local base = import "base/base.jsonnet"; local images = import "values/images.jsonnet"; local url = import "values/url.jsonnet"; local prompts = import "prompts/mixtral.jsonnet"; { "openai-key":: "${OPENAI_KEY}", "openai-max-output-tokens":: 4096, "openai-temperature":: 0.0, "openai-model":: "GPT-3.5-Turbo", "text-completion" +: { create:: function(engine) local container = engine.container("text-completion") .with_image(images.trustgraph) .with_command([ "text-completion-openai", "-p", url.pulsar, "-k", $["openai-key"], "-x", std.toString($["openai-max-output-tokens"]), "-t", std.toString($["openai-temperature"]), "-m", $["openai-model"], ]) .with_limits("0.5", "128M") .with_reservations("0.1", "128M"); local containerSet = engine.containers( "text-completion", [ container ] ); engine.resources([ containerSet, ]) }, "text-completion-rag" +: { create:: function(engine) local container = engine.container("text-completion-rag") .with_image(images.trustgraph) .with_command([ "text-completion-openai", "-p", url.pulsar, "-k", $["openai-key"], "-x", std.toString($["openai-max-output-tokens"]), "-t", std.toString($["openai-temperature"]), "-m", $["openai-model"], "-i", "non-persistent://tg/request/text-completion-rag", "-o", "non-persistent://tg/response/text-completion-rag-response", ]) .with_limits("0.5", "128M") .with_reservations("0.1", "128M"); local containerSet = engine.containers( "text-completion-rag", [ container ] ); engine.resources([ containerSet, ]) } } + prompts