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3export async function getModelBuilder(spec: {
4  type?: "llm" | "chat" | "embedding";
5  provider?: "openai" | "huggingface";
6} = { type: "llm", provider: "openai" }, options?: any) {
7  const { extend, cond, matches, invoke } = await import("npm:lodash-es");
8  // Set up LangSmith tracer
17  // Set up API key for each providers
18  const args = extend({ callbacks }, options);
19  if (spec?.provider === "openai")
20    args.openAIApiKey = process.env.OPENAI;
21  else if (spec?.provider === "huggingface")
22    args.apiKey = process.env.HUGGINGFACE;
24  const setup = cond([
25    [
26      matches({ type: "llm", provider: "openai" }),
27      async () => {
28        const { OpenAI } = await import("npm:langchain/llms/openai");
29        return new OpenAI(args);
30      },
31    ],
32    [
33      matches({ type: "chat", provider: "openai" }),
34      async () => {
35        const { ChatOpenAI } = await import("npm:langchain/chat_models/openai");
36        return new ChatOpenAI(args);
37      },
38    ],
39    [
40      matches({ type: "embedding", provider: "openai" }),
41      async () => {
42        const { OpenAIEmbeddings } = await import(
43          "npm:langchain/embeddings/openai"
44        );
45        return new OpenAIEmbeddings(args);
46      },
47    ],

3
4export const elevenlabsTTS = async (req, res) => {
5  // https://platform.openai.com/docs/api-reference/images/create
6  // https://ale_annini-elevenlabstts.express.val.run/?args=[%22{\%22text\%22:\%22it%20beautiful\%22}%22]
7  const payload = {

4  let repsonse_obj = await chatGPT(
5    "hello assistant",
6    [], // this can be an empty list, or if you're using this to continue a conversation, you can pass in someting of the form: https://platform.openai.com/docs/guides/chat/introduction
7    API_KEY
8  );

4  const cheerio = await import("npm:cheerio");
5  const html = await fetchText(
6    "https://en.wikipedia.org/wiki/OpenAI",
7  );
8  const $ = cheerio.load(html);

1import { trackOpenAiFreeUsage } from "https://esm.town/v/patrickjm/trackOpenAiFreeUsage";
2import { openAiTextCompletion } from "https://esm.town/v/patrickjm/openAiTextCompletion";
3import { openAiModeration } from "https://esm.town/v/patrickjm/openAiModeration";
4import { openAiFreeQuotaExceeded } from "https://esm.town/v/patrickjm/openAiFreeQuotaExceeded";
5import { openAiFreeUsageConfig } from "https://esm.town/v/patrickjm/openAiFreeUsageConfig";
6
7/**
8 * OpenAI text completion. https://platform.openai.com/docs/api-reference/completions
9 * 
10 * val.town has generously provided a free daily quota. Until the quota is met, no need to provide an API key.
11 * To see if the quota has been met, you can run @patrickjm.openAiFreeQuotaExceeded()
12 *
13 * For full REST API access, see @patrickjm.openAiTextCompletion
14 */
15export let gpt3 = async (params: {
16  openAiKey?: string,
17  prompt: string,
18  maxTokens?: number,
21
22  // Determine whether to use provided apiKey or free usage apiKey based on daily quota.
23  const apiKey = params.openAiKey ?? openAiFreeUsageConfig.key;
24  const exceeded = await openAiFreeQuotaExceeded();
25  if (!params.openAiKey && exceeded) {
26    throw new Error(openAiFreeUsageConfig.quota_error);
27  }
28
29  // If using free token, first check inputs against moderation api
30  if (!params.openAiKey) {
31    const moderation = await openAiModeration({
32      apiKey,
33      input: params.prompt,
35    if (moderation.results.some((r) => r.flagged)) {
36      throw new Error(
37        "Sorry, this prompt was flagged by OpenAI moderation. If you provide your own API key, moderation will be turned off."
38      );
39    }
41
42  // Call completion API
43  const response = await openAiTextCompletion({
44    apiKey: apiKey,
45    prompt: params.prompt,
50  // If using free token, track usage against the quota.
51  try {
52    if (!params.openAiKey) {
53      await trackOpenAiFreeUsage(MODEL, response.usage.total_tokens);
54    }
55  } catch (e) {}

3
4/**
5 * OpenAI text completion. https://platform.openai.com/docs/api-reference/completions
6 * 
7 * val.town and rlimit.com has generously provided a free daily quota. Until the quota is met, no need to provide an API key.

9  query: string;
10}): Promise<number[]> =>
11  fetchJSON("https://api.openai.com/v1/embeddings", {
12    method: "POST",
13    headers: {

2
3export const questionsWithGuidelinesChain = (async () => {
4  const { ChatOpenAI } = await import(
5    "https://esm.sh/langchain@0.0.150/chat_models/openai"
6  );
7  const { LLMChain } = await import("https://esm.sh/langchain@0.0.150/chains");
19  ]);
20  const questionChain = questionPrompt
21    .pipe(new ChatOpenAI({
22      openAIApiKey: process.env.OPENAI_API_KEY,
23    })
24      .pipe(new StringOutputParser()));
31  const styleChain = stylePrompt
32    .pipe(
33      new ChatOpenAI({
34        openAIApiKey: process.env.OPENAI_API_KEY,
35      }),
36    )

15  );
16  const { SupabaseVectorStore } = await import("npm:langchain/vectorstores");
17  const { ChatOpenAI } = await import("npm:langchain/chat_models");
18  const { OpenAIEmbeddings } = await import("npm:langchain/embeddings");
19  const { createClient } = await import(
20    "https://esm.sh/@supabase/supabase-js@2"
25  );
26  let streamedResponse = "";
27  const chat = new ChatOpenAI({
28    modelName: "gpt-3.5-turbo",
29    openAIApiKey: process.env.OPEN_API_KEY,
30    streaming: true,
31    callbacks: [{
35  });
36  const vectorStore = await SupabaseVectorStore.fromExistingIndex(
37    new OpenAIEmbeddings({
38      openAIApiKey: process.env.OPEN_API_KEY,
39    }),
40    {

4export let generateValCodeAPI = (description: string) =>
5  generateValCode(
6    process.env.VT_OPENAI_KEY,
7    description,
8  );