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Added jsonnet for GoogleAIStudio

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This commit is contained in:
JackColquitt 2024-10-14 18:33:38 -07:00
parent 4ef8332c6f
commit 9d0b79cd82
4 changed files with 124 additions and 1 deletions
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1
templates/components.jsonnet
View file

@ -7,6 +7,7 @@
"document-rag": import "components/document-rag.jsonnet",
"embeddings-hf": import "components/embeddings-hf.jsonnet",
"embeddings-ollama": import "components/embeddings-ollama.jsonnet",
"googleaistudio": import "components/googleaistudio.jsonnet",
"grafana": import "components/grafana.jsonnet",
"graph-rag": import "components/graph-rag.jsonnet",
"triple-store-cassandra": import "components/cassandra.jsonnet",

90
templates/components/googleaistudio.jsonnet Normal file
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@ -0,0 +1,90 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
{
"googleaistudio-key":: "${GOOGLEAISTUDIO_KEY}",
"googleaistudio-max-output-tokens":: 4096,
"googleaistudio-temperature":: 0.0,
"text-completion" +: {
create:: function(engine)
local container =
engine.container("text-completion")
.with_image(images.trustgraph)
.with_command([
"text-completion-googleaistudio",
"-p",
url.pulsar,
"-k",
$["googleaistudio-key"],
"-x",
std.toString($["googleaistudio-max-output-tokens"]),
"-t",
std.toString($["googleaistudio-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-googleaistudio",
"-p",
url.pulsar,
"-k",
$["googleaistudio-key"],
"-x",
std.toString($["googleaistudio-max-output-tokens"]),
"-t",
std.toString($["googleaistudio-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

2
templates/generate-all
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@ -123,7 +123,7 @@ def generate_all(output, version):
]:
for model in [
"azure", "azure-openai", "bedrock", "claude", "cohere",
"llamafile", "ollama", "openai", "vertexai"
"googleaistudio", "llamafile", "ollama", "openai", "vertexai",
]:
for graph in [ "cassandra", "neo4j" ]:

32
templates/patterns/llm-googleaistudio.jsonnet Normal file
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@ -0,0 +1,32 @@
{
pattern: {
name: "googleaistudio",
icon: "🤖💬",
title: "Add GoogleAIStudio for text completion",
description: "This pattern integrates a GoogleAIStudio LLM service for text completion operations. You need a GoogleAISTudio API key to be able to use this service.",
requires: ["pulsar", "trustgraph"],
features: ["llm"],
args: [
{
name: "googleaistudio-max-output-tokens",
label: "Maximum output tokens",
type: "integer",
description: "Limit on number tokens to generate",
default: 4096,
required: true,
},
{
name: "googleaistudio-temperature",
label: "Temperature",
type: "slider",
description: "Controlling predictability / creativity balance",
min: 0,
max: 1,
step: 0.05,
default: 0.5,
},
],
category: [ "llm" ],
},
module: "components/googleaistudio.jsonnet",
}