require "vellum_ai"


client = Vellum::Client.new(api_key: ENV['VELLUM_API_KEY'])

result = client.execute_prompt(
    prompt_deployment_name: "my-deployment",
    inputs: [
        {
            "type": "STRING",
            "name": "question",
            "value": "Can I get a refund?"
        }
    ],
)

puts result.outputs[0].value

require "vellum_ai"


client = Vellum::AsyncClient.new(api_key: ENV['VELLUM_API_KEY'])

result = client.execute_prompt(
    prompt_deployment_name: "my-deployment",
    inputs: [
        {
            "type": "STRING",
            "name": "question",
            "value": "Can I get a refund?"
        }
    ],
)

puts result.wait.outputs[0].value

require "vellum_ai"


client = Vellum::Client.new(api_key: ENV['VELLUM_API_KEY'])
result = client.documents.upload(
    # File to upload
    contents: "/path/to/your/file.txt",
    # Document label
    label: "Human-friendly label for your document",
    # The names of indexes that you'd like this document to be added to.
    add_to_index_names: ["<your-index-name>"],
    # Optionally include a unique ID from your system to this document later.
    #   Useful if you want to perform updates later
    external_id: "<your-index-name>",
    # Optionally include keywords to associate with the document that can be used in hybrid search
    keywords: [],
)

puts result