kindle_gpt

// code to put in pipedream node for kindle gpt mod
// 95% AI generated code
import OpenAI from "openai"

function extractArticle(evt) {
  const b = evt?.body
  if (!b) return ""

  if (typeof b === "object" && b.article != null) {
    return String(b.article)
  }

  if (typeof b === "string") {
    // Try JSON first
    try {
      const j = JSON.parse(b)
      if (j && j.article != null) return String(j.article)
    } catch {}

    // Try x-www-form-urlencoded
    const params = new URLSearchParams(b)
    if (params.has("article")) return params.get("article")

    return b
  }

  return ""
}

export default defineComponent({
  async run({ steps, $ }) {
    const evt = steps.trigger.event || {}
    const article = extractArticle(evt)

    const openai = new OpenAI({
      baseURL: "https://openrouter.ai/api/v1",
      apiKey: process.env.OPENROUTER_API_KEY,    })

    const systemPrompt = `
Depending on the input content provide a definition (if it is a word or phrase
that may need one), translate to English (if the input content is in a foreign
language) or provide further context and explanation as well as verify accuracy
(for example for historic facts or scientific descriptions). Be straight to the
point and concise. Always respond in English. Output HTML. Use tags such as <b>,
<i>, <ul>, <li>, <p> as needed. Do not use header tags such as <h1>, <h2> etc.
`.trim()

    const userPrompt = `
I'm reading a book and encountered the following content "${article}".
`.trim()

    try {
      const completion = await openai.chat.completions.create({
        model: "google/gemini-2.5-flash",
        models: ["openai/gpt-4.1-mini"],
        messages: [
          { role: "system", content: systemPrompt },
          { role: "user", content: userPrompt },
        ],
      })

      const msg =
        completion.choices?.[0]?.message?.content?.trim() || ""
      const usedModel = completion.model || "unknown"

      await $.respond({
        status: 200,
        headers: { "Content-Type": "application/json" },
        body: {
          status: 200,
          // Model returns HTML per the system prompt
          articleHtml: msg,
          articleUrl: "",
          licenseMessage: `Response generated via OpenRouter (model="${usedModel}")`,
          errorMessage: null,
        },
      })
    } catch (err) {
      await $.respond({
        status: 502,
        headers: { "Content-Type": "application/json" },
        body: {
          status: 502,
          articleHtml: "",
          articleUrl: "",
          licenseMessage: "",
          errorMessage:
            err?.message || "OpenRouter call failed",
        },
      })
    }
  },
})