mirror of
https://github.com/BerriAI/litellm.git
synced 2026-10-08 03:08:45 +00:00
init ui for bedrock s3 vectors
This commit is contained in:
Ishaan Jaffer
parent
7aa11ecf4a
commit
fc4a484cb1
6 changed files with 611 additions and 5 deletions
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@ -6954,7 +6954,8 @@ export const ragIngestCall = async (
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customLlmProvider: string,
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vectorStoreId?: string,
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vectorStoreName?: string,
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vectorStoreDescription?: string
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vectorStoreDescription?: string,
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providerSpecificParams?: Record<string, any>
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): Promise<any> => {
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try {
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let url = proxyBaseUrl ? `${proxyBaseUrl}/rag/ingest` : `/rag/ingest`;
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@ -6967,6 +6968,7 @@ export const ragIngestCall = async (
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vector_store: {
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custom_llm_provider: customLlmProvider,
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...(vectorStoreId && { vector_store_id: vectorStoreId }),
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...(providerSpecificParams && providerSpecificParams),
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},
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},
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};
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@ -22,17 +22,51 @@ vi.mock("../vector_store_providers", () => ({
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BEDROCK: "Amazon Bedrock",
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OPENAI: "OpenAI",
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AZURE_OPENAI: "Azure OpenAI",
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S3Vectors: "AWS S3 Vectors",
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},
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vectorStoreProviderMap: {
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BEDROCK: "bedrock",
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OPENAI: "openai",
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AZURE_OPENAI: "azure_openai",
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S3Vectors: "s3_vectors",
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},
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vectorStoreProviderLogoMap: {
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"Amazon Bedrock": "https://example.com/bedrock.png",
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"OpenAI": "https://example.com/openai.png",
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"Azure OpenAI": "https://example.com/azure.png",
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"AWS S3 Vectors": "https://example.com/aws.png",
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},
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getProviderSpecificFields: vi.fn((provider: string) => {
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if (provider === "s3_vectors") {
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return [
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{
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name: "vector_bucket_name",
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label: "Vector Bucket Name",
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tooltip: "S3 bucket name for vector storage",
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placeholder: "my-vector-bucket",
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required: true,
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type: "text",
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},
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{
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name: "aws_region_name",
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label: "AWS Region",
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tooltip: "AWS region",
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placeholder: "us-west-2",
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required: true,
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type: "text",
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},
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{
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name: "embedding_model",
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label: "Embedding Model",
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tooltip: "Embedding model to use",
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placeholder: "text-embedding-3-small",
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required: true,
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type: "select",
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},
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];
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}
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return [];
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}),
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}));
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describe("CreateVectorStore", () => {
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@ -43,9 +77,9 @@ describe("CreateVectorStore", () => {
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it("should render the component successfully", () => {
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render(<CreateVectorStore accessToken="test-token" />);
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expect(screen.getByText("Create Vector Store")).toBeInTheDocument();
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expect(screen.getAllByText("Create Vector Store").length).toBeGreaterThan(0);
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expect(screen.getByText("Step 1: Upload Documents")).toBeInTheDocument();
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expect(screen.getByText("Step 2: Select Provider")).toBeInTheDocument();
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expect(screen.getByText("Step 2: Configure Vector Store")).toBeInTheDocument();
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});
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it("should display upload area with correct text", () => {
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@ -123,7 +157,15 @@ describe("CreateVectorStore", () => {
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});
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await waitFor(() => {
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expect(mockRagIngestCall).toHaveBeenCalledWith("test-token", expect.any(File), "bedrock", undefined);
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expect(mockRagIngestCall).toHaveBeenCalledWith(
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"test-token",
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expect.any(File),
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"bedrock",
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undefined,
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undefined,
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undefined,
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{}
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);
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});
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});
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@ -163,4 +205,72 @@ describe("CreateVectorStore", () => {
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expect(screen.getByText("Vector Store Created Successfully")).toBeInTheDocument();
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});
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});
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it("should display S3 Vectors provider-specific fields when selected", async () => {
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render(<CreateVectorStore accessToken="test-token" />);
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// Find and click the provider dropdown
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const providerSelect = screen.getByRole("combobox");
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await act(async () => {
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fireEvent.mouseDown(providerSelect);
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});
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// Wait for dropdown options to appear
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await waitFor(() => {
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const s3Option = screen.queryByText("AWS S3 Vectors");
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if (s3Option) {
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fireEvent.click(s3Option);
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}
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});
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// Check if S3-specific fields are displayed
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await waitFor(() => {
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expect(screen.queryByText("Vector Bucket Name")).toBeInTheDocument();
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expect(screen.queryByText("AWS Region")).toBeInTheDocument();
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expect(screen.queryByText("Embedding Model")).toBeInTheDocument();
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});
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});
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it("should validate S3 Vectors required fields before submission", async () => {
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render(<CreateVectorStore accessToken="test-token" />);
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// Upload a file first
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const file = new File(["test content"], "test.pdf", { type: "application/pdf" });
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const uploadInput = document.querySelector('input[type="file"]') as HTMLInputElement;
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await act(async () => {
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if (uploadInput) {
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fireEvent.change(uploadInput, { target: { files: [file] } });
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}
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});
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await waitFor(() => {
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expect(screen.getByText("Uploaded Documents (1)")).toBeInTheDocument();
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});
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// Select S3 Vectors provider
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const providerSelect = screen.getByRole("combobox");
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await act(async () => {
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fireEvent.mouseDown(providerSelect);
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});
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await waitFor(() => {
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const s3Option = screen.queryByText("AWS S3 Vectors");
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if (s3Option) {
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fireEvent.click(s3Option);
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}
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});
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// Try to create without filling required fields
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const createButton = screen.getByRole("button", { name: /Create Vector Store/i });
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await act(async () => {
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fireEvent.click(createButton);
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});
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// Should show validation warning (mocked message.warning would be called)
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// The actual validation happens in the component
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});
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});
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@ -10,8 +10,11 @@ import {
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VectorStoreProviders,
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vectorStoreProviderLogoMap,
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vectorStoreProviderMap,
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getProviderSpecificFields,
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VectorStoreFieldConfig,
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} from "../vector_store_providers";
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import NotificationsManager from "../molecules/notifications_manager";
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import S3VectorsConfig from "./S3VectorsConfig";
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const { Dragger } = Upload;
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@ -28,6 +31,7 @@ const CreateVectorStore: React.FC<CreateVectorStoreProps> = ({ accessToken, onSu
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const [vectorStoreName, setVectorStoreName] = useState<string>("");
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const [vectorStoreDescription, setVectorStoreDescription] = useState<string>("");
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const [ingestResults, setIngestResults] = useState<RAGIngestResponse[]>([]);
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const [providerParams, setProviderParams] = useState<Record<string, any>>({});
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const uploadProps: UploadProps = {
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name: "file",
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@ -92,6 +96,15 @@ const CreateVectorStore: React.FC<CreateVectorStoreProps> = ({ accessToken, onSu
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return;
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}
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// Validate provider-specific required fields
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const requiredFields = getProviderSpecificFields(selectedProvider).filter((field) => field.required);
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for (const field of requiredFields) {
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if (!providerParams[field.name]) {
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message.warning(`Please provide ${field.label}`);
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return;
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}
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}
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if (!accessToken) {
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message.error("No access token available");
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return;
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@ -118,7 +131,8 @@ const CreateVectorStore: React.FC<CreateVectorStoreProps> = ({ accessToken, onSu
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selectedProvider,
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vectorStoreId, // Use the same vector store ID for subsequent uploads
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vectorStoreName || undefined,
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vectorStoreDescription || undefined
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vectorStoreDescription || undefined,
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providerParams
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);
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// Store the vector store ID from the first successful ingest
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@ -298,6 +312,74 @@ const CreateVectorStore: React.FC<CreateVectorStoreProps> = ({ accessToken, onSu
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})}
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</Select>
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</Form.Item>
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{/* S3 Vectors Configuration */}
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{selectedProvider === "s3_vectors" && (
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<S3VectorsConfig
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accessToken={accessToken}
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providerParams={providerParams}
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onParamsChange={setProviderParams}
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/>
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)}
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{/* Other Provider-specific fields */}
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{selectedProvider !== "s3_vectors" &&
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getProviderSpecificFields(selectedProvider).map((field: VectorStoreFieldConfig) => {
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if (field.type === "select") {
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// For embedding model selection, we'd need to fetch available models
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// For now, provide a text input as fallback
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return (
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<Form.Item
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key={field.name}
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label={
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<span>
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{field.label}{" "}
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<Tooltip title={field.tooltip}>
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<InfoCircleOutlined style={{ marginLeft: "4px" }} />
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</Tooltip>
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</span>
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}
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required={field.required}
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>
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<Input
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value={providerParams[field.name] || ""}
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onChange={(e) =>
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setProviderParams((prev) => ({ ...prev, [field.name]: e.target.value }))
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}
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placeholder={field.placeholder}
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size="large"
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className="rounded-md"
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/>
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</Form.Item>
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);
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}
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return (
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<Form.Item
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key={field.name}
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label={
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<span>
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{field.label}{" "}
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<Tooltip title={field.tooltip}>
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<InfoCircleOutlined style={{ marginLeft: "4px" }} />
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</Tooltip>
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</span>
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}
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required={field.required}
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>
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<Input
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type={field.type === "password" ? "password" : "text"}
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value={providerParams[field.name] || ""}
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onChange={(e) =>
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setProviderParams((prev) => ({ ...prev, [field.name]: e.target.value }))
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}
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placeholder={field.placeholder}
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size="large"
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className="rounded-md"
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/>
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</Form.Item>
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);
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})}
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</Form>
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<div className="flex justify-end">
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@ -0,0 +1,203 @@
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import { render, screen, fireEvent, waitFor, act } from "@testing-library/react";
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import { describe, it, expect, vi, beforeEach } from "vitest";
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import S3VectorsConfig from "./S3VectorsConfig";
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import * as fetchModels from "../playground/llm_calls/fetch_models";
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// Mock fetchAvailableModels
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vi.mock("../playground/llm_calls/fetch_models", () => ({
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fetchAvailableModels: vi.fn(),
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}));
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describe("S3VectorsConfig", () => {
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const mockOnParamsChange = vi.fn();
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const defaultProps = {
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accessToken: "test-token",
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providerParams: {},
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onParamsChange: mockOnParamsChange,
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};
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beforeEach(() => {
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vi.clearAllMocks();
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});
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it("should render the component successfully", () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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render(<S3VectorsConfig {...defaultProps} />);
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expect(screen.getByText("AWS S3 Vectors Setup")).toBeInTheDocument();
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expect(screen.getByText("Vector Bucket Name")).toBeInTheDocument();
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expect(screen.getByText("Index Name")).toBeInTheDocument();
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expect(screen.getByText("AWS Region")).toBeInTheDocument();
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expect(screen.getByText("Embedding Model")).toBeInTheDocument();
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});
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it("should display setup instructions", () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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render(<S3VectorsConfig {...defaultProps} />);
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expect(
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screen.getByText(/AWS S3 Vectors allows you to store and query vector embeddings directly in S3/)
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).toBeInTheDocument();
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expect(screen.getByText(/Vector buckets and indexes will be automatically created/)).toBeInTheDocument();
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expect(screen.getByText(/Vector dimensions are auto-detected/)).toBeInTheDocument();
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});
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it("should fetch embedding models on mount", async () => {
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const mockModels = [
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{ model_group: "text-embedding-3-small", mode: "embedding" },
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{ model_group: "text-embedding-3-large", mode: "embedding" },
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{ model_group: "gpt-4", mode: "chat" },
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];
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const fetchSpy = vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue(mockModels);
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render(<S3VectorsConfig {...defaultProps} />);
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await waitFor(() => {
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expect(fetchSpy).toHaveBeenCalledWith("test-token");
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});
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});
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it("should filter and display only embedding models", async () => {
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const mockModels = [
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{ model_group: "text-embedding-3-small", mode: "embedding" },
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{ model_group: "text-embedding-3-large", mode: "embedding" },
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{ model_group: "gpt-4", mode: "chat" },
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{ model_group: "gpt-3.5-turbo", mode: "chat" },
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];
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue(mockModels);
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render(<S3VectorsConfig {...defaultProps} />);
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// Wait for models to load
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await waitFor(() => {
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expect(fetchModels.fetchAvailableModels).toHaveBeenCalled();
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});
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// The component should filter to only embedding models internally
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// We can verify this by checking the component loaded successfully
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expect(screen.getByText("Embedding Model")).toBeInTheDocument();
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});
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it("should call onParamsChange when vector bucket name changes", async () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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render(<S3VectorsConfig {...defaultProps} />);
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const bucketInput = screen.getByPlaceholderText("my-vector-bucket");
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await act(async () => {
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fireEvent.change(bucketInput, { target: { value: "test-bucket" } });
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});
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expect(mockOnParamsChange).toHaveBeenCalledWith({
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vector_bucket_name: "test-bucket",
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});
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});
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it("should call onParamsChange when AWS region changes", async () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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render(<S3VectorsConfig {...defaultProps} />);
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const regionInput = screen.getByPlaceholderText("us-west-2");
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await act(async () => {
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fireEvent.change(regionInput, { target: { value: "us-east-1" } });
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});
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expect(mockOnParamsChange).toHaveBeenCalledWith({
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aws_region_name: "us-east-1",
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});
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});
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it("should call onParamsChange when embedding model is selected", async () => {
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const mockModels = [
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{ model_group: "text-embedding-3-small", mode: "embedding" },
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{ model_group: "text-embedding-3-large", mode: "embedding" },
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];
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue(mockModels);
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render(<S3VectorsConfig {...defaultProps} />);
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await waitFor(() => {
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expect(fetchModels.fetchAvailableModels).toHaveBeenCalled();
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});
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// Find the Select component and trigger change directly
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const selectElement = screen.getByRole("combobox");
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await act(async () => {
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// Simulate selecting a value by firing the change event
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fireEvent.change(selectElement, { target: { value: "text-embedding-3-small" } });
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});
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// The component should handle the selection
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expect(screen.getByText("Embedding Model")).toBeInTheDocument();
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});
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it("should preserve existing params when updating a field", async () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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const existingParams = {
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vector_bucket_name: "existing-bucket",
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aws_region_name: "us-west-2",
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};
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render(<S3VectorsConfig {...defaultProps} providerParams={existingParams} />);
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const indexInput = screen.getByPlaceholderText("my-vector-index");
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await act(async () => {
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fireEvent.change(indexInput, { target: { value: "my-index" } });
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});
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expect(mockOnParamsChange).toHaveBeenCalledWith({
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vector_bucket_name: "existing-bucket",
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aws_region_name: "us-west-2",
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index_name: "my-index",
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});
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});
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it("should display existing param values", () => {
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vi.spyOn(fetchModels, "fetchAvailableModels").mockResolvedValue([]);
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const existingParams = {
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vector_bucket_name: "my-bucket",
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index_name: "my-index",
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aws_region_name: "eu-west-1",
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embedding_model: "text-embedding-3-small",
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};
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render(<S3VectorsConfig {...defaultProps} providerParams={existingParams} />);
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expect(screen.getByDisplayValue("my-bucket")).toBeInTheDocument();
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expect(screen.getByDisplayValue("my-index")).toBeInTheDocument();
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expect(screen.getByDisplayValue("eu-west-1")).toBeInTheDocument();
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||||
});
|
||||
|
||||
it("should handle model fetch error gracefully", async () => {
|
||||
const consoleErrorSpy = vi.spyOn(console, "error").mockImplementation(() => {});
|
||||
vi.spyOn(fetchModels, "fetchAvailableModels").mockRejectedValue(new Error("Failed to fetch models"));
|
||||
|
||||
render(<S3VectorsConfig {...defaultProps} />);
|
||||
|
||||
await waitFor(() => {
|
||||
expect(consoleErrorSpy).toHaveBeenCalledWith("Error fetching embedding models:", expect.any(Error));
|
||||
});
|
||||
|
||||
consoleErrorSpy.mockRestore();
|
||||
});
|
||||
|
||||
it("should not fetch models if accessToken is null", () => {
|
||||
const fetchSpy = vi.spyOn(fetchModels, "fetchAvailableModels");
|
||||
|
||||
render(<S3VectorsConfig {...defaultProps} accessToken={null} />);
|
||||
|
||||
expect(fetchSpy).not.toHaveBeenCalled();
|
||||
});
|
||||
});
|
||||
|
|
@ -0,0 +1,172 @@
|
|||
import React, { useState, useEffect } from "react";
|
||||
import { Alert, Form, Input, Select, Tooltip } from "antd";
|
||||
import { InfoCircleOutlined } from "@ant-design/icons";
|
||||
import { fetchAvailableModels, ModelGroup } from "../playground/llm_calls/fetch_models";
|
||||
|
||||
interface S3VectorsConfigProps {
|
||||
accessToken: string | null;
|
||||
providerParams: Record<string, any>;
|
||||
onParamsChange: (params: Record<string, any>) => void;
|
||||
}
|
||||
|
||||
const S3VectorsConfig: React.FC<S3VectorsConfigProps> = ({
|
||||
accessToken,
|
||||
providerParams,
|
||||
onParamsChange,
|
||||
}) => {
|
||||
const [embeddingModels, setEmbeddingModels] = useState<ModelGroup[]>([]);
|
||||
const [isLoadingModels, setIsLoadingModels] = useState(false);
|
||||
|
||||
useEffect(() => {
|
||||
if (!accessToken) return;
|
||||
|
||||
const loadModels = async () => {
|
||||
setIsLoadingModels(true);
|
||||
try {
|
||||
const models = await fetchAvailableModels(accessToken);
|
||||
// Filter for embedding models only
|
||||
const embeddingOnly = models.filter((model) => model.mode === "embedding");
|
||||
setEmbeddingModels(embeddingOnly);
|
||||
} catch (error) {
|
||||
console.error("Error fetching embedding models:", error);
|
||||
} finally {
|
||||
setIsLoadingModels(false);
|
||||
}
|
||||
};
|
||||
|
||||
loadModels();
|
||||
}, [accessToken]);
|
||||
|
||||
const handleFieldChange = (fieldName: string, value: string) => {
|
||||
onParamsChange({
|
||||
...providerParams,
|
||||
[fieldName]: value,
|
||||
});
|
||||
};
|
||||
|
||||
return (
|
||||
<>
|
||||
{/* S3 Vectors Setup Instructions */}
|
||||
<Alert
|
||||
message="AWS S3 Vectors Setup"
|
||||
description={
|
||||
<div>
|
||||
<p>AWS S3 Vectors allows you to store and query vector embeddings directly in S3:</p>
|
||||
<ul style={{ marginLeft: "16px", marginTop: "8px" }}>
|
||||
<li>Vector buckets and indexes will be automatically created if they don't exist</li>
|
||||
<li>Vector dimensions are auto-detected from your selected embedding model</li>
|
||||
<li>Ensure your AWS credentials have permissions for S3 Vectors operations</li>
|
||||
<li>
|
||||
Learn more:{" "}
|
||||
<a
|
||||
href="https://docs.aws.amazon.com/AmazonS3/latest/userguide/s3-vector-buckets.html"
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
>
|
||||
AWS S3 Vectors Documentation
|
||||
</a>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
}
|
||||
type="info"
|
||||
showIcon
|
||||
style={{ marginBottom: "16px" }}
|
||||
/>
|
||||
|
||||
{/* Vector Bucket Name */}
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
Vector Bucket Name{" "}
|
||||
<Tooltip title="S3 bucket name for vector storage (will be auto-created if it doesn't exist)">
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
required
|
||||
>
|
||||
<Input
|
||||
value={providerParams.vector_bucket_name || ""}
|
||||
onChange={(e) => handleFieldChange("vector_bucket_name", e.target.value)}
|
||||
placeholder="my-vector-bucket"
|
||||
size="large"
|
||||
className="rounded-md"
|
||||
/>
|
||||
</Form.Item>
|
||||
|
||||
{/* Index Name (Optional) */}
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
Index Name{" "}
|
||||
<Tooltip title="Name for the vector index (optional, will be auto-generated if not provided)">
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
>
|
||||
<Input
|
||||
value={providerParams.index_name || ""}
|
||||
onChange={(e) => handleFieldChange("index_name", e.target.value)}
|
||||
placeholder="my-vector-index"
|
||||
size="large"
|
||||
className="rounded-md"
|
||||
/>
|
||||
</Form.Item>
|
||||
|
||||
{/* AWS Region */}
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
AWS Region{" "}
|
||||
<Tooltip title="AWS region where the S3 bucket is located (e.g., us-west-2)">
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
required
|
||||
>
|
||||
<Input
|
||||
value={providerParams.aws_region_name || ""}
|
||||
onChange={(e) => handleFieldChange("aws_region_name", e.target.value)}
|
||||
placeholder="us-west-2"
|
||||
size="large"
|
||||
className="rounded-md"
|
||||
/>
|
||||
</Form.Item>
|
||||
|
||||
{/* Embedding Model */}
|
||||
<Form.Item
|
||||
label={
|
||||
<span>
|
||||
Embedding Model{" "}
|
||||
<Tooltip title="Select the embedding model to use for vector generation">
|
||||
<InfoCircleOutlined style={{ marginLeft: "4px" }} />
|
||||
</Tooltip>
|
||||
</span>
|
||||
}
|
||||
required
|
||||
>
|
||||
<Select
|
||||
value={providerParams.embedding_model || undefined}
|
||||
onChange={(value) => handleFieldChange("embedding_model", value)}
|
||||
placeholder="Select an embedding model"
|
||||
size="large"
|
||||
showSearch
|
||||
loading={isLoadingModels}
|
||||
filterOption={(input, option) =>
|
||||
(option?.label ?? "").toLowerCase().includes(input.toLowerCase())
|
||||
}
|
||||
options={embeddingModels.map((model) => ({
|
||||
value: model.model_group,
|
||||
label: model.model_group,
|
||||
}))}
|
||||
style={{ width: "100%" }}
|
||||
/>
|
||||
</Form.Item>
|
||||
</>
|
||||
);
|
||||
};
|
||||
|
||||
export default S3VectorsConfig;
|
||||
|
|
@ -5,6 +5,7 @@ export enum VectorStoreProviders {
|
|||
OpenAI = "OpenAI",
|
||||
Azure = "Azure OpenAI",
|
||||
Milvus = "Milvus",
|
||||
S3Vectors = "AWS S3 Vectors",
|
||||
}
|
||||
|
||||
export const vectorStoreProviderMap: Record<string, string> = {
|
||||
|
|
@ -14,6 +15,7 @@ export const vectorStoreProviderMap: Record<string, string> = {
|
|||
OpenAI: "openai",
|
||||
Azure: "azure",
|
||||
Milvus: "milvus",
|
||||
S3Vectors: "s3_vectors",
|
||||
};
|
||||
|
||||
const asset_logos_folder = "../ui/assets/logos/";
|
||||
|
|
@ -25,6 +27,7 @@ export const vectorStoreProviderLogoMap: Record<string, string> = {
|
|||
[VectorStoreProviders.OpenAI]: `${asset_logos_folder}openai_small.svg`,
|
||||
[VectorStoreProviders.Azure]: `${asset_logos_folder}microsoft_azure.svg`,
|
||||
[VectorStoreProviders.Milvus]: `${asset_logos_folder}milvus.svg`,
|
||||
[VectorStoreProviders.S3Vectors]: `${asset_logos_folder}aws.svg`,
|
||||
};
|
||||
|
||||
// Define field types for provider-specific configurations
|
||||
|
|
@ -114,6 +117,40 @@ export const vectorStoreProviderFields: Record<string, VectorStoreFieldConfig[]>
|
|||
type: "select",
|
||||
},
|
||||
],
|
||||
s3_vectors: [
|
||||
{
|
||||
name: "vector_bucket_name",
|
||||
label: "Vector Bucket Name",
|
||||
tooltip: "S3 bucket name for vector storage (will be auto-created if it doesn't exist)",
|
||||
placeholder: "my-vector-bucket",
|
||||
required: true,
|
||||
type: "text",
|
||||
},
|
||||
{
|
||||
name: "index_name",
|
||||
label: "Index Name",
|
||||
tooltip: "Name for the vector index (optional, will be auto-generated if not provided)",
|
||||
placeholder: "my-vector-index",
|
||||
required: false,
|
||||
type: "text",
|
||||
},
|
||||
{
|
||||
name: "aws_region_name",
|
||||
label: "AWS Region",
|
||||
tooltip: "AWS region where the S3 bucket is located (e.g., us-west-2)",
|
||||
placeholder: "us-west-2",
|
||||
required: true,
|
||||
type: "text",
|
||||
},
|
||||
{
|
||||
name: "embedding_model",
|
||||
label: "Embedding Model",
|
||||
tooltip: "Select the embedding model to use for vector generation",
|
||||
placeholder: "text-embedding-3-small",
|
||||
required: true,
|
||||
type: "select",
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
export const getVectorStoreProviderLogoAndName = (providerValue: string): { logo: string; displayName: string } => {
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue