Workflow Steps
Last updated
Last updated
Browse Data Hub:
Navigate to the Data Hub within the Sahara platform.
Explore available datasets by filtering by domain, size, or licensing terms. (Some explore features coming in Beta)
Purchase Dataset:
Select a dataset and click Purchase.
Complete the payment process using the supported token or currency.
Add Dataset to Vault:
A Screen will pop up and you will select the Vault you want to import to and click Import.
Navigate to your Vaults Tab and see the imported data set.
Navigate to Vaults:
Go to the Vaults Tab in the Sahara dashboard.
Create a New Vault:
Click Create Vault and provide a name and description.
Upload Data:
Click Upload Files and select files from your local storage.
Supported formats include CSV, JSON, and Parquet.
Configure Metadata:
Add metadata tags for better discoverability and provenance tracking.
Access Compute Hub:
Open the Compute Hub Tab on the Sahara dashboard.
Initiate:
Click the New Endpoint button on the Compute Hub home page.
Configuration:
Fill out the form with the following details:
Select Provider: Select Provider from list (Lepton, Predibase, Sagemaker, Bedrock, OpenAI)
Select Model: Opens a popup and allows users to select from available models on platform. Search and press “Select” when you have chosen a model.
Name: Assign a unique name to the instance.
Review and Create:
Review the configuration.
Click Create Instance to launch the instance.
Open Model Hub:
Navigate to the Model Hub Tab.
Click Create Pipeline:
Choose between:
RAG Pipeline: Requires Vault integration for retrieval tasks.
Prompt-Based Pipeline: For conversational or structured AI tasks.
Configure Pipeline:
Upload an avatar for the pipeline.
Provide the following:
Pipeline Name.
Description.
Instructions (prompt).
Conversation Starter (optional).
Select an AI model.
(RAG only) Choose Vaults for data retrieval.
Publish Pipeline:
Click Publish and select a compute provider matching your pipeline’s requirements.
Generate API Endpoint:
Upon deployment, an API endpoint is generated for integration.
Test the API:
Use the generated endpoint to send sample requests.
Example payload:
Review the AI response and refine configurations as needed.
Open Dashboard Tab:
Navigate to the Metrics Tab in your pipeline’s details page.
Review Usage:
Monitor token usage, API calls, and system performance metrics.
