docs: migrate to Nextra 4 and Next.js App Router

docs/app/[[...mdxPath]]/page.jsx

@@ -0,0 +1,25 @@
+import { generateStaticParamsFor, importPage } from 'nextra/pages';
+
+import { useMDXComponents } from '../../mdx-components';
+
+export const generateStaticParams = generateStaticParamsFor('mdxPath');
+
+export async function generateMetadata(props) {
+  const params = await props.params;
+  const { metadata } = await importPage(params?.mdxPath);
+  return metadata;
+}
+
+const Wrapper = useMDXComponents().wrapper;
+
+export default async function Page(props) {
+  const params = await props.params;
+  const result = await importPage(params?.mdxPath);
+  const { default: MDXContent, metadata, sourceCode, toc } = result;
+
+  return (
+    <Wrapper metadata={metadata} sourceCode={sourceCode} toc={toc}>
+      <MDXContent {...props} params={params} />
+    </Wrapper>
+  );
+}

docs/app/layout.jsx

@@ -0,0 +1,86 @@
+import Image from 'next/image';
+import { Analytics } from '@vercel/analytics/react';
+import { Banner, Head } from 'nextra/components';
+import { getPageMap } from 'nextra/page-map';
+import { Footer, Layout, Navbar } from 'nextra-theme-docs';
+import 'nextra-theme-docs/style.css';
+
+import CuteLogo from '../public/cute-docsgpt.png';
+import themeConfig from '../theme.config';
+
+const github = 'https://github.com/arc53/DocsGPT';
+
+export const metadata = {
+  title: {
+    default: 'DocsGPT Documentation',
+    template: '%s - DocsGPT Documentation',
+  },
+  description:
+    'Use DocsGPT to chat with your data. DocsGPT is a GPT-powered chatbot that can answer questions about your data.',
+};
+
+const navbar = (
+  <Navbar
+    logo={
+      <div style={{ alignItems: 'center', display: 'flex', gap: '8px' }}>
+        <Image src={CuteLogo} alt="DocsGPT logo" width={28} height={28} />
+        <span style={{ fontWeight: 'bold', fontSize: 18 }}>DocsGPT Docs</span>
+      </div>
+    }
+    projectLink={github}
+    chatLink="https://discord.com/invite/n5BX8dh8rU"
+  />
+);
+
+const footer = (
+  <Footer>
+    <span>MIT {new Date().getFullYear()} © </span>
+    <a href="https://www.docsgpt.cloud/" target="_blank" rel="noreferrer">
+      DocsGPT
+    </a>
+    {' | '}
+    <a href="https://github.com/arc53/DocsGPT" target="_blank" rel="noreferrer">
+      GitHub
+    </a>
+    {' | '}
+    <a href="https://blog.docsgpt.cloud/" target="_blank" rel="noreferrer">
+      Blog
+    </a>
+  </Footer>
+);
+
+export default async function RootLayout({ children }) {
+  return (
+    <html lang="en" dir="ltr" suppressHydrationWarning>
+      <Head>
+        <link
+          rel="apple-touch-icon"
+          sizes="180x180"
+          href="/favicons/apple-touch-icon.png"
+        />
+        <link rel="icon" type="image/png" sizes="32x32" href="/favicons/favicon-32x32.png" />
+        <link rel="icon" type="image/png" sizes="16x16" href="/favicons/favicon-16x16.png" />
+        <link rel="manifest" href="/favicons/site.webmanifest" />
+        <meta httpEquiv="Content-Language" content="en" />
+      </Head>
+      <body>
+        <Layout
+          banner={
+            <Banner storageKey="docs-launch">
+              <div className="flex justify-center items-center gap-2">
+                Welcome to the new DocsGPT docs!
+              </div>
+            </Banner>
+          }
+          navbar={navbar}
+          footer={footer}
+          pageMap={await getPageMap()}
+          {...themeConfig}
+        >
+          {children}
+        </Layout>
+        <Analytics />
+      </body>
+    </html>
+  );
+}

docs/components/DeploymentCards.jsx

@@ -1,3 +1,5 @@
+'use client';
+
 import Image from 'next/image';
 
 const iconMap = {
@@ -117,4 +119,4 @@ export function DeploymentCards({ items }) {
             `}</style>
         </>
     );
-}
+}

docs/components/ToolCards.jsx

@@ -1,3 +1,5 @@
+'use client';
+
 import Image from 'next/image';
 
 const iconMap = {
@@ -114,4 +116,4 @@ export function ToolCards({ items }) {
             `}</style>
         </>
     );
-}
+}

docs/content/Agents/api.mdx

@@ -0,0 +1,342 @@
+---
+title: Interacting with Agents via API
+description: Learn how to programmatically interact with DocsGPT Agents using the streaming and non-streaming API endpoints.
+---
+
+import { Callout, Tabs } from 'nextra/components';
+
+# Interacting with Agents via API
+
+DocsGPT Agents can be accessed programmatically through API endpoints. This page covers:
+
+- Non-streaming answers (`/api/answer`)
+- Streaming answers over SSE (`/stream`)
+- File/image attachments (`/api/store_attachment` + `/api/task_status` + `/stream`)
+
+When you use an agent `api_key`, DocsGPT loads that agent's configuration automatically (prompt, tools, sources, default model). You usually only need to send `question` and `api_key`.
+
+## Base URL
+
+<Callout type="info">
+For DocsGPT Cloud, use `https://gptcloud.arc53.com` as the base URL.
+</Callout>
+
+- Local: `http://localhost:7091`
+- Cloud: `https://gptcloud.arc53.com`
+
+## How Request Resolution Works
+
+DocsGPT resolves your request in this order:
+
+1. If `api_key` is provided, DocsGPT loads the mapped agent and executes with that config.
+2. If `agent_id` is provided (typically with JWT auth), DocsGPT loads that agent if allowed.
+3. If neither is provided, DocsGPT uses request-level fields (`prompt_id`, `active_docs`, `retriever`, etc.).
+
+Authentication:
+
+- Agent API-key flow: include `api_key` in JSON/form payload.
+- JWT flow (if auth enabled): include `Authorization: Bearer <token>`.
+
+## Endpoints
+
+- `POST /api/answer` (non-streaming)
+- `POST /stream` (SSE streaming)
+- `POST /api/store_attachment` (multipart upload)
+- `GET /api/task_status?task_id=...` (Celery task polling)
+
+## Request Parameters
+
+Common request body fields:
+
+| Field | Type | Required | Applies to | Notes |
+| --- | --- | --- | --- | --- |
+| `question` | `string` | Yes | `/api/answer`, `/stream` | User query. |
+| `api_key` | `string` | Usually | `/api/answer`, `/stream` | Recommended for agent API use. Loads agent config from key. |
+| `conversation_id` | `string` | No | `/api/answer`, `/stream` | Continue an existing conversation. |
+| `history` | `string` (JSON-encoded array) | No | `/api/answer`, `/stream` | Used for new conversations. Format: `[{\"prompt\":\"...\",\"response\":\"...\"}]`. |
+| `model_id` | `string` | No | `/api/answer`, `/stream` | Override model for this request. |
+| `save_conversation` | `boolean` | No | `/api/answer`, `/stream` | Default `true`. If `false`, no conversation is persisted. |
+| `passthrough` | `object` | No | `/api/answer`, `/stream` | Dynamic values injected into prompt templates. |
+| `prompt_id` | `string` | No | `/api/answer`, `/stream` | Ignored when `api_key` already defines prompt. |
+| `active_docs` | `string` or `string[]` | No | `/api/answer`, `/stream` | Overrides active docs when not using key-owned source config. |
+| `retriever` | `string` | No | `/api/answer`, `/stream` | Retriever type (for example `classic`). |
+| `chunks` | `number` | No | `/api/answer`, `/stream` | Retrieval chunk count, default `2`. |
+| `isNoneDoc` | `boolean` | No | `/api/answer`, `/stream` | Skip document retrieval. |
+| `agent_id` | `string` | No | `/api/answer`, `/stream` | Alternative to `api_key` when using authenticated user context. |
+
+Streaming-only fields:
+
+| Field | Type | Required | Notes |
+| --- | --- | --- | --- |
+| `attachments` | `string[]` | No | List of attachment IDs from `/api/task_status` success result. |
+| `index` | `number` | No | Update an existing query index. If provided, `conversation_id` is required. |
+
+## Non-Streaming API (`/api/answer`)
+
+`/api/answer` waits for completion and returns one JSON response.
+
+<Callout type="info">
+`attachments` are currently handled through `/stream`. For file/image-attached queries, use the streaming endpoint.
+</Callout>
+
+Response fields:
+
+- `conversation_id`
+- `answer`
+- `sources`
+- `tool_calls`
+- `thought`
+- Optional structured output metadata (`structured`, `schema`) when enabled
+
+### Examples
+
+<Tabs items={['cURL', 'Python', 'JavaScript']}>
+  <Tabs.Tab>
+    ```bash
+    curl -X POST http://localhost:7091/api/answer \
+    -H "Content-Type: application/json" \
+    -d '{"question":"your question here","api_key":"your_agent_api_key"}'
+    ```
+  </Tabs.Tab>
+  <Tabs.Tab>
+    ```python
+    import requests
+
+    API_URL = "http://localhost:7091/api/answer"
+    API_KEY = "your_agent_api_key"
+    QUESTION = "your question here"
+
+    response = requests.post(
+        API_URL,
+        json={"question": QUESTION, "api_key": API_KEY}
+    )
+
+    if response.status_code == 200:
+        print(response.json())
+    else:
+        print(f"Error: {response.status_code}")
+        print(response.text)
+    ```
+  </Tabs.Tab>
+  <Tabs.Tab>
+    ```javascript
+    const apiUrl = 'http://localhost:7091/api/answer';
+    const apiKey = 'your_agent_api_key';
+    const question = 'your question here';
+
+    async function getAnswer() {
+    try {
+        const response = await fetch(apiUrl, {
+        method: 'POST',
+        headers: {
+            'Content-Type': 'application/json',
+        },
+        body: JSON.stringify({ question, api_key: apiKey }),
+        });
+
+        if (!response.ok) {
+        throw new Error(`HTTP error! Status: ${response.status}`);
+        }
+
+        const data = await response.json();
+        console.log(data);
+    } catch (error) {
+        console.error("Failed to fetch answer:", error);
+    }
+    }
+
+    getAnswer();
+    ```
+  </Tabs.Tab>
+</Tabs>
+
+---
+
+## Streaming API (`/stream`)
+
+`/stream` returns a Server-Sent Events (SSE) stream so you can render output token-by-token.
+
+### SSE Event Types
+
+Each `data:` frame is JSON with `type`:
+
+- `answer`: incremental answer chunk
+- `source`: source list/chunks
+- `tool_calls`: tool invocation results/metadata
+- `thought`: reasoning/thought chunk (agent dependent)
+- `structured_answer`: final structured payload (when schema mode is active)
+- `id`: final conversation ID
+- `error`: error message
+- `end`: stream is complete
+
+### Examples
+
+<Tabs items={['cURL', 'Python', 'JavaScript']}>
+  <Tabs.Tab>
+    ```bash
+    curl -X POST http://localhost:7091/stream \
+    -H "Content-Type: application/json" \
+    -H "Accept: text/event-stream" \
+    -d '{"question":"your question here","api_key":"your_agent_api_key"}'
+    ```
+  </Tabs.Tab>
+  <Tabs.Tab>
+    ```python
+    import requests
+    import json
+
+    API_URL = "http://localhost:7091/stream"
+    payload = {
+        "question": "your question here",
+        "api_key": "your_agent_api_key"
+    }
+
+    with requests.post(API_URL, json=payload, stream=True) as r:
+        for line in r.iter_lines():
+            if line:
+                decoded_line = line.decode('utf-8')
+                if decoded_line.startswith('data: '):
+                    try:
+                        data = json.loads(decoded_line[6:])
+                        print(data)
+                    except json.JSONDecodeError:
+                        pass
+    ```
+  </Tabs.Tab>
+  <Tabs.Tab>
+    ```javascript
+    const apiUrl = 'http://localhost:7091/stream';
+    const apiKey = 'your_agent_api_key';
+    const question = 'your question here';
+
+    async function getStream() {
+    try {
+        const response = await fetch(apiUrl, {
+        method: 'POST',
+        headers: {
+            'Content-Type': 'application/json',
+            'Accept': 'text/event-stream'
+        },
+        body: JSON.stringify({ question, api_key: apiKey }),
+        });
+
+        if (!response.ok) {
+        throw new Error(`HTTP error! Status: ${response.status}`);
+        }
+
+        const reader = response.body.getReader();
+        const decoder = new TextDecoder();
+
+        while (true) {
+        const { done, value } = await reader.read();
+        if (done) break;
+
+        const chunk = decoder.decode(value, { stream: true });
+        // Note: This parsing method assumes each chunk contains whole lines.
+        // For a more robust production implementation, buffer the chunks
+        // and process them line by line.
+        const lines = chunk.split('\n');
+        
+        for (const line of lines) {
+            if (line.startsWith('data: ')) {
+            try {
+                const data = JSON.parse(line.substring(6));
+                console.log(data);
+            } catch (e) {
+                console.error("Failed to parse JSON from SSE event:", e);
+            }
+            }
+        }
+        }
+    } catch (error) {
+        console.error("Failed to fetch stream:", error);
+    }
+    }
+
+    getStream();
+    ```
+  </Tabs.Tab>
+</Tabs>
+
+---
+
+## Attachments API (Including Images)
+
+To attach an image (or other file) to a query:
+
+1. Upload file(s) to `/api/store_attachment` (multipart/form-data).
+2. Poll `/api/task_status` until `status=SUCCESS`.
+3. Read `result.attachment_id` from task result.
+4. Send that ID in `/stream` as `attachments: ["..."]`.
+
+<Callout type="warning">
+Attachments are processed asynchronously. Do not call `/stream` with an attachment until its task has finished with `SUCCESS`.
+</Callout>
+
+### Step 1: Upload Attachment
+
+`POST /api/store_attachment`
+
+- Content type: `multipart/form-data`
+- Form fields:
+  - `file` (required, can be repeated for multi-file upload)
+  - `api_key` (optional if JWT is present; useful for API-key-only flows)
+
+Example upload (single image):
+
+```bash
+curl -X POST http://localhost:7091/api/store_attachment \
+  -F "file=@/absolute/path/to/image.png" \
+  -F "api_key=your_agent_api_key"
+```
+
+Possible response (single-file upload):
+
+```json
+{
+  "success": true,
+  "task_id": "34f1cb56-7c7f-4d5f-a973-4ea7e65f7a10",
+  "message": "File uploaded successfully. Processing started."
+}
+```
+
+### Step 2: Poll Task Status
+
+```bash
+curl "http://localhost:7091/api/task_status?task_id=34f1cb56-7c7f-4d5f-a973-4ea7e65f7a10"
+```
+
+When complete:
+
+```json
+{
+  "status": "SUCCESS",
+  "result": {
+    "attachment_id": "67b4f8f2618dc9f19384a9e1",
+    "filename": "image.png",
+    "mime_type": "image/png"
+  }
+}
+```
+
+### Step 3: Attach to `/stream` Request
+
+Use the `attachment_id` in `attachments`.
+
+```bash
+curl -X POST http://localhost:7091/stream \
+  -H "Content-Type: application/json" \
+  -H "Accept: text/event-stream" \
+  -d '{
+    "question": "Describe this image",
+    "api_key": "your_agent_api_key",
+    "attachments": ["67b4f8f2618dc9f19384a9e1"]
+  }'
+```
+
+### Image/Attachment Behavior Notes
+
+- Typical image MIME types supported for native vision flows: `image/png`, `image/jpeg`, `image/jpg`, `image/webp`, `image/gif`.
+- If the selected model/provider does not support a file type natively, DocsGPT falls back to parsed text content.
+- For providers that support images but not native PDF file attachments, DocsGPT can convert PDF pages to images (synthetic PDF support).
+- Attachments are user-scoped. Upload and query must be done under the same user context (same API key owner or same JWT user).

docs/content/_meta.js

@@ -8,8 +8,7 @@ export default {
   "Extensions": "Extensions",
   "https://gptcloud.arc53.com/": {
     "title": "API",
-    "href": "https://gptcloud.arc53.com/",
-    "newWindow": true
+    "href": "https://gptcloud.arc53.com/"
   },
   "Guides": "Guides",
   "changelog": {

docs/mdx-components.jsx

@@ -0,0 +1,8 @@
+import { useMDXComponents as getThemeComponents } from 'nextra-theme-docs';
+
+export function useMDXComponents(components) {
+  return {
+    ...getThemeComponents(),
+    ...components,
+  };
+}

docs/next.config.js

@@ -1,9 +1,9 @@
-const withNextra = require('nextra').default({
-  theme: 'nextra-theme-docs',
-  themeConfig: './theme.config.jsx'
-})
+const nextra = require('nextra').default;
 
-module.exports = withNextra()
-   
-// If you have other Next.js configurations, you can pass them as the parameter:
-// module.exports = withNextra({ /* other next.js config */ })
+const withNextra = nextra({
+  // Nextra v4 config lives in app/layout + theme.config.jsx
+});
+
+module.exports = withNextra({
+  reactStrictMode: true,
+});

docs/package.json

@@ -9,8 +9,8 @@
     "@vercel/analytics": "^1.1.1",
     "docsgpt-react": "^0.5.1",
     "next": "^15.5.9",
-    "nextra": "^3.3.1",
-    "nextra-theme-docs": "^3.3.1",
+    "nextra": "^4.6.1",
+    "nextra-theme-docs": "^4.6.1",
     "react": "^18.2.0",
     "react-dom": "^18.2.0"
   },

docs/pages/Agents/api.mdx

@@ -1,227 +0,0 @@
----
-title: Interacting with Agents via API
-description: Learn how to programmatically interact with DocsGPT Agents using the streaming and non-streaming API endpoints.
----
-
-import { Callout, Tabs } from 'nextra/components';
-
-# Interacting with Agents via API
-
-DocsGPT Agents can be accessed programmatically through a dedicated API, allowing you to integrate their specialized capabilities into your own applications, scripts, and workflows. This guide covers the two primary methods for interacting with an agent: the streaming API for real-time responses and the non-streaming API for a single, consolidated answer.
-
-When you use an API key generated for a specific agent, you do not need to pass `prompt`, `tools` etc. The agent's configuration (including its prompt, selected tools, and knowledge sources) is already associated with its unique API key. 
-
-### API Endpoints
-
-- **Non-Streaming:** `http://localhost:7091/api/answer`
-- **Streaming:** `http://localhost:7091/stream`
-
-<Callout type="info">
-For DocsGPT Cloud, use `https://gptcloud.arc53.com/` as the base URL.
-</Callout>
-
-For more technical details, you can explore the API swagger documentation available for the cloud version or your local instance.
-
----
-
-## Non-Streaming API (`/api/answer`)
-
-This is a standard synchronous endpoint. It waits for the agent to fully process the request and returns a single JSON object with the complete answer. This is the simplest method and is ideal for backend processes where a real-time feed is not required.
-
-### Request
-
--   **Endpoint:** `/api/answer`
--   **Method:** `POST`
--   **Payload:**
-    -   `question` (string, required): The user's query or input for the agent.
-    -   `api_key` (string, required): The unique API key for the agent you wish to interact with.
-    -   `history` (string, optional): A JSON string representing the conversation history, e.g., `[{\"prompt\": \"first question\", \"answer\": \"first answer\"}]`.
-
-### Response
-
-A single JSON object containing:
--   `answer`: The complete, final answer from the agent.
--   `sources`: A list of sources the agent consulted.
--   `conversation_id`: The unique ID for the interaction.
-
-### Examples
-
-<Tabs items={['cURL', 'Python', 'JavaScript']}>
-  <Tabs.Tab>
-    ```bash
-    curl -X POST http://localhost:7091/api/answer \
-    -H "Content-Type: application/json" \
-    -d '{
-        "question": "your question here",
-        "api_key": "your_agent_api_key"
-    }'
-    ```
-  </Tabs.Tab>
-  <Tabs.Tab>
-    ```python
-    import requests
-
-    API_URL = "http://localhost:7091/api/answer"
-    API_KEY = "your_agent_api_key"
-    QUESTION = "your question here"
-
-    response = requests.post(
-        API_URL,
-        json={"question": QUESTION, "api_key": API_KEY}
-    )
-
-    if response.status_code == 200:
-        print(response.json())
-    else:
-        print(f"Error: {response.status_code}")
-        print(response.text)
-    ```
-  </Tabs.Tab>
-  <Tabs.Tab>
-    ```javascript
-    const apiUrl = 'http://localhost:7091/api/answer';
-    const apiKey = 'your_agent_api_key';
-    const question = 'your question here';
-
-    async function getAnswer() {
-    try {
-        const response = await fetch(apiUrl, {
-        method: 'POST',
-        headers: {
-            'Content-Type': 'application/json',
-        },
-        body: JSON.stringify({ question, api_key: apiKey }),
-        });
-
-        if (!response.ok) {
-        throw new Error(`HTTP error! Status: ${response.status}`);
-        }
-
-        const data = await response.json();
-        console.log(data);
-    } catch (error) {
-        console.error("Failed to fetch answer:", error);
-    }
-    }
-
-    getAnswer();
-    ```
-  </Tabs.Tab>
-</Tabs>
-
----
-
-## Streaming API (`/stream`)
-
-The `/stream` endpoint uses Server-Sent Events (SSE) to push data in real-time. This is ideal for applications where you want to display the response as it's being generated, such as in a live chatbot interface.
-
-### Request
-
--   **Endpoint:** `/stream`
--   **Method:** `POST`
--   **Payload:** Same as the non-streaming API.
-
-### Response (SSE Stream)
-
-The stream consists of multiple `data:` events, each containing a JSON object. Your client should listen for these events and process them based on their `type`.
-
-**Event Types:**
--   `answer`: A chunk of the agent's final answer.
--   `source`: A document or source used by the agent.
--   `thought`: A reasoning step from the agent (for ReAct agents).
--   `id`: The unique `conversation_id` for the interaction.
--   `error`: An error message.
--   `end`: A final message indicating the stream has concluded.
-
-### Examples
-
-<Tabs items={['cURL', 'Python', 'JavaScript']}>
-  <Tabs.Tab>
-    ```bash
-    curl -X POST http://localhost:7091/stream \
-    -H "Content-Type: application/json" \
-    -H "Accept: text/event-stream" \
-    -d '{
-        "question": "your question here",
-        "api_key": "your_agent_api_key"
-    }'
-    ```
-  </Tabs.Tab>
-  <Tabs.Tab>
-    ```python
-    import requests
-    import json
-
-    API_URL = "http://localhost:7091/stream"
-    payload = {
-        "question": "your question here",
-        "api_key": "your_agent_api_key"
-    }
-
-    with requests.post(API_URL, json=payload, stream=True) as r:
-        for line in r.iter_lines():
-            if line:
-                decoded_line = line.decode('utf-8')
-                if decoded_line.startswith('data: '):
-                    try:
-                        data = json.loads(decoded_line[6:])
-                        print(data)
-                    except json.JSONDecodeError:
-                        pass
-    ```
-  </Tabs.Tab>
-  <Tabs.Tab>
-    ```javascript
-    const apiUrl = 'http://localhost:7091/stream';
-    const apiKey = 'your_agent_api_key';
-    const question = 'your question here';
-
-    async function getStream() {
-    try {
-        const response = await fetch(apiUrl, {
-        method: 'POST',
-        headers: {
-            'Content-Type': 'application/json',
-            'Accept': 'text/event-stream'
-        },
-        // Corrected line: 'apiKey' is changed to 'api_key'
-        body: JSON.stringify({ question, api_key: apiKey }),
-        });
-
-        if (!response.ok) {
-        throw new Error(`HTTP error! Status: ${response.status}`);
-        }
-
-        const reader = response.body.getReader();
-        const decoder = new TextDecoder();
-
-        while (true) {
-        const { done, value } = await reader.read();
-        if (done) break;
-
-        const chunk = decoder.decode(value, { stream: true });
-        // Note: This parsing method assumes each chunk contains whole lines.
-        // For a more robust production implementation, buffer the chunks
-        // and process them line by line.
-        const lines = chunk.split('\n');
-        
-        for (const line of lines) {
-            if (line.startsWith('data: ')) {
-            try {
-                const data = JSON.parse(line.substring(6));
-                console.log(data);
-            } catch (e) {
-                console.error("Failed to parse JSON from SSE event:", e);
-            }
-            }
-        }
-        }
-    } catch (error) {
-        console.error("Failed to fetch stream:", error);
-    }
-    }
-
-    getStream();
-    ```
-  </Tabs.Tab>
-</Tabs>

docs/pages/_app.jsx

@@ -1,10 +0,0 @@
-import { DocsGPTWidget } from "docsgpt-react";
-
-export default function MyApp({ Component, pageProps }) {
-  return (
-    <>
-      <Component {...pageProps} />
-        <DocsGPTWidget showSources={true} apiKey="5d8270cb-735f-484e-9dc9-5b407f24e652" theme="dark" size="medium" />
-    </>
-  )
-}

docs/theme.config.jsx

@@ -1,161 +1,18 @@
-import Image from 'next/image'
-import { Analytics } from '@vercel/analytics/react';
-
 const github = 'https://github.com/arc53/DocsGPT';
 
-
-
-
-import { useConfig, useTheme } from 'nextra-theme-docs';
-import CuteLogo from './public/cute-docsgpt.png';
-const Logo = ({ height, width }) => {
-  const { theme } = useTheme();
-  return (
-    <div style={{ alignItems: 'center', display: 'flex', gap: '8px' }}>
-       <Image src={CuteLogo} alt="DocsGPT logo" width={width} height={height} />
-
-      <span style={{ fontWeight: 'bold', fontSize: 18 }}>DocsGPT Docs</span>
-
-
-    </div>
-  );
-};
-
 const config = {
   docsRepositoryBase: `${github}/blob/main/docs`,
-  chat: {
-    link: 'https://discord.com/invite/n5BX8dh8rU',
-  },
-  banner: {
-    key: 'docs-launch',
-    text: (
-      <div className="flex justify-center items-center gap-2">
-        Welcome to the new DocsGPT 🦖 docs! 👋
-      </div>
-    ),
-  },
-  toc: {
-    float: true,
-  },
-  project: {
-    link: github,
-  },
   darkMode: true,
   nextThemes: {
     defaultTheme: 'dark',
   },
-  primaryHue: {
-    dark: 207,
-    light: 212,
-  },
-  footer: {
-    text: (
-      <div>
-        <span>MIT {new Date().getFullYear()} © </span>
-        <a href="https://www.docsgpt.cloud/" target="_blank">
-          DocsGPT
-        </a>
-        {' | '}
-        <a href="https://github.com/arc53/DocsGPT" target="_blank">
-          GitHub
-        </a>
-        {' | '}
-        <a href="https://blog.docsgpt.cloud/" target="_blank">
-          Blog
-        </a>
-      </div>
-    ),
-  },
-  editLink: {
-    content: 'Edit this page on GitHub',
-  },
-  logo() {
-    return (
-      <div className="flex items-center gap-2">
-        <Logo width={28} height={28} />
-      </div>
-    );
-  },
-  useNextSeoProps() {
-    return {
-      titleTemplate: `%s - DocsGPT Documentation`,
-    };
-  },
-
-  head() {
-    const { frontMatter } = useConfig();
-    const { theme } = useTheme();
-    const title = frontMatter?.title || 'Chat with your data with DocsGPT';
-    const description =
-      frontMatter?.description ||
-      'Use DocsGPT to chat with your data. DocsGPT is a GPT powered chatbot that can answer questions about your data.'
-    const image = '/cute-docsgpt.png';
-
-    const composedTitle = `${title} – DocsGPT Documentation`;
-
-    return (
-      <>
-        <link
-          rel="apple-touch-icon"
-          sizes="180x180"
-          href={`/favicons/apple-touch-icon.png`}
-        />
-        <link
-          rel="icon"
-          type="image/png"
-          sizes="32x32"
-          href={`/favicons/favicon-32x32.png`}
-        />
-        <link
-          rel="icon"
-          type="image/png"
-          sizes="16x16"
-          href={`/favicons/favicon-16x16.png`}
-        />
-        <meta name="theme-color" content="#ffffff" />
-        <meta name="msapplication-TileColor" content="#00a300" />
-        <link rel="manifest" href={`/favicons/site.webmanifest`} />
-        <meta httpEquiv="Content-Language" content="en" />
-        <meta name="title" content={composedTitle} />
-        <meta name="description" content={description} />
-
-        <meta name="twitter:card" content="summary_large_image" />
-        <meta name="twitter:site" content="@ATushynski" />
-        <meta name="twitter:image" content={image} />
-
-        <meta property="og:description" content={description} />
-        <meta property="og:title" content={composedTitle} />
-        <meta property="og:image" content={image} />
-        <meta property="og:type" content="website" />
-        <meta
-          name="apple-mobile-web-app-title"
-          content="DocsGPT Documentation"
-        />
-
-      </>
-    );
-  },
   sidebar: {
     defaultMenuCollapseLevel: 1,
-    titleComponent: ({ title, type }) =>
-      type === 'separator' ? (
-        <div className="flex items-center gap-2">
-          <Logo height={10} width={10} />
-          {title}
-            <Analytics />
-        </div>
-
-      ) : (
-        <>{title}
-        <Analytics />
-        </>
-
-      ),
   },
-
-  gitTimestamp: ({ timestamp }) => (
-    <>Last updated on {timestamp.toLocaleDateString()}</>
-  ),
+  toc: {
+    float: true,
+  },
+  editLink: 'Edit this page on GitHub',
 };
 
-export default config;
+export default config;

frontend/.env.development

@@ -3,4 +3,5 @@ VITE_BASE_URL=http://localhost:5173
 VITE_API_HOST=http://127.0.0.1:7091
 VITE_API_STREAMING=true
 VITE_NOTIFICATION_TEXT="What's new in 0.15.0 — Changelog"
-VITE_NOTIFICATION_LINK="https://blog.docsgpt.cloud/docsgpt-0-15-masters-long-term-memory-and-tooling/"
+VITE_NOTIFICATION_LINK="https://blog.docsgpt.cloud/docsgpt-0-15-masters-long-term-memory-and-tooling/"
+VITE_GOOGLE_CLIENT_ID=896376503572-u46l78n8ctgtdr4dlei4u06jv6rbpqc5.apps.googleusercontent.com