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The CSVLoader loads a CSV file into a list of documents.
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Check out more about the CSVLoader in LangChain{.internal-link target=_blank} documentation.
⛓️LangFlow example
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Download Flow{: .md-button download="Csv_loader"}
File path:
Download CSV{: .md-button download="organizations-100.csv"}
CharacterTextSplitter implements splitting text based on characters.
Text splitters operate as follows:
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Split the text into small, meaningful chunks (usually sentences).
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Combine these small chunks into larger ones until they reach a certain size (measured by a function).
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Once a chunk reaches the desired size, make it its piece of text and create a new chunk with some overlap to maintain context.
Separator used:
.
Chunk size used:
2000
Chunk overlap used:
200
For the example, we used `OpenAI` as the LLM, but you can use any LLM that has an API. Make sure to get the API key from the LLM provider. For example, [OpenAI](https://platform.openai.com/){.internal-link target=_blank} requires you to create an account to get your API key.
Check out the OpenAI{.internal-link target=_blank} documentation to learn more about the API and the options that contain in the node.
The OpenAIEmbeddings, wrapper around OpenAI Embeddings{.internal-link target=_blank} models. Make sure to get the API key from the LLM provider, in this case OpenAI{.internal-link target=_blank}.
Chroma vector databases can be used as vector stores to conduct a semantic search or to select examples, thanks to a wrapper around them.
A VectorStoreInfo set information about the vector store, such as the name and description.
Name used:
organizations-100
Description used:
A table contains 100 companies.
The VectoStoreAgentis an agent designed to retrieve information from one or more vector stores, either with or without sources.