Explore popular use cases to empower your teams

Explore popular use cases to empower your teams

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End-to-end RAG with Airbyte Cloud, Microsoft Sharepoint, and Milvus (Zilliz)

Learn how to build an end-to-end RAG pipeline, extracting data from Microsoft Sharepoint using Airbyte Cloud, loading it on Milvus (Zilliz), and then using LangChain to perform RAG on the stored data.

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

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.

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End-to-end RAG using Airbyte's Terraform, dbt, Notion, BigQuery and Pinecone

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

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End-to-end RAG using GitHub, PyAirbyte, and Langchain

Learn how to use the PyAirbyte library to read records from Github, converts those records to documents, which can then be passed to LangChain for RAG.

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Sentiment analysis using Google sheets and Snowflake Cortex

Learn how to load user review data from Google Sheets intoS nowflake Cortex based vector store, and perform sentiment analysis using Snowflake Cortex's sentiment function.

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

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.

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Illustrating the Usage of langchain _airbyte Package

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.

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End-to-end RAG using Jira, PyAirbyte, Pinecone, and LangChain

Learn how to build a RAG pipeline, extracting data from Jira using PyAirbyte, storing it in a Pinecone vector store, and then using LangChain to perform RAG on the stored data.

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End-to-end RAG using Milvus Lite and PyAirbyte - fully in Python

Learn how to build a simple RAG (Retrieval-Augmented Generation) pipeline with Milvus Lite and PyAirbyte, for a fully local development in Python.

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Storing GitHub vector data into Snowflake Cortex using PyAirbyte

Learn how to load data from GitHub airbyte-source into Snowflake using PyAirbyte, and afterwards convert the stream data into vector.

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End-to-end RAG using Github, PyAirbyte and Chroma Vector DB

Learn how to set up a RAG pipeline from GitHub, using PyAirbyte, storing the data in Chroma, using LangChain to perform RAG on the stored data.

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End-to-end RAG using a file source, PyAirbyte, Pinecone, and Langchain

Learn how to build a RAG pipeline, extracting data from a file source using PyAirbyte, storing it in a Pinecone vector store, and then using LangChain to perform RAG on the stored data.