fix(dashboard): delete dataset, docs

Author: louis030195

dashboard/components/DatasetList.tsx

@@ -107,29 +107,33 @@ function DeleteDatasetModal({ userId, datasetId, open, setOpen }) {
   const supabase = useSupabaseClient()
 
   const onHandleDelete = async () => {
-    const { error: datasetsError } = await supabase
-      .from('datasets')
-      .delete()
-      .eq('owner', userId)
-      .eq('name', datasetId)
-    if (datasetsError) {
-      console.error(datasetsError)
-      toast.error('😭 Could not delete dataset')
+
+    const p = new Promise(async (resolve, reject) => {
+      const { error: documentsError } = await supabase
+        .from('documents')
+        .delete()
+        .eq('user_id', userId)
+        .eq('dataset_id', datasetId)
+      if (documentsError) {
+        throw new Error('Could not delete dataset' + documentsError)
+      }
+
+      const { error: datasetsError } = await supabase
+        .from('datasets')
+        .delete()
+        .eq('owner', userId)
+        .eq('name', datasetId)
+      if (datasetsError) {
+        throw new Error('Could not delete dataset' + datasetsError)
+      }
       setOpen(undefined)
-      return
-    }
-    const { error: documentsError } = await supabase
-      .from('documents')
-      .delete()
-      .eq('user_id', userId)
-      .eq('dataset_id', datasetId)
-    if (documentsError) {
-      console.error(documentsError)
-      toast.error('😭 Could not delete dataset')
-    } else {
-      toast.success('🎉 Dataset deleted, refresh to see changes')
-    }
-    setOpen(undefined)
+      resolve(null)
+    })
+    toast.promise(p, {
+      loading: 'Deleting...',
+      success: <b>🎉 Dataset deleted, refresh to see changes!</b>,
+      error: <b>😭 Could not delete dataset</b>,
+    }).finally(() => setOpen(undefined)).catch(console.error)
   }
 
   const cancelButtonRef = useRef(null)

docs/pages/how-it-works.mdx

@@ -28,4 +28,3 @@ Embeddings are a tool that can be used to solve a wide variety of problems. Belo
 ## Usage
 
 - [Javascript SDK](./sdk)
-- [Self-Hosting](./self-hosting/deployment)

docs/pages/index.mdx

@@ -7,7 +7,7 @@ Embedbase is a single API to access both LLMs and a VectorDB\*
 
 ## Key features
 
-- Generate: use `.generate()` to use 6+ LLMs
+- Generate: use `.generateText()` to use 5+ LLMs
 - Semantic Search: use `.add()` to create a list of semantically searchable information and `.search()` to run semantic queries
 
 ### Quickstart

docs/pages/sdk.mdx

@@ -567,7 +567,7 @@ console.log(data)
 [
  "Embedbase API allows to store unstructured data...",
  "Embedbase API has 3 main functions a) provides a plug and play solution to store embeddings b) makes it easy to connect to get the right data into llms c)..",
- "Embedabase API is self-hostable...",
+ "Embedabase API let you use hundreds of llms with a unified api...",
 ]
 ```
   </Tab>
@@ -580,7 +580,7 @@ print(data)
 # [
 #   "Embedbase API allows to store unstructured data...",
 #   "Embedbase API has 3 main functions a) provides a plug and play solution to store embeddings b) makes it easy to connect to get the right data into llms c)..",
-#   "Embedabase API is self-hostable...",
+#   "Embedabase API let you use hundreds of llms with a unified api...",
 # ]
 ```
   </Tab>

docs/pages/self-hosting.mdx

@@ -139,7 +139,7 @@ The magic here is that Embedbase automatically find the right information to pro
 
 That's it for today, you just learned how to use Zapier to connect any data source to Embedbase.
 
-If you liked this blog post, leave a star ⭐️ on https://github.com/different-ai/embedbase, we are also eager for feedback ❤️. If you want to self-host it, please [book a demo](https://cal.com/potato/20min) 😁.
+If you liked this blog post, leave a star ⭐️ on https://github.com/different-ai/embedbase, we are also eager for feedback ❤️.
 Please feel free to contact us for any help or join the [Embedbase Discord](https://discord.gg/pMNeuGrDky) if you have any questions.
 
 ## Where to go from here

docs/pages/tutorials/connect-notion-to-embedbase-with-zapier.mdx

@@ -539,7 +539,7 @@ In summary, we have:
 
 Thank you for reading this document, there is an open-source template to create this type of documentation [here](https://github.com/different-ai/embedbase-nextra-docs-template).
 
-If you liked this blog post, leave a star ⭐️ on https://github.com/different-ai/embedbase, we are also eager for feedback ❤️. If you want to self-host it, please [book a demo](https://cal.com/potato/20min) 😁.
+If you liked this blog post, leave a star ⭐️ on https://github.com/different-ai/embedbase, we are also eager for feedback ❤️.
 Please feel free to contact us for any help!
 
 ## Further reading