trustgraph/templates/components/googleaistudio-rag.jsonnet

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local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["googleaistudio-rag-" + key]:: value,
},
"googleaistudio-rag-max-output-tokens":: 4096,
"googleaistudio-rag-temperature":: 0.0,
"googleaistudio-rag-model":: "gemini-1.5-flash-002",
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("googleaistudio-key")
.with_env_var("GOOGLE_AI_STUDIO_KEY", "googleaistudio-key");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-googleaistudio",
"-p",
url.pulsar,
"-x",
std.toString(
$["googleaistudio-rag-max-output-tokens"]
),
"-t",
"%0.3f" % $["googleaistudio-rag-temperature"],
"-m",
$["googleaistudio-rag-model"],
"-i",
"non-persistent://tg/request/text-completion-rag",
"-o",
"non-persistent://tg/response/text-completion-rag",
])
.with_env_var_secrets(envSecrets)
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSetRag,
serviceRag,
])
},
} + prompts