud (see [Deployment](/deployment/overview))
* `DECLAW_API_KEY` and `DECLAW_DOMAIN` set in your environment
* `ANTHROPIC_API_KEY` set in your environment (optional — demo mode runs without it)

<Note>
  This example is available in Python. TypeScript support coming soon.
</Note>

## Code Walkthrough

### Live mode (requires `ANTHROPIC_API_KEY`)

```python theme={null}
import anthropic
from declaw import Sandbox

client = anthropic.Anthropic()

task = "Write a Python script that computes the Fibonacci sequence up to the 20th number."

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": (
                f"You are a code generation agent. Given a task, respond "
                f"ONLY with Python code that accomplishes the task and "
                f"prints the results. No markdown fences, no explanation.\n\n"
                f"Task: {task}"
            ),
        },
    ],
)

code = strip_code_fences(message.content[0].text)

sbx = Sandbox.create(template="python", timeout=300)
try:
    sbx.files.write("/tmp/generated.py", code)
    result = sbx.commands.run("python3 /tmp/generated.py", timeout=30)
    print(result.stdout)
finally:
    sbx.kill()
```

The Anthropic Messages API returns a list of content blocks. For text output, access `message.content[0].text`.

### Prompt engineering for code-only output

The system prompt tells Claude to respond only with Python code. Two keys:

1. State `ONLY with Python code` explicitly
2. Add `No markdown fences, no explanation` — Claude sometimes wraps code in ` ```python ` blocks regardless

Always call `strip_code_fences()` as a defensive measure even when the prompt says not to include fences.

### Demo mode — text readability analysis

The demo mode runs a pre-written analysis script that computes Flesch Reading Ease for a sample text:

```python theme={null}
simulated_code = textwrap.dedent("""\
    import re

    text = (
        "The quick brown fox jumps over the lazy dog. "
        "Pack my box with five dozen liquor jugs."
    )

    sentences = [s.strip() for s in re.split(r'[.!?]+', text) if s.strip()]
    words = text.split()
    syllable_count = sum(
        max(1, len(re.findall(r'[aeiouy]+', w.lower())))
        for w in words
    )
    avg_sentence_length = round(len(words) / len(sentences), 2)
    avg_syllables_per_word = round(syllable_count / len(words), 2)

    flesch = round(206.835 - 1.015 * avg_sentence_length - 84.6 * avg_syllables_per_word, 1)
    print(f"Flesch Reading Ease: {flesch}")
""")

sbx = Sandbox.create(template="python", timeout=300)
try:
    sbx.files.write("/tmp/generated.py", simulated_code)
    result = sbx.commands.run("python3 /tmp/generated.py", timeout=30)
    print(result.stdout)
finally:
    sbx.kill()
```

## Expected Output (demo mode)

```
Agent in Sandbox (Anthropic) Example
============================================================
ANTHROPIC_API_KEY not set — running in demo mode.

--- Demo: Simulating Anthropic Claude agent workflow ---

  Simulated task: Analyze text and compute readability statistics
  Creating sandbox and executing...
  Sandbox created: sbx-abc123

  Output:
    === Text Readability Analysis ===
      Sentences:             4
      Words:                 36
      Characters (alpha):    151
      Syllables (approx):    46
      Avg word length:       4.19
      Avg sentence length:   9.0
      Avg syllables/word:    1.28
      Flesch Reading Ease:   67.2
      Readability:           Easy to read

  Sandbox sbx-abc123 killed.
```

## Comparison with OpenAI Example

The pattern is identical to the [OpenAI example](/cookbook/agent-in-sandbox/openai) — only the API client and model differ. This makes it easy to swap providers:

| Provider  | Client                  | Model                      |
| --------- | ----------------------- | -------------------------- |
| Anthropic | `anthropic.Anthropic()` | `claude-sonnet-4-20250514` |
| OpenAI    | `openai.OpenAI()`       | `gpt-4o-mini`              |

The sandbox creation and execution steps are the same regardless of which LLM you use.