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python-lint (#14689)
# Description: _python-lint_ This agent writes Python code that is formatted and linted using `black`, `ruff`, and `mypy`, but does not execute the code. It writes the code to a temporary file and then runs the linters. Once these checks pass, the code is returned. # Dependencies - black - ruff - mypy # Demo The functionality can be seen here: https://huggingface.co/spaces/joshuasundance/langchain-streamlit-demo
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templates/python-lint/.gitignore
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templates/python-lint/.gitignore
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__pycache__
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templates/python-lint/LICENSE
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templates/python-lint/LICENSE
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MIT License
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Copyright (c) 2023 LangChain, Inc.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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templates/python-lint/README.md
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templates/python-lint/README.md
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# python-lint
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This agent specializes in generating high-quality Python code with a focus on proper formatting and linting. It uses `black`, `ruff`, and `mypy` to ensure the code meets standard quality checks.
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This streamlines the coding process by integrating and responding to these checks, resulting in reliable and consistent code output.
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It cannot actually execute the code it writes, as code execution may introduce additional dependencies and potential security vulnerabilities.
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This makes the agent both a secure and efficient solution for code generation tasks.
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You can use it to generate Python code directly, or network it with planning and execution agents.
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## Environment Setup
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- Install `black`, `ruff`, and `mypy`: `pip install -U black ruff mypy`
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- Set `OPENAI_API_KEY` environment variable.
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## Usage
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To use this package, you should first have the LangChain CLI installed:
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```shell
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pip install -U langchain-cli
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```
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To create a new LangChain project and install this as the only package, you can do:
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```shell
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langchain app new my-app --package python-lint
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```
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If you want to add this to an existing project, you can just run:
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```shell
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langchain app add python-lint
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```
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And add the following code to your `server.py` file:
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```python
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from python_lint import agent_executor as python_lint_agent
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add_routes(app, python_lint_agent, path="/python-lint")
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```
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(Optional) Let's now configure LangSmith.
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LangSmith will help us trace, monitor and debug LangChain applications.
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LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
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If you don't have access, you can skip this section
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```shell
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export LANGCHAIN_TRACING_V2=true
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export LANGCHAIN_API_KEY=<your-api-key>
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export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
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```
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If you are inside this directory, then you can spin up a LangServe instance directly by:
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```shell
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langchain serve
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```
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This will start the FastAPI app with a server is running locally at
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[http://localhost:8000](http://localhost:8000)
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We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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We can access the playground at [http://127.0.0.1:8000/python-lint/playground](http://127.0.0.1:8000/python-lint/playground)
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We can access the template from code with:
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```python
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from langserve.client import RemoteRunnable
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runnable = RemoteRunnable("http://localhost:8000/python-lint")
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```
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templates/python-lint/pyproject.toml
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templates/python-lint/pyproject.toml
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[tool.poetry]
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name = "python-lint"
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version = "0.0.1"
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description = "Python code-writing agent whose work is checked by black, ruff, and mypy."
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authors = ["Joshua Sundance Bailey"]
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readme = "README.md"
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[tool.poetry.dependencies]
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ruff = ">=0.1.8"
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black = ">=23.12.0"
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mypy = ">=1.7.1"
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python = ">=3.8.1,<4.0"
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langchain = ">=0.0.313, <0.1"
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openai = ">=1.3.9"
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[tool.poetry.group.dev.dependencies]
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langchain-cli = ">=0.0.4"
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fastapi = "^0.104.0"
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sse-starlette = "^1.6.5"
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[tool.langserve]
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export_module = "python_lint"
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export_attr = "agent_executor"
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[tool.templates-hub]
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use-case = "code-generation"
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author = "Joshua Sundance Bailey"
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integrations = ["OpenAI"]
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tags = ["python", "agent"]
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[build-system]
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requires = ["poetry-core"]
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build-backend = "poetry.core.masonry.api"
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templates/python-lint/python_lint/__init__.py
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templates/python-lint/python_lint/__init__.py
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from python_lint.agent_executor import agent_executor
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__all__ = ["agent_executor"]
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templates/python-lint/python_lint/agent_executor.py
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templates/python-lint/python_lint/agent_executor.py
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import os
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import re
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import subprocess # nosec
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import tempfile
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from langchain.agents import AgentType, initialize_agent
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from langchain.agents.tools import Tool
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from langchain.chat_models import ChatOpenAI
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from langchain.llms.base import BaseLLM
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from langchain.prompts import ChatPromptTemplate
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from langchain.pydantic_v1 import BaseModel, Field, ValidationError, validator
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from langchain.schema.runnable import ConfigurableField, Runnable
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def strip_python_markdown_tags(text: str) -> str:
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pat = re.compile(r"```python\n(.*)```", re.DOTALL)
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code = pat.match(text)
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if code:
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return code.group(1)
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else:
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return text
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def format_black(filepath: str):
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"""Format a file with black."""
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subprocess.run( # nosec
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f"black {filepath}",
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stderr=subprocess.STDOUT,
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text=True,
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shell=True,
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timeout=3,
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check=False,
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)
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def format_ruff(filepath: str):
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"""Run ruff format on a file."""
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subprocess.run( # nosec
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f"ruff check --fix {filepath}",
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shell=True,
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text=True,
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timeout=3,
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universal_newlines=True,
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check=False,
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)
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subprocess.run( # nosec
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f"ruff format {filepath}",
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stderr=subprocess.STDOUT,
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shell=True,
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timeout=3,
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text=True,
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check=False,
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)
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def check_ruff(filepath: str):
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"""Run ruff check on a file."""
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subprocess.check_output( # nosec
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f"ruff check {filepath}",
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stderr=subprocess.STDOUT,
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shell=True,
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timeout=3,
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text=True,
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)
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def check_mypy(filepath: str, strict: bool = True, follow_imports: str = "skip"):
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"""Run mypy on a file."""
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cmd = (
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f"mypy {'--strict' if strict else ''} "
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f"--follow-imports={follow_imports} {filepath}"
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)
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subprocess.check_output( # nosec
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cmd,
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stderr=subprocess.STDOUT,
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shell=True,
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text=True,
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timeout=3,
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)
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class PythonCode(BaseModel):
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code: str = Field(
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description="Python code conforming to "
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"ruff, black, and *strict* mypy standards.",
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)
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@validator("code")
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@classmethod
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def check_code(cls, v: str) -> str:
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v = strip_python_markdown_tags(v).strip()
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try:
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with tempfile.NamedTemporaryFile(mode="w", delete=False) as temp_file:
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temp_file.write(v)
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temp_file_path = temp_file.name
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try:
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# format with black and ruff
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format_black(temp_file_path)
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format_ruff(temp_file_path)
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except subprocess.CalledProcessError:
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pass
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# update `v` with formatted code
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with open(temp_file_path, "r") as temp_file:
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v = temp_file.read()
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# check
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complaints = dict(ruff=None, mypy=None)
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try:
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check_ruff(temp_file_path)
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except subprocess.CalledProcessError as e:
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complaints["ruff"] = e.output
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try:
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check_mypy(temp_file_path)
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except subprocess.CalledProcessError as e:
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complaints["mypy"] = e.output
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# raise ValueError if ruff or mypy had complaints
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if any(complaints.values()):
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code_str = f"```{temp_file_path}\n{v}```"
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error_messages = [
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f"```{key}\n{value}```"
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for key, value in complaints.items()
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if value
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]
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raise ValueError("\n\n".join([code_str] + error_messages))
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finally:
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os.remove(temp_file_path)
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return v
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def check_code(code: str) -> str:
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try:
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code_obj = PythonCode(code=code)
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return (
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f"# LGTM\n"
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f"# use the `submit` tool to submit this code:\n\n"
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f"```python\n{code_obj.code}\n```"
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)
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except ValidationError as e:
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return e.errors()[0]["msg"]
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prompt = ChatPromptTemplate.from_messages(
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[
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(
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"system",
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"You are a world class Python coder who uses "
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"black, ruff, and *strict* mypy for all of your code. "
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"Provide complete, end-to-end Python code "
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"to meet the user's description/requirements. "
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"Always `check` your code. When you're done, "
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"you must ALWAYS use the `submit` tool.",
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),
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(
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"human",
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": {input}",
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),
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],
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)
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check_code_tool = Tool.from_function(
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check_code,
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name="check-code",
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description="Always check your code before submitting it!",
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)
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submit_code_tool = Tool.from_function(
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strip_python_markdown_tags,
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name="submit-code",
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description="THIS TOOL is the most important. "
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"use it to submit your code to the user who requested it... "
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"but be sure to `check` it first!",
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return_direct=True,
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)
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tools = [check_code_tool, submit_code_tool]
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def get_agent_executor(
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llm: BaseLLM,
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agent_type: AgentType = AgentType.OPENAI_FUNCTIONS,
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) -> Runnable:
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_agent_executor = initialize_agent(
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tools,
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llm,
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agent=agent_type,
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verbose=True,
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handle_parsing_errors=True,
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prompt=prompt,
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)
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return _agent_executor | (lambda output: output["output"])
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class Instruction(BaseModel):
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__root__: str
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agent_executor = (
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get_agent_executor(ChatOpenAI(model_name="gpt-4-1106-preview", temperature=0.0))
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.configurable_alternatives(
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ConfigurableField("model_name"),
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default_key="gpt4turbo",
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gpt4=get_agent_executor(ChatOpenAI(model_name="gpt-4", temperature=0.0)),
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gpt35t=get_agent_executor(
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ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0.0),
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),
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)
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.with_types(input_type=Instruction, output_type=str)
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)
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0
templates/python-lint/tests/__init__.py
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0
templates/python-lint/tests/__init__.py
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