feat: migrate @google/generative-ai → @google/genai + add Deep Research config

Task 1 — SDK Migration:
- Replace @google/generative-ai with @google/genai in package.json
- lib/gemini.ts: lazy-init GoogleGenAI client, ai.models.generateContent()
- lib/sponsor/gemini-intent.ts: migrate to new SDK API surface
- lib/sponsor/gemini-outreach.ts: migrate to new SDK API surface
- response.text is now a property (not method) in new SDK

Task 2 — Deep Research Config:
- pipelineConfig.ts: add enableDeepResearch, deepResearchAgent,
  deepResearchPromptTemplate, infographicModel fields
- lib/types/config.ts: add matching PipelineConfig interface fields

Author: codercatdev

lib/gemini.ts

@@ -1,7 +1,16 @@
-import { GoogleGenerativeAI } from "@google/generative-ai";
+import { GoogleGenAI } from "@google/genai";
 import { getConfigValue } from "@/lib/config";
 
-const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY || "");
+let _ai: GoogleGenAI | null = null;
+
+/** Lazy-initialize the GoogleGenAI client (avoids crash at import time if GEMINI_API_KEY is missing). */
+function getAI(): GoogleGenAI {
+	if (!_ai) {
+		const apiKey = process.env.GEMINI_API_KEY || "";
+		_ai = new GoogleGenAI({ apiKey });
+	}
+	return _ai;
+}
 
 /**
  * Generate text content using Gemini Flash.
@@ -14,13 +23,13 @@ export async function generateWithGemini(
 	systemInstruction?: string,
 ): Promise<string> {
 	const geminiModel = await getConfigValue("pipeline_config", "geminiModel", "gemini-2.0-flash");
-	const model = genAI.getGenerativeModel({
+	const ai = getAI();
+	const response = await ai.models.generateContent({
 		model: geminiModel,
-		...(systemInstruction && { systemInstruction }),
+		contents: prompt,
+		...(systemInstruction && { config: { systemInstruction } }),
 	});
-	const result = await model.generateContent(prompt);
-	const response = result.response;
-	return response.text();
+	return response.text ?? "";
 }
 
 /**

lib/sponsor/gemini-intent.ts

@@ -1,4 +1,4 @@
-import { GoogleGenerativeAI } from '@google/generative-ai'
+import { GoogleGenAI } from '@google/genai'
 import { getConfigValue } from '@/lib/config'
 
 const SPONSORSHIP_TIERS = [
@@ -17,10 +17,6 @@ export interface SponsorIntent {
   urgency: 'low' | 'medium' | 'high'
 }
 
-/**
- * Uses Gemini Flash to parse inbound sponsor emails/messages
- * and extract structured data for creating a sponsorLead.
- */
 export async function extractSponsorIntent(message: string): Promise<SponsorIntent> {
   const apiKey = process.env.GEMINI_API_KEY
   if (!apiKey) {
@@ -35,8 +31,7 @@ export async function extractSponsorIntent(message: string): Promise<SponsorInte
   }
 
   const geminiModel = await getConfigValue('pipeline_config', 'geminiModel', 'gemini-2.0-flash')
-  const genAI = new GoogleGenerativeAI(apiKey)
-  const model = genAI.getGenerativeModel({ model: geminiModel })
+  const ai = new GoogleGenAI({ apiKey })
 
   const prompt = `You are analyzing an inbound sponsorship inquiry for CodingCat.dev, a developer education platform with YouTube videos, podcasts, blog posts, and newsletters.
 
@@ -61,9 +56,11 @@ Message to analyze:
 ${message}`
 
   try {
-    const result = await model.generateContent(prompt)
-    const response = result.response
-    const text = response.text().trim()
+    const response = await ai.models.generateContent({
+      model: geminiModel,
+      contents: prompt,
+    })
+    const text = (response.text ?? '').trim()
 
     // Strip any markdown code fences if present
     const jsonStr = text.replace(/^```json?\n?/i, '').replace(/\n?```$/i, '').trim()

lib/sponsor/gemini-outreach.ts

@@ -1,4 +1,4 @@
-import { GoogleGenerativeAI } from '@google/generative-ai'
+import { GoogleGenAI } from '@google/genai'
 import { getConfigValue } from '@/lib/config'
 
 export interface SponsorPoolEntry {
@@ -28,10 +28,6 @@ CodingCat.dev Sponsorship Tiers:
 Our audience: 50K+ developers interested in web development, JavaScript/TypeScript, React, Next.js, and modern dev tools.
 `.trim()
 
-/**
- * Uses Gemini to generate a personalized cold outreach email
- * for a potential sponsor from the sponsor pool.
- */
 export async function generateOutreachEmail(
   sponsor: SponsorPoolEntry,
   rateCard: string = DEFAULT_RATE_CARD
@@ -42,9 +38,8 @@ export async function generateOutreachEmail(
     return getTemplateEmail(sponsor, rateCard)
   }
 
-  const genAI = new GoogleGenerativeAI(apiKey)
+  const ai = new GoogleGenAI({ apiKey })
   const geminiModel = await getConfigValue("pipeline_config", "geminiModel", "gemini-2.0-flash");
-  const model = genAI.getGenerativeModel({ model: geminiModel })
 
   const optOutUrl = sponsor.optOutToken
     ? `${process.env.NEXT_PUBLIC_URL || 'https://codingcat.dev'}/api/sponsor/opt-out?token=${sponsor.optOutToken}`
@@ -74,9 +69,11 @@ Respond ONLY with valid JSON, no markdown formatting:
 {"subject": "...", "body": "..."}`
 
   try {
-    const result = await model.generateContent(prompt)
-    const response = result.response
-    const text = response.text().trim()
+    const response = await ai.models.generateContent({
+      model: geminiModel,
+      contents: prompt,
+    })
+    const text = (response.text ?? '').trim()
 
     const jsonStr = text.replace(/^```json?\n?/i, '').replace(/\n?```$/i, '').trim()
     const parsed = JSON.parse(jsonStr) as OutreachEmail

lib/types/config.ts

@@ -11,6 +11,10 @@ export interface PipelineConfig {
   youtubeUploadVisibility: string;
   youtubeChannelId: string;
   enableNotebookLmResearch: boolean;
+  enableDeepResearch: boolean;
+  deepResearchAgent: string;
+  deepResearchPromptTemplate: string;
+  infographicModel: string;
   qualityThreshold: number;
   stuckTimeoutMinutes: number;
   maxIdeasPerRun: number;

package.json

@@ -12,7 +12,7 @@
 	},
 	"dependencies": {
 		"@codingcatdev/sanity-plugin-podcast-rss": "^1.0.0",
-		"@google/generative-ai": "^0.24.1",
+		"@google/genai": "^1.0.0",
 		"@hookform/resolvers": "^5.2.2",
 		"@marsidev/react-turnstile": "^1.4.2",
 		"@portabletext/block-tools": "^5.0.5",

sanity/schemas/singletons/pipelineConfig.ts

@@ -34,7 +34,7 @@ export default defineType({
       name: "youtubeChannelId",
       title: "YouTube Channel ID",
       type: "string",
-      description: "Your YouTube channel ID \u2014 used for analytics and upload targeting",
+      description: "Your YouTube channel ID — used for analytics and upload targeting",
       initialValue: "",
     }),
     defineField({
@@ -44,6 +44,34 @@ export default defineType({
       description: "When enabled, the ingest cron creates a NotebookLM notebook for deep research before script generation. Requires NOTEBOOKLM_AUTH_JSON env var",
       initialValue: false,
     }),
+    defineField({
+      name: "enableDeepResearch",
+      title: "Enable Deep Research",
+      type: "boolean",
+      description: "When enabled, the ingest cron uses Gemini Deep Research API for comprehensive topic research before script generation. Replaces NotebookLM research.",
+      initialValue: false,
+    }),
+    defineField({
+      name: "deepResearchAgent",
+      title: "Deep Research Agent",
+      type: "string",
+      description: "The Gemini Deep Research agent model ID. This is the agent used for autonomous web research via the Interactions API",
+      initialValue: "deep-research-pro-preview-12-2025",
+    }),
+    defineField({
+      name: "deepResearchPromptTemplate",
+      title: "Deep Research Prompt Template",
+      type: "text",
+      description: "Template for Deep Research queries. Use {topic} as placeholder for the trend topic. Sent to the Deep Research agent for autonomous web research",
+      initialValue: "Research comprehensively: \"{topic}\"\n\nFocus areas:\n- What is it and why does it matter?\n- How does it work technically?\n- Key features and capabilities\n- Comparison with alternatives\n- Getting started guide\n- Common pitfalls and best practices\n\nTarget audience: Web developers learning new tech.\nTone: Educational, accessible, engaging.",
+    }),
+    defineField({
+      name: "infographicModel",
+      title: "Infographic Model",
+      type: "string",
+      description: "Model used for generating brand-consistent infographics from research data. Imagen 4 Fast ($0.02/image) supports seed-based reproducibility",
+      initialValue: "imagen-4-fast",
+    }),
     defineField({
       name: "qualityThreshold",
       title: "Quality Threshold",