mirror of
https://github.com/Azure/cosmos-explorer.git
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Add embedding source validation rules
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Archie Agarwal
@@ -150,30 +150,54 @@ describe("VectorEmbeddingPoliciesComponent - embedding source", () => {
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});
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await waitFor(() => {
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expect(screen.getByText("At least one source path is required")).toBeInTheDocument();
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expect(screen.getByText("Model name is required")).toBeInTheDocument();
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expect(screen.getByText("Endpoint is required")).toBeInTheDocument();
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expect(screen.getByText("Embedding model name is required")).toBeInTheDocument();
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expect(screen.getByText("Microsoft Foundry Endpoint is required")).toBeInTheDocument();
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});
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const last = onChange.mock.calls[onChange.mock.calls.length - 1];
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expect(last[2]).toBe(false);
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});
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test("invalid endpoint shows the https:// error", async () => {
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test("source paths must start with slash and differ from vector path", async () => {
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expandSection();
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-sourcePaths-1"), {
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target: { value: "description" },
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});
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await waitFor(() => expect(screen.getByText("Source paths must start with /")).toBeInTheDocument());
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-sourcePaths-1"), {
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target: { value: "/vector2" },
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});
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await waitFor(() => expect(screen.getByText("Source path must be different from vector path")).toBeInTheDocument());
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});
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test("invalid endpoint shows the Azure OpenAI or Foundry URL error", async () => {
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expandSection();
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-endpoint-1"), {
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target: { value: "not-a-url" },
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});
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await waitFor(() => expect(screen.getByText("Endpoint must be a valid https:// URL")).toBeInTheDocument());
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await waitFor(() =>
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expect(screen.getByText("Endpoint must be a valid Azure OpenAI or Foundry https:// URL")).toBeInTheDocument(),
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);
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-endpoint-1"), {
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target: { value: "http://insecure.example.com" },
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});
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await waitFor(() => expect(screen.getByText("Endpoint must be a valid https:// URL")).toBeInTheDocument());
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await waitFor(() =>
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expect(screen.getByText("Endpoint must be a valid Azure OpenAI or Foundry https:// URL")).toBeInTheDocument(),
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);
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-endpoint-1"), {
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target: { value: "https://example.com" },
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});
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await waitFor(() =>
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expect(screen.getByText("Endpoint must be a valid Azure OpenAI or Foundry https:// URL")).toBeInTheDocument(),
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);
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});
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test("valid input propagates an embeddingSource with parsed sourcePaths", async () => {
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expandSection();
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-sourcePaths-1"), {
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target: { value: "/description, title" },
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target: { value: "/description, /title" },
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});
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-deploymentName-1"), {
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target: { value: "my-deployment" },
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@@ -213,7 +237,7 @@ describe("VectorEmbeddingPoliciesComponent - embedding source", () => {
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fireEvent.change(sourcePaths, { target: { value: "/description" } });
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fireEvent.change(deploymentName, { target: { value: "d" } });
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fireEvent.change(modelName, { target: { value: "m" } });
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fireEvent.change(endpoint, { target: { value: "https://x.example.com" } });
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fireEvent.change(endpoint, { target: { value: "https://x.openai.azure.com" } });
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await waitFor(() => {
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const lastCall = onChange.mock.calls[onChange.mock.calls.length - 1];
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@@ -264,6 +288,102 @@ describe("VectorEmbeddingPoliciesComponent - embedding source", () => {
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await new Promise((resolve) => setTimeout(resolve, 100));
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expect(onChange.mock.calls.length).toBe(stable);
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});
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test("model-specific dimension validation blocks out-of-range values", async () => {
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expandSection();
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fireEvent.change(view.container.querySelector("#vector-policy-dimension-1"), { target: { value: "3073" } });
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-sourcePaths-1"), {
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target: { value: "/description" },
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});
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-deploymentName-1"), {
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target: { value: "text-embedding-3-large" },
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});
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-modelName-1"), {
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target: { value: "text-embedding-3-large" },
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});
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fireEvent.change(view.container.querySelector("#vector-policy-embeddingSource-endpoint-1"), {
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target: { value: "https://my-foundry.openai.azure.com" },
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});
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await waitFor(() => {
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expect(screen.getByText("Dimension must be greater than 0 and less than or equal 3072")).toBeInTheDocument();
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const lastCall = onChange.mock.calls[onChange.mock.calls.length - 1];
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expect(lastCall[2]).toBe(false);
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});
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});
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test("existing embedding source allows endpoint edit but keeps source fields read-only", async () => {
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const existingEmbedding: VectorEmbedding[] = [
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{
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path: "/vector4",
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dataType: "float32",
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distanceFunction: "cosine",
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dimensions: 1536,
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embeddingSource: {
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sourcePaths: ["/description"],
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deploymentName: "text-embedding-3-small",
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modelName: "text-embedding-3-small",
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endpoint: "https://old.openai.azure.com",
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authType: "Entra",
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},
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},
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];
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const existingOnChange = jest.fn();
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const existingView = render(
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<VectorEmbeddingPoliciesComponent
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vectorEmbeddingsBaseline={existingEmbedding}
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vectorEmbeddings={existingEmbedding}
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vectorIndexes={[]}
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onVectorEmbeddingChange={existingOnChange}
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/>,
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);
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const sourcePaths = existingView.container.querySelector(
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"#vector-policy-embeddingSource-sourcePaths-1",
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) as HTMLInputElement;
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const endpoint = existingView.container.querySelector(
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"#vector-policy-embeddingSource-endpoint-1",
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) as HTMLInputElement;
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expect(sourcePaths).toBeDisabled();
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expect(endpoint).not.toBeDisabled();
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fireEvent.change(endpoint, { target: { value: "https://new.openai.azure.com" } });
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await waitFor(() => {
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const lastCall = existingOnChange.mock.calls[existingOnChange.mock.calls.length - 1];
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expect(lastCall[2]).toBe(true);
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expect(lastCall[0][0].embeddingSource.endpoint).toBe("https://new.openai.azure.com");
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});
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});
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test("existing vector policy without an embedding source cannot add one", () => {
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const existingEmbedding: VectorEmbedding[] = [
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{
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path: "/vector5",
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dataType: "float32",
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distanceFunction: "cosine",
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dimensions: 1536,
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},
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];
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const existingView = render(
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<VectorEmbeddingPoliciesComponent
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vectorEmbeddingsBaseline={existingEmbedding}
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vectorEmbeddings={existingEmbedding}
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vectorIndexes={[]}
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onVectorEmbeddingChange={jest.fn()}
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/>,
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);
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fireEvent.click(existingView.container.querySelector('[data-test="VectorEmbeddingSource/Section/1"]'));
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expect(existingView.container.querySelector("#vector-policy-embeddingSource-sourcePaths-1")).toBeDisabled();
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expect(existingView.container.querySelector("#vector-policy-embeddingSource-deploymentName-1")).toBeDisabled();
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expect(existingView.container.querySelector("#vector-policy-embeddingSource-modelName-1")).toBeDisabled();
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expect(existingView.container.querySelector("#vector-policy-embeddingSource-authType-1")).toHaveAttribute(
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"aria-disabled",
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"true",
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);
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expect(existingView.container.querySelector("#vector-policy-embeddingSource-endpoint-1")).not.toBeDisabled();
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});
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});
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describe("VectorEmbeddingPoliciesComponent - embedding source gating", () => {
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@@ -41,6 +41,7 @@ export interface VectorEmbeddingPolicyData {
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distanceFunction: VectorEmbedding["distanceFunction"];
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dimensions: number;
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indexType: VectorIndex["type"] | "none";
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dataTypeError: string;
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pathError: string;
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dimensionsError: string;
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vectorIndexShardKey?: string[];
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@@ -54,6 +55,18 @@ export interface VectorEmbeddingPolicyData {
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}
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type VectorEmbeddingPolicyProperty = "dataType" | "distanceFunction" | "indexType";
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const embeddingSourceSupportedDataTypes: VectorEmbedding["dataType"][] = ["float32", "float16"];
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const getEmbeddingSourceDimensionLimit = (modelName: string | undefined): number | undefined => {
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switch (modelName?.trim()) {
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case "text-embedding-3-large":
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return 3072;
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case "text-embedding-3-small":
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return 1536;
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default:
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return undefined;
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}
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};
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export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddingPoliciesComponentProps> = ({
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vectorEmbeddingsBaseline,
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@@ -95,7 +108,21 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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return error;
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};
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const onVectorEmbeddingDimensionError = (dimension: number, indexType: VectorIndex["type"] | "none"): string => {
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const onVectorEmbeddingDataTypeError = (
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dataType: VectorEmbedding["dataType"],
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embeddingSource?: VectorEmbeddingSource,
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): string => {
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if (embeddingSource && !embeddingSourceSupportedDataTypes.includes(dataType)) {
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return t(Keys.controls.vectorEmbeddingPolicies.embeddingSourceDataTypeError);
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}
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return "";
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};
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const onVectorEmbeddingDimensionError = (
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dimension: number,
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indexType: VectorIndex["type"] | "none",
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embeddingSource?: VectorEmbeddingSource,
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): string => {
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let error = "";
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if (dimension <= 0 || dimension > 4096) {
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error = t(Keys.controls.vectorEmbeddingPolicies.dimensionRangeError);
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@@ -103,6 +130,15 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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if (indexType === "flat" && dimension > 505) {
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error = t(Keys.controls.vectorEmbeddingPolicies.dimensionFlatIndexError);
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}
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if (embeddingSource?.modelName === "text-embedding-ada-002" && dimension !== 1536) {
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error = t(Keys.controls.vectorEmbeddingPolicies.adaDimensionError);
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}
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const modelDimensionLimit = getEmbeddingSourceDimensionLimit(embeddingSource?.modelName);
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if (modelDimensionLimit && (dimension <= 0 || dimension > modelDimensionLimit)) {
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error = t(Keys.controls.vectorEmbeddingPolicies.modelDimensionRangeError, {
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max: modelDimensionLimit,
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});
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}
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return error;
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};
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@@ -137,7 +173,12 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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quantizerType: supportsQuantizer ? matchingIndex?.quantizerType || "product" : undefined,
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vectorIndexShardKey: matchingIndex?.vectorIndexShardKey || undefined,
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pathError: onVectorEmbeddingPathError(embedding.path),
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dimensionsError: onVectorEmbeddingDimensionError(embedding.dimensions, matchingIndex?.type || "none"),
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dataTypeError: onVectorEmbeddingDataTypeError(embedding.dataType, embedding.embeddingSource),
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dimensionsError: onVectorEmbeddingDimensionError(
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embedding.dimensions,
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matchingIndex?.type || "none",
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embedding.embeddingSource,
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),
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embeddingSource: embedding.embeddingSource,
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embeddingSourceValid: true,
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});
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@@ -192,7 +233,10 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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);
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const validationPassed = vectorEmbeddingPolicyData.every(
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(policy: VectorEmbeddingPolicyData) =>
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policy.pathError === "" && policy.dimensionsError === "" && policy.embeddingSourceValid,
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policy.pathError === "" &&
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policy.dataTypeError === "" &&
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policy.dimensionsError === "" &&
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policy.embeddingSourceValid,
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);
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onVectorEmbeddingChange(vectorEmbeddings, vectorIndexes, validationPassed);
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@@ -216,7 +260,7 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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const vectorEmbeddings = [...vectorEmbeddingPolicyData];
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const vectorEmbedding = vectorEmbeddings[index];
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vectorEmbeddings[index].dimensions = value;
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const error = onVectorEmbeddingDimensionError(value, vectorEmbedding.indexType);
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const error = onVectorEmbeddingDimensionError(value, vectorEmbedding.indexType, vectorEmbedding.embeddingSource);
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vectorEmbeddings[index].dimensionsError = error;
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setVectorEmbeddingPolicyData(vectorEmbeddings);
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};
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@@ -225,7 +269,11 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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const vectorEmbeddings = [...vectorEmbeddingPolicyData];
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const vectorEmbedding = vectorEmbeddings[index];
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vectorEmbeddings[index].indexType = option.key as never;
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const error = onVectorEmbeddingDimensionError(vectorEmbedding.dimensions, vectorEmbedding.indexType);
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const error = onVectorEmbeddingDimensionError(
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vectorEmbedding.dimensions,
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vectorEmbedding.indexType,
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vectorEmbedding.embeddingSource,
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);
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vectorEmbeddings[index].dimensionsError = error;
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if (vectorEmbedding.indexType === "diskANN") {
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vectorEmbedding.indexingSearchListSize = 100;
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@@ -280,6 +328,12 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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): void => {
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const vectorEmbeddings = [...vectorEmbeddingPolicyData];
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vectorEmbeddings[index][property] = option.key as never;
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if (property === "dataType") {
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vectorEmbeddings[index].dataTypeError = onVectorEmbeddingDataTypeError(
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vectorEmbeddings[index].dataType,
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vectorEmbeddings[index].embeddingSource,
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);
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}
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setVectorEmbeddingPolicyData(vectorEmbeddings);
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};
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@@ -294,7 +348,15 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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return prev;
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}
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const next = [...prev];
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next[index] = { ...current, embeddingSource, embeddingSourceValid: isValid };
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const dataType = embeddingSourceSupportedDataTypes.includes(current.dataType) ? current.dataType : "float32";
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next[index] = {
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...current,
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dataType,
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dataTypeError: onVectorEmbeddingDataTypeError(dataType, embeddingSource),
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dimensionsError: onVectorEmbeddingDimensionError(current.dimensions, current.indexType, embeddingSource),
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embeddingSource,
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embeddingSourceValid: isValid,
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};
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return next;
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});
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},
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@@ -311,6 +373,7 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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distanceFunction: "euclidean",
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dimensions: 0,
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indexType: "none",
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dataTypeError: "",
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pathError: onVectorEmbeddingPathError(""),
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dimensionsError: onVectorEmbeddingDimensionError(0, "none"),
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embeddingSource: undefined,
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@@ -381,11 +444,12 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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disabled={isExistingPolicy(vectorEmbeddingPolicy)}
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required={true}
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styles={dropdownStyles}
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options={getDataTypeOptions()}
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options={getDataTypeOptions(!!vectorEmbeddingPolicy.embeddingSource)}
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selectedKey={vectorEmbeddingPolicy.dataType}
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onChange={(_event: React.FormEvent<HTMLDivElement>, option: IDropdownOption) =>
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onVectorEmbeddingPolicyChange(index, option, "dataType")
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}
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errorMessage={vectorEmbeddingPolicy.dataTypeError}
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></Dropdown>
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</Stack>
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<Stack>
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@@ -529,6 +593,7 @@ export const VectorEmbeddingPoliciesComponent: FunctionComponent<IVectorEmbeddin
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{isIntegratedEmbeddingEnabled() && (
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<VectorEmbeddingSourceComponent
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index={index}
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vectorPath={vectorEmbeddingPolicy.path}
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disabled={isExistingPolicy(vectorEmbeddingPolicy)}
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initialEmbeddingSource={vectorEmbeddingPolicy.embeddingSource}
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discardChanges={discardChanges}
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@@ -3,7 +3,7 @@ import { CollapsibleSectionComponent } from "Explorer/Controls/CollapsiblePanel/
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import { VectorEmbeddingSource } from "Contracts/DataModels";
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import {
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getAuthTypeOptions,
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isValidHttpsUrl,
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isValidFoundryEndpoint,
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parseSourcePaths,
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} from "Explorer/Controls/VectorSearch/VectorSearchUtils";
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import { dropdownStyles, labelStyles, textFieldStyles } from "Explorer/Controls/VectorSearch/vectorSearchStyles";
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@@ -13,6 +13,7 @@ import React, { FunctionComponent, useState } from "react";
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export interface IVectorEmbeddingSourceComponentProps {
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index: number;
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vectorPath: string;
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disabled: boolean;
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initialEmbeddingSource?: VectorEmbeddingSource;
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discardChanges?: boolean;
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@@ -38,13 +39,19 @@ const EmbeddingSourceLabel = ({ disabled, label, tooltip }: EmbeddingSourceLabel
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</Label>
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);
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const validateSourcePaths = (raw: string): string => {
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const validateSourcePaths = (raw: string, vectorPath: string): string => {
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const parsed = parseSourcePaths(raw);
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if (parsed.length === 0) {
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return t(Keys.controls.vectorEmbeddingPolicies.sourcePathsRequiredError);
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}
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const seen = new Set<string>();
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for (const p of parsed) {
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if (!p.startsWith("/")) {
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return t(Keys.controls.vectorEmbeddingPolicies.sourcePathInvalidError);
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}
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if (p === vectorPath) {
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return t(Keys.controls.vectorEmbeddingPolicies.sourcePathSameAsVectorPathError);
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}
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if (seen.has(p)) {
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return t(Keys.controls.vectorEmbeddingPolicies.sourcePathDuplicateError);
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}
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@@ -64,7 +71,7 @@ const validateEndpoint = (value: string | undefined): string => {
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if (!value || value.trim().length === 0) {
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return t(Keys.controls.vectorEmbeddingPolicies.endpointRequiredError);
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}
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if (!isValidHttpsUrl(value.trim())) {
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if (!isValidFoundryEndpoint(value.trim())) {
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return t(Keys.controls.vectorEmbeddingPolicies.endpointInvalidError);
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}
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return "";
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@@ -72,6 +79,7 @@ const validateEndpoint = (value: string | undefined): string => {
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export const VectorEmbeddingSourceComponent: FunctionComponent<IVectorEmbeddingSourceComponentProps> = ({
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index,
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vectorPath,
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disabled,
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initialEmbeddingSource,
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discardChanges,
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@@ -93,7 +101,7 @@ export const VectorEmbeddingSourceComponent: FunctionComponent<IVectorEmbeddingS
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modelName.trim().length > 0 ||
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endpoint.trim().length > 0;
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const sourcePathsError = hasAnyValue ? validateSourcePaths(sourcePathsRaw) : "";
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const sourcePathsError = hasAnyValue ? validateSourcePaths(sourcePathsRaw, vectorPath) : "";
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const deploymentNameError = hasAnyValue
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? validateRequired(deploymentName, Keys.controls.vectorEmbeddingPolicies.deploymentNameRequiredError)
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: "";
|
||||
@@ -196,11 +204,11 @@ export const VectorEmbeddingSourceComponent: FunctionComponent<IVectorEmbeddingS
|
||||
/>
|
||||
</Stack>
|
||||
<Stack>
|
||||
<Label disabled={disabled} styles={labelStyles}>
|
||||
<Label disabled={false} styles={labelStyles}>
|
||||
{t(Keys.controls.vectorEmbeddingPolicies.endpoint)}
|
||||
</Label>
|
||||
<TextField
|
||||
disabled={disabled}
|
||||
disabled={false}
|
||||
id={`vector-policy-embeddingSource-endpoint-${suffix}`}
|
||||
data-test={`VectorEmbeddingSource/Endpoint/${suffix}`}
|
||||
placeholder={t(Keys.controls.vectorEmbeddingPolicies.endpointPlaceholder)}
|
||||
|
||||
@@ -3,11 +3,13 @@ import { VectorEmbeddingSource, VectorIndex } from "Contracts/DataModels";
|
||||
import { Keys, t } from "Localization";
|
||||
|
||||
const dataTypes = ["float32", "uint8", "int8", "float16"];
|
||||
const embeddingSourceDataTypes = ["float32", "float16"];
|
||||
const distanceFunctions = ["euclidean", "cosine", "dotproduct"];
|
||||
const indexTypes = ["none", "flat", "diskANN", "quantizedFlat"];
|
||||
const authTypes: VectorEmbeddingSource["authType"][] = ["Entra"];
|
||||
|
||||
export const getDataTypeOptions = (): IDropdownOption[] => createDropdownOptionsFromLiterals(dataTypes);
|
||||
export const getDataTypeOptions = (hasEmbeddingSource = false): IDropdownOption[] =>
|
||||
createDropdownOptionsFromLiterals(hasEmbeddingSource ? embeddingSourceDataTypes : dataTypes);
|
||||
export const getDistanceFunctionOptions = (): IDropdownOption[] => createDropdownOptionsFromLiterals(distanceFunctions);
|
||||
export const getIndexTypeOptions = (): IDropdownOption[] => createDropdownOptionsFromLiterals(indexTypes);
|
||||
export const getAuthTypeOptions = (): IDropdownOption[] => createDropdownOptionsFromLiterals(authTypes);
|
||||
@@ -26,14 +28,14 @@ export const parseSourcePaths = (raw: string): string[] => {
|
||||
return raw
|
||||
.split(",")
|
||||
.map((p) => p.trim())
|
||||
.filter((p) => p.length > 0)
|
||||
.map((p) => (p.startsWith("/") ? p : `/${p}`));
|
||||
.filter((p) => p.length > 0);
|
||||
};
|
||||
|
||||
export const isValidHttpsUrl = (value: string): boolean => {
|
||||
export const isValidFoundryEndpoint = (value: string): boolean => {
|
||||
try {
|
||||
const url = new URL(value);
|
||||
return url.protocol === "https:";
|
||||
const allowedHostSuffixes = [".openai.azure.com", ".openai.azure.us", ".openai.azure.cn", ".services.ai.azure.com"];
|
||||
return url.protocol === "https:" && allowedHostSuffixes.some((suffix) => url.hostname.endsWith(suffix));
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -1014,14 +1014,19 @@
|
||||
"pathDuplicateError": "Path is already defined",
|
||||
"dimensionRangeError": "Dimension must be greater than 0 and less than or equal 4096",
|
||||
"dimensionFlatIndexError": "Maximum allowed dimension for flat index is 505",
|
||||
"modelDimensionRangeError": "Dimension must be greater than 0 and less than or equal {{max}}",
|
||||
"adaDimensionError": "Dimensions must be 1536",
|
||||
"quantizationByteSizeRangeError": "Quantization byte size must be greater than 0 and less than or equal to 512",
|
||||
"indexingSearchListSizeRangeError": "Indexing search list size must be greater than or equal to 25 and less than or equal to 500",
|
||||
"sourcePathsRequiredError": "At least one source path is required",
|
||||
"sourcePathInvalidError": "Source paths must start with /",
|
||||
"sourcePathDuplicateError": "Source paths must be unique",
|
||||
"sourcePathSameAsVectorPathError": "Source path must be different from vector path",
|
||||
"deploymentNameRequiredError": "Deployment name is required",
|
||||
"modelNameRequiredError": "Model name is required",
|
||||
"endpointRequiredError": "Endpoint is required",
|
||||
"endpointInvalidError": "Endpoint must be a valid https:// URL"
|
||||
"modelNameRequiredError": "Embedding model name is required",
|
||||
"endpointRequiredError": "Microsoft Foundry Endpoint is required",
|
||||
"endpointInvalidError": "Endpoint must be a valid Azure OpenAI or Foundry https:// URL",
|
||||
"embeddingSourceDataTypeError": "Embedding generation supports only float32 or float16 data types"
|
||||
}
|
||||
},
|
||||
"containerCopy": {
|
||||
|
||||
Reference in New Issue
Block a user