• Use the sidebar to navigate to the Repositories page. Click New Repository to create a new place to store your documents.

You can also create a Repository using the SDK or the API.

const response = await client.repositories.create({
    name: "test-repository",
    organization: "your-org-name",
    description: "This is a test repository"
}) 

• Upload your documents to a repository using the Prem web app (click the add document button), API or using the SDK. You can either upload documents individually or in batches. Make sure to provide meaningful names or identifiers for your documents.

const response = await client.repository.document.create({
    repository_id: 3,
    file: "./testfile.txt" // This could be a .txt, .pdf, .docx file.
})

console.log(response)

• Once the documents are uploaded, Prem will automatically index them to enable fast and efficient retrieval.

You can view the indexes of a document by clicking on each document in the repository as shown in the image below.

You have three ways to configure retrival settings. In the Lab for testing, in the Launchpad for production and in your code using the SDK or API for custom use cases.

Once you’ve uploaded your documents, you can choose a model and configure the retrieval settings. Head over to the Lab or the Launchpad if you’re ready to give a model you’re planning to put in production the knowledge of the doucments.

You can edit the following retrieval settings in the Lab,Launchpad or in your code using the SDK or API:

• Limit: Sets the maximum number of top-matching documents to retrieve based on similarity.

• Similarity: Measures how closely a query matches document embeddings. Higher values indicate greater similarity, ranging from 0 to 1.

Here’s a quick overview of the differences between the three ways to configure retrieval settings:

Configure in Lab

Test out how your model performs with the documents in the Lab playground. Click Repo and add a repository to each model you’d like to test. You can add up to 4 repositories to each model.

Configure on the Launchpad

Head over to the Launchpad and click on the Add Repository button. Its right underneath the system prompt text area. You can also edit the retrieval settings in the Launchpad under Linked repositories. You can add up to 4 repositories to the model you are launching.

Configure in Code

Use the SDK or API to configure the retrieval settings in your code. Its really simple and only takes a few lines of code. You can add up to 4 repositories to a model.

const messages = [
    { role: "user", content: "Which is Jack's pet name?" },
]

const repositories = {
  ids: [REPOSITORY_ID, ...],
  similarity_threshold: 0.65,
  limit: 3
}

// Create completion
const response = await client.chat.completions.create({
  project_id,
  messages,
  repositories,
  stream: false
})

console.log(response.choices[0].message.content)
// "Jack's pet name is Sparky."

console.log(response.document_chunks)
// E.g. [{ repository_id=4, document_id=14, chunk_id=15, document_name="pets_and_their_owners.txt", similarity_score=0.67, content="..." }, ...]

Before deploying your configured model, it’s crucial to thoroughly test and evaluate its performance in the Lab.

• Test Queries: Prepare a set of test queries that cover different scenarios and edge cases. Send these queries to your assistant and evaluate the quality and relevance of the generated responses.

• Iterative Refinement: Based on the evaluation results, iteratively refine your assistant by adjusting the retrieval settings, fine-tuning the generative model, or improving the document collection.

Once you’re satisfied with the performance of your models, you can deploy them with the Launchpad and integrate your application with the Prem SDKs or API.