mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-25 08:26:21 +02:00
f661791bbf
Added templates which produce K8s resources. With the provided GCP wrapper, it works on GCP K8s cluster. This isn't stable enough for other folks to use so will need more piloting before it can be documented and released.
106 lines
3.3 KiB
Jsonnet
106 lines
3.3 KiB
Jsonnet
local base = import "base/base.jsonnet";
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local images = import "values/images.jsonnet";
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local url = import "values/url.jsonnet";
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local prompts = import "prompts/mixtral.jsonnet";
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local chunker = import "chunker-recursive.jsonnet";
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{
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"aws-id-key":: "${AWS_ID_KEY}",
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"aws-secret-key":: "${AWS_SECRET_KEY}",
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"aws-region":: "us-west-2",
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"bedrock-max-output-tokens":: 4096,
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"bedrock-temperature":: 0.0,
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"bedrock-model":: "mistral.mixtral-8x7b-instruct-v0:1",
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"text-completion" +: {
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create:: function(engine)
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local container =
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engine.container("text-completion")
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.with_image(images.trustgraph)
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.with_command([
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"text-completion-bedrock",
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"-p",
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url.pulsar,
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"-z",
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$["aws-id-key"],
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"-k",
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$["aws-secret-key"],
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"-r",
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$["aws-region"],
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"-x",
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std.toString($["bedrock-max-output-tokens"]),
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"-t",
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std.toString($["bedrock-temperature"]),
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"-m",
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$["bedrock-model"],
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])
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.with_limits("0.5", "128M")
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.with_reservations("0.1", "128M");
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local containerSet = engine.containers(
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"text-completion", [ container ]
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);
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local service =
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engine.internalService(containerSet)
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.with_port(8000, 8000, "metrics");
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engine.resources([
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containerSet,
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service,
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])
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},
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"text-completion-rag" +: {
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create:: function(engine)
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local container =
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engine.container("text-completion-rag")
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.with_image(images.trustgraph)
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.with_command([
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"text-completion-bedrock",
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"-p",
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url.pulsar,
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"-z",
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$["aws-id-key"],
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"-k",
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$["aws-secret-key"],
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"-r",
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$["aws-region"],
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"-x",
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std.toString($["bedrock-max-output-tokens"]),
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"-t",
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std.toString($["bedrock-temperature"]),
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"-m",
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$["bedrock-model"],
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"-i",
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"non-persistent://tg/request/text-completion-rag",
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"-o",
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"non-persistent://tg/response/text-completion-rag-response",
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])
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.with_limits("0.5", "128M")
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.with_reservations("0.1", "128M");
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local containerSet = engine.containers(
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"text-completion-rag", [ container ]
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);
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local service =
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engine.internalService(containerSet)
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.with_port(8000, 8000, "metrics");
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engine.resources([
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containerSet,
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service,
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])
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}
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} + prompts + chunker
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