chore: import upstream snapshot with attribution

2026-07-13 13:24:08 +08:00
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+# integration-e2b (E2B Code Evaluation)
+
+## What This Example Demonstrates
+
+This example shows a complete prompt→LLM→sandboxed-execution→metric pipeline using:
+
+- `promptfoo` to run LLM prompts and manage evaluation cases.
+- An LLM provider to generate Python functions from a short problem prompt.
+- e2b sandboxes (via `e2b-code-interpreter`) to run generated code safely.
+- OpenAI step to generate small verification unit tests and re-run them in the sandbox.
+- Per-run JSON metrics written to .promptfoo_results/ and a human-friendly markdown report produced by report.py.
+
+You can run this example with:
+
+```bash
+npx promptfoo@latest init --example integration-e2b
+cd integration-e2b
+```
+
+## Environment Variables
+
+Set these in your shell before running the example.
+
+```bash
+# Required
+export E2B_API_KEY="e2b_xxx_your_key_here"        # e2b sandbox API key
+export OPENAI_API_KEY="sk_xxx_your_key_here"     # OpenAI key (or your chosen LLM provider)
+
+# Recommended
+export PROMPTFOO_PYTHON="$(pwd)/.venv/bin/python"  # tell promptfoo which Python/venv to use
+```
+
+- If you use a different provider name in promptfooconfig.yaml, add that provider's key instead.
+
+## Prerequisites
+
+Install and prepare a Python virtual environment, and install the required packages.
+
+```bash
+# create & activate venv
+python -m venv .venv
+source .venv/bin/activate
+
+# install Python packages
+pip install --upgrade pip
+pip install e2b-code-interpreter
+npm i -g promptfoo
+```
+
+## Running the Example
+
+Activate venv and ensure env vars are set:
+
+```bash
+source .venv/bin/activate
+export E2B_API_KEY="e2b_xxx"
+export OPENAI_API_KEY="sk_xxx"
+export PROMPTFOO_PYTHON="$(pwd)/.venv/bin/python"
+```
+
+Run the evaluation:
+
+```bash
+promptfoo eval
+```
+
+Open the interactive viewer:
+
+```bash
+promptfoo view
+```