Step-by-Step Guides

CSV Loader

CSV Loader

The VectoStoreAgent component retrieves information from one or more vector stores. This example shows a VectoStoreAgent connected to a CSV file through the Chroma vector store. Process description:

  • The CSVLoader loads a CSV file into a list of documents.

  • The extracted data is then processed by the CharacterTextSplitter, which splits the text into small, meaningful chunks (usually sentences).

  • These chunks feed the Chroma vector store, which converts them into vectors and stores them for fast indexing.

  • Finally, the agent accesses the information of the vector store through the VectorStoreInfo tool.


The vector store is used for efficient semantic search, while VectorStoreInfo carries information about it, such as its name and description. Embeddings are a way to represent words, phrases, or any entities in a vector space. Learn more about them here.


Once you build this flow, ask questions about the data in the chat interface (e.g., number of rows or columns).

⛓️ Langflow Example

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Assynchronous Processing
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Step-by-Step Guides

Async API
Integrating documents with prompt variables
Building chatbots with System Message
Integrating Langfuse with Langflow


FlowRunner Component
Conversation Chain
Buffer Memory
MidJourney Prompt Chain
CSV Loader
Serp API Tool
Multiple Vector Stores
Python Function
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