├── .gitignore ├── LICENSE ├── README.md ├── poetry.lock ├── pyproject.toml └── src └── replit_code_exec └── __init__.py /.gitignore: -------------------------------------------------------------------------------- 1 | /dist/ 2 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Copyright 2023 Replit 2 | 3 | Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies. 4 | 5 | THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. 6 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # `replit-code-exec` 2 | 3 | An interface to interact with Replit's code-exec API. 4 | 5 | This is an interface for the simpler use cases of https://replit.com/@luisreplit/eval-python, 6 | which is a stateless API that is optimized to be called from AI Agents so that they can perform 7 | numerical reasoning through the evaluation of generated Python code. In general, this allows 8 | the execution of an untrusted snippet of Python code and returns whatever is printed to standard 9 | output / standard error as the result. The execution is done inside an ephemeral unprivileged 10 | container created on the fly running in Replit Deployments using 11 | https://github.com/omegaup/omegajail as code sandbox. 12 | 13 | To set up your own copy of the API server, you need to follow these easy 2-3 steps (the second 14 | is optional): 15 | 16 | 1. Open the https://replit.com/@luisreplit/eval-python in your browser and Fork it to your 17 | account. 18 | 2. (Optional): if you want to change the Docker container, run `evalctl image ${DOCKER_IMAGE}` 19 | (e.g. `evalctl image python:3` or `evalctl image replco/python-kitchen-sink:latest`). 20 | * Open `.replit` and change the `EVAL_FILENAME`, `EVAL_RUN_COMMAND`, `EVAL_ENV` to suite the 21 | new container, if needed. 22 | 3. Deploy the Repl! (just pressing `Run` is not enough) 23 | * This is only compatible with the Autoscale Deployments. 24 | * Make sure you set the `EVAL_TOKEN_AUTH` Deployments secrets when 25 | doing so for authentication. 26 | 27 | ## Sample usage 28 | 29 | Here is a small example of this library being used as a small math solver using OpenAI API: 30 | 31 | ```python 32 | import openai 33 | import replit_code_exec 34 | 35 | code_exec = replit_code_exec.build_code_exec(...) 36 | 37 | def solve_math(prompt: str, model: str = 'gpt-3.5-turbo-0613') -> str: 38 | completion = openai.ChatCompletion.create( 39 | model=model, 40 | temperature=0.7, 41 | functions=[code_exec.openai_schema], 42 | function_call={"name": "code_exec"}, 43 | messages=[ 44 | { 45 | "role": "system", 46 | "content": ("You are an assistant that knows how to solve math " + 47 | "problems by converting them into Python programs."), 48 | }, 49 | { 50 | "role": "user", 51 | "content": ("Please solve the following problem by creating a Python " + 52 | "program that prints the solution to standard output using " + 53 | "`print()`: " + prompt), 54 | }, 55 | ], 56 | ) 57 | return code_exec.from_response(completion) 58 | ``` 59 | -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "aiohappyeyeballs" 5 | version = "2.4.0" 6 | description = "Happy Eyeballs for asyncio" 7 | optional = false 8 | python-versions = ">=3.8" 9 | files = [ 10 | {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"}, 11 | {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"}, 12 | ] 13 | 14 | [[package]] 15 | name = "aiohttp" 16 | version = "3.10.2" 17 | 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"pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] 1258 | 1259 | [metadata] 1260 | lock-version = "2.0" 1261 | python-versions = ">=3.9,<4.0" 1262 | content-hash = "8345ad5db3d2835041c722040ca2f5d8badf779d5212645f6a7c3969080f9285" 1263 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "replit-code-exec" 3 | version = "0.0.1" 4 | description = "A library for interacting with Replit's code-exec API" 5 | authors = ["Repl.it "] 6 | license = "ISC" 7 | readme = "README.md" 8 | repository = "https://github.com/replit/replit-code-exec" 9 | homepage = "https://github.com/replit/replit-code-exec" 10 | classifiers = [ 11 | "Programming Language :: Python :: 3", 12 | "License :: OSI Approved :: ISC License (ISCL)", 13 | "Operating System :: OS Independent", 14 | ] 15 | packages = [ 16 | { include = "replit_code_exec", from = "src" } 17 | ] 18 | 19 | [tool.poetry.dependencies] 20 | python = ">=3.9,<4.0" 21 | instructor = "^0.2.7" 22 | requests = "^2.31.0" 23 | 24 | [tool.poetry.group.dev.dependencies] 25 | black = ">=23.3,<25.0" 26 | mypy = "^1.4.0" 27 | ruff = "^0.0.278" 28 | types-requests = "^2.31.0.2" 29 | 30 | 31 | [tool.pyright] 32 | # https://github.com/microsoft/pyright/blob/main/docs/configuration.md 33 | useLibraryCodeForTypes = true 34 | 35 | 36 | [tool.poetry.dev-dependencies] 37 | Flask = "^2.2.0" 38 | pytest = "^7.4.1" 39 | 40 | 41 | [build-system] 42 | requires = ["poetry>=0.12"] 43 | build-backend = "poetry.masonry.api" 44 | 45 | 46 | [tool.ruff] 47 | # https://beta.ruff.rs/docs/configuration/ 48 | line-length = 100 49 | -------------------------------------------------------------------------------- /src/replit_code_exec/__init__.py: -------------------------------------------------------------------------------- 1 | """An interface to interact with Replit's code-exec API.""" 2 | 3 | import logging 4 | from typing import Any, Dict, Optional 5 | 6 | import instructor # type: ignore 7 | import requests 8 | 9 | 10 | def code_exec( 11 | url: str, 12 | bearer_token: str, 13 | code: str, 14 | files: Optional[Dict[str, str]] = None, 15 | strace: bool = False, 16 | interpreter_mode: bool = False, 17 | ) -> str: 18 | """Evaluates a snippet of Python code in a sandbox. 19 | 20 | This is an interface for the simpler use cases of https://replit.com/@luisreplit/eval-python. In 21 | general, this allows executed an untrusted snippet of Python code and returns whatever is 22 | printed to standard output / standard error as the result. The execution is done inside an 23 | ephemeral unprivileged container created on the fly running in Replit Deployments using 24 | https://github.com/omegaup/omegajail as code sandbox. 25 | 26 | To set up your own copy of the API server, you need to follow these easy 2-3 steps (the second 27 | is optional): 28 | 29 | 1. Open the https://replit.com/@luisreplit/eval-python in your browser and Fork it to your 30 | account. 31 | 2. (Optional): if you want to change the Docker container, run `evalctl image ${DOCKER_IMAGE}` 32 | (e.g. `evalctl image python:3` or `evalctl image replco/python-kitchen-sink:latest`). 33 | * Open `.replit` and change the `EVAL_FILENAME`, `EVAL_RUN_COMMAND`, `EVAL_ENV` to suite the 34 | new container, if needed. 35 | 3. Deploy the Repl! (just pressing `Run` is not enough) 36 | * This is only compatible with the Autoscale Deployments. 37 | * Make sure you set the `EVAL_TOKEN_AUTH` Deployments secrets when 38 | doing so for authentication. 39 | 40 | Args: 41 | url: The URL of the Deployed version of your fork of 42 | https://replit.com/@luisreplit/eval-python 43 | bearer_token: The contents of the `EVAL_TOKEN_AUTH` Deployments secret. 44 | code: The snippet of Python code that will be evaluated. 45 | files: (Optional): a map of filenames -> contents that will be written to the current 46 | directory where the Python code will be executed. 47 | strace: (Optional): For debugging purposes, run `strace` before executing the code. 48 | interpreter_mode: (Optional): Sometimes it is desirable to avoid needing to explicitly call 49 | `print()` to get access to the values that are evaluated. When this option is enabled, 50 | the sandbox will behave like the `python` CLI interpreter, where any expressions are 51 | output into standard output. 52 | 53 | Returns: 54 | A string containing the standard output / standard input printed during the execution of 55 | `code`. 56 | """ 57 | data: Dict[str, Any] = {"code": code} 58 | if files is not None: 59 | data["files"] = files 60 | if strace: 61 | data["strace"] = True 62 | if interpreter_mode: 63 | data["interpreter_mode"] = True 64 | return requests.post( 65 | url, 66 | json=data, 67 | headers={ 68 | "Content-Type": "application/json", 69 | "Authorization": "Bearer " + bearer_token, 70 | }, 71 | ).text 72 | 73 | 74 | def build_code_exec( 75 | url: str, 76 | bearer_token: str, 77 | files: Optional[Dict[str, str]] = None, 78 | strace: bool = False, 79 | interpreter_mode: bool = False, 80 | ) -> instructor.openai_function: 81 | """An ergonomic way to use `code_exec` with the OpenAI API. 82 | 83 | Sample usage: 84 | 85 | import openai 86 | import replit_code_exec 87 | 88 | code_exec = replit_code_exec.build_code_exec(...) 89 | 90 | def solve_math(prompt: str, model: str = 'gpt-3.5-turbo-0613') -> str: 91 | completion = openai.ChatCompletion.create( 92 | model=model, 93 | temperature=0.7, 94 | functions=[code_exec.openai_schema], 95 | function_call={"name": "code_exec"}, 96 | messages=[ 97 | { 98 | "role": "system", 99 | "content": ("You are an assistant that knows how to solve math " + 100 | "problems by converting them into Python programs."), 101 | }, 102 | { 103 | "role": "user", 104 | "content": ("Please solve the following problem by creating a Python " + 105 | "program that prints the solution to standard output using " + 106 | "`print()`: " + prompt), 107 | }, 108 | ], 109 | ) 110 | return code_exec.from_response(completion) 111 | 112 | See the documentation of `code_exec` for more information. 113 | 114 | Args: 115 | url: The URL of the Deployed version of your fork of 116 | https://replit.com/@luisreplit/eval-python 117 | bearer_token: The contents of the `EVAL_TOKEN_AUTH` Deployments secret. 118 | files: (Optional): a map of filenames -> contents that will be written to the current 119 | directory where the Python code will be executed. 120 | strace: (Optional): For debugging purposes, run `strace` before executing the code. 121 | interpreter_mode: (Optional): Sometimes it is desirable to avoid needing to explicitly call 122 | `print()` to get access to the values that are evaluated. When this option is enabled, 123 | the sandbox will behave like the `python` CLI interpreter, where any expressions are 124 | output into standard output. 125 | 126 | Returns: 127 | A `instructor.openai_function`-wrapped function that can be used with 128 | OpenAI's function invocation API. 129 | """ 130 | 131 | @instructor.openai_function # type: ignore 132 | def _code_exec(code: str) -> str: 133 | """ 134 | Evaluates an arbitrary snippet of Python code. This is useful if you want answer to 135 | a computation that can be answered by creating a standalone Python code that prints 136 | the answer to standard output. 137 | 138 | In order to use it, you need to specify the code as if it were the contents of a 139 | file called main.py with no code fences and run with the Python interpreter as 140 | `python3 main.py`. The answer should be printed to standard output. 141 | 142 | Some things to note: 143 | - There are no other files in the current directory. This means that any attempt to 144 | open() files will fail. 145 | - Make sure the code is optimized so that it runs fast. Try to use memoization. 146 | - Always call print() with the final result so that it is printed to standard 147 | output. 148 | 149 | Bad response: 150 | ```python 151 | 1 + 1 152 | ``` 153 | 154 | Good response: 155 | import urllib.request 156 | print(urllib.request.urlopen(\"https://ifconfig.me\").read().decode(\"utf-8\")) 157 | """ 158 | code = code.strip() 159 | if code.startswith("```") and code.endswith("```"): 160 | # We told the agent to not add code fences and it ignored us >:( 161 | code = "\n".join(code.split("\n")[1:-1]) 162 | response = code_exec(url, bearer_token, code, files, strace, interpreter_mode) 163 | logging.debug("code to evaluate %r, response %r", code, response) 164 | return response 165 | 166 | return _code_exec 167 | --------------------------------------------------------------------------------