docs: fix broken doc link (#670)

Author: Mini256

.env.example

@@ -17,15 +17,5 @@ TIDB_PASSWORD=
 TIDB_DATABASE=
 TIDB_SSL=true
 
-# EMBEDDING_MAX_TOKENS indicates the max size of document chunks.
-#
-# EMBEDDING_MAX_TOKENS should be smaller than the embedding model's max tokens due
-# to the tokenizer difference. (see: https://github.com/pingcap/autoflow/issues/397)
-#
-# Go to https://tidb.ai/docs/embedding-model to check the max tokens of the embedding model.
-#
-# Notice: this variable will be deprecated in the future.
-EMBEDDING_MAX_TOKENS=2048
-
 # JS Widgets: if you want to use JS widgets, you need to set the following variables to enable CORS.
 # BACKEND_CORS_ORIGINS=https://your-domain.com

CONTRIBUTING.md

@@ -17,7 +17,7 @@ In this section, you should have some prerequisites software installed on your l
 
 #### Setting up your development environment
 
-Setting up the project on your local machine is the first step to contributing to the project. You can clone the project from the GitHub repository and then start the project on your local machine. You can follow the instructions in the [Deployment Guide](https://tidb.ai/docs/deploy-with-docker) file to set up the project on your local machine.
+Setting up the project on your local machine is the first step to contributing to the project. You can clone the project from the GitHub repository and then start the project on your local machine. You can follow the instructions in the [Deployment Guide](https://autoflow.tidb.ai/deploy-with-docker) file to set up the project on your local machine.
 
 To test your local changes, you can build and run the project using:
 

README.md

@@ -21,7 +21,7 @@
 AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowledge base tool built on top of [TiDB Vector](https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community) and [LlamaIndex](https://github.com/run-llama/llama_index) and [DSPy](https://github.com/stanfordnlp/dspy).
 
 - **Live Demo**: [https://tidb.ai](https://tidb.ai?utm_source=tidb.ai&utm_medium=community)
-- **Deployment Docs**: [Deployment Docs](https://tidb.ai/docs/?utm_source=github&utm_medium=tidb.ai)
+- **Deployment Docs**: [Deployment Docs](https://autoflow.tidb.ai/?utm_source=github&utm_medium=tidb.ai)
 
 ## Features
 
@@ -35,7 +35,7 @@ AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowl
 
 ## Deploy
 
-- [Deploy with Docker Compose](https://tidb.ai/docs/deploy-with-docker) (with: 4 CPU cores and 8GB RAM)
+- [Deploy with Docker Compose](https://autoflow.tidb.ai/deploy-with-docker) (with: 4 CPU cores and 8GB RAM)
 
 ## Tech Stack
 

backend/app/site_settings/default_settings.yml

@@ -25,7 +25,7 @@ website:
   homepage_footer_links:
     default:
       - text: "Release Notes"
-        href: "https://tidb.ai/docs/changelog"
+        href: "https://autoflow.tidb.ai/releases"
       - text: "Powered by TiDB"
         href: "https://tidb.cloud/ai"
       - text: "© 2024 PingCAP"

docs/next.config.mjs

@@ -2,8 +2,9 @@ import nextra from 'nextra'
 
 const withNextra = nextra({
   latex: true,
+  defaultShowCopyCode: true,
   search: {
-    codeblocks: false
+    codeblocks: true
   },
   contentDirBasePath: '/',
 })

docs/src/app/layout.jsx

@@ -35,7 +35,7 @@ export default async function RootLayout({ children }) {
           </span>
         </div>
       }
-      logoLink="/docs"
+      logoLink="/"
       projectLink="https://github.com/pingcap/autoflow"
     >
       <div style={{ display: 'flex', alignItems: 'center', gap: '1rem' }}>

docs/src/content/README.md

@@ -21,7 +21,7 @@
 AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowledge base tool built on top of [TiDB Vector](https://www.pingcap.com/ai?utm_source=tidb.ai&utm_medium=community) and [LlamaIndex](https://github.com/run-llama/llama_index) and [DSPy](https://github.com/stanfordnlp/dspy).
 
 - **Live Demo**: [https://tidb.ai](https://tidb.ai?utm_source=tidb.ai&utm_medium=community)
-- **Deployment Docs**: [Deployment Docs](https://tidb.ai/docs/?utm_source=github&utm_medium=tidb.ai)
+- **Deployment Docs**: [Deployment Docs](https://autoflow.tidb.ai/?utm_source=github&utm_medium=tidb.ai)
 
 ## Features
 
@@ -35,7 +35,7 @@ AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowl
 
 ## Deploy
 
-- [Deploy with Docker Compose](https://tidb.ai/docs/deploy-with-docker) (with: 4 CPU cores and 8GB RAM)
+- [Deploy with Docker Compose](https://autoflow.tidb.ai/deploy-with-docker) (with: 4 CPU cores and 8GB RAM)
 
 ## Tech Stack
 

docs/src/content/releases/index.mdx

@@ -0,0 +1,27 @@
+---
+title: Releases
+asIndexPage: true
+---
+
+# Releases
+
+import { Cards } from 'nextra/components'
+ 
+<Cards>
+  <Cards.Card
+    title="v0.4.0"
+    href="/releases/v0.4.0"
+  />
+  <Cards.Card
+    title="v0.3.0"
+    href="/releases/v0.3.0"
+  />
+  <Cards.Card
+    title="v0.2.0"
+    href="/releases/v0.2.0"
+  />
+  <Cards.Card
+    title="v0.1.0"
+    href="/releases/v0.1.0"
+  />
+</Cards>

docs/src/content/releases/v0.2.0.md

@@ -14,4 +14,4 @@
 - Fixed a SiteSetting cache issue that prevented proper synchronization across processes.
 
 
-If you are deploying tidb.ai using docker, please refer to this [document](https://tidb.ai/docs/deploy-with-docker#upgrade) for upgrading your tidb.ai.
+If you are deploying tidb.ai using docker, please refer to this [document](https://autoflow.tidb.ai/deploy-with-docker#upgrade) for upgrading your tidb.ai.