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---
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pagination_next: null
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pagination_prev: null
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---
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## How to add a community integration (not recommended)
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## How to add a community integration (not recommended)
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:::danger
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:::danger
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---
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pagination_next: null
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pagination_prev: null
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---
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# How to publish an integration package from a template
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# How to publish an integration package from a template
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:::danger
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:::danger
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@ -1,5 +1,5 @@
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---
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---
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sidebar_position: 5
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pagination_next: docs/contributing/how_to/integrations/package
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---
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---
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# Contribute Integrations
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# Contribute Integrations
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---
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pagination_next: docs/contributing/how_to/integrations/standard_tests
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pagination_prev: docs/contributing/how_to/integrations
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---
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# How to bootstrap a new integration package
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# How to bootstrap a new integration package
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This guide walks through the process of publishing a new LangChain integration
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This guide walks through the process of publishing a new LangChain integration
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@ -22,7 +26,10 @@ First, install Poetry:
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pip install poetry
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pip install poetry
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```
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```
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Next, create a new Python package with Poetry:
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Next, come up with a name for your package. For this guide, we'll use `langchain-parrot-link`.
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You can confirm that the name is available on PyPi by searching for it on the [PyPi website](https://pypi.org/).
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Next, create your new Python package with Poetry:
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```bash
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```bash
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poetry new langchain-parrot-link
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poetry new langchain-parrot-link
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@ -39,12 +46,12 @@ you are not using Poetry, we recommend adding these in a way that won't package
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with your published package, or just installing them separately when you run tests.
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with your published package, or just installing them separately when you run tests.
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`langchain-tests` will provide the [standard tests](./standard_tests) we will use later.
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`langchain-tests` will provide the [standard tests](./standard_tests) we will use later.
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We recommended pinning these to the latest version:
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We recommended pinning these to the latest version: <img src="https://img.shields.io/pypi/v/langchain-tests" style={{position:"relative",top:4,left:3}} />
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<img src="https://img.shields.io/pypi/v/langchain-tests" style={{position:"relative",top:4,left:3}} />
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Note: Replace `{latest version}` with the latest version of `langchain-tests` below.
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```bash
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```bash
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poetry add --group test pytest langchain-tests=={latest version}
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poetry add --group test pytest pytest-socket langchain-tests=={latest version}
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```
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```
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You're now ready to start writing your integration package!
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You're now ready to start writing your integration package!
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later, following the [standard tests](./standard_tests) guide.
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later, following the [standard tests](./standard_tests) guide.
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To implement `chat_models.py`, let's copy the implementation from our
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To implement `chat_models.py`, let's copy the implementation from our
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[Custom Chat Model Guide](../../../how_to/custom_chat_model).
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[Custom Chat Model Guide](../../../../how_to/custom_chat_model).
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<details>
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<details>
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<summary>chat_models.py</summary>
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<summary>chat_models.py</summary>
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```
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```
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</details>
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</details>
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## Publishing your package to PyPi
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First, make sure you have a PyPi account and have logged in with Poetry:
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```bash
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poetry config pypi-token.pypi <your-pypi-token>
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```
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Next, build your package:
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```bash
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poetry build
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```
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Finally, publish your package to PyPi:
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```bash
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poetry publish
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```
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You're all set! Your package is now available on PyPi and can be installed with `pip install langchain-parrot-link`.
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## Next Steps
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## Next Steps
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Now that you've published your package, you can move on to the next step: [Implement the standard tests](./standard_tests) for your integration and successfully run them.
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Now that you've implemented your package, you can move on to [testing your integration](../standard_tests) for your integration and successfully run them.
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143
docs/docs/contributing/how_to/integrations/publish.mdx
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143
docs/docs/contributing/how_to/integrations/publish.mdx
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---
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---
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# Publishing your package
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Now that your package is implemented and tested, you can:
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1. Publish your package to PyPi
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2. Add documentation for your package to the LangChain Monorepo
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## Publishing your package to PyPi
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This guide assumes you have already implemented your package and written tests for it. If you haven't done that yet, please refer to the [implementation guide](../package) and the [testing guide](../standard_tests).
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Note that Poetry is not required to publish a package to PyPi, and we're using it in this guide end-to-end for convenience.
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You are welcome to publish your package using any other method you prefer.
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First, make sure you have a PyPi account and have logged in with Poetry:
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<details>
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<summary>How to create a PyPi Token</summary>
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1. Go to the [PyPi website](https://pypi.org/) and create an account.
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2. Go to your account settings and enable 2FA. To generate an API token, you **must** have 2FA enabled currently.
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3. Go to your account settings and [generate a new API token](https://pypi.org/manage/account/token/).
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</details>
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```bash
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poetry config pypi-token.pypi <your-pypi-token>
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```
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Next, build your package:
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```bash
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poetry build
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```
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Finally, publish your package to PyPi:
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```bash
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poetry publish
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```
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You're all set! Your package is now available on PyPi and can be installed with `pip install langchain-parrot-link`.
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## Adding documentation to the LangChain Monorepo
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To add documentation for your package to the LangChain Monorepo, you will need to:
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1. Fork and clone the LangChain Monorepo
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2. Make a "Provider Page" at `docs/docs/integrations/providers/<your-package-name>.ipynb`
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3. Make "Component Pages" at `docs/docs/integrations/<component-type>/<your-package-name>.ipynb`
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4. Register your package in `libs/packages.yml`
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5. Submit a PR with **only these changes** to the LangChain Monorepo
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### Fork and clone the LangChain Monorepo
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First, fork the [LangChain Monorepo](https://github.com/langchain-ai/langchain) to your GitHub account.
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Next, clone the repository to your local machine:
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```bash
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git clone https://github.com/<your-username>/langchain.git
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```
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You're now ready to make your PR!
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### Bootstrap your documentation pages with the langchain-cli (recommended)
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To make it easier to create the necessary documentation pages, you can use the `langchain-cli` to bootstrap them for you.
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First, install the latest version of the `langchain-cli` package:
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```bash
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pip install --upgrade langchain-cli
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```
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To see the available commands to bootstrap your documentation pages, run:
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```bash
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langchain-cli integration create-doc --help
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```
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Let's bootstrap a provider page from the root of the monorepo:
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```bash
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langchain-cli integration create-doc \
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--component-type Provider \
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--destination-dir docs/docs/integrations/providers \
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--name parrot-link \
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--name-class ParrotLink \
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```
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And a chat model component page:
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```bash
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langchain-cli integration create-doc \
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--component-type ChatModel \
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--destination-dir docs/docs/integrations/chat \
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--name parrot-link \
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--name-class ParrotLink \
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```
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And a vector store component page:
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```bash
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langchain-cli integration create-doc \
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--component-type VectorStore \
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--destination-dir docs/docs/integrations/vectorstores \
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--name parrot-link \
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--name-class ParrotLink \
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```
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These commands will create the following 3 files, which you should fill out with information about your package:
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- `docs/docs/integrations/providers/parrot-link.ipynb`
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- `docs/docs/integrations/chat/parrot-link.ipynb`
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- `docs/docs/integrations/vectorstores/parrot-link.ipynb`
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### Manually create your documentation pages (if you prefer)
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If you prefer to create the documentation pages manually, you can create the same files listed
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above and fill them out with information about your package.
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You can view the templates that the CLI uses to create these files [here](https://github.com/langchain-ai/langchain/tree/master/libs/cli/langchain_cli/integration_template/docs) if helpful!
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### Register your package in `libs/packages.yml`
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Finally, add your package to the `libs/packages.yml` file in the LangChain Monorepo.
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```yaml
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packages:
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- name: langchain-parrot-link
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repo: <your github handle>/<your repo>
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path: .
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```
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For `path`, you can use `.` if your package is in the root of your repository, or specify a subdirectory (e.g. `libs/parrot-link`) if it is in a subdirectory.
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### Submit a PR with your changes
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Once you have completed these steps, you can submit a PR to the LangChain Monorepo with **only these changes**.
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"cell_type": "markdown",
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"cell_type": "markdown",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"---\n",
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"pagination_next: null\n",
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"pagination_prev: docs/contributing/how_to/integrations/standard_tests\n",
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"---\n",
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"# How to add standard tests to an integration\n",
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"# How to add standard tests to an integration\n",
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"\n",
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"\n",
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"When creating either a custom class for yourself or a new tool to publish in a LangChain integration, it is important to add standard tests to ensure it works as expected. This guide will show you how to add standard tests to a tool, and you can **[Skip to the test templates](#standard-test-templates-per-component)** for implementing tests for each integration.\n",
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"When creating either a custom class for yourself or a new tool to publish in a LangChain integration, it is important to add standard tests to ensure it works as expected. This guide will show you how to add standard tests to a tool, and you can **[Skip to the test templates](#standard-test-templates-per-component)** for implementing tests for each integration.\n",
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"Retriever": "retrievers.ipynb",
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"Retriever": "retrievers.ipynb",
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}
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}
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_component_types_str = ", ".join(f"`{k}`" for k in TEMPLATE_MAP.keys())
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@integration_cli.command()
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@integration_cli.command()
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def create_doc(
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def create_doc(
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str,
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str,
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typer.Option(
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typer.Option(
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help=(
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help=(
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"The type of component. Currently only 'ChatModel', "
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f"The type of component. Currently supported: {_component_types_str}."
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"'DocumentLoader', 'VectorStore' supported."
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),
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),
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),
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),
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] = "ChatModel",
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] = "ChatModel",
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docs_template = template_dir / TEMPLATE_MAP[component_type]
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docs_template = template_dir / TEMPLATE_MAP[component_type]
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else:
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else:
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raise ValueError(
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raise ValueError(
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f"Unrecognized {component_type=}. Expected one of 'ChatModel', "
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f"Unrecognized {component_type=}. Expected one of {_component_types_str}."
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f"'DocumentLoader', 'Tool'."
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)
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)
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shutil.copy(docs_template, destination_path)
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shutil.copy(docs_template, destination_path)
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