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102 lines
2.6 KiB
TypeScript
102 lines
2.6 KiB
TypeScript
import { WorkflowOperator } from "manifold-workflow-engine";
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import { zodResponseFormat } from "openai/helpers/zod";
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import { z } from "zod";
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const QuerySchema = z.object({
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query: z.string(),
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});
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export function createNewsWebhookOperator({
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eventHost,
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streamId,
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openai,
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messages,
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}) {
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return new WorkflowOperator("news-search", async (state: any) => {
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const { latestUserMessage } = state;
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console.log(`Processing user message: ${latestUserMessage}`);
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const resource = "news-search";
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const input = await getQueryFromContext({
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openai,
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messages,
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latestUserMessage,
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});
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const eventSource = new URL(eventHost);
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const url = `${eventSource}api/webhooks`;
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console.log({ url });
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const stream = {
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id: crypto.randomUUID(),
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parent: streamId,
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resource,
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payload: input,
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};
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const createStreamResponse = await fetch(`${eventSource}api/webhooks`, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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},
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body: JSON.stringify({
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id: stream.id,
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parent: streamId,
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resource: "news-search",
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payload: {
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input,
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},
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}),
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});
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const raw = await createStreamResponse.text();
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const { stream_url } = JSON.parse(raw);
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const surl = eventHost + stream_url;
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const webhook = { url: surl, id: stream.id, resource };
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return {
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...state,
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webhook,
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latestUserMessage: "",
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latestAiMessage: "",
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};
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});
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async function getQueryFromContext({ messages, openai, latestUserMessage }) {
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const systemMessage = {
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role: "system",
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content: `Analyze the latest message in a conversation and generate a JSON object with a single implied question for a news search. The JSON should be structured as follows:
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{
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"query": "<question to be answered by a news search>"
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}
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## Example
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{
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"query": "When was the last Buffalo Sabres hockey game?"
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}
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Focus on the most recent message to determine the query. Output only the JSON object without any additional text.`,
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};
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const conversation = messages.map((m) => ({
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role: m.role,
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content: m.content,
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}));
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conversation.push({ role: "user", content: `${latestUserMessage}` });
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const m = [systemMessage, ...conversation];
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const completion = await openai.beta.chat.completions.parse({
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model: "gpt-4o-mini",
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messages: m,
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temperature: 0,
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response_format: zodResponseFormat(QuerySchema, "query"),
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});
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const { query } = completion.choices[0].message.parsed;
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console.log({ newsWebhookQuery: query });
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return query;
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}
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}
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