Completions#
Generate text completions using a model through the NIM Proxy microservice through a POST API call.
Prerequisites#
Before you can generate completions, make sure that you have:
Access to the NIM Proxy microservice through the base URL where the service is deployed. Store the base URL in an environment variable
NIM_PROXY_BASE_URL
.A valid model name. To retrieve the list of models deployed as NIM microservices in your environment, use the
${NIM_PROXY_BASE_URL}/v1/models
API. For more information, see List Models.
Options#
You can generate completions in the following ways.
API#
Perform a
POST
request to the/v1/completions
endpoint.Use the following cURL command. For more details on the request body, refer to the NIM for LLMs API reference and find the API named the same as
v1/completions
. The NIM Proxy API endpoint routes your requests to the NIM for LLMs microservice.curl -X POST \ "${NIM_PROXY_BASE_URL}/v1/completions" \ -H 'accept: application/json' \ -H 'Content-Type: application/json' \ -d '{ "model": "meta/llama-3.1-8b-instruct", "prompt": "Once upon a time", "max_tokens": 64 }' | jq
Review the response.
Example Response
{ "id": "cmpl-123", "object": "text_completion", "created": 1677652288, "model": "llama2-7b", "choices": [ { "text": "In a sunlit studio, a robot named Pixel carefully dipped its metallic fingers into a palette of vibrant colors. Its optical sensors studied the blank canvas with intense focus, analyzing the interplay of light and shadow. With precise movements, it began to paint, each stroke a calculated expression of its growing understanding of art. The robot's journey from mechanical precision to artistic intuition was captured in the evolving masterpiece before it.", "index": 0, "finish_reason": "stop" } ], "usage": { "prompt_tokens": 10, "completion_tokens": 89, "total_tokens": 99 } }