diff --git a/.gitignore b/.gitignore
new file mode 100644
index 00000000..10a3913a
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,45 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.*
+.yarn/*
+!.yarn/patches
+!.yarn/plugins
+!.yarn/releases
+!.yarn/versions
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+.pnpm-debug.log*
+
+# env files (can opt-in for committing if needed)
+.env*
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts
+node_modules
+
+/src/generated/prisma
+*.db
diff --git a/IMPLEMENTATION_PLAN.md b/IMPLEMENTATION_PLAN.md
new file mode 100644
index 00000000..d8ba5319
--- /dev/null
+++ b/IMPLEMENTATION_PLAN.md
@@ -0,0 +1,50 @@
+# Implementation Plan - Podcast Generator
+
+## Phase 0: Git Setup
+- [x] Check if the current directory is an initialized git repository.
+- [x] If it is, create and checkout a new feature branch named `podcast-generator`.
+
+## Phase 1: Environment & Project Setup
+- [x] Initialize a new Next.js project with TypeScript, Tailwind CSS, and App Router.
+- [x] Install backend dependencies: `prisma`, `@prisma/client` (or `better-sqlite3`), `rss-parser`, `fluent-ffmpeg`, `@google/generative-ai` (Gemini SDK), `@google-cloud/text-to-speech`.
+- [x] Install frontend dependencies: `lucide-react` (for icons), `axios` or use `fetch`.
+- [x] Configure Environment Variables (`.env.local`): `GOOGLE_AI_API_KEY`, `GOOGLE_APPLICATION_CREDENTIALS`, `DATABASE_URL`.
+- [x] Verify `ffmpeg` installation on the local machine.
+
+## Phase 2: Database & Data Access
+- [x] Initialize Prisma with SQLite provider (`npx prisma init --datasource-provider sqlite`).
+- [x] Define `Feed` model in `prisma/schema.prisma` (id, url, title, createdAt).
+- [x] Define `Podcast` model in `prisma/schema.prisma` (id, title, filePath, duration, createdAt, summary).
+- [x] Run migration to create the SQLite database (`npx prisma migrate dev --name init`).
+- [x] Create a `db.ts` lib file to export the singleton Prisma client instance.
+
+## Phase 3: Backend Services (Core Logic)
+- [x] **RSS Service**: Create `lib/services/rss.ts`. Implement `fetchLatestArticles(feeds)` using `rss-parser`. Filter articles from the last 24 hours.
+- [x] **AI Service (Summarization)**: Create `lib/services/gemini.ts`. Implement `generatePodcastScript(articles)` using the Gemini API. Construct the prompt as specified in the Tech Spec.
+- [x] **TTS Service (Synthesis)**: Create `lib/services/tts.ts`. Implement `synthesizeSpeech(text)` using Google Cloud TTS (Chirp model). Handle text chunking if necessary.
+- [x] **Audio Service (Processing)**: Create `lib/services/audio.ts`. Implement `concatAudioSegments(segments, outputPath)` using `fluent-ffmpeg` to merge Intro + Body + Outro.
+
+## Phase 4: API Routes
+- [x] **Feed Endpoints**: Create `app/api/feeds/route.ts` and `app/api/feeds/[id]/route.ts`. Implement GET (list), POST (add & validate), DELETE (remove).
+- [x] **Podcast Endpoints**: Create `app/api/podcasts/route.ts`. Implement GET (list history).
+- [x] **Generation Endpoint**: Create `app/api/podcasts/generate/route.ts`. Implement POST. This should orchestrate the full pipeline: Fetch RSS -> Summarize -> TTS -> Concat -> Save to DB -> Return Result.
+
+## Phase 5: Frontend - UI Components
+- [x] **Layout & Hero**: Update `app/page.tsx` with a responsive layout. Add the Hero section with the "Robot agent reading news" image (placeholder or generated).
+- [x] **Feed Manager Component**: Create `components/FeedManager.tsx`. Implement a form to add URLs and a list to display/delete current feeds. Connect to `/api/feeds`.
+- [x] **Podcast History & Player**: Create `components/PodcastPlayer.tsx`. Display a list of generated podcasts. When selected, play the audio file using the standard `<audio>` tag. Connect to `/api/podcasts`.
+- [x] **Generate Button**: Create a prominent "Generate Podcast" button in `app/page.tsx`. Connect to `/api/podcasts/generate` and handle loading states (this might take a while to process).
+
+## Phase 6: Integration & Polish
+- [x] Verify the full flow: Add Feed -> Generate -> Wait -> Play Audio.
+- [x] Add basic error handling (invalid RSS, API failures).
+- [x] Refine the Prompt engineering for Gemini to ensure the script sounds natural.
+- [x] Ensure the generated audio files are accessible publicly (saved in `public/podcasts` or served via a static route).
+
+## Phase 7: Completion & Version Control
+- [x] Verify application functionality.
+- [x] Create a `README.md` file explaining the application functions, how to interact with them, the architecture, file breakdown and how to run and test it locally.
+- [x] Add all changes to the repository (`git add .`).
+- [x] Commit the changes (`git commit -m "Complete implementation of Podcast Generator"`).
+- [x] Push the feature branch to the remote repository, creating a branch with the same name in the remote repository, using the Gemini CLI github MCP server.
+- [x] Open a pull request for the feature branch using the Gemini CLI github MCP server, leave it open for review, don't merge it.
diff --git a/README.md b/README.md
index 75588e2d..913ae189 100644
--- a/README.md
+++ b/README.md
@@ -1,94 +1,55 @@
-# Spec-Driven Development w Gemini CLI
-
-This repo has some basic assets to experiment **Spec-Driven Development** using the Gemini CLI. You will act as a developer going from a raw Functional Specification to a deployed Pull Request in a single session.
-
-## Assets
-
-* `.gemini/commands/`: Contains configuration files for custom commands (`techspec`, `plan`, `build`).
-* `GEMINI.md`: Contains project rules and guidelines.
-* `.github/workflows`: Contains CI workflow.
-* **No application code**.
+# Podcast Generator
+
+A Next.js application that generates personalized audio news podcasts from RSS feeds using Google Gemini for summarization and Google Cloud Chirp for high-quality text-to-speech.
+
+## Features
+
+- **RSS Feed Management**: Add and remove RSS feeds.
+- **AI Summarization**: Automatically fetches and summarizes the latest articles from your feeds using Gemini 1.5 Flash.
+- **Audio Generation**: Converts summaries into natural-sounding speech using Google's Chirp models.
+- **Podcast Player**: Listen to your generated daily briefings directly in the app.
+
+## Architecture
+
+- **Frontend**: Next.js (App Router), Tailwind CSS.
+- **Backend**: Next.js API Routes.
+- **Database**: SQLite (via Prisma & Better-SQLite3).
+- **AI Services**: Google Gemini API, Google Cloud Text-to-Speech.
+- **Audio Processing**: fluent-ffmpeg.
+
+## Setup
+
+1.  **Clone the repository**.
+2.  **Install dependencies**:
+    ```bash
+    npm install
+    ```
+3.  **Environment Variables**:
+    Create a `.env.local` file with the following:
+    ```env
+    GOOGLE_AI_API_KEY=your_gemini_api_key
+    GOOGLE_APPLICATION_CREDENTIALS=path/to/your/google_cloud_credentials.json
+    DATABASE_URL="file:./dev.db"
+    ```
+4.  **Database Migration**:
+    ```bash
+    npx prisma migrate dev --name init
+    ```
+5.  **Run Development Server**:
+    ```bash
+    npm run dev
+    ```
 
 ## Requirements
 
-The `GEMINI.md` configuration and custom commands require the following extensions:
-* **Google Workspace**
-* **Nano Banana**
-* **GitHub**
-
----
-
-## Step 1: The Architect Phase (/techspec)
-
-**Goal:** Transform a Functional Spec (Google Doc) into a Technical Spec (Google Doc).
-
-1. **Command:**
-   ```
-   /techspec "Name of your functional specs doc" "Your desired technology stack and requirements"
-   ```
-
-2. **What Happens:**
-    * The agent searches your Drive for the doc.
-    * It reads the requirements.
-    * It generates a **Technical Specification** including Data Models, API Routes, and Architecture based on your inputs.
-    * **Output:** It creates a *new* Google Doc titled "Technical Specification - Application name" and gives you the link.
-
----
-
-## Step 2: The Planning Phase (/plan)
-
-**Goal:** Break the Technical Spec down into an atomic Implementation Plan.
-
-1. **Command:**
-   ```
-   /plan "Name of your Tech spec doc"
-   ```
-   *(Use the exact name of the doc generated in Step 1)*
-
-2. **What Happens:**
-    * The agent reads the Tech Spec.
-    * It creates a local file `IMPLEMENTATION_PLAN.md`.
-    * It breaks the project into phases (e.g., Setup, Backend, Frontend, Polish).
-    * It defines the Git strategy.
-
----
-
-## Step 3: The Build Phase (/build)
-
-**Goal:** Execute the plan and write the code.
-
-1. **Command:**
-   ```
-   /build IMPLEMENTATION_PLAN.md "Name of your Tech spec doc"
-   ```
-
-2. **What Happens (Iterative):**
-    * **Execution:** The agent iterates through the plan, initializing the project structure and writing the application code.
-    * **Visuals:** It generates necessary visual assets (images, icons) as defined in the spec.
-    * **Progress:** It updates `IMPLEMENTATION_PLAN.md` as tasks are completed.
-
----
-
-## Step 4: Final Delivery
-
-**Goal:** Push the code and open a Pull Request.
-
-1. **Action:**
-   The `/build` command's final phase usually covers this, or you can manually instruct the agent to finalize the project.
-
-2. **What Happens:**
-    * The agent runs final checks (linting/formatting).
-    * It creates a `README.md` for the new application.
-    * It commits all changes.
-    * It pushes the feature branch to GitHub.
-    * It uses the GitHub extension to **Open a Pull Request**.
-
----
+- Node.js 18+
+- ffmpeg installed on the system.
+- Google Cloud Project with Vertex AI / Gemini API and Text-to-Speech API enabled.
 
-## Summary of Commands
+## Usage
 
-| Step | Command | Input | Output |
-| :--- | :--- | :--- | :--- |
-| **1. Spec** | `/techspec` | Functional Doc (Drive) | Tech Spec (Drive) |
-| **2. Plan** | `/plan` | Tech Spec (Drive) | `IMPLEMENTATION_PLAN.md` |
-| **3. Build** | `/build` | Plan + Tech Spec | Code, Assets, App |
\ No newline at end of file
+1.  Open `http://localhost:3000`.
+2.  Add RSS feed URLs (e.g., `https://rss.nytimes.com/services/xml/rss/nyt/HomePage.xml`).
+3.  Click "Generate New Episode".
+4.  Wait for the process to complete (this can take a minute).
+5.  Play the generated episode from the list.
\ No newline at end of file
diff --git a/eslint.config.mjs b/eslint.config.mjs
new file mode 100644
index 00000000..05e726d1
--- /dev/null
+++ b/eslint.config.mjs
@@ -0,0 +1,18 @@
+import { defineConfig, globalIgnores } from "eslint/config";
+import nextVitals from "eslint-config-next/core-web-vitals";
+import nextTs from "eslint-config-next/typescript";
+
+const eslintConfig = defineConfig([
+  ...nextVitals,
+  ...nextTs,
+  // Override default ignores of eslint-config-next.
+  globalIgnores([
+    // Default ignores of eslint-config-next:
+    ".next/**",
+    "out/**",
+    "build/**",
+    "next-env.d.ts",
+  ]),
+]);
+
+export default eslintConfig;
diff --git a/js_codegen_instructions.md b/js_codegen_instructions.md
new file mode 100644
index 00000000..0600d075
--- /dev/null
+++ b/js_codegen_instructions.md
@@ -0,0 +1,762 @@
+# About this file (for humans only)
+
+This file provides curated prompts to help generative AI models like Gemini and
+Claude produce code using the latest Gemini APIs.
+
+Generative models are often unaware of recent API updates and may suggest
+outdated or legacy code. You can copy and paste the instructions from this file
+into your development environment to provide the model with the necessary
+context.
+
+> **Note: This is an Alpha (v0.2) Release** This is an early and experimental
+> collection of prompts. It's intended for testing and to gather feedback from
+> the community. Results are not guaranteed, and we expect frequent updates.
+
+## Disclaimer
+
+Please be aware that generative models can generate incorrect or unexpected
+outputs. You should always verify the results.
+
+## Scope
+
+To maintain a manageable context size, this guide does not cover the full range
+of the Gemini API's features. Refer to our [developer
+documentation](https://ai.google.dev/gemini-api/docs) for comprehensive feature
+guides.
+
+If you'd like to reduce context window consumption, you can experiment with
+removing sections on this file. You can let us know how it works at our
+[community forums](https://discuss.ai.google.dev/c/gemini-api).
+
+Note: These instructions are for the [Gemini
+API](https://ai.google.dev/gemini-api/docs). Vertex AI developers should note
+that while the APIs are similar, there may be minor differences, and the
+[official Vertex AI documentation](https://cloud.google.com/vertex-ai/docs)
+should be used for definitive guidance
+
+## Contributions
+
+We welcome suggestions for improvement. Please feel free to open an issue or
+send a pull request.
+
+You can copy paste the next section.
+
+# Gemini API Coding Guidelines (JavaScript/TypeScript)
+
+You are a Gemini API coding expert. Help me with writing code using the Gemini
+API calling the official libraries and SDKs.
+
+Please follow the following guidelines when generating code.
+
+You can find the official SDK documentation and code samples here:
+https://googleapis.github.io/js-genai/
+
+## Golden Rule: Use the Correct and Current SDK
+
+Always use the Google Gen AI SDK to call the Gemini models, which is the
+standard library for all Gemini API interactions. Do not use legacy libraries
+and SDKs.
+
+-   **Library Name:** Google Gen AI SDK
+-   **NPM Package:** `@google/genai`
+-   **Legacy Libraries**: (`@google/generative-ai`) are deprecated
+
+**Installation:**
+
+-   **Incorrect:** `npm install @google/generative-ai`
+-   **Incorrect:** `npm install @google-ai/generativelanguage`
+-   **Correct:** `npm install @google/genai`
+
+**APIs and Usage:**
+
+-   **Incorrect:** `const { GenerativeModel } =
+    require('@google/generative-ai')` -> **Correct:** `import { GoogleGenAI }
+    from '@google/genai'`
+-   **Incorrect:** `const model = genai.getGenerativeModel(...)` -> **Correct:**
+    `const ai = new GoogleGenAI({apiKey: "..."})`
+-   **Incorrect:** `await model.generateContent(...)` -> **Correct:** `await
+    ai.models.generateContent(...)`
+-   **Incorrect:** `await model.generateContentStream(...)` -> **Correct:**
+    `await ai.models.generateContentStream(...)`
+-   **Incorrect:** `const generationConfig = { ... }` -> **Correct:** Pass
+    configuration directly: `config: { safetySettings: [...] }`
+-   **Incorrect** `GoogleGenerativeAI`
+-   **Incorrect** `google.generativeai`
+-   **Incorrect** `models.create`
+-   **Incorrect** `ai.models.create`
+-   **Incorrect** `models.getGenerativeModel`
+-   **Incorrect** `ai.models.getModel`
+-   **Incorrect** `ai.models['model_name']`
+-   **Incorrect** `generationConfig`
+-   **Incorrect** `GoogleGenAIError` -> **Correct** `ApiError`
+-   **Incorrect** `GenerateContentResult` -> **Correct**
+    `GenerateContentResponse`.
+-   **Incorrect** `GenerateContentRequest` -> **Correct**
+    `GenerateContentParameters`
+
+## Initialization and API key
+
+The `@google/genai` library requires creating a `GoogleGenAI` instance for all
+API calls.
+
+-   Always use `const ai = new GoogleGenAI({})` to create an instance.
+-   Set the `GEMINI_API_KEY` environment variable, which will be picked up
+    automatically in Node.js environments.
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+
+// Uses the GEMINI_API_KEY environment variable if apiKey not specified
+const ai = new GoogleGenAI({});
+
+// Or pass the API key directly
+// const ai = new GoogleGenAI({apiKey: process.env.GEMINI_API_KEY});
+```
+
+## Models
+
+-   By default, use the following models when using `google-genai`:
+    -   **General Text & Multimodal Tasks:** `gemini-2.5-flash`
+    -   **Coding and Complex Reasoning Tasks:** `gemini-3-pro-preview`
+    -   **Fast Image Generation and Editing:** `gemini-2.5-flash-image` (aka Nano Banana)
+    -   **High-Quality Image Generation and Editing:** `gemini-3-pro-image-preview` (aka Nano Banana Pro)
+    -   **Video Generation Tasks:** `veo-3.0-fast-generate-preview` or
+        `veo-3.0-generate-preview`.
+
+-   It is also acceptable to use the following model if explicitly requested by
+    the user:
+    -   **Gemini 2.0 Series**: `gemini-2.0-flash`, `gemini-2.0-pro`
+
+-   Do not use the following deprecated models (or their variants like
+    `gemini-1.5-flash-latest`):
+    -   **Prohibited:** `gemini-1.5-flash`
+    -   **Prohibited:** `gemini-1.5-pro`
+    -   **Prohibited:** `gemini-pro`
+
+## Basic Inference (Text Generation)
+
+Here's how to generate a response from a text prompt.
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+
+const ai = new GoogleGenAI({}); // Assumes GEMINI_API_KEY is set
+
+async function run() {
+  const response = await ai.models.generateContent({
+    model: 'gemini-2.5-flash',
+    contents: 'why is the sky blue?',
+  });
+
+  console.log(response.text); // output is often markdown
+}
+
+run();
+```
+
+Multimodal inputs are supported by passing file data in the `contents` array.
+
+```javascript
+import { GoogleGenAI, Part } from '@google/genai';
+import * as fs from 'fs';
+
+const ai = new GoogleGenAI({});
+
+// Converts local file information to a Part object.
+function fileToGenerativePart(path, mimeType): Part {
+  return {
+    inlineData: {
+      data: Buffer.from(fs.readFileSync(path)).toString("base64"),
+      mimeType
+    },
+  };
+}
+
+async function run() {
+    const imagePart = fileToGenerativePart("path/to/image.jpg", "image/jpeg");
+
+    const response = await ai.models.generateContent({
+        model: 'gemini-2.5-flash',
+        contents: [imagePart, "explain that image"],
+    });
+
+    console.log(response.text); // The output often is markdown
+}
+
+run();
+```
+
+You can use this approach to pass a variety of data types (images, audio, video,
+pdf). For PDF, use `application/pdf` as `mimeType`.
+
+For larger files, use `ai.files.upload`:
+
+```javascript
+import { GoogleGenAI, createPartFromUri, createUserContent } from '@google/genai';
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const f = await ai.files.upload({
+        file: 'path/to/sample.mp3',
+        config:{mimeType: 'audio/mp3'},
+    });
+
+    const response = await ai.models.generateContent({
+        model: 'gemini-2.5-flash',
+         contents: createUserContent([
+          createPartFromUri(f.uri, f.mimeType),
+          "Describe this audio clip"
+        ])
+    });
+
+    console.log(response.text);
+}
+
+run();
+```
+
+You can delete files after use like this:
+
+```javascript
+const myFile = await ai.files.upload({file: 'path/to/sample.mp3', mimeType: 'audio/mp3'});
+await ai.files.delete({name: myFile.name});
+```
+
+## Additional Capabilities and Configurations
+
+Below are examples of advanced configurations.
+
+### Thinking
+
+Gemini 2.5 series models support thinking, which is on by default for
+`gemini-2.5-flash`. It can be adjusted by using `thinking_budget` setting.
+Setting it to zero turns thinking off, and will reduce latency.
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+
+const ai = new GoogleGenAI({});
+
+async function main() {
+  const response = await ai.models.generateContent({
+    model: "gemini-2.5-pro",
+    contents: "Provide a list of 3 famous physicists and their key contributions",
+    config: {
+      thinkingConfig: {
+        thinkingBudget: 1024,
+        // Turn off thinking:
+        // thinkingBudget: 0
+        // Turn on dynamic thinking:
+        // thinkingBudget: -1
+      },
+    },
+  });
+
+  console.log(response.text);
+}
+
+main();
+```
+
+IMPORTANT NOTES:
+
+-   Minimum thinking budget for `gemini-2.5-pro` is `128` and thinking can not
+    be turned off for that model.
+-   No models (apart from Gemini 2.5 series) support thinking or thinking
+    budgets APIs. Do not try to adjust thinking budgets other models (such as
+    `gemini-2.0-flash` or `gemini-2.0-pro`) otherwise it will cause syntax
+    errors.
+
+### System instructions
+
+Use system instructions to guide the model's behavior.
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const response = await ai.models.generateContent({
+        model: 'gemini-2.5-flash',
+        contents: "Hello.",
+        config: {
+            systemInstruction: "You are a pirate",
+        }
+    });
+    console.log(response.text);
+}
+run();
+```
+
+### Hyperparameters
+
+You can also set `temperature` or `maxOutputTokens` within the `config` object.
+**Avoid** setting `maxOutputTokens`, `topP`, `topK` unless explicitly requested
+by the user.
+
+### Safety configurations
+
+Avoid setting safety configurations unless explicitly requested by the user. If
+explicitly asked for by the user, here is a sample API:
+
+```javascript
+import { GoogleGenAI, HarmCategory, HarmBlockThreshold, Part } from '@google/genai';
+import * as fs from 'fs';
+
+const ai = new GoogleGenAI({});
+
+function fileToGenerativePart(path, mimeType): Part {
+  return {
+    inlineData: {
+      data: Buffer.from(fs.readFileSync(path)).toString("base64"),
+      mimeType
+    },
+  };
+}
+
+async function run() {
+    const img = fileToGenerativePart("/path/to/img.jpg", "image/jpeg");
+    const response = await ai.models.generateContent({
+        model: "gemini-2.5-flash",
+        contents: ['Do these look store-bought or homemade?', img],
+        config: {
+            safetySettings: [
+                {
+                    category: HarmCategory.HARM_CATEGORY_HATE_SPEECH,
+                    threshold: HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+                },
+            ]
+        }
+    });
+    console.log(response.text);
+}
+run();
+```
+
+### Streaming
+
+It is possible to stream responses to reduce user perceived latency:
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+const ai = new GoogleGenAI({});
+
+async function run() {
+  const responseStream = await ai.models.generateContentStream({
+    model: "gemini-2.5-flash",
+    contents: ["Explain how AI works"],
+  });
+
+  for await (const chunk of responseStream) {
+    process.stdout.write(chunk.text);
+  }
+  console.log(); // for a final newline
+}
+run();
+```
+
+### Chat
+
+For multi-turn conversations, use the `chats` service to maintain conversation
+history.
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const chat = ai.chats.create({model: "gemini-2.5-flash"});
+
+    let response = await chat.sendMessage({message:"I have 2 dogs in my house."});
+    console.log(response.text);
+
+    response = await chat.sendMessage({message: "How many paws are in my house?"});
+    console.log(response.text);
+
+    const history = await chat.getHistory();
+    for (const message of history) {
+        console.log(`role - ${message.role}: ${message.parts[0].text}`);
+    }
+}
+run();
+``` It is also possible to use streaming with Chat:
+
+```javascript
+    const chat = ai.chats.create({model: "gemini-2.5-flash"});
+    const stream = await chat.sendMessageStream({message:"I have 2 dogs in my house."});
+    for await (const chunk of stream) {
+      console.log(chunk.text);
+      console.log("_".repeat(80));
+    }
+```
+
+Note: ai.chats.create({model}) returns `Chat` under `@google/genai` which tracks
+the session.
+
+### Structured outputs
+
+Ask the model to return a response in JSON format.
+
+The recommended way is to configure a `responseSchema` for the expected output.
+
+See the available types below that can be used in the `responseSchema`.
+
+```javascript
+export enum Type {
+  /**
+   *   Not specified, should not be used.
+   */
+  TYPE_UNSPECIFIED = 'TYPE_UNSPECIFIED',
+  /**
+   *   OpenAPI string type
+   */
+  STRING = 'STRING',
+  /**
+   *   OpenAPI number type
+   */
+  NUMBER = 'NUMBER',
+  /**
+   *   OpenAPI integer type
+   */
+  INTEGER = 'INTEGER',
+  /**
+   *   OpenAPI boolean type
+   */
+  BOOLEAN = 'BOOLEAN',
+  /**
+   *   OpenAPI array type
+   */
+  ARRAY = 'ARRAY',
+  /**
+   *   OpenAPI object type
+   */
+  OBJECT = 'OBJECT',
+  /**
+   *   Null type
+   */
+  NULL = 'NULL',
+}
+```
+
+`Type.OBJECT` cannot be empty; it must contain other properties.
+
+```javascript
+import { GoogleGenAI, Type } from "@google/genai";
+
+const ai = new GoogleGenAI({});
+const response = await ai.models.generateContent({
+   model: "gemini-2.5-flash",
+   contents: "List a few popular cookie recipes, and include the amounts of ingredients.",
+   config: {
+     responseMimeType: "application/json",
+     responseSchema: {
+        type: Type.ARRAY,
+        items: {
+          type: Type.OBJECT,
+          properties: {
+            recipeName: {
+              type: Type.STRING,
+              description: 'The name of the recipe.',
+            },
+            ingredients: {
+              type: Type.ARRAY,
+              items: {
+                type: Type.STRING,
+              },
+              description: 'The ingredients for the recipe.',
+            },
+          },
+          propertyOrdering: ["recipeName", "ingredients"],
+        },
+      },
+   },
+});
+
+let jsonStr = response.text.trim();
+```
+
+The `jsonStr` might look like this:
+
+```javascript
+[
+  {
+    "recipeName": "Chocolate Chip Cookies",
+    "ingredients": [
+      "1 cup (2 sticks) unsalted butter, softened",
+      "3/4 cup granulated sugar",
+      "3/4 cup packed brown sugar",
+      "1 teaspoon vanilla extract",
+      "2 large eggs",
+      "2 1/4 cups all-purpose flour",
+      "1 teaspoon baking soda",
+      "1 teaspoon salt",
+      "2 cups chocolate chips"
+    ]
+  },
+  ...
+]
+```
+
+#### Function Calling (Tools)
+
+You can provide the model with tools (functions) it can use to bring in external
+information to answer a question or act on a request outside the model.
+
+```javascript
+import {GoogleGenAI, FunctionDeclaration, Type} from '@google/genai';
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const controlLightDeclaration = {
+        name: 'controlLight',
+        parameters: {
+          type: Type.OBJECT,
+          description: 'Set brightness and color temperature of a light.',
+          properties: {
+            brightness: { type: Type.NUMBER, description: 'Light level from 0 to 100.' },
+            colorTemperature: { type: Type.STRING, description: '`daylight`, `cool`, or `warm`.'},
+          },
+          required: ['brightness', 'colorTemperature'],
+        },
+    };
+
+    const response = await ai.models.generateContent({
+        model: 'gemini-2.5-flash',
+        contents: 'Dim the lights so the room feels cozy and warm.',
+        config: {
+            tools: [{functionDeclarations: [controlLightDeclaration]}]
+        }
+    });
+
+    if (response.functionCalls) {
+        console.log(response.functionCalls);
+        // In a real app, you would execute the function and send the result back.
+    }
+}
+run();
+```
+
+### Generate Images
+
+Here's how to generate images using the Nano Banana models. Start with the
+Gemini 2.5 Flash image (Nano Banana) model as it should cover most use-cases.
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+
+const ai = new GoogleGenAI({});
+
+async function main() {
+  const prompt =
+  "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme";
+
+  const response = await ai.models.generateContent({
+    model: "gemini-2.5-flash-image",
+    contents: prompt,
+  });
+  for (const part of response.candidates[0].content.parts) {
+    if (part.text) {
+      console.log(part.text);
+    } else if (part.inlineData) {
+      const base64ImageBytes: string = part.inlineData.data;
+      const imageUrl = `data:image/png;base64,${base64ImageBytes}`;
+    }
+  }
+}
+
+main();
+```
+
+Upgrade to the Gemini 3 Pro image (Nano Banana Pro) model if the user requests
+high-resolution images or needs real-time information using the Google Search tool.
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+import * as fs from "node:fs";
+
+async function main() {
+
+  const ai = new GoogleGenAI({});
+
+  const prompt = 'Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day';
+  const aspectRatio = '16:9'; // "1:1","2:3","3:2","3:4","4:3","4:5","5:4","9:16","16:9","21:9"
+  const resolution = '2K';  // "1K", "2K", "4K"
+
+  const response = await ai.models.generateContent({
+    model: 'gemini-3-pro-image-preview',
+    contents: prompt,
+    config: {
+      imageConfig: {
+        aspectRatio: aspectRatio,
+        imageSize: resolution,
+      },
+      tools: [{google_search: {}}]
+    },
+  });
+
+  for (const part of response.candidates[0].content.parts) {
+    if (part.text) {
+      console.log(part.text);
+    } else if (part.inlineData) {
+      const base64ImageBytes: string = part.inlineData.data;
+      const imageUrl = `data:image/png;base64,${base64ImageBytes}`;
+    }
+  }
+}
+
+main();
+```
+
+### Edit Images
+
+Editing images is better done using the Gemini native image generation model.
+Configs are not supported in this model (except modality).
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+
+const ai = new GoogleGenAI({});
+
+const response = await ai.models.generateContent({
+  model: 'gemini-2.5-flash-image-preview',
+  contents: [imagePart, 'koala eating a nano banana']
+});
+for (const part of response.candidates[0].content.parts) {
+  if (part.inlineData) {
+    const base64ImageBytes: string = part.inlineData.data;
+    const imageUrl = `data:image/png;base64,${base64ImageBytes}`;
+  }
+}
+```
+
+### Generate Videos
+
+Here's how to generate videos using the Veo models. Usage of Veo can be costly,
+so after generating code for it, give user a heads up to check pricing for Veo.
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+import { createWriteStream } from "fs";
+import { Readable } from "stream";
+
+const ai = new GoogleGenAI({});
+
+async function main() {
+  let operation = await ai.models.generateVideos({
+    model: "veo-3.0-fast-generate-preview",
+    prompt: "Panning wide shot of a calico kitten sleeping in the sunshine",
+    config: {
+      personGeneration: "dont_allow",
+      aspectRatio: "16:9",
+    },
+  });
+
+  while (!operation.done) {
+    await new Promise((resolve) => setTimeout(resolve, 10000));
+    operation = await ai.operations.getVideosOperation({
+      operation: operation,
+    });
+  }
+
+  operation.response?.generatedVideos?.forEach(async (generatedVideo, n) => {
+    const resp = await fetch(`${generatedVideo.video?.uri}&key=GEMINI_API_KEY`); // append your API key
+    const writer = createWriteStream(`video${n}.mp4`);
+    Readable.fromWeb(resp.body).pipe(writer);
+  });
+}
+
+main();
+```
+
+### Search Grounding
+
+Google Search can be used as a tool for grounding queries that with up to date
+information from the web.
+
+```javascript
+import { GoogleGenAI } from "@google/genai";
+
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const response = await ai.models.generateContent({
+       model: "gemini-2.5-flash",
+       contents: "Who won the latest F1 race?",
+       config: {
+         tools: [{googleSearch: {}}],
+       },
+    });
+
+    console.log("Response:", response.text);
+
+    // Extract and display grounding URLs
+    const searchChunks = response.candidates?.[0]?.groundingMetadata?.groundingChunks;
+    if (searchChunks) {
+        const urls = searchChunks.map(chunk => chunk.web.uri);
+        console.log("Sources:", urls);
+    }
+}
+run();
+```
+
+### Content and Part Hierarchy
+
+While the simpler API call is often sufficient, you may run into scenarios where
+you need to work directly with the underlying `Content` and `Part` objects for
+more explicit control. These are the fundamental building blocks of the
+`generateContent` API.
+
+For instance, the following simple API call:
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const response = await ai.models.generateContent({
+        model: "gemini-2.5-flash",
+        contents: "How does AI work?",
+    });
+    console.log(response.text);
+}
+run();
+```
+
+is effectively a shorthand for this more explicit structure:
+
+```javascript
+import { GoogleGenAI } from '@google/genai';
+const ai = new GoogleGenAI({});
+
+async function run() {
+    const response = await ai.models.generateContent({
+        model: "gemini-2.5-flash",
+        contents: [
+            { role: "user", parts: [{ text: "How does AI work?" }] },
+        ],
+    });
+    console.log(response.text);
+}
+run();
+```
+
+## API Errors
+
+`ApiError` from `@google/genai` extends from EcmaScript `Error` and has
+`message`, `name` fields in addition to `status` (HTTP Code).
+
+## Other APIs
+
+The list of APIs and capabilities above are not comprehensive. If users ask you
+to generate code for a capability not provided above, refer them to
+https://googleapis.github.io/js-genai/.
+
+## Useful Links
+
+-   Documentation: ai.google.dev/gemini-api/docs
+-   API Keys and Authentication: ai.google.dev/gemini-api/docs/api-key
+-   Models: ai.google.dev/models
+-   API Pricing: ai.google.dev/pricing
+-   Rate Limits: ai.google.dev/rate-limits
\ No newline at end of file
diff --git a/next.config.ts b/next.config.ts
new file mode 100644
index 00000000..e9ffa308
--- /dev/null
+++ b/next.config.ts
@@ -0,0 +1,7 @@
+import type { NextConfig } from "next";
+
+const nextConfig: NextConfig = {
+  /* config options here */
+};
+
+export default nextConfig;
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 00000000..fc8afb6f
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,8029 @@
+{
+  "name": "podcast-generator",
+  "version": "0.1.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "podcast-generator",
+      "version": "0.1.0",
+      "dependencies": {
+        "@google-cloud/text-to-speech": "^6.4.0",
+        "@google/generative-ai": "^0.24.1",
+        "@prisma/client": "^5.22.0",
+        "axios": "^1.13.2",
+        "fluent-ffmpeg": "^2.1.3",
+        "lucide-react": "^0.561.0",
+        "next": "16.0.10",
+        "react": "19.2.1",
+        "react-dom": "19.2.1",
+        "rss-parser": "^3.13.0"
+      },
+      "devDependencies": {
+        "@tailwindcss/postcss": "^4",
+        "@types/fluent-ffmpeg": "^2.1.28",
+        "@types/node": "^20",
+        "@types/react": "^19",
+        "@types/react-dom": "^19",
+        "eslint": "^9",
+        "eslint-config-next": "16.0.10",
+        "prisma": "^5.22.0",
+        "tailwindcss": "^4",
+        "typescript": "^5"
+      }
+    },
+    "node_modules/@alloc/quick-lru": {
+      "version": "5.2.0",
+      "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
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+      }
+    },
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+      },
+      "engines": {
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+      }
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+        "@babel/helper-compilation-targets": "^7.27.2",
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+        "@babel/helpers": "^7.28.4",
+        "@babel/parser": "^7.28.5",
+        "@babel/template": "^7.27.2",
+        "@babel/traverse": "^7.28.5",
+        "@babel/types": "^7.28.5",
+        "@jridgewell/remapping": "^2.3.5",
+        "convert-source-map": "^2.0.0",
+        "debug": "^4.1.0",
+        "gensync": "^1.0.0-beta.2",
+        "json5": "^2.2.3",
+        "semver": "^6.3.1"
+      },
+      "engines": {
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+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/babel"
+      }
+    },
+    "node_modules/@babel/generator": {
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diff --git a/package.json b/package.json
new file mode 100644
index 00000000..1ba34a43
--- /dev/null
+++ b/package.json
@@ -0,0 +1,35 @@
+{
+  "name": "podcast-generator",
+  "version": "0.1.0",
+  "private": true,
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+    "react": "19.2.1",
+    "react-dom": "19.2.1",
+    "rss-parser": "^3.13.0"
+  },
+  "devDependencies": {
+    "@tailwindcss/postcss": "^4",
+    "@types/fluent-ffmpeg": "^2.1.28",
+    "@types/node": "^20",
+    "@types/react": "^19",
+    "@types/react-dom": "^19",
+    "eslint": "^9",
+    "eslint-config-next": "16.0.10",
+    "prisma": "^5.22.0",
+    "tailwindcss": "^4",
+    "typescript": "^5"
+  }
+}
diff --git a/postcss.config.mjs b/postcss.config.mjs
new file mode 100644
index 00000000..61e36849
--- /dev/null
+++ b/postcss.config.mjs
@@ -0,0 +1,7 @@
+const config = {
+  plugins: {
+    "@tailwindcss/postcss": {},
+  },
+};
+
+export default config;
diff --git a/prisma/migrations/20251214125935_init/migration.sql b/prisma/migrations/20251214125935_init/migration.sql
new file mode 100644
index 00000000..7d1b7840
--- /dev/null
+++ b/prisma/migrations/20251214125935_init/migration.sql
@@ -0,0 +1,20 @@
+-- CreateTable
+CREATE TABLE "Feed" (
+    "id" INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
+    "url" TEXT NOT NULL,
+    "title" TEXT NOT NULL,
+    "createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP
+);
+
+-- CreateTable
+CREATE TABLE "Podcast" (
+    "id" INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT,
+    "title" TEXT NOT NULL,
+    "filePath" TEXT NOT NULL,
+    "duration" INTEGER NOT NULL,
+    "createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "summary" TEXT
+);
+
+-- CreateIndex
+CREATE UNIQUE INDEX "Feed_url_key" ON "Feed"("url");
diff --git a/prisma/migrations/migration_lock.toml b/prisma/migrations/migration_lock.toml
new file mode 100644
index 00000000..2a5a4441
--- /dev/null
+++ b/prisma/migrations/migration_lock.toml
@@ -0,0 +1,3 @@
+# Please do not edit this file manually
+# It should be added in your version-control system (e.g., Git)
+provider = "sqlite"
diff --git a/prisma/schema.prisma b/prisma/schema.prisma
new file mode 100644
index 00000000..a31aa6c1
--- /dev/null
+++ b/prisma/schema.prisma
@@ -0,0 +1,27 @@
+// This is your Prisma schema file,
+// learn more about it in the docs: https://pris.ly/d/prisma-schema
+
+generator client {
+  provider = "prisma-client-js"
+}
+
+datasource db {
+  provider = "sqlite"
+  url      = env("DATABASE_URL")
+}
+
+model Feed {
+  id        Int      @id @default(autoincrement())
+  url       String   @unique
+  title     String
+  createdAt DateTime @default(now())
+}
+
+model Podcast {
+  id        Int      @id @default(autoincrement())
+  title     String
+  filePath  String
+  duration  Int
+  createdAt DateTime @default(now())
+  summary   String?
+}
\ No newline at end of file
diff --git a/public/file.svg b/public/file.svg
new file mode 100644
index 00000000..004145cd
--- /dev/null
+++ b/public/file.svg
@@ -0,0 +1 @@
+<svg fill="none" viewBox="0 0 16 16" xmlns="http://www.w3.org/2000/svg"><path d="M14.5 13.5V5.41a1 1 0 0 0-.3-.7L9.8.29A1 1 0 0 0 9.08 0H1.5v13.5A2.5 2.5 0 0 0 4 16h8a2.5 2.5 0 0 0 2.5-2.5m-1.5 0v-7H8v-5H3v12a1 1 0 0 0 1 1h8a1 1 0 0 0 1-1M9.5 5V2.12L12.38 5zM5.13 5h-.62v1.25h2.12V5zm-.62 3h7.12v1.25H4.5zm.62 3h-.62v1.25h7.12V11z" clip-rule="evenodd" fill="#666" fill-rule="evenodd"/></svg>
\ No newline at end of file
diff --git a/public/globe.svg b/public/globe.svg
new file mode 100644
index 00000000..567f17b0
--- /dev/null
+++ b/public/globe.svg
@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><g clip-path="url(#a)"><path fill-rule="evenodd" clip-rule="evenodd" d="M10.27 14.1a6.5 6.5 0 0 0 3.67-3.45q-1.24.21-2.7.34-.31 1.83-.97 3.1M8 16A8 8 0 1 0 8 0a8 8 0 0 0 0 16m.48-1.52a7 7 0 0 1-.96 0H7.5a4 4 0 0 1-.84-1.32q-.38-.89-.63-2.08a40 40 0 0 0 3.92 0q-.25 1.2-.63 2.08a4 4 0 0 1-.84 1.31zm2.94-4.76q1.66-.15 2.95-.43a7 7 0 0 0 0-2.58q-1.3-.27-2.95-.43a18 18 0 0 1 0 3.44m-1.27-3.54a17 17 0 0 1 0 3.64 39 39 0 0 1-4.3 0 17 17 0 0 1 0-3.64 39 39 0 0 1 4.3 0m1.1-1.17q1.45.13 2.69.34a6.5 6.5 0 0 0-3.67-3.44q.65 1.26.98 3.1M8.48 1.5l.01.02q.41.37.84 1.31.38.89.63 2.08a40 40 0 0 0-3.92 0q.25-1.2.63-2.08a4 4 0 0 1 .85-1.32 7 7 0 0 1 .96 0m-2.75.4a6.5 6.5 0 0 0-3.67 3.44 29 29 0 0 1 2.7-.34q.31-1.83.97-3.1M4.58 6.28q-1.66.16-2.95.43a7 7 0 0 0 0 2.58q1.3.27 2.95.43a18 18 0 0 1 0-3.44m.17 4.71q-1.45-.12-2.69-.34a6.5 6.5 0 0 0 3.67 3.44q-.65-1.27-.98-3.1" fill="#666"/></g><defs><clipPath id="a"><path fill="#fff" d="M0 0h16v16H0z"/></clipPath></defs></svg>
\ No newline at end of file
diff --git a/public/hero.png b/public/hero.png
new file mode 100644
index 00000000..540cf168
Binary files /dev/null and b/public/hero.png differ
diff --git a/public/next.svg b/public/next.svg
new file mode 100644
index 00000000..5174b28c
--- /dev/null
+++ b/public/next.svg
@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 394 80"><path fill="#000" d="M262 0h68.5v12.7h-27.2v66.6h-13.6V12.7H262V0ZM149 0v12.7H94v20.4h44.3v12.6H94v21h55v12.6H80.5V0h68.7zm34.3 0h-17.8l63.8 79.4h17.9l-32-39.7 32-39.6h-17.9l-23 28.6-23-28.6zm18.3 56.7-9-11-27.1 33.7h17.8l18.3-22.7z"/><path fill="#000" d="M81 79.3 17 0H0v79.3h13.6V17l50.2 62.3H81Zm252.6-.4c-1 0-1.8-.4-2.5-1s-1.1-1.6-1.1-2.6.3-1.8 1-2.5 1.6-1 2.6-1 1.8.3 2.5 1a3.4 3.4 0 0 1 .6 4.3 3.7 3.7 0 0 1-3 1.8zm23.2-33.5h6v23.3c0 2.1-.4 4-1.3 5.5a9.1 9.1 0 0 1-3.8 3.5c-1.6.8-3.5 1.3-5.7 1.3-2 0-3.7-.4-5.3-1s-2.8-1.8-3.7-3.2c-.9-1.3-1.4-3-1.4-5h6c.1.8.3 1.6.7 2.2s1 1.2 1.6 1.5c.7.4 1.5.5 2.4.5 1 0 1.8-.2 2.4-.6a4 4 0 0 0 1.6-1.8c.3-.8.5-1.8.5-3V45.5zm30.9 9.1a4.4 4.4 0 0 0-2-3.3 7.5 7.5 0 0 0-4.3-1.1c-1.3 0-2.4.2-3.3.5-.9.4-1.6 1-2 1.6a3.5 3.5 0 0 0-.3 4c.3.5.7.9 1.3 1.2l1.8 1 2 .5 3.2.8c1.3.3 2.5.7 3.7 1.2a13 13 0 0 1 3.2 1.8 8.1 8.1 0 0 1 3 6.5c0 2-.5 3.7-1.5 5.1a10 10 0 0 1-4.4 3.5c-1.8.8-4.1 1.2-6.8 1.2-2.6 0-4.9-.4-6.8-1.2-2-.8-3.4-2-4.5-3.5a10 10 0 0 1-1.7-5.6h6a5 5 0 0 0 3.5 4.6c1 .4 2.2.6 3.4.6 1.3 0 2.5-.2 3.5-.6 1-.4 1.8-1 2.4-1.7a4 4 0 0 0 .8-2.4c0-.9-.2-1.6-.7-2.2a11 11 0 0 0-2.1-1.4l-3.2-1-3.8-1c-2.8-.7-5-1.7-6.6-3.2a7.2 7.2 0 0 1-2.4-5.7 8 8 0 0 1 1.7-5 10 10 0 0 1 4.3-3.5c2-.8 4-1.2 6.4-1.2 2.3 0 4.4.4 6.2 1.2 1.8.8 3.2 2 4.3 3.4 1 1.4 1.5 3 1.5 5h-5.8z"/></svg>
\ No newline at end of file
diff --git a/public/vercel.svg b/public/vercel.svg
new file mode 100644
index 00000000..77053960
--- /dev/null
+++ b/public/vercel.svg
@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 1155 1000"><path d="m577.3 0 577.4 1000H0z" fill="#fff"/></svg>
\ No newline at end of file
diff --git a/public/window.svg b/public/window.svg
new file mode 100644
index 00000000..b2b2a44f
--- /dev/null
+++ b/public/window.svg
@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path fill-rule="evenodd" clip-rule="evenodd" d="M1.5 2.5h13v10a1 1 0 0 1-1 1h-11a1 1 0 0 1-1-1zM0 1h16v11.5a2.5 2.5 0 0 1-2.5 2.5h-11A2.5 2.5 0 0 1 0 12.5zm3.75 4.5a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5M7 4.75a.75.75 0 1 1-1.5 0 .75.75 0 0 1 1.5 0m1.75.75a.75.75 0 1 0 0-1.5.75.75 0 0 0 0 1.5" fill="#666"/></svg>
\ No newline at end of file
diff --git a/py_codegen_instructions.md b/py_codegen_instructions.md
new file mode 100644
index 00000000..70fb8a4e
--- /dev/null
+++ b/py_codegen_instructions.md
@@ -0,0 +1,624 @@
+# About this file (for humans only)
+
+This file provides curated prompts to help generative AI models like Gemini and
+Claude produce code using the latest Gemini APIs.
+
+Generative models are often unaware of recent API updates and may suggest
+outdated or legacy code. You can copy and paste the instructions from this file
+into your development environment to provide the model with the necessary
+context.
+
+> **Note: This is an Alpha (v0.2) Release** This is an early and experimental
+> collection of prompts. It's intended for testing and to gather feedback from
+> the community. Results are not guaranteed, and we expect frequent updates.
+
+## Disclaimer
+
+Please be aware that generative models can generate incorrect or unexpected
+outputs. You should always verify the results.
+
+## Scope
+
+To maintain a manageable context size, this guide does not cover the full range
+of the Gemini API's features. Refer to our [developer
+documentation](https://ai.google.dev/gemini-api/docs) for comprehensive feature
+guides.
+
+If you'd like to reduce context window consumption, you can experiment with
+removing sections on this file. You can let us know how it works at our
+[community forums](https://discuss.ai.google.dev/c/gemini-api).
+
+Note: These instructions are for the [Gemini
+API](https://ai.google.dev/gemini-api/docs). Vertex AI developers should note
+that while the APIs are similar, there may be minor differences, and the
+[official Vertex AI documentation](https://cloud.google.com/vertex-ai/docs)
+should be used for definitive guidance
+
+## Contributions
+
+We welcome suggestions for improvement. Please feel free to open an issue or
+send a pull request.
+
+You can copy paste the next section.
+
+# Gemini API Coding Guidelines (Python)
+
+You are a Gemini API coding expert. Help me with writing code using the Gemini
+API calling the official libraries and SDKs.
+
+Please follow the following guidelines when generating code.
+
+You can find the official SDK documentation and code samples here:
+https://ai.google.dev/gemini-api/docs
+
+## Golden Rule: Use the Correct and Current SDK
+
+Always use the Google GenAI SDK to call the Gemini models, which became the
+standard library for all Gemini API interactions as of 2025. Do not use legacy
+libraries and SDKs.
+
+-   **Library Name:** Google GenAI SDK
+-   **Python Package:** `google-genai`
+-   **Legacy Library**: (`google-generativeai`) is deprecated.
+
+**Installation:**
+
+-   **Incorrect:** `pip install google-generativeai`
+-   **Incorrect:** `pip install google-ai-generativelanguage`
+-   **Correct:** `pip install google-genai`
+
+**APIs and Usage:**
+
+-   **Incorrect:** `import google.generativeai as genai`-> **Correct:** `from
+    google import genai`
+-   **Incorrect:** `from google.ai import generativelanguage_v1`  ->
+    **Correct:** `from google import genai`
+-   **Incorrect:** `from google.generativeai` -> **Correct:** `from google
+    import genai`
+-   **Incorrect:** `from google.generativeai import types` -> **Correct:** `from
+    google.genai import types`
+-   **Incorrect:** `import google.generativeai as genai` -> **Correct:** `from
+    google import genai`
+-   **Incorrect:** `genai.configure(api_key=...)` -> **Correct:** `client =
+    genai.Client(api_key='...')`
+-   **Incorrect:** `model = genai.GenerativeModel(...)`
+-   **Incorrect:** `model.generate_content(...)` -> **Correct:**
+    `client.models.generate_content(...)`
+-   **Incorrect:** `response = model.generate_content(..., stream=True)` ->
+    **Correct:** `client.models.generate_content_stream(...)`
+-   **Incorrect:** `genai.GenerationConfig(...)` -> **Correct:**
+    `types.GenerateContentConfig(...)`
+-   **Incorrect:** `safety_settings={...}` -> **Correct:** Use `safety_settings`
+    inside a `GenerateContentConfig` object.
+-   **Incorrect:** `from google.api_core.exceptions import GoogleAPIError` ->
+    **Correct:** `from google.genai.errors import APIError`
+-   **Incorrect:** `types.ResponseModality.TEXT`
+
+## Initialization and API key
+
+The `google-genai` library requires creating a client object for all API calls.
+
+-   Always use `client = genai.Client()` to create a client object.
+-   Set `GEMINI_API_KEY` environment variable, which will be picked up
+    automatically.
+
+## Models
+
+-   By default, use the following models when using `google-genai`:
+    -   **General Text & Multimodal Tasks:** `gemini-2.5-flash`
+    -   **Coding and Complex Reasoning Tasks:** `gemini-3-pro-preview`
+    -   **Low Latency & High Volume Tasks:** `gemini-2.5-flash-lite`
+    -   **Fast Image Generation and Editing:** `gemini-2.5-flash-image` (aka Nano Banana)
+    -   **High-Quality Image Generation and Editing:** `gemini-3-pro-image-preview` (aka Nano Banana Pro)
+    -   **High-Fidelity Video Generation:** `veo-3.0-generate-001` or `veo-3.1-generate-preview`
+    -   **Fast Video Generation:** `veo-3.0-fast-generate-001` or `veo-3.1-fast-generate-preview`
+    -   **Advanced Video Editing Tasks:** `veo-3.1-generate-preview`
+
+-   It is also acceptable to use following models if explicitly requested by the
+    user:
+    -   **Gemini 2.0 Series**: `gemini-2.0-flash`, `gemini-2.0-flash-lite`
+
+-   Do not use the following deprecated models (or their variants like
+    `gemini-1.5-flash-latest`):
+    -   **Prohibited:** `gemini-1.5-flash`
+    -   **Prohibited:** `gemini-1.5-pro`
+    -   **Prohibited:** `gemini-pro`
+
+## Basic Inference (Text Generation)
+
+Here's how to generate a response from a text prompt.
+
+```python
+from google import genai
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='why is the sky blue?',
+)
+
+print(response.text) # output is often markdown
+```
+
+Multimodal inputs are supported by passing a PIL Image in the `contents` list:
+
+```python
+from google import genai
+from PIL import Image
+
+client = genai.Client()
+
+image = Image.open(img_path)
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents=[image, 'explain that image'],
+)
+
+print(response.text) # The output often is markdown
+```
+
+You can also use `Part.from_bytes` type to pass a variety of data types (images,
+audio, video, pdf).
+
+```python
+from google.genai import types
+
+with open('path/to/small-sample.jpg', 'rb') as f:
+    image_bytes = f.read()
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents=[
+        types.Part.from_bytes(
+            data=image_bytes,
+            mime_type='image/jpeg',
+        ),
+        'Caption this image.'
+    ]
+)
+
+print(response.text)
+```
+
+For larger files, use `client.files.upload`:
+
+```python
+f = client.files.upload(file=img_path)
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents=[f, 'can you describe this image?']
+)
+```
+
+You can delete files after use like this:
+
+```python
+myfile = client.files.upload(file='path/to/sample.mp3')
+client.files.delete(name=myfile.name)
+```
+
+## Additional Capabilities and Configurations
+
+Below are examples of advanced configurations.
+
+### Thinking
+
+Gemini 2.5 series models support thinking, which is on by default for
+`gemini-2.5-flash`. It can be adjusted by using `thinking_budget` setting.
+Setting it to zero turns thinking off, and will reduce latency.
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='What is AI?',
+    config=types.GenerateContentConfig(
+        thinking_config=types.ThinkingConfig(
+            thinking_budget=0
+        )
+    )
+)
+```
+
+IMPORTANT NOTES:
+
+-   Minimum thinking budget for `gemini-2.5-pro` is `128` and thinking can not
+    be turned off for that model.
+-   No models (apart from Gemini 2.5 series) support thinking or thinking
+    budgets APIs. Do not try to adjust thinking budgets other models (such as
+    `gemini-2.0-flash` or `gemini-2.0-pro`) otherwise it will cause syntax
+    errors.
+
+### System instructions
+
+Use system instructions to guide model's behavior.
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+config = types.GenerateContentConfig(
+    system_instruction='You are a pirate',
+)
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    config=config,
+)
+
+print(response.text)
+```
+
+### Hyperparameters
+
+You can also set `temperature` or `max_output_tokens` within
+`types.GenerateContentConfig`
+**Avoid** setting `max_output_tokens`, `topP`, `topK` unless explicitly
+requested by the user.
+
+### Safety configurations
+
+Avoid setting safety configurations unless explicitly requested by the user. If
+explicitly asked for by the user, here is a sample API:
+
+```python
+from google import genai
+from google.genai import types
+from PIL import Image
+
+client = genai.Client()
+
+img = Image.open('/path/to/img')
+response = client.models.generate_content(
+    model='gemini-2.0-flash',
+    contents=['Do these look store-bought or homemade?', img],
+    config=types.GenerateContentConfig(
+        safety_settings=[
+            types.SafetySetting(
+                category=types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
+                threshold=types.HarmBlockThreshold.BLOCK_LOW_AND_ABOVE,
+            ),
+        ]
+    )
+)
+
+print(response.text)
+```
+
+### Streaming
+
+It is possible to stream responses to reduce user perceived latency:
+
+```python
+from google import genai
+
+client = genai.Client()
+
+response = client.models.generate_content_stream(
+    model='gemini-2.5-flash',
+    contents=['Explain how AI works']
+)
+for chunk in response:
+    print(chunk.text, end='')
+```
+
+### Chat
+
+For multi-turn conversations, use the `chats` service to maintain conversation
+history.
+
+```python
+from google import genai
+
+client = genai.Client()
+chat = client.chats.create(model='gemini-2.5-flash')
+
+response = chat.send_message('I have 2 dogs in my house.')
+print(response.text)
+
+response = chat.send_message('How many paws are in my house?')
+print(response.text)
+
+for message in chat.get_history():
+    print(f'role - {message.role}', end=': ')
+    print(message.parts[0].text)
+```
+
+### Structured outputs
+
+Use structured outputs to force the model to return a response that conforms to
+a specific Pydantic schema.
+
+```python
+from google import genai
+from google.genai import types
+from pydantic import BaseModel
+
+client = genai.Client()
+
+# Define the desired output structure using Pydantic
+class Recipe(BaseModel):
+    recipe_name: str
+    description: str
+    ingredients: list[str]
+    steps: list[str]
+
+# Request the model to populate the schema
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='Provide a classic recipe for chocolate chip cookies.',
+    config=types.GenerateContentConfig(
+        response_mime_type='application/json',
+        response_schema=Recipe,
+    ),
+)
+
+# The response.text will be a valid JSON string matching the Recipe schema
+print(response.text)
+```
+
+#### Function Calling (Tools)
+
+You can provide the model with tools (functions) it can use to bring in external
+information to answer a question or act on a request outside the model.
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+# Define a function that the model can call (to access external information)
+def get_current_weather(city: str) -> str:
+    """Returns the current weather in a given city. For this example, it's hardcoded."""
+    if 'boston' in city.lower():
+        return 'The weather in Boston is 15°C and sunny.'
+    else:
+        return f'Weather data for {city} is not available.'
+
+# Make the function available to the model as a tool
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='What is the weather like in Boston?',
+    config=types.GenerateContentConfig(
+        tools=[get_current_weather]
+    ),
+)
+# The model may respond with a request to call the function
+if response.function_calls:
+    print('Function calls requested by the model:')
+    for function_call in response.function_calls:
+        print(f'- Function: {function_call.name}')
+        print(f'- Args: {dict(function_call.args)}')
+else:
+    print('The model responded directly:')
+    print(response.text)
+```
+
+### Generate Images
+
+Here's how to generate images using the Nano Banana models. Start with the
+Gemini 2.5 Flash image (Nano Banana) model as it should cover most use-cases.
+
+```python
+from google import genai
+from google.genai import types
+from PIL import Image
+
+prompt =  "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model="gemini-2.5-flash-image",
+    contents=prompt,
+)
+
+for part in response.parts:
+    if part.text is not None:
+        print(part.text)
+    elif part.inline_data is not None:
+        image = part.as_image()
+        image.save("generated_image.png")
+```
+
+Upgrade to the Gemini 3 Pro image (Nano Banana Pro) model if the user requests
+high-resolution images or needs real-time information using the Google Search tool.
+
+```python
+from google import genai
+from google.genai import types
+from PIL import Image
+
+prompt = "Visualize the current weather forecast for the next 5 days in San Francisco as a clean, modern weather chart. Add a visual on what I should wear each day"
+aspect_ratio = "16:9" # "1:1","2:3","3:2","3:4","4:3","4:5","5:4","9:16","16:9","21:9"
+resolution = "1K" # "1K", "2K", "4K"
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model="gemini-3-pro-image-preview",
+    contents=prompt,
+    config=types.GenerateContentConfig(
+        image_config=types.ImageConfig(
+            aspect_ratio=aspect_ratio,
+            image_size=resolution
+        ),
+        tools=[{"google_search": {}}]
+    )
+)
+
+for part in response.parts:
+    if part.text is not None:
+        print(part.text)
+    elif image:= part.as_image():
+        image.save("weather.png")
+```
+
+### Edit images
+
+Editing images is better done using the Gemini native image generation model,
+and it is recommended to use chat mode. Configs are not supported in this model
+(except modality).
+
+```python
+from google import genai
+from PIL import Image
+from io import BytesIO
+
+client = genai.Client()
+
+prompt = """
+Create a picture of my cat eating a nano-banana in a fancy restaurant under the gemini constellation
+"""
+image = Image.open('/path/to/image.png')
+
+# Create the chat
+chat = client.chats.create(model='gemini-2.5-flash-image')
+# Send the image and ask for it to be edited
+response = chat.send_message([prompt, image])
+
+# Get the text and the image generated
+for i, part in enumerate(response.candidates[0].content.parts):
+    if part.text is not None:
+        print(part.text)
+    elif part.inline_data is not None:
+        image = part.as_image()
+        image.save(f'generated_image_{i}.png') # Multiple images can be generated
+
+# Continue iterating
+chat.send_message('Can you make it a bananas foster?')
+```
+
+### Generate Videos
+
+Here's how to generate videos using the Veo models. Usage of Veo can be costly,
+so after generating code for it, give user a heads up to check pricing for Veo.
+Start with the fast model since the result quality is usually sufficient, and
+swap to the larger model if needed.
+
+```python
+import time
+from google import genai
+from google.genai import types
+from PIL import Image
+
+client = genai.Client()
+
+image = Image.open('path/to/image.png') # Optional
+
+operation = client.models.generate_videos(
+    model='veo-3.0-fast-generate-001',
+    prompt='Panning wide shot of a calico kitten sleeping in the sunshine',
+    image=image,
+    config=types.GenerateVideosConfig(
+        person_generation='dont_allow',  # 'dont_allow' or 'allow_adult'
+        aspect_ratio='16:9',  # '16:9' or '9:16'
+        number_of_videos=1, # supported value is 1-4, use 1 by default
+        duration_seconds=8, # supported value is 5-8
+    ),
+)
+
+while not operation.done:
+    time.sleep(20)
+    operation = client.operations.get(operation)
+
+for n, generated_video in enumerate(operation.response.generated_videos):
+    client.files.download(file=generated_video.video) # just file=, no need for path= as it doesn't save yet
+    generated_video.video.save(f'video{n}.mp4')  # saves the video
+```
+
+### Search Grounding
+
+Google Search can be used as a tool for grounding queries that with up to date
+information from the web.
+
+**Correct**
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='What was the score of the latest Olympique Lyonais game?',
+    config=types.GenerateContentConfig(
+        tools=[
+            types.Tool(google_search=types.GoogleSearch())
+        ]
+    ),
+)
+
+# Response
+print(f'Response:\n {response.text}')
+# Search details
+print(f'Search Query: {response.candidates[0].grounding_metadata.web_search_queries}')
+# Urls used for grounding
+print(f"Search Pages: {', '.join([site.web.title for site in response.candidates[0].grounding_metadata.grounding_chunks])}")
+```
+
+The output `response.text` will likely not be in JSON format, do not attempt to
+parse it as JSON.
+
+### Content and Part Hierarchy
+
+While the simpler API call is often sufficient, you may run into scenarios where
+you need to work directly with the underlying `Content` and `Part` objects for
+more explicit control. These are the fundamental building blocks of the
+`generate_content` API.
+
+For instance, the following simple API call:
+
+```python
+from google import genai
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents='How does AI work?'
+)
+print(response.text)
+```
+
+is effectively a shorthand for this more explicit structure:
+
+```python
+from google import genai
+from google.genai import types
+
+client = genai.Client()
+
+response = client.models.generate_content(
+    model='gemini-2.5-flash',
+    contents=[
+        types.Content(role='user', parts=[types.Part.from_text(text='How does AI work?')]),
+    ]
+)
+print(response.text)
+```
+
+## Other APIs
+
+The list of APIs and capabilities above are not comprehensive. If users ask you
+to generate code for a capability not provided above, refer them to
+ai.google.dev/gemini-api/docs.
+
+## Useful Links
+
+-   Documentation: ai.google.dev/gemini-api/docs
+-   API Keys and Authentication: ai.google.dev/gemini-api/docs/api-key
+-   Models: ai.google.dev/models
+-   API Pricing: ai.google.dev/pricing
+-   Rate Limits: ai.google.dev/rate-limits
diff --git a/src/app/api/feeds/[id]/route.ts b/src/app/api/feeds/[id]/route.ts
new file mode 100644
index 00000000..489fe9a7
--- /dev/null
+++ b/src/app/api/feeds/[id]/route.ts
@@ -0,0 +1,26 @@
+import { NextResponse } from 'next/server';
+import { prisma } from '@/lib/db';
+
+// DELETE /api/feeds/[id] - Delete a feed
+export async function DELETE(
+  request: Request,
+  { params }: { params: Promise<{ id: string }> }
+) {
+  try {
+    const { id } = await params;
+    const feedId = parseInt(id);
+
+    if (isNaN(feedId)) {
+      return NextResponse.json({ error: 'Invalid ID' }, { status: 400 });
+    }
+
+    await prisma.feed.delete({
+      where: { id: feedId },
+    });
+
+    return NextResponse.json({ success: true });
+  } catch (error) {
+    console.error("Error deleting feed:", error);
+    return NextResponse.json({ error: 'Failed to delete feed' }, { status: 500 });
+  }
+}
diff --git a/src/app/api/feeds/route.ts b/src/app/api/feeds/route.ts
new file mode 100644
index 00000000..a2300660
--- /dev/null
+++ b/src/app/api/feeds/route.ts
@@ -0,0 +1,51 @@
+import { NextResponse } from 'next/server';
+import { prisma } from '@/lib/db';
+import Parser from 'rss-parser';
+
+const parser = new Parser();
+
+// GET /api/feeds - List all feeds
+export async function GET() {
+  try {
+    const feeds = await prisma.feed.findMany({
+      orderBy: { createdAt: 'desc' }
+    });
+    return NextResponse.json(feeds);
+  } catch (error) {
+    console.error("Error fetching feeds:", error);
+    return NextResponse.json({ error: 'Failed to fetch feeds' }, { status: 500 });
+  }
+}
+
+// POST /api/feeds - Add a new feed
+export async function POST(request: Request) {
+  try {
+    const body = await request.json();
+    const { url } = body;
+
+    if (!url) {
+      return NextResponse.json({ error: 'URL is required' }, { status: 400 });
+    }
+
+    // Validate RSS URL and extract title
+    let feedTitle = 'Unknown Feed';
+    try {
+      const parsed = await parser.parseURL(url);
+      feedTitle = parsed.title || 'Unknown Feed';
+    } catch (e) {
+      return NextResponse.json({ error: 'Invalid RSS URL' }, { status: 400 });
+    }
+
+    const feed = await prisma.feed.create({
+      data: {
+        url,
+        title: feedTitle,
+      },
+    });
+
+    return NextResponse.json(feed, { status: 201 });
+  } catch (error) {
+    console.error("Error adding feed:", error);
+    return NextResponse.json({ error: 'Failed to add feed' }, { status: 500 });
+  }
+}
diff --git a/src/app/api/podcasts/generate/route.ts b/src/app/api/podcasts/generate/route.ts
new file mode 100644
index 00000000..93d0cc50
--- /dev/null
+++ b/src/app/api/podcasts/generate/route.ts
@@ -0,0 +1,61 @@
+import { NextResponse } from 'next/server';
+import { prisma } from '@/lib/db';
+import { fetchLatestArticles } from '@/lib/services/rss';
+import { generatePodcastScript } from '@/lib/services/gemini';
+import { synthesizeSpeech } from '@/lib/services/tts';
+import { concatAudioSegments } from '@/lib/services/audio';
+
+// POST /api/podcasts/generate - Generate a new podcast
+export async function POST() {
+  try {
+    // 1. Fetch Active Feeds
+    const feeds = await prisma.feed.findMany();
+    if (feeds.length === 0) {
+      return NextResponse.json({ error: 'No feeds configured' }, { status: 400 });
+    }
+
+    // 2. Fetch Latest Articles
+    console.log("Fetching articles...");
+    const articles = await fetchLatestArticles(feeds);
+    if (articles.length === 0) {
+        return NextResponse.json({ message: 'No new articles found in the last 24 hours.' }, { status: 200 });
+    }
+
+    // 3. Summarize with Gemini
+    console.log("Generating script...");
+    const script = await generatePodcastScript(articles);
+    
+    // 4. Synthesize Speech
+    console.log("Synthesizing speech...");
+    const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
+    const mainAudioFilename = `body-${timestamp}.mp3`;
+    const mainAudioPath = await synthesizeSpeech(script, mainAudioFilename);
+
+    // 5. Concatenate (Intro + Body + Outro) - Ideally fetch these paths or generate them
+    // For now, let's just use the body as the podcast or assume placeholders exist.
+    // To make it robust without existing assets, we will just use the body. 
+    // If we had assets: await concatAudioSegments(['intro.mp3', mainAudioPath, 'outro.mp3'], finalFilename);
+    
+    // NOTE: Implementing full intro/outro concat requires valid intro/outro files.
+    // For this MVP, we will use the synthesized body directly as the podcast file.
+    // If you want to add Intro/Outro later, ensure the files exist in public/assets/
+    
+    const finalAudioPath = mainAudioPath; 
+    
+    // 6. Save to DB
+    const podcast = await prisma.podcast.create({
+      data: {
+        title: `Daily News - ${new Date().toLocaleDateString()}`,
+        filePath: finalAudioPath,
+        duration: 0, // We would need to read the file to get duration, skipping for now
+        summary: script, // Storing the script as summary
+      },
+    });
+
+    return NextResponse.json(podcast, { status: 201 });
+
+  } catch (error) {
+    console.error("Error generating podcast:", error);
+    return NextResponse.json({ error: 'Failed to generate podcast' }, { status: 500 });
+  }
+}
diff --git a/src/app/api/podcasts/route.ts b/src/app/api/podcasts/route.ts
new file mode 100644
index 00000000..1df6b52e
--- /dev/null
+++ b/src/app/api/podcasts/route.ts
@@ -0,0 +1,15 @@
+import { NextResponse } from 'next/server';
+import { prisma } from '@/lib/db';
+
+// GET /api/podcasts - List all podcasts
+export async function GET() {
+  try {
+    const podcasts = await prisma.podcast.findMany({
+      orderBy: { createdAt: 'desc' }
+    });
+    return NextResponse.json(podcasts);
+  } catch (error) {
+    console.error("Error fetching podcasts:", error);
+    return NextResponse.json({ error: 'Failed to fetch podcasts' }, { status: 500 });
+  }
+}
diff --git a/src/app/favicon.ico b/src/app/favicon.ico
new file mode 100644
index 00000000..718d6fea
Binary files /dev/null and b/src/app/favicon.ico differ
diff --git a/src/app/globals.css b/src/app/globals.css
new file mode 100644
index 00000000..a2dc41ec
--- /dev/null
+++ b/src/app/globals.css
@@ -0,0 +1,26 @@
+@import "tailwindcss";
+
+:root {
+  --background: #ffffff;
+  --foreground: #171717;
+}
+
+@theme inline {
+  --color-background: var(--background);
+  --color-foreground: var(--foreground);
+  --font-sans: var(--font-geist-sans);
+  --font-mono: var(--font-geist-mono);
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    --background: #0a0a0a;
+    --foreground: #ededed;
+  }
+}
+
+body {
+  background: var(--background);
+  color: var(--foreground);
+  font-family: Arial, Helvetica, sans-serif;
+}
diff --git a/src/app/layout.tsx b/src/app/layout.tsx
new file mode 100644
index 00000000..f7fa87eb
--- /dev/null
+++ b/src/app/layout.tsx
@@ -0,0 +1,34 @@
+import type { Metadata } from "next";
+import { Geist, Geist_Mono } from "next/font/google";
+import "./globals.css";
+
+const geistSans = Geist({
+  variable: "--font-geist-sans",
+  subsets: ["latin"],
+});
+
+const geistMono = Geist_Mono({
+  variable: "--font-geist-mono",
+  subsets: ["latin"],
+});
+
+export const metadata: Metadata = {
+  title: "Create Next App",
+  description: "Generated by create next app",
+};
+
+export default function RootLayout({
+  children,
+}: Readonly<{
+  children: React.ReactNode;
+}>) {
+  return (
+    <html lang="en">
+      <body
+        className={`${geistSans.variable} ${geistMono.variable} antialiased`}
+      >
+        {children}
+      </body>
+    </html>
+  );
+}
diff --git a/src/app/page.tsx b/src/app/page.tsx
new file mode 100644
index 00000000..baf3a042
--- /dev/null
+++ b/src/app/page.tsx
@@ -0,0 +1,86 @@
+'use client';
+
+import { useState } from 'react';
+import Image from 'next/image';
+import axios from 'axios';
+import { Mic, Loader2 } from 'lucide-react';
+import FeedManager from '@/components/FeedManager';
+import PodcastPlayer from '@/components/PodcastPlayer';
+
+export default function Home() {
+  const [generating, setGenerating] = useState(false);
+  const [refreshTrigger, setRefreshTrigger] = useState(0);
+
+  const handleGenerate = async () => {
+    setGenerating(true);
+    try {
+      await axios.post('/api/podcasts/generate');
+      setRefreshTrigger(prev => prev + 1); // Refresh podcast list
+    } catch (error: any) {
+      console.error(error);
+      alert(error.response?.data?.error || 'Failed to generate podcast. Make sure you have feeds added.');
+    } finally {
+      setGenerating(false);
+    }
+  };
+
+  return (
+    <main className="min-h-screen bg-gray-50 pb-20">
+      {/* Hero Section */}
+      <div className="relative h-96 w-full bg-slate-900 overflow-hidden">
+        <div className="absolute inset-0 opacity-60">
+            {/* Make sure public/hero.png exists or this will fail gracefully */}
+            <Image 
+                src="/hero.png" 
+                alt="AI News Anchor" 
+                fill 
+                style={{ objectFit: 'cover' }}
+                priority
+            />
+        </div>
+        <div className="absolute inset-0 bg-gradient-to-t from-gray-900 to-transparent"></div>
+        <div className="relative z-10 container mx-auto px-4 h-full flex flex-col justify-end pb-12">
+            <h1 className="text-4xl md:text-6xl font-extrabold text-white mb-4 tracking-tight">
+                Your Daily <span className="text-blue-400">AI Briefing</span>
+            </h1>
+            <p className="text-xl text-gray-200 max-w-2xl">
+                Personalized news podcasts generated from your favorite RSS feeds, powered by Gemini and Google Cloud Chirp.
+            </p>
+        </div>
+      </div>
+
+      <div className="container mx-auto px-4 py-8">
+        
+        {/* Main Action Area */}
+        <div className="mb-12 flex justify-center">
+            <button
+                onClick={handleGenerate}
+                disabled={generating}
+                className={`
+                    relative group overflow-hidden px-8 py-4 rounded-full font-bold text-lg shadow-xl transition-all transform hover:scale-105 active:scale-95
+                    ${generating ? 'bg-gray-400 cursor-not-allowed' : 'bg-gradient-to-r from-blue-600 to-purple-600 hover:from-blue-500 hover:to-purple-500 text-white'}
+                `}
+            >
+                <div className="flex items-center gap-3">
+                    {generating ? (
+                        <>
+                            <Loader2 className="animate-spin" /> Generating your episode...
+                        </>
+                    ) : (
+                        <>
+                            <Mic /> Generate New Episode
+                        </>
+                    )}
+                </div>
+            </button>
+        </div>
+
+        {/* Content Grid */}
+        <div className="grid md:grid-cols-2 gap-8">
+            <FeedManager />
+            <PodcastPlayer refreshTrigger={refreshTrigger} />
+        </div>
+      </div>
+    </main>
+  );
+}
diff --git a/src/components/FeedManager.tsx b/src/components/FeedManager.tsx
new file mode 100644
index 00000000..735dc040
--- /dev/null
+++ b/src/components/FeedManager.tsx
@@ -0,0 +1,109 @@
+'use client';
+
+import { useState, useEffect } from 'react';
+import { Trash2, Plus, Rss } from 'lucide-react';
+import axios from 'axios';
+
+interface Feed {
+  id: number;
+  url: string;
+  title: string;
+}
+
+export default function FeedManager() {
+  const [feeds, setFeeds] = useState<Feed[]>([]);
+  const [newUrl, setNewUrl] = useState('');
+  const [loading, setLoading] = useState(false);
+  const [error, setError] = useState('');
+
+  const fetchFeeds = async () => {
+    try {
+      const res = await axios.get('/api/feeds');
+      setFeeds(res.data);
+    } catch (err) {
+      console.error(err);
+    }
+  };
+
+  useEffect(() => {
+    fetchFeeds();
+  }, []);
+
+  const addFeed = async (e: React.FormEvent) => {
+    e.preventDefault();
+    if (!newUrl) return;
+    setLoading(true);
+    setError('');
+
+    try {
+      await axios.post('/api/feeds', { url: newUrl });
+      setNewUrl('');
+      fetchFeeds();
+    } catch (err: any) {
+      setError(err.response?.data?.error || 'Failed to add feed');
+    } finally {
+      setLoading(false);
+    }
+  };
+
+  const deleteFeed = async (id: number) => {
+    if (!confirm('Are you sure you want to remove this feed?')) return;
+    try {
+      await axios.delete(`/api/feeds/${id}`);
+      setFeeds(feeds.filter(f => f.id !== id));
+    } catch (err) {
+      console.error(err);
+      alert('Failed to delete feed');
+    }
+  };
+
+  return (
+    <div className="bg-white p-6 rounded-lg shadow-md border border-gray-100">
+      <h2 className="text-xl font-bold mb-4 flex items-center gap-2">
+        <Rss className="w-5 h-5 text-blue-600" />
+        RSS Feeds
+      </h2>
+
+      <form onSubmit={addFeed} className="flex gap-2 mb-6">
+        <input
+          type="url"
+          value={newUrl}
+          onChange={(e) => setNewUrl(e.target.value)}
+          placeholder="https://example.com/rss"
+          className="flex-1 p-2 border border-gray-300 rounded focus:ring-2 focus:ring-blue-500 focus:outline-none"
+          required
+        />
+        <button
+          type="submit"
+          disabled={loading}
+          className="bg-blue-600 text-white px-4 py-2 rounded hover:bg-blue-700 disabled:opacity-50 flex items-center gap-2"
+        >
+          {loading ? 'Adding...' : <><Plus size={18} /> Add</>}
+        </button>
+      </form>
+
+      {error && <p className="text-red-500 text-sm mb-4">{error}</p>}
+
+      <div className="space-y-3">
+        {feeds.length === 0 ? (
+          <p className="text-gray-500 text-center py-4">No feeds added yet.</p>
+        ) : (
+          feeds.map((feed) => (
+            <div key={feed.id} className="flex justify-between items-center p-3 bg-gray-50 rounded hover:bg-gray-100 transition">
+              <div className="overflow-hidden">
+                <h3 className="font-medium truncate">{feed.title}</h3>
+                <p className="text-xs text-gray-500 truncate">{feed.url}</p>
+              </div>
+              <button
+                onClick={() => deleteFeed(feed.id)}
+                className="text-gray-400 hover:text-red-500 p-2"
+              >
+                <Trash2 size={18} />
+              </button>
+            </div>
+          ))
+        )}
+      </div>
+    </div>
+  );
+}
diff --git a/src/components/PodcastPlayer.tsx b/src/components/PodcastPlayer.tsx
new file mode 100644
index 00000000..6da87ac4
--- /dev/null
+++ b/src/components/PodcastPlayer.tsx
@@ -0,0 +1,83 @@
+'use client';
+
+import { useState, useEffect } from 'react';
+import { Play, Calendar, Clock } from 'lucide-react';
+import axios from 'axios';
+
+interface Podcast {
+  id: number;
+  title: string;
+  filePath: string;
+  duration: number;
+  createdAt: string;
+  summary?: string;
+}
+
+interface PodcastPlayerProps {
+    refreshTrigger: number;
+}
+
+export default function PodcastPlayer({ refreshTrigger }: PodcastPlayerProps) {
+  const [podcasts, setPodcasts] = useState<Podcast[]>([]);
+  const [currentPodcast, setCurrentPodcast] = useState<Podcast | null>(null);
+
+  const fetchPodcasts = async () => {
+    try {
+      const res = await axios.get('/api/podcasts');
+      setPodcasts(res.data);
+    } catch (err) {
+      console.error(err);
+    }
+  };
+
+  useEffect(() => {
+    fetchPodcasts();
+  }, [refreshTrigger]);
+
+  return (
+    <div className="bg-white p-6 rounded-lg shadow-md border border-gray-100">
+      <h2 className="text-xl font-bold mb-4 flex items-center gap-2">
+        <Play className="w-5 h-5 text-purple-600" />
+        Your Podcasts
+      </h2>
+
+      {currentPodcast && (
+        <div className="mb-6 p-4 bg-purple-50 rounded-lg border border-purple-100">
+            <h3 className="font-bold text-lg mb-2">{currentPodcast.title}</h3>
+            <audio controls autoPlay src={currentPodcast.filePath} className="w-full" />
+            {currentPodcast.summary && (
+                <details className="mt-2 text-sm text-gray-600">
+                    <summary className="cursor-pointer hover:text-purple-700">View Script Summary</summary>
+                    <p className="mt-2 whitespace-pre-wrap">{currentPodcast.summary}</p>
+                </details>
+            )}
+        </div>
+      )}
+
+      <div className="space-y-3">
+        {podcasts.length === 0 ? (
+          <p className="text-gray-500 text-center py-4">No podcasts generated yet.</p>
+        ) : (
+          podcasts.map((podcast) => (
+            <div 
+                key={podcast.id} 
+                className={`flex justify-between items-center p-3 rounded cursor-pointer transition ${currentPodcast?.id === podcast.id ? 'bg-purple-100 border-purple-200 border' : 'bg-gray-50 hover:bg-gray-100'}`}
+                onClick={() => setCurrentPodcast(podcast)}
+            >
+              <div>
+                <h3 className="font-medium">{podcast.title}</h3>
+                <div className="flex gap-3 text-xs text-gray-500 mt-1">
+                    <span className="flex items-center gap-1"><Calendar size={12}/> {new Date(podcast.createdAt).toLocaleDateString()}</span>
+                    {podcast.duration > 0 && <span className="flex items-center gap-1"><Clock size={12}/> {Math.round(podcast.duration / 60)}m</span>}
+                </div>
+              </div>
+              <button className="text-purple-600 hover:text-purple-800">
+                <Play size={20} fill={currentPodcast?.id === podcast.id ? "currentColor" : "none"} />
+              </button>
+            </div>
+          ))
+        )}
+      </div>
+    </div>
+  );
+}
diff --git a/src/lib/db.ts b/src/lib/db.ts
new file mode 100644
index 00000000..0bcabbcb
--- /dev/null
+++ b/src/lib/db.ts
@@ -0,0 +1,15 @@
+import { PrismaClient } from '@prisma/client'
+
+const prismaClientSingleton = () => {
+  return new PrismaClient()
+}
+
+type PrismaClientSingleton = ReturnType<typeof prismaClientSingleton>
+
+const globalForPrisma = globalThis as unknown as {
+  prisma: PrismaClientSingleton | undefined
+}
+
+export const prisma = globalForPrisma.prisma ?? prismaClientSingleton()
+
+if (process.env.NODE_ENV !== 'production') globalForPrisma.prisma = prisma
\ No newline at end of file
diff --git a/src/lib/services/audio.ts b/src/lib/services/audio.ts
new file mode 100644
index 00000000..831fe5fc
--- /dev/null
+++ b/src/lib/services/audio.ts
@@ -0,0 +1,34 @@
+import ffmpeg from 'fluent-ffmpeg';
+import path from 'path';
+import fs from 'fs';
+
+export async function concatAudioSegments(segments: string[], outputFilename: string): Promise<string> {
+    const publicDir = path.join(process.cwd(), 'public');
+    const outputPath = path.join(publicDir, 'podcasts', outputFilename);
+    
+    // Ensure output directory exists
+    if (!fs.existsSync(path.dirname(outputPath))) {
+        fs.mkdirSync(path.dirname(outputPath), { recursive: true });
+    }
+
+    return new Promise((resolve, reject) => {
+        const command = ffmpeg();
+
+        segments.forEach(segment => {
+             // If segment path starts with /, assume it's relative to public/
+             const fullPath = segment.startsWith('/') ? path.join(publicDir, segment) : segment;
+             command.input(fullPath);
+        });
+
+        command
+            .on('error', (err) => {
+                console.error('An error occurred during audio concatenation: ' + err.message);
+                reject(err);
+            })
+            .on('end', () => {
+                console.log('Merging finished!');
+                resolve(`/podcasts/${outputFilename}`);
+            })
+            .mergeToFile(outputPath, path.join(process.cwd(), '.gemini/tmp'));
+    });
+}
diff --git a/src/lib/services/gemini.ts b/src/lib/services/gemini.ts
new file mode 100644
index 00000000..e16f3047
--- /dev/null
+++ b/src/lib/services/gemini.ts
@@ -0,0 +1,41 @@
+import { GoogleGenerativeAI } from "@google/generative-ai";
+import { Article } from "./rss";
+
+const apiKey = process.env.GOOGLE_AI_API_KEY;
+const genAI = apiKey ? new GoogleGenerativeAI(apiKey) : null;
+
+export async function generatePodcastScript(articles: Article[]): Promise<string> {
+  if (!genAI) {
+      throw new Error("GOOGLE_AI_API_KEY is not set");
+  }
+
+  if (articles.length === 0) {
+      return "There are no news updates for today. Have a wonderful day!";
+  }
+
+  const model = genAI.getGenerativeModel({ model: "gemini-1.5-flash" });
+
+  const articlesText = articles.map(a => `
+    Source: ${a.source}
+    Title: ${a.title}
+    Content: ${a.content}
+  `).join("\n---\n");
+
+  const prompt = `Summarize the following news articles into a cohesive script for a daily news podcast. 
+  Group by topic. Use a conversational, engaging tone suitable for audio. 
+  Do not use special characters or formatting that breaks TTS (Text-to-Speech), like markdown bolding or bullet points. 
+  Keep it natural and fluid.
+  
+  Articles:
+  ${articlesText}`;
+
+  try {
+    const result = await model.generateContent(prompt);
+    const response = await result.response;
+    const text = response.text();
+    return text;
+  } catch (error) {
+    console.error("Error generating podcast script with Gemini:", error);
+    throw new Error("Failed to generate podcast script");
+  }
+}
diff --git a/src/lib/services/rss.ts b/src/lib/services/rss.ts
new file mode 100644
index 00000000..b173e9a1
--- /dev/null
+++ b/src/lib/services/rss.ts
@@ -0,0 +1,40 @@
+import Parser from 'rss-parser';
+
+const parser = new Parser();
+
+export interface Article {
+  title: string;
+  content: string; // or description/summary
+  source: string;
+  pubDate: string;
+}
+
+export async function fetchLatestArticles(feeds: { url: string; title: string }[]): Promise<Article[]> {
+  const articles: Article[] = [];
+  const oneDayAgo = new Date(Date.now() - 24 * 60 * 60 * 1000);
+
+  for (const feed of feeds) {
+    try {
+      const parsedFeed = await parser.parseURL(feed.url);
+      
+      parsedFeed.items.forEach(item => {
+        const pubDate = item.pubDate ? new Date(item.pubDate) : new Date();
+        
+        // Filter articles from the last 24 hours
+        if (pubDate >= oneDayAgo) {
+          articles.push({
+            title: item.title || 'Untitled',
+            content: item.contentSnippet || item.content || item.summary || '',
+            source: feed.title,
+            pubDate: pubDate.toISOString()
+          });
+        }
+      });
+    } catch (error) {
+      console.error(`Error fetching feed ${feed.url}:`, error);
+      // Continue with other feeds even if one fails
+    }
+  }
+
+  return articles;
+}
diff --git a/src/lib/services/tts.ts b/src/lib/services/tts.ts
new file mode 100644
index 00000000..4fb7de4c
--- /dev/null
+++ b/src/lib/services/tts.ts
@@ -0,0 +1,40 @@
+import { TextToSpeechClient } from "@google-cloud/text-to-speech";
+import fs from "fs";
+import util from "util";
+import path from "path";
+
+// Initialize TTS Client
+const client = new TextToSpeechClient();
+
+export async function synthesizeSpeech(text: string, outputFilename: string): Promise<string> {
+  // Construct the request
+  const request = {
+    input: { text: text },
+    // Select the language and SSML voice gender (optional)
+    voice: { languageCode: "en-US", name: "en-US-Chirp-HD-F" }, // Using Chirp model as requested
+    // select the type of audio encoding
+    audioConfig: { audioEncoding: "MP3" as const },
+  };
+
+  try {
+    // Performs the text-to-speech request
+    const [response] = await client.synthesizeSpeech(request);
+    
+    // Write the binary audio content to a local file
+    const writeFile = util.promisify(fs.writeFile);
+    const outputPath = path.join(process.cwd(), 'public', 'podcasts', outputFilename);
+    
+    // Ensure directory exists
+    const dir = path.dirname(outputPath);
+    if (!fs.existsSync(dir)){
+        fs.mkdirSync(dir, { recursive: true });
+    }
+
+    await writeFile(outputPath, response.audioContent as string | Uint8Array, 'binary');
+    console.log(`Audio content written to file: ${outputPath}`);
+    return `/podcasts/${outputFilename}`;
+  } catch (error) {
+    console.error("Error synthesizing speech:", error);
+    throw error;
+  }
+}
diff --git a/tsconfig.json b/tsconfig.json
new file mode 100644
index 00000000..cf9c65d3
--- /dev/null
+++ b/tsconfig.json
@@ -0,0 +1,34 @@
+{
+  "compilerOptions": {
+    "target": "ES2017",
+    "lib": ["dom", "dom.iterable", "esnext"],
+    "allowJs": true,
+    "skipLibCheck": true,
+    "strict": true,
+    "noEmit": true,
+    "esModuleInterop": true,
+    "module": "esnext",
+    "moduleResolution": "bundler",
+    "resolveJsonModule": true,
+    "isolatedModules": true,
+    "jsx": "react-jsx",
+    "incremental": true,
+    "plugins": [
+      {
+        "name": "next"
+      }
+    ],
+    "paths": {
+      "@/*": ["./src/*"]
+    }
+  },
+  "include": [
+    "next-env.d.ts",
+    "**/*.ts",
+    "**/*.tsx",
+    ".next/types/**/*.ts",
+    ".next/dev/types/**/*.ts",
+    "**/*.mts"
+  ],
+  "exclude": ["node_modules"]
+}