Files
at-mintel/packages/payload-ai/src/endpoints/generateEndpoints.ts
Marc Mintel 541f1c17b7
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feat(mcps): add kabelfachmann MCP with Kabelhandbuch integration and remove legacy PM2 orchestration
2026-03-08 01:01:43 +01:00

190 lines
5.8 KiB
TypeScript

import { PayloadRequest } from "payload";
import * as fs from "node:fs/promises";
import * as path from "node:path";
import * as os from "node:os";
async function getOrchestrator() {
const OPENROUTER_KEY =
process.env.OPENROUTER_KEY || process.env.OPENROUTER_API_KEY;
const REPLICATE_KEY = process.env.REPLICATE_API_KEY;
if (!OPENROUTER_KEY) {
throw new Error(
"Missing OPENROUTER_API_KEY in .env (Required for AI generation)",
);
}
const importDynamic = new Function("modulePath", "return import(modulePath)");
const { AiBlogPostOrchestrator } = await importDynamic(
"@mintel/content-engine",
);
return new AiBlogPostOrchestrator({
apiKey: OPENROUTER_KEY,
replicateApiKey: REPLICATE_KEY,
model: "google/gemini-3-flash-preview",
});
}
export const generateSlugEndpoint = async (req: PayloadRequest) => {
try {
let body: any = {};
try {
if (req.body) body = (await req.json?.()) || {};
} catch {
/* ignore */
}
const { title, draftContent, oldSlug, instructions } = body;
const orchestrator = await getOrchestrator();
const newSlug = await orchestrator.generateSlug(
draftContent,
title,
instructions,
);
if (oldSlug && oldSlug !== newSlug) {
await req.payload.create({
collection: "redirects" as any,
data: {
from: oldSlug,
to: newSlug,
},
});
}
return Response.json({ success: true, slug: newSlug });
} catch (e: any) {
return Response.json({ success: false, error: e.message }, { status: 500 });
}
};
export const generateThumbnailEndpoint = async (req: PayloadRequest) => {
try {
let body: any = {};
try {
if (req.body) body = (await req.json?.()) || {};
} catch {
/* ignore */
}
const { draftContent, title, instructions } = body;
const OPENROUTER_KEY =
process.env.OPENROUTER_KEY || process.env.OPENROUTER_API_KEY;
const REPLICATE_KEY = process.env.REPLICATE_API_KEY;
if (!OPENROUTER_KEY) throw new Error("Missing OPENROUTER_API_KEY in .env");
if (!REPLICATE_KEY) throw new Error("Missing REPLICATE_API_KEY in .env");
const importDynamic = new Function(
"modulePath",
"return import(modulePath)",
);
const { AiBlogPostOrchestrator } = await importDynamic(
"@mintel/content-engine",
);
const { ThumbnailGenerator } = await importDynamic(
"@mintel/thumbnail-generator",
);
const orchestrator = new AiBlogPostOrchestrator({
apiKey: OPENROUTER_KEY,
replicateApiKey: REPLICATE_KEY,
model: "google/gemini-3-flash-preview",
});
const tg = new ThumbnailGenerator({ replicateApiKey: REPLICATE_KEY });
const prompt = await orchestrator.generateVisualPrompt(
draftContent || title || "Technology",
instructions,
);
const tmpPath = path.join(os.tmpdir(), `mintel-thumb-${Date.now()}.png`);
await tg.generateImage(prompt, tmpPath);
const fileData = await fs.readFile(tmpPath);
const stat = await fs.stat(tmpPath);
const fileName = path.basename(tmpPath);
const newMedia = await req.payload.create({
collection: "media" as any,
data: {
alt: title ? `Thumbnail for ${title}` : "AI Generated Thumbnail",
},
file: {
data: fileData,
name: fileName,
mimetype: "image/png",
size: stat.size,
},
});
await fs.unlink(tmpPath).catch(() => {});
return Response.json({ success: true, mediaId: newMedia.id });
} catch (e: any) {
return Response.json({ success: false, error: e.message }, { status: 500 });
}
};
export const generateSingleFieldEndpoint = async (req: PayloadRequest) => {
try {
let body: any = {};
try {
if (req.body) body = (await req.json?.()) || {};
} catch {
/* ignore */
}
const {
documentTitle,
documentContent,
fieldName,
fieldDescription,
instructions,
} = body;
const OPENROUTER_KEY =
process.env.OPENROUTER_KEY || process.env.OPENROUTER_API_KEY;
if (!OPENROUTER_KEY) throw new Error("Missing OPENROUTER_API_KEY");
const contextDocsData = await req.payload.find({
collection: "context-files" as any,
limit: 100,
});
const projectContext = contextDocsData.docs
.map((doc: any) => `--- ${doc.filename} ---\n${doc.content}`)
.join("\n\n");
const prompt = `You are an expert AI assistant perfectly trained for generating exact data values for CMS components.
PROJECT STRATEGY & CONTEXT:
${projectContext}
DOCUMENT TITLE: ${documentTitle}
DOCUMENT DRAFT:\n${documentContent}\n
YOUR TASK: Generate the exact value for a specific field named "${fieldName}".
${fieldDescription ? `FIELD DESCRIPTION / CONSTRAINTS: ${fieldDescription}\n` : ""}
${instructions ? `EDITOR INSTRUCTIONS for this field: ${instructions}\n` : ""}
CRITICAL RULES:
1. Respond ONLY with the requested content value.
2. NO markdown wrapping blocks (like \`\`\`mermaid or \`\`\`html) around the output! Just the raw code or text.
3. If the field implies a diagram or flow, output RAW Mermaid.js code.
4. If it's standard text, write professional B2B German. No quotes, no conversational filler.`;
const res = await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${OPENROUTER_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "google/gemini-3-flash-preview",
messages: [{ role: "user", content: prompt }],
}),
});
const data = await res.json();
const text = data.choices?.[0]?.message?.content?.trim() || "";
return Response.json({ success: true, text });
} catch (e: any) {
return Response.json({ success: false, error: e.message }, { status: 500 });
}
};