Chat with your data using LangChain, Pinecone, and Airbyte
Hi HN, A few of our team members at Airbyte (and Joe, who killed it!) recently played with building our own internal support chat bot, using Airbyte, Langchain, Pinecone and OpenAI, that would answer any questions we ask when developing a new connector on Airbyte. As we prototyped it, we realized that it could be applied for many other use cases and sources of data, so... we created a tutorial that other community members can leverage [http://airbyte.com/tutorials/chat-with-your-data-using-opena...] and the Github repo to run it…
Chat with your data using LangChain, Pinecone, and Airbyte launched on August 8, 2023 with 220 votes, #167 of 4,347 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
This tutorial demonstrates how to build a chat interface that answers questions about custom data using Airbyte, LangChain, Pinecone, and OpenAI. It is for developers who want to create conversational AI applications. The tutorial covers extracting unstructured data from various sources with Airbyte, loading data into a vector database, and integrating that database with ChatGPT. A GitHub repository provides working code to implement the approach for different data sources and use cases.
written from the facts on this page · September 2026
From the sources
The context layer for production-grade AI agents. Connect Salesforce, Stripe, Zendesk +50 more into a queryable Context Store, so your agent reasons across systems without stitching APIs at runtime. UI, MCP, or SDK. 40% fewer tool calls, up to 80% fewer tokens.
This tutorial will show how you can build a Slackbot on your own data
In a previous article , we explained how Dagster and Airbyte can be leveraged to power LLM-supported use cases. Our newly introduced vector database destination makes this even easier as it removes the need to orchestrate chunking and embedding manually - instead the sources can be directly connected to the vector database through an Airbyte connection. This tutorial walks you through a real-world use case of how to leverage vector databases and LLMs to make sense out of your unstructured data. By the end of this, you will: To better illustrate how this can look in practice, let’s use something that’s relevant for Airbyte itself. Airbyte is a highly extensible system that allows users to…from airbyte.com
In the maker’s words, at launch
Hi HN, A few of our team members at Airbyte (and Joe, who killed it!) recently played with building our own internal support chat bot, using Airbyte, Langchain, Pinecone and OpenAI, that would answer any questions we ask when developing a new connector on Airbyte. As we prototyped it, we realized that it could be…
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