Add llms.vector module for vector search using grafana-llm-app

This adds convenience functions to access the endpoints added in
grafana/grafana-llm-app#33.

src/llms/constants.ts

@@ -0,0 +1,2 @@
+export const LLM_PLUGIN_ID = 'grafana-llm-app';
+export const LLM_PLUGIN_ROUTE = `/api/plugins/${LLM_PLUGIN_ID}`;

src/llms/index.ts

@@ -1 +1,2 @@
 export * as openai from './openai';
+export * as vector from './vector';

src/llms/openai.ts

@@ -14,8 +14,8 @@ import { getBackendSrv, getGrafanaLiveSrv, logDebug } from "@grafana/runtime";
 import { pipe, Observable, UnaryFunction } from "rxjs";
 import { filter, map, scan, takeWhile } from "rxjs/operators";
 
-const LLM_PLUGIN_ID = 'grafana-llm-app';
-const LLM_PLUGIN_ROUTE = `/api/plugins/${LLM_PLUGIN_ID}`;
+import { LLM_PLUGIN_ID, LLM_PLUGIN_ROUTE } from "./constants";
+
 const OPENAI_CHAT_COMPLETIONS_PATH = 'openai/v1/chat/completions';
 
 /** The role of a message's author. */

src/llms/vector.ts

@@ -0,0 +1,91 @@
+/**
+ * Vector search API.
+ *
+ * This module can be used to interact with the vector database configured
+ * in the Grafana LLM app plugin. That plugin must be installed, enabled and configured
+ * in order for these functions to work.
+ *
+ * The {@link enabled} function can be used to check if the plugin is enabled and configured.
+ */
+
+import { getBackendSrv, logDebug } from "@grafana/runtime";
+import { LLM_PLUGIN_ROUTE } from "./constants";
+
+interface SearchResultPayload extends Record<string, any> { }
+
+/**
+ * A request to search for resources in the vector database.
+ **/
+export interface SearchRequest {
+  /**
+   * The name of the collection to search in.
+   *
+   * Available collections can be obtained using the `collections` function.
+   **/
+  collection: string;
+
+  /** The query to search for. */
+  query: string;
+
+  /**
+   * The maximum number of results to return.
+   * 
+   * Defaults to 10.
+   **/
+  limit?: number;
+}
+
+/**
+ * The results of a vector search.
+ *
+ * Results will be ordered by score, descending.
+ */
+export interface SearchResult<T extends SearchResultPayload> {
+  /**
+   * The payload of the result.
+   *
+   * The type of this payload depends on the collection that was searched in.
+   * Grafana core types can be found in the same module as this type.
+   **/
+  payload: T;
+
+  /**
+   * The score of the result.
+   *
+   * This is a number between 0 and 1, where 1 is the best possible match.
+   */
+  score: number;
+}
+
+interface SearchResultResponse<T extends SearchResultPayload> {
+  results: SearchResult<T>[];
+}
+
+/**
+ * Search for resources in the configured vector database.
+ */
+export async function search<T extends SearchResultPayload>(request: SearchRequest): Promise<SearchResult<T>[]> {
+  const response = await getBackendSrv().post<SearchResultResponse<T>>('/api/plugins/grafana-llm-app/resources/vector/search', request, {
+    headers: { 'Content-Type': 'application/json' }
+  });
+  return response.results;
+}
+
+let loggedWarning = false;
+
+/** Check if the vector API is enabled and configured via the LLM plugin. */
+export const enabled = async () => {
+  try {
+    const settings = await getBackendSrv().get(`${LLM_PLUGIN_ROUTE}/settings`, undefined, undefined, {
+      showSuccessAlert: false, showErrorAlert: false,
+    });
+    return settings.enabled && (settings?.secureJsonFields?.openAIKey ?? false);
+  } catch (e) {
+    if (!loggedWarning) {
+      logDebug(String(e));
+      logDebug('Failed to check if OpenAI is enabled. This is expected if the Grafana LLM plugin is not installed, and the above error can be ignored.');
+      loggedWarning = true;
+    }
+    return false;
+  }
+}