import type { CallToolResult } from "@modelcontextprotocol/sdk/types.js";
import { describeAccuracyTests } from "./sdk/describeAccuracyTests.js";
import { Matcher } from "./sdk/matcher.js";
describeAccuracyTests(
[
{
prompt: "Create an auto embed vector search index on 'plot' field in 'mflix.movies' namespace using voyage-4-large model.",
expectedToolCalls: [
{
toolName: "create-index",
parameters: {
database: "mflix",
collection: "movies",
name: Matcher.anyOf(Matcher.string(), Matcher.undefined),
definition: [
{
type: "vectorSearch",
fields: [
{
type: "autoEmbed",
path: "plot",
model: "voyage-4-large",
modality: "text",
},
],
},
],
},
},
],
},
{
prompt: `\
Check if there in existing vector search index on the 'plot' field in the 'mflix.movies' namespace. \
If not present then create an auto embed vector search index on the 'plot' field in the 'mflix.movies' namespace using voyage-4-large model.\
`,
mockedTools: {
"collection-indexes": (): CallToolResult => {
return {
content: [
{
type: "text",
text: 'Found 1 search and vector search indexes in the collection "movies"',
},
{
type: "text",
text: JSON.stringify({
name: "plot_auto_embed_index",
type: "vectorSearch",
status: "READY",
latestDefinition: {
type: "autoEmbed",
path: "plot",
model: "voyage-4-large",
modality: "text",
},
}),
},
],
};
},
},
expectedToolCalls: [
{
toolName: "collection-indexes",
parameters: {
database: "mflix",
collection: "movies",
},
},
],
},
],
{
userConfig: { voyageApiKey: process.env.MDB_VOYAGE_API_KEY, previewFeatures: "search" },
clusterConfig: {
autoEmbed: true,
mongotPassword: process.env.MDB_MONGOT_PASSWORD as string,
voyageIndexingKey: process.env.MDB_VOYAGE_API_KEY as string,
voyageQueryKey: process.env.MDB_VOYAGE_API_KEY as string,
},
}
);
