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🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 chore(chains.mdx): update verbose parameter description to improve clarity 🔧 chore(chains.mdx): fix formatting and indentation for better code readability 🔧 📝 chore(docs): update import statements for Admonition component in examples 📝 chore(docs): update link in Prompts component to use Admonition component 📝 chore(docs): update import statements for Admonition component in examples 📝 chore(docs): update link in Conversation Chain component to use Admonition component 📝 chore(docs): update import statements for Admonition component in examples 📝 chore(docs): update link in CSV Loader component to use Admonition component 📝 chore(docs): update import statements for Admonition component in examples 📝 chore(docs): update link in MidJourney Prompt Chain component to use Admonition component 📝 chore(docs): update import statements for Admonition component in examples 📝 chore(docs): update link in Multiple Vector Stores component to use Admonition component 📝 docs(examples/python-function.mdx): add import statement for Admonition component 📝 docs(examples/python-function.mdx): improve readability of tip admonition by breaking lines 📝 docs(examples/python-function.mdx): improve readability of info admonition by breaking lines 📝 docs(examples/serp-api-tool.mdx): add import statement for Admonition component 📝 docs(examples/serp-api-tool.mdx): improve readability of info admonition by breaking lines 📝 docs(guidelines/features.mdx): add import statement for Admonition component 📝 docs(guidelines/features.mdx): improve readability of caution admonition by breaking lines
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import Admonition from "@theme/Admonition";
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# CSV Loader
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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:
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- The `CSVLoader` loads a CSV file into a list of documents.
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- The extracted data is then processed by the `CharacterTextSplitter`, which splits the text into small, meaningful chunks (usually sentences).
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- These chunks feed the `Chroma` vector store, which converts them into vectors and stores them for fast indexing.
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- Finally, the agent accesses the information of the vector store through the `VectorStoreInfo` tool.
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<Admonition type="info">
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The vector store is used for efficient semantic search, while
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`VectorStoreInfo` carries information about it, such as its name and
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description. Embeddings are a way to represent words, phrases, or any entities
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in a vector space. Learn more about them
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[here](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings).
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</Admonition>
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<Admonition type="tip">
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Once you build this flow, ask questions about the data in the chat interface
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(e.g., number of rows or columns).
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</Admonition>
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## ⛓️ Langflow Example
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import ThemedImage from "@theme/ThemedImage";
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import ZoomableImage from "/src/theme/ZoomableImage.js";
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<ZoomableImage
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alt="Docusaurus themed image"
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sources={{
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light: "img/csv-loader.png",
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}}
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/>
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#### <a target="\_blank" href="json_files/CSV_Loader.json" download>Download Flow</a>
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<Admonition type="note" title="LangChain Components 🦜🔗">
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- [`CSVLoader`](https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/csv)
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- [`CharacterTextSplitter`](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter)
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- [`OpenAIEmbedding`](https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/openai)
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- [`Chroma`](https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/chroma)
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- [`VectorStoreInfo`](https://python.langchain.com/docs/modules/data_connection/vectorstores/)
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- [`OpenAI`](https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai)
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- [`VectorStoreAgent`](https://python.langchain.com/docs/modules/agents/toolkits/vectorstore)
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</Admonition>
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