Provides a vector/similarity search for any documentation site. It's headless, so that you can integrate it into your existing website.

• This repo initializes a new docs schema inside your database.
• The accompanying GitHub Action ingests your markdown docs into your database as embeddings.
• This repo provides an Edge Function that handles user queries, converting them into ChatGPT-like responses.

• Supabase: Database & Edge Functions.
• OpenAI: Embeddings and completions.
• GitHub Actions: for ingesting your markdown docs.

Start by creating a new Supabase Project: database.new.

1. Clone this repo
2. Link the repo to your remote project: supabase link --project-ref XXX
3. Apply the database migrations: supabase db push
4. Set your OpenAI key as a secret: supabase secrets set OPENAI_API_KEY=sk-xxx
5. Deploy the Edge Functions: supabase functions deploy --no-verify-jwt
6. Expose docs schema via API in Supabase Dashboard settings > API Settings > Exposed schemas
7. Setup supabase-vector-embeddings GitHub action in your Knowledge Base repo. You will see the embeddings populated in your database after the GitHub Action has run.

1. Find the URL for the vector-search Edge Function in the Functions section of the Dashboard.
2. Inside your appliction, you can send the user queries to this endpoint to receive a streamed response from OpenAI.

 curl -i --location --request GET 'https://your-project-ref.functions.supabase.co/vector-search?query=What%27s+Supabase%3F'

const onSubmit = (e: Event) => {
  e.preventDefault()
  answer.value = ""
  isLoading.value = true

  const query = new URLSearchParams({ query: inputRef.current!.value })
  const projectUrl = `https://your-project-ref.functions.supabase.co`
  const queryURL = `${projectURL}/${query}`
  const eventSource = new EventSource(queryURL)

  eventSource.addEventListener("error", (err) => {
    isLoading.value = false
    console.error(err)
  })
  
  eventSource.addEventListener("message", (e: MessageEvent) => {
    isLoading.value = false

    if (e.data === "[DONE]") {
      eventSource.close()
      return
    }

    const completionResponse: CreateCompletionResponse = JSON.parse(e.data)
    const text = completionResponse.choices[0].text

    answer.value += text
  });

  isLoading.value = true
}

• docs.supabase.com - Use cmd+k to access.

MIT