community: add Dappier retriever

[amaan-ai20]

Add a retriever to interact with Dappier APIs with an example notebook.

The retriever can be invoked with:

from langchain_community.retrievers import DappierRetriever

retriever = DappierRetriever(data_model_id="dm_01jagy9nqaeer9hxx8z1sk1jx6", k=5)

retriever.invoke("latest tech news")

To retrieve 5 documents related to latest news in the tech sector. The included notebook also includes deeper details about controlling filters such as selecting a data model, number of documents to return, site domain reference, minimum articles from the reference domain, and search algorithm, as well as including the retriever in a chain.

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Name	Status	Preview	Comments	Updated (UTC)
langchain	✅ Ready (Inspect)	Visit Preview	💬 Add feedback	Dec 23, 2024 6:26pm

[ccurme]

Hello, thanks for this.

Would you be interested in implementing this via a separate integration package (e.g., langchain-dappier)? We've written a walkthrough on this process here:

https://python.langchain.com/docs/contributing/how_to/integrations/

We are encouraging contributors of LangChain integrations to go this route. This way we don't have to be in the loop for reviews, you're able to properly integration test the model, and you have control over versioning.

Docs would continue to be maintained in the langchain repo.

Let me know what you think!

[amaan-ai20]

Hello, thanks for this.

Would you be interested in implementing this via a separate integration package (e.g., langchain-dappier)? We've written a walkthrough on this process here:

https://python.langchain.com/docs/contributing/how_to/integrations/

We are encouraging contributors of LangChain integrations to go this route. This way we don't have to be in the loop for reviews, you're able to properly integration test the model, and you have control over versioning.

Docs would continue to be maintained in the langchain repo.

Let me know what you think!

Sure, thanks! I feel this is a cleaner and better way to do things.