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import { defaultEmbeddingModel, embeddingModels } from "$lib/server/embeddingModels";
import type { Conversation } from "$lib/types/Conversation";
import type { Message } from "$lib/types/Message";
import type { WebSearch, WebSearchScrapedSource } from "$lib/types/WebSearch";
import type { Assistant } from "$lib/types/Assistant";
import type { MessageWebSearchUpdate } from "$lib/types/MessageUpdate";
import { search } from "./search/search";
import { scrape } from "./scrape/scrape";
import { findContextSources } from "./embed/embed";
import { removeParents } from "./markdown/tree";
import {
makeErrorUpdate,
makeFinalAnswerUpdate,
makeGeneralUpdate,
makeSourcesUpdate,
} from "./update";
import { mergeAsyncGenerators } from "$lib/utils/mergeAsyncGenerators";
import { MetricsServer } from "../metrics";
import { logger } from "$lib/server/logger";
const MAX_N_PAGES_TO_SCRAPE = 8 as const;
const MAX_N_PAGES_TO_EMBED = 5 as const;
export async function* runWebSearch(
conv: Conversation,
messages: Message[],
ragSettings?: Assistant["rag"],
query?: string
): AsyncGenerator<MessageWebSearchUpdate, WebSearch, undefined> {
const prompt = messages[messages.length - 1].content;
const createdAt = new Date();
const updatedAt = new Date();
MetricsServer.getMetrics().webSearch.requestCount.inc();
try {
const embeddingModel =
embeddingModels.find((m) => m.id === conv.embeddingModel) ?? defaultEmbeddingModel;
if (!embeddingModel) {
throw Error(`Embedding model ${conv.embeddingModel} not available anymore`);
}
// Search the web
const { searchQuery, pages } = yield* search(messages, ragSettings, query);
if (pages.length === 0) throw Error("No results found for this search query");
// Scrape pages
yield makeGeneralUpdate({ message: "Browsing search results" });
const allScrapedPages = yield* mergeAsyncGenerators(
pages.slice(0, MAX_N_PAGES_TO_SCRAPE).map(scrape(embeddingModel.chunkCharLength))
);
const scrapedPages = allScrapedPages
.filter((p): p is WebSearchScrapedSource => Boolean(p))
.filter((p) => p.page.markdownTree.children.length > 0)
.slice(0, MAX_N_PAGES_TO_EMBED);
if (!scrapedPages.length) {
throw Error(`No text found in the first ${MAX_N_PAGES_TO_SCRAPE} results`);
}
// Chunk the text of each of the elements and find the most similar chunks to the prompt
yield makeGeneralUpdate({ message: "Extracting relevant information" });
const contextSources = await findContextSources(scrapedPages, prompt, embeddingModel).then(
(ctxSources) =>
ctxSources.map((source) => ({
...source,
page: { ...source.page, markdownTree: removeParents(source.page.markdownTree) },
}))
);
yield makeSourcesUpdate(contextSources);
const webSearch: WebSearch = {
prompt,
searchQuery,
results: scrapedPages.map(({ page, ...source }) => ({
...source,
page: { ...page, markdownTree: removeParents(page.markdownTree) },
})),
contextSources,
createdAt,
updatedAt,
};
yield makeFinalAnswerUpdate();
return webSearch;
} catch (searchError) {
const message = searchError instanceof Error ? searchError.message : String(searchError);
logger.error(message);
yield makeErrorUpdate({ message: "An error occurred", args: [message] });
const webSearch: WebSearch = {
prompt,
searchQuery: "",
results: [],
contextSources: [],
createdAt,
updatedAt,
};
yield makeFinalAnswerUpdate();
return webSearch;
}
}
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