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docs/multiple-vectorstores.md

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+`VectorStoreRouterAgent` construct an agent that routes between multiple vectorstores.
+
+<br>
+
+![Description](img/single_node/mult_vect.png#only-light){width=50%}
+![Description](img/single_node/mult_vect2.png#only-dark){width=50%}
+
+<br>
+
+For more information about [VectorStoreRouterAgent](https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/agent_vectorstore.html?highlight=Router){.internal-link target=\_blank}, check out the LangChain documentation.
+
+---
+### ⛓️LangFlow example
+
+![Description](img/multiple-vectorstores2.png#only-dark){width=100%}
+![Description](img/multiple-vectorstores.png#only-light){width=100%}
+
+<br>
+
+[Download Flow](data/Multiple_vectorstores.json){: .md-button download="Multiple_vectorstores"}
+
+<br>
+
+`TextLoader` loads text from a file.
+
+<br>
+
+[Download txt](data/state_of_the_union.txt){: .md-button download="state-of-the-union"}
+
+<br>
+
+By using `WebBaseLoader`, you can load all text from webpages into a document format that we can use downstream. Web path used:
+
+```txt
+https://beta.ruff.rs/docs/faq/
+```
+
+`CharacterTextSplitter` implements splitting text based on characters.
+
+Text splitters operate as follows:
+
+- Split the text into small, meaningful chunks (usually sentences).
+
+- Combine these small chunks into larger ones until they reach a certain size (measured by a function).
+
+- 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**:
+
+```txt
+.
+```
+
+**Chunk size used**:
+
+```txt
+2000
+```
+
+**Chunk overlap used**:
+
+```txt
+200
+```
+
+<br>
+
+The `OpenAIEmbeddings`, wrapper around [OpenAI Embeddings](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings){.internal-link target=\_blank} models. Make sure to get the API key from the LLM provider, in this case [OpenAI](https://platform.openai.com/){.internal-link target=\_blank}.
+
+<br>
+
+`Chroma` vector databases can be used as vectorstores to conduct a semantic search or to select examples, thanks to a wrapper around them.
+
+<br>
+
+`VectorStoreInfo` set information about the vectorstore, such as the name and description.
+
+<br>
+
+**First VectorStoreInfo**
+
+<br>
+
+Name:
+
+```txt
+state_of_union_address
+```
+
+Description:
+
+```txt
+the most recent state of the Union address
+```
+
+**Second VectorStoreInfo**
+
+<br>
+
+Name:
+
+```txt
+ruff
+```
+
+Description:
+
+```txt
+Information about the Ruff python linting library
+```
+
+<br>
+
+The `VectorStoreRouterToolkit` is a toolkit that allows you to create a `VectorStoreRouter` agent. This allows it to route between vector stores.
+
+<br>
+
+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.
+
+<br>
+
+Check out the [OpenAI](https://platform.openai.com/docs/introduction/overview){.internal-link target=\_blank} documentation to learn more about the API and the options that contain in the node.