mirror of
https://github.com/arc53/DocsGPT.git
synced 2026-02-21 20:01:26 +00:00
docs: migrate to Nextra 4 and Next.js App Router
This commit is contained in:
Alex
25
docs/app/[[...mdxPath]]/page.jsx
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25
docs/app/[[...mdxPath]]/page.jsx
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@@ -0,0 +1,25 @@
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import { generateStaticParamsFor, importPage } from 'nextra/pages';
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import { useMDXComponents } from '../../mdx-components';
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export const generateStaticParams = generateStaticParamsFor('mdxPath');
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export async function generateMetadata(props) {
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const params = await props.params;
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const { metadata } = await importPage(params?.mdxPath);
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return metadata;
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}
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const Wrapper = useMDXComponents().wrapper;
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export default async function Page(props) {
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const params = await props.params;
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const result = await importPage(params?.mdxPath);
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const { default: MDXContent, metadata, sourceCode, toc } = result;
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return (
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<Wrapper metadata={metadata} sourceCode={sourceCode} toc={toc}>
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<MDXContent {...props} params={params} />
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</Wrapper>
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);
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}
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86
docs/app/layout.jsx
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86
docs/app/layout.jsx
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import Image from 'next/image';
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import { Analytics } from '@vercel/analytics/react';
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import { Banner, Head } from 'nextra/components';
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import { getPageMap } from 'nextra/page-map';
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import { Footer, Layout, Navbar } from 'nextra-theme-docs';
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import 'nextra-theme-docs/style.css';
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import CuteLogo from '../public/cute-docsgpt.png';
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import themeConfig from '../theme.config';
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const github = 'https://github.com/arc53/DocsGPT';
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export const metadata = {
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title: {
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default: 'DocsGPT Documentation',
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template: '%s - DocsGPT Documentation',
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},
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description:
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'Use DocsGPT to chat with your data. DocsGPT is a GPT-powered chatbot that can answer questions about your data.',
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};
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const navbar = (
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<Navbar
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logo={
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<div style={{ alignItems: 'center', display: 'flex', gap: '8px' }}>
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<Image src={CuteLogo} alt="DocsGPT logo" width={28} height={28} />
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<span style={{ fontWeight: 'bold', fontSize: 18 }}>DocsGPT Docs</span>
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</div>
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}
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projectLink={github}
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chatLink="https://discord.com/invite/n5BX8dh8rU"
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/>
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);
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const footer = (
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<Footer>
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<span>MIT {new Date().getFullYear()} © </span>
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<a href="https://www.docsgpt.cloud/" target="_blank" rel="noreferrer">
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DocsGPT
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</a>
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{' | '}
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<a href="https://github.com/arc53/DocsGPT" target="_blank" rel="noreferrer">
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GitHub
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</a>
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{' | '}
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<a href="https://blog.docsgpt.cloud/" target="_blank" rel="noreferrer">
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Blog
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</a>
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</Footer>
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);
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export default async function RootLayout({ children }) {
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return (
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<html lang="en" dir="ltr" suppressHydrationWarning>
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<Head>
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<link
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rel="apple-touch-icon"
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sizes="180x180"
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href="/favicons/apple-touch-icon.png"
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/>
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<link rel="icon" type="image/png" sizes="32x32" href="/favicons/favicon-32x32.png" />
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<link rel="icon" type="image/png" sizes="16x16" href="/favicons/favicon-16x16.png" />
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<link rel="manifest" href="/favicons/site.webmanifest" />
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<meta httpEquiv="Content-Language" content="en" />
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</Head>
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<body>
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<Layout
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banner={
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<Banner storageKey="docs-launch">
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<div className="flex justify-center items-center gap-2">
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Welcome to the new DocsGPT docs!
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</div>
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</Banner>
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}
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navbar={navbar}
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footer={footer}
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pageMap={await getPageMap()}
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{...themeConfig}
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>
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{children}
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</Layout>
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<Analytics />
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</body>
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</html>
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);
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}
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@@ -1,3 +1,5 @@
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'use client';
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import Image from 'next/image';
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const iconMap = {
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@@ -117,4 +119,4 @@ export function DeploymentCards({ items }) {
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`}</style>
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</>
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);
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}
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}
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@@ -1,3 +1,5 @@
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'use client';
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import Image from 'next/image';
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const iconMap = {
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@@ -114,4 +116,4 @@ export function ToolCards({ items }) {
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`}</style>
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</>
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);
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}
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}
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342
docs/content/Agents/api.mdx
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342
docs/content/Agents/api.mdx
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@@ -0,0 +1,342 @@
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---
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title: Interacting with Agents via API
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description: Learn how to programmatically interact with DocsGPT Agents using the streaming and non-streaming API endpoints.
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---
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import { Callout, Tabs } from 'nextra/components';
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# Interacting with Agents via API
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DocsGPT Agents can be accessed programmatically through API endpoints. This page covers:
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- Non-streaming answers (`/api/answer`)
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- Streaming answers over SSE (`/stream`)
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- File/image attachments (`/api/store_attachment` + `/api/task_status` + `/stream`)
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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`.
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## Base URL
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<Callout type="info">
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For DocsGPT Cloud, use `https://gptcloud.arc53.com` as the base URL.
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</Callout>
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- Local: `http://localhost:7091`
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- Cloud: `https://gptcloud.arc53.com`
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## How Request Resolution Works
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DocsGPT resolves your request in this order:
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1. If `api_key` is provided, DocsGPT loads the mapped agent and executes with that config.
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2. If `agent_id` is provided (typically with JWT auth), DocsGPT loads that agent if allowed.
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3. If neither is provided, DocsGPT uses request-level fields (`prompt_id`, `active_docs`, `retriever`, etc.).
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Authentication:
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- Agent API-key flow: include `api_key` in JSON/form payload.
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- JWT flow (if auth enabled): include `Authorization: Bearer <token>`.
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## Endpoints
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- `POST /api/answer` (non-streaming)
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- `POST /stream` (SSE streaming)
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- `POST /api/store_attachment` (multipart upload)
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- `GET /api/task_status?task_id=...` (Celery task polling)
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## Request Parameters
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Common request body fields:
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| Field | Type | Required | Applies to | Notes |
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| --- | --- | --- | --- | --- |
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| `question` | `string` | Yes | `/api/answer`, `/stream` | User query. |
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| `api_key` | `string` | Usually | `/api/answer`, `/stream` | Recommended for agent API use. Loads agent config from key. |
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| `conversation_id` | `string` | No | `/api/answer`, `/stream` | Continue an existing conversation. |
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| `history` | `string` (JSON-encoded array) | No | `/api/answer`, `/stream` | Used for new conversations. Format: `[{\"prompt\":\"...\",\"response\":\"...\"}]`. |
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| `model_id` | `string` | No | `/api/answer`, `/stream` | Override model for this request. |
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| `save_conversation` | `boolean` | No | `/api/answer`, `/stream` | Default `true`. If `false`, no conversation is persisted. |
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| `passthrough` | `object` | No | `/api/answer`, `/stream` | Dynamic values injected into prompt templates. |
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| `prompt_id` | `string` | No | `/api/answer`, `/stream` | Ignored when `api_key` already defines prompt. |
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| `active_docs` | `string` or `string[]` | No | `/api/answer`, `/stream` | Overrides active docs when not using key-owned source config. |
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| `retriever` | `string` | No | `/api/answer`, `/stream` | Retriever type (for example `classic`). |
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| `chunks` | `number` | No | `/api/answer`, `/stream` | Retrieval chunk count, default `2`. |
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| `isNoneDoc` | `boolean` | No | `/api/answer`, `/stream` | Skip document retrieval. |
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| `agent_id` | `string` | No | `/api/answer`, `/stream` | Alternative to `api_key` when using authenticated user context. |
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Streaming-only fields:
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| Field | Type | Required | Notes |
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| --- | --- | --- | --- |
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| `attachments` | `string[]` | No | List of attachment IDs from `/api/task_status` success result. |
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| `index` | `number` | No | Update an existing query index. If provided, `conversation_id` is required. |
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## Non-Streaming API (`/api/answer`)
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`/api/answer` waits for completion and returns one JSON response.
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<Callout type="info">
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`attachments` are currently handled through `/stream`. For file/image-attached queries, use the streaming endpoint.
|
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</Callout>
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Response fields:
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|
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- `conversation_id`
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- `answer`
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- `sources`
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- `tool_calls`
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- `thought`
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- Optional structured output metadata (`structured`, `schema`) when enabled
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|
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### Examples
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|
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<Tabs items={['cURL', 'Python', 'JavaScript']}>
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<Tabs.Tab>
|
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```bash
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curl -X POST http://localhost:7091/api/answer \
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-H "Content-Type: application/json" \
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-d '{"question":"your question here","api_key":"your_agent_api_key"}'
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```
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</Tabs.Tab>
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<Tabs.Tab>
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```python
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import requests
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API_URL = "http://localhost:7091/api/answer"
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API_KEY = "your_agent_api_key"
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QUESTION = "your question here"
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response = requests.post(
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API_URL,
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json={"question": QUESTION, "api_key": API_KEY}
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)
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|
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if response.status_code == 200:
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print(response.json())
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else:
|
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print(f"Error: {response.status_code}")
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print(response.text)
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```
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</Tabs.Tab>
|
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<Tabs.Tab>
|
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```javascript
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const apiUrl = 'http://localhost:7091/api/answer';
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const apiKey = 'your_agent_api_key';
|
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const question = 'your question here';
|
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|
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async function getAnswer() {
|
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try {
|
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const response = await fetch(apiUrl, {
|
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method: 'POST',
|
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headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
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body: JSON.stringify({ question, api_key: apiKey }),
|
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});
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|
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if (!response.ok) {
|
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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).
|
||||
@@ -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": {
|
||||
8
docs/mdx-components.jsx
Normal file
8
docs/mdx-components.jsx
Normal file
@@ -0,0 +1,8 @@
|
||||
import { useMDXComponents as getThemeComponents } from 'nextra-theme-docs';
|
||||
|
||||
export function useMDXComponents(components) {
|
||||
return {
|
||||
...getThemeComponents(),
|
||||
...components,
|
||||
};
|
||||
}
|
||||
@@ -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,
|
||||
});
|
||||
|
||||
707
docs/package-lock.json
generated
707
docs/package-lock.json
generated
File diff suppressed because it is too large
Load Diff
@@ -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"
|
||||
},
|
||||
|
||||
@@ -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>
|
||||
@@ -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" />
|
||||
</>
|
||||
)
|
||||
}
|
||||
@@ -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;
|
||||
|
||||
@@ -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
|
||||
|
||||
Reference in New Issue
Block a user