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https://github.com/hwchase17/langchain
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# 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
75 lines
2.4 KiB
Markdown
75 lines
2.4 KiB
Markdown
# 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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