Explore popular use cases to empower your teams

Illustrating the Usage of langchain _airbyte Package

made by

The langchain-airbyte package integrates LangChain with Airbyte. It has a very powerful function AirbyteLoader which can be used to load data as document into langchain from any Airbyte source.

Check the tutorial >

End-to-end RAG using Facebook Marketing, PyAirbyte, Milvus (Zilliz), and Langchain

made by

Learn how to use PyAirbyte to load data from Facebook marketing, store the data in Milvus (Zilliz) vector store and perform a short RAG demo (using OpenAI/LangChain).

Check the tutorial >

End-to-end RAG using Github, PyAirbyte and Weaviate

made by

Learn how to load data from Github into Weaviate using PyAirbyte, then to use source-github and its stream 'issues'.

Check the tutorial >

End-to-end RAG using Airbyte Cloud, S3 and Pinecone

made by

Learn how to build a full data stack using Airbyte Cloud, Terraform, and dbt to move data from S3 -> BigQuery -> Pinecone for interacting with fetched data through an LLM and form a full fledged RAG.

Check the tutorial >

End-to-end RAG using Google Drive, PyAirbyte, Pinecone, and LangChain

made by

Learn how to build an end-to-end RAG pipeline, extracting data from Google Drive using PyAirbyte, storing it in Pinecone, and then using LangChain to perform RAG on the stored data.

Check the tutorial >

Building data chat agent with PyAirbyte Polygon.io source & Langchain

made by

Learn how to use polygon.io as a data source and use the Langchain experimental agent.

Check the tutorial >

Quickstart for End-to-end RAG using Gitlab, PyAirbyte, and Qdrant

made by

Learn how to build an end-to-end RAG pipeline, extracting data from Gitlab using PyAirbyte, storing it in Qdrant, and then using LangChain to perform RAG on the stored data.

Check the tutorial >

RAG based recommendation system on Shopify, using PyAirbyte, Langchain and Pinecone

made by

Learn how to build an end-to-end RAG pipeline, extracting data from Shopify using PyAirbyte, storing it on Pinecone, and then use LangChain to perform RAG on the stored data.

Check the tutorial >

Streamlining Amazon Product Review Analysis with Apify and Snowflake Cortex

made by

Learn how to scrape customer reviews from an Amazon product page, loading the data into Snowflake Cortex, and performing summarization.

Check the tutorial >

End-to-end RAG using S3, PyAirbyte, Pinecone, and Langchain

made by

Learn how to build an end-to-end RAG pipeline, extracting data from an S3 bucket using PyAirbyte, storing it in a Pinecone vector store, and then use LangChain to perform RAG on the stored data.

Check the tutorial >

Scraping web data from Apify source into Airbyte for Langchain

made by

Learn how to scrape data from a website and load it in a database using PyAirbyte and LangChain. Integrating web data into LLMs can enhance their performance by providing up-to-date and relevant information.

Check the tutorial >

End-to-end RAG using Airbyte Cloud, S3 and Snowflake Cortex

made by

Learn how to set up an end-to-end RAG pipeline using Airbyte Cloud, Amazon S3, and Snowflake Cortex.

Check the tutorial >
Loading more...