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Feature/azure openai templates (#104)

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* Azure OpenAI LLM templates
* Bump version, fix package versions
* Add azure-openai to template generation
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cybermaggedon 2024-10-04 15:47:46 +01:00 • committed by GitHub
parent d96ef8269a
commit 222dc9982c
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6 changed files with 133 additions and 4 deletions
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templates/components/azure-openai.jsonnet Normal file
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@ -0,0 +1,95 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
{
"azure-openai-token":: "${AZURE_OPENAI_TOKEN}",
"azure-openai-model":: "GPT-3.5-Turbo",
"azure-openai-max-output-tokens":: 4192,
"azure-openai-temperature":: 0.0,
"text-completion" +: {
create:: function(engine)
local container =
engine.container("text-completion")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure-openai",
"-p",
url.pulsar,
"-k",
$["azure-openai-token"],
"-m",
$["azure-openai-model"],
"-x",
std.toString($["azure-openai-max-output-tokens"]),
"-t",
std.toString($["azure-openai-temperature"]),
])
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerSet = engine.containers(
"text-completion", [ container ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
engine.resources([
containerSet,
service,
])
},
"text-completion-rag" +: {
create:: function(engine)
local container =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure",
"-p",
url.pulsar,
"-k",
$["azure-openai-token"],
"-e",
$["azure-openai-model"],
"-x",
std.toString($["azure-openai-max-output-tokens"]),
"-t",
std.toString($["azure-openai-temperature"]),
"-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 ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
engine.resources([
containerSet,
service,
])
}
} + prompts