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docs: Update VectorStoreTab vector store initializations (#30413)

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Description: Update vector store tab inits to match either the docs or
api_ref (whichever was more comprehensive)

List of changes per vector stores:

- In-memory
  - no change
- AstraDB
  - match to docs - docs/api_refs match (excluding embeddings)
- Chroma
  - match to docs - api_refs is less descriptive
- FAISS
  - match to docs - docs/api_refs match (excluding embeddings)
- Milvus
- match to docs to use Milvus Lite with Flat index - api_refs does not
have index_param for generalization
- MongoDB
  - match to docs - api_refs are sparser
- PGVector
  - match to api_ref
  - changed to include docker cmd directly in code
- docs/api_ref has comment to view docker command in separate code block
- Pinecone
  - match to api_refs - docs have code dispersed
- Qdrant
  - match to api_ref - docs has size=3072, api_ref has size=1536

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
This commit is contained in:
Brandon Luu 2025-03-22 14:29:45 -07:00 committed by GitHub
parent e7032901c3
commit bbbd4e1db8
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1 changed files with 3 additions and 3 deletions
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6
docs/src/theme/VectorStoreTabs.js
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@ -28,21 +28,21 @@ export default function VectorStoreTabs(props) {
{ {
value: "Chroma", value: "Chroma",
label: "Chroma", label: "Chroma",
text: `from langchain_chroma import Chroma\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = Chroma(embedding_function=embeddings)`, text: `from langchain_chroma import Chroma\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = Chroma(\n collection_name="example_collection",\n embedding_function=embeddings,\n persist_directory="./chroma_langchain_db", # Where to save data locally, remove if not necessary\n)`,
packageName: "langchain-chroma", packageName: "langchain-chroma",
default: false, default: false,
}, },
{ {
value: "FAISS", value: "FAISS",
label: "FAISS", label: "FAISS",
text: `from langchain_community.vectorstores import FAISS\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = FAISS(embedding_function=embeddings)`, text: `import faiss\nfrom langchain_community.docstore.in_memory import InMemoryDocstore\nfrom langchain_community.vectorstores import FAISS\n\nembedding_dim = len(embeddings.embed_query("hello world"))\nindex = faiss.IndexFlatL2(embedding_dim)\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = FAISS(\n embedding_function=embeddings,\n index=index,\n docstore=InMemoryDocstore(),\n index_to_docstore_id={},\n)`,
packageName: "langchain-community", packageName: "langchain-community",
default: false, default: false,
}, },
{ {
value: "Milvus", value: "Milvus",
label: "Milvus", label: "Milvus",
text: `from langchain_milvus import Milvus\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = Milvus(embedding_function=embeddings)`, text: `from langchain_milvus import Milvus\n\nURI = "./milvus_example.db"\n${useFakeEmbeddings ? fakeEmbeddingsString : ""}\n${vectorStoreVarName} = Milvus(\n embedding_function=embeddings,\n connection_args={"uri": URI},\n index_params={"index_type": "FLAT", "metric_type": "L2"},\n)`,
packageName: "langchain-milvus", packageName: "langchain-milvus",
default: false, default: false,
}, },