mirror of
https://github.com/hwchase17/langchain.git
synced 2026-01-29 21:30:18 +00:00
docs: add component tabs to integration landing pages (#28142)
- Add to embedding model tabs - Add tabs for vector stores - Add "hello world" examples in integration landing pages using tabs
This commit is contained in:
ccurme
GitHub
@@ -114,7 +114,7 @@ export default function ChatModelTabs(props) {
|
||||
value: "Google",
|
||||
label: "Google",
|
||||
text: `from langchain_google_vertexai import ChatVertexAI\n\n${llmVarName} = ChatVertexAI(${googleParamsOrDefault})`,
|
||||
apiKeyName: "GOOGLE_API_KEY",
|
||||
apiKeyText: "# Ensure your VertexAI credentials are configured",
|
||||
packageName: "langchain-google-vertexai",
|
||||
default: false,
|
||||
shouldHide: hideGoogle,
|
||||
|
||||
@@ -7,15 +7,41 @@ export default function EmbeddingTabs(props) {
|
||||
const {
|
||||
openaiParams,
|
||||
hideOpenai,
|
||||
azureOpenaiParams,
|
||||
hideAzureOpenai,
|
||||
googleParams,
|
||||
hideGoogle,
|
||||
awsParams,
|
||||
hideAws,
|
||||
huggingFaceParams,
|
||||
hideHuggingFace,
|
||||
ollamaParams,
|
||||
hideOllama,
|
||||
cohereParams,
|
||||
hideCohere,
|
||||
mistralParams,
|
||||
hideMistral,
|
||||
nomicParams,
|
||||
hideNomic,
|
||||
nvidiaParams,
|
||||
hideNvidia,
|
||||
fakeEmbeddingParams,
|
||||
hideFakeEmbedding,
|
||||
customVarName,
|
||||
} = props;
|
||||
|
||||
const openAIParamsOrDefault = openaiParams ?? `model="text-embedding-3-large"`;
|
||||
const azureParamsOrDefault =
|
||||
azureOpenaiParams ??
|
||||
`\n azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],\n azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT_NAME"],\n openai_api_version=os.environ["AZURE_OPENAI_API_VERSION"],\n`;
|
||||
const googleParamsOrDefault = googleParams ?? `model="text-embedding-004"`;
|
||||
const awsParamsOrDefault = awsParams ?? `model_id="amazon.titan-embed-text-v2:0"`;
|
||||
const huggingFaceParamsOrDefault = huggingFaceParams ?? `model="sentence-transformers/all-mpnet-base-v2"`;
|
||||
const ollamaParamsOrDefault = ollamaParams ?? `model="llama3"`;
|
||||
const cohereParamsOrDefault = cohereParams ?? `model="embed-english-v3.0"`;
|
||||
const mistralParamsOrDefault = mistralParams ?? `model="mistral-embed"`;
|
||||
const nomicsParamsOrDefault = nomicParams ?? `model="nomic-embed-text-v1.5"`;
|
||||
const nvidiaParamsOrDefault = nvidiaParams ?? `model="NV-Embed-QA"`;
|
||||
const fakeEmbeddingParamsOrDefault = fakeEmbeddingParams ?? `size=4096`;
|
||||
|
||||
const embeddingVarName = customVarName ?? "embeddings";
|
||||
@@ -30,6 +56,33 @@ export default function EmbeddingTabs(props) {
|
||||
default: true,
|
||||
shouldHide: hideOpenai,
|
||||
},
|
||||
{
|
||||
value: "Azure",
|
||||
label: "Azure",
|
||||
text: `from langchain_openai import AzureOpenAIEmbeddings\n\n${embeddingVarName} = AzureOpenAIEmbeddings(${azureParamsOrDefault})`,
|
||||
apiKeyName: "AZURE_OPENAI_API_KEY",
|
||||
packageName: "langchain-openai",
|
||||
default: false,
|
||||
shouldHide: hideAzureOpenai,
|
||||
},
|
||||
{
|
||||
value: "Google",
|
||||
label: "Google",
|
||||
text: `from langchain_google_vertexai import VertexAIEmbeddings\n\n${embeddingVarName} = VertexAIEmbeddings(${googleParamsOrDefault})`,
|
||||
apiKeyName: undefined,
|
||||
packageName: "langchain-google-vertexai",
|
||||
default: false,
|
||||
shouldHide: hideGoogle,
|
||||
},
|
||||
{
|
||||
value: "AWS",
|
||||
label: "AWS",
|
||||
text: `from langchain_aws import BedrockEmbeddings\n\n${embeddingVarName} = BedrockEmbeddings(${awsParamsOrDefault})`,
|
||||
apiKeyName: undefined,
|
||||
packageName: "langchain-aws",
|
||||
default: false,
|
||||
shouldHide: hideAws,
|
||||
},
|
||||
{
|
||||
value: "HuggingFace",
|
||||
label: "HuggingFace",
|
||||
@@ -40,8 +93,53 @@ export default function EmbeddingTabs(props) {
|
||||
shouldHide: hideHuggingFace,
|
||||
},
|
||||
{
|
||||
value: "Fake Embedding",
|
||||
label: "Fake Embedding",
|
||||
value: "Ollama",
|
||||
label: "Ollama",
|
||||
text: `from langchain_ollama import OllamaEmbeddings\n\n${embeddingVarName} = OllamaEmbeddings(${ollamaParamsOrDefault})`,
|
||||
apiKeyName: undefined,
|
||||
packageName: "langchain-ollama",
|
||||
default: false,
|
||||
shouldHide: hideOllama,
|
||||
},
|
||||
{
|
||||
value: "Cohere",
|
||||
label: "Cohere",
|
||||
text: `from langchain_cohere import CohereEmbeddings\n\n${embeddingVarName} = CohereEmbeddings(${cohereParamsOrDefault})`,
|
||||
apiKeyName: "COHERE_API_KEY",
|
||||
packageName: "langchain-cohere",
|
||||
default: false,
|
||||
shouldHide: hideCohere,
|
||||
},
|
||||
{
|
||||
value: "MistralAI",
|
||||
label: "MistralAI",
|
||||
text: `from langchain_mistralai import MistralAIEmbeddings\n\n${embeddingVarName} = MistralAIEmbeddings(${mistralParamsOrDefault})`,
|
||||
apiKeyName: "MISTRALAI_API_KEY",
|
||||
packageName: "langchain-mistralai",
|
||||
default: false,
|
||||
shouldHide: hideMistral,
|
||||
},
|
||||
{
|
||||
value: "Nomic",
|
||||
label: "Nomic",
|
||||
text: `from langchain_nomic import NomicEmbeddings\n\n${embeddingVarName} = NomicEmbeddings(${nomicsParamsOrDefault})`,
|
||||
apiKeyName: "NOMIC_API_KEY",
|
||||
packageName: "langchain-nomic",
|
||||
default: false,
|
||||
shouldHide: hideNomic,
|
||||
},
|
||||
{
|
||||
value: "NVIDIA",
|
||||
label: "NVIDIA",
|
||||
text: `from langchain_nvidia_ai_endpoints import NVIDIAEmbeddings\n\n${embeddingVarName} = NVIDIAEmbeddings(${nvidiaParamsOrDefault})`,
|
||||
apiKeyName: "NVIDIA_API_KEY",
|
||||
packageName: "langchain-nvidia-ai-endpoints",
|
||||
default: false,
|
||||
shouldHide: hideNvidia,
|
||||
},
|
||||
{
|
||||
value: "Fake",
|
||||
label: "Fake",
|
||||
text: `from langchain_core.embeddings import FakeEmbeddings\n\n${embeddingVarName} = FakeEmbeddings(${fakeEmbeddingParamsOrDefault})`,
|
||||
apiKeyName: undefined,
|
||||
packageName: "langchain-core",
|
||||
|
||||
@@ -406,7 +406,7 @@ const FEATURE_TABLES = {
|
||||
},
|
||||
{
|
||||
name: "NVIDIA",
|
||||
link: "NVIDIAEmbeddings",
|
||||
link: "nvidia_ai_endpoints",
|
||||
package: "langchain-nvidia",
|
||||
apiLink: "https://python.langchain.com/api_reference/nvidia_ai_endpoints/embeddings/langchain_nvidia_ai_endpoints.embeddings.NVIDIAEmbeddings.html"
|
||||
},
|
||||
|
||||
92
docs/src/theme/VectorStoreTabs.js
Normal file
92
docs/src/theme/VectorStoreTabs.js
Normal file
@@ -0,0 +1,92 @@
|
||||
import React from "react";
|
||||
import Tabs from "@theme/Tabs";
|
||||
import TabItem from "@theme/TabItem";
|
||||
import CodeBlock from "@theme-original/CodeBlock";
|
||||
|
||||
export default function VectorStoreTabs(props) {
|
||||
const { customVarName } = props;
|
||||
|
||||
const vectorStoreVarName = customVarName ?? "vector_store";
|
||||
|
||||
const tabItems = [
|
||||
{
|
||||
value: "In-memory",
|
||||
label: "In-memory",
|
||||
text: `from langchain_core.vector_stores import InMemoryVectorStore\n\n${vectorStoreVarName} = InMemoryVectorStore(embeddings)`,
|
||||
packageName: "langchain-core",
|
||||
default: true,
|
||||
},
|
||||
{
|
||||
value: "AstraDB",
|
||||
label: "AstraDB",
|
||||
text: `from langchain_astradb import AstraDBVectorStore\n\n${vectorStoreVarName} = AstraDBVectorStore(\n embedding=embeddings,\n api_endpoint=ASTRA_DB_API_ENDPOINT,\n collection_name="astra_vector_langchain",\n token=ASTRA_DB_APPLICATION_TOKEN,\n namespace=ASTRA_DB_NAMESPACE,\n)`,
|
||||
packageName: "langchain-astradb",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "Chroma",
|
||||
label: "Chroma",
|
||||
text: `from langchain_chroma import Chroma\n\n${vectorStoreVarName} = Chroma(embedding_function=embeddings)`,
|
||||
packageName: "langchain-chroma",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "FAISS",
|
||||
label: "FAISS",
|
||||
text: `from langchain_community.vectorstores import FAISS\n\n${vectorStoreVarName} = FAISS(embedding_function=embeddings)`,
|
||||
packageName: "langchain-community",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "Milvus",
|
||||
label: "Milvus",
|
||||
text: `from langchain_milvus import Milvus\n\n${vectorStoreVarName} = Milvus(embedding_function=embeddings)`,
|
||||
packageName: "langchain-milvus",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "MongoDB",
|
||||
label: "MongoDB",
|
||||
text: `from langchain_mongodb import MongoDBAtlasVectorSearch\n\n${vectorStoreVarName} = MongoDBAtlasVectorSearch(\n embedding=embeddings,\n collection=MONGODB_COLLECTION,\n index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME,\n relevance_score_fn="cosine",\n)`,
|
||||
packageName: "langchain-mongodb",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "PGVector",
|
||||
label: "PGVector",
|
||||
text: `from langchain_postgres import PGVector\n\n${vectorStoreVarName} = PGVector(\n embedding=embeddings,\n collection_name="my_docs",\n connection="postgresql+psycopg://...",\n)`,
|
||||
packageName: "langchain-postgres",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "Pinecone",
|
||||
label: "Pinecone",
|
||||
text: `from langchain_pinecone import PineconeVectorStore\nfrom pinecone import Pinecone\n\npc = Pinecone(api_key=...)\nindex = pc.Index(index_name)\n\n${vectorStoreVarName} = PineconeVectorStore(embedding=embeddings, index=index)`,
|
||||
packageName: "langchain-pinecone",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "Qdrant",
|
||||
label: "Qdrant",
|
||||
text: `from langchain_qdrant import QdrantVectorStore\nfrom qdrant_client import QdrantClient\n\nclient = QdrantClient(":memory:")\n${vectorStoreVarName} = QdrantVectorStore(\n client=client,\n collection_name="test",\n embedding=embeddings,\n)`,
|
||||
packageName: "langchain-qdrant",
|
||||
default: false,
|
||||
},
|
||||
];
|
||||
|
||||
return (
|
||||
<Tabs groupId="vectorStoreTabs">
|
||||
{tabItems.map((tabItem) => (
|
||||
<TabItem
|
||||
key={tabItem.value}
|
||||
value={tabItem.value}
|
||||
label={tabItem.label}
|
||||
default={tabItem.default}
|
||||
>
|
||||
<CodeBlock language="bash">{`pip install -qU ${tabItem.packageName}`}</CodeBlock>
|
||||
<CodeBlock language="python">{tabItem.text}</CodeBlock>
|
||||
</TabItem>
|
||||
))}
|
||||
</Tabs>
|
||||
);
|
||||
}
|
||||
Reference in New Issue
Block a user