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Dual model templates (#263)

Browse source 
* Dual-mode templates

* Fixed generate-all so that works

* Fix ability to specify Claude model
This commit is contained in:
cybermaggedon 2025-01-11 11:40:42 +00:00 • committed by GitHub
parent 1bb1112569
commit cec9e29222
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24 changed files with 725 additions and 360 deletions
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61
templates/components/azure-openai-rag.jsonnet Normal file
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@ -0,0 +1,61 @@
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 + {
["ollama-rag-" + key]:: value,
},
"azure-openai-rag-model":: "GPT-3.5-Turbo",
"azure-openai-rag-max-output-tokens":: 4192,
"azure-openai-rag-temperature":: 0.0,
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("azure-openai-credentials")
.with_env_var("AZURE_TOKEN", "azure-token");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure",
"-p",
url.pulsar,
"-x",
std.toString($["azure-openai-rag-max-output-tokens"]),
"-t",
"%0.3f" % $["azure-openai-rag-temperature"],
"-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

35
templates/components/azure-openai.jsonnet
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@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["azure-openai-" + key]:: value,
},
"azure-openai-model":: "GPT-3.5-Turbo",
"azure-openai-max-output-tokens":: 4192,
"azure-openai-temperature":: 0.0,
@ -34,48 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure",
"-p",
url.pulsar,
"-x",
std.toString($["azure-openai-max-output-tokens"]),
"-t",
"%0.3f" % $["azure-openai-temperature"],
"-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

60
templates/components/azure-rag.jsonnet Normal file
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@ -0,0 +1,60 @@
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["azure-rag-" + key]:: value,
},
"azure-rag-max-output-tokens":: 4096,
"azure-rag-temperature":: 0.0,
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("azure-credentials")
.with_env_var("AZURE_TOKEN", "azure-token")
.with_env_var("AZURE_ENDPOINT", "azure-endpoint");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure",
"-p",
url.pulsar,
"-x",
std.toString($["azure-rag-max-output-tokens"]),
"-t",
"%0.3f" % $["azure-rag-temperature"],
"-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

36
templates/components/azure.jsonnet
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@ -1,10 +1,14 @@
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 + {
["azure-" + key]:: value,
},
"azure-max-output-tokens":: 4096,
"azure-temperature":: 0.0,
@ -32,48 +36,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-azure",
"-p",
url.pulsar,
"-x",
std.toString($["azure-max-output-tokens"]),
"-t",
"%0.3f" % $["azure-temperature"],
"-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
}

66
templates/components/bedrock-rag.jsonnet Normal file
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@ -0,0 +1,66 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
local chunker = import "chunker-recursive.jsonnet";
{
with:: function(key, value)
self + {
["bedrock-rag-" + key]:: value,
},
"bedrock-rag-max-output-tokens":: 4096,
"bedrock-rag-temperature":: 0.0,
"bedrock-rag-model":: "mistral.mixtral-8x7b-instruct-v0:1",
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("bedrock-credentials")
.with_env_var("AWS_ID_KEY", "aws-id-key")
.with_env_var("AWS_SECRET", "aws-secret")
.with_env_var("AWS_REGION", "aws-region");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-bedrock",
"-p",
url.pulsar,
"-x",
std.toString($["bedrock-rag-max-output-tokens"]),
"-t",
"%0.3f" % $["bedrock-rag-temperature"],
"-m",
$["bedrock-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 + chunker

37
templates/components/bedrock.jsonnet
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@ -6,6 +6,11 @@ local chunker = import "chunker-recursive.jsonnet";
{
with:: function(key, value)
self + {
["bedrock-" + key]:: value,
},
"bedrock-max-output-tokens":: 4096,
"bedrock-temperature":: 0.0,
"bedrock-model":: "mistral.mixtral-8x7b-instruct-v0:1",
@ -37,50 +42,18 @@ local chunker = import "chunker-recursive.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-bedrock",
"-p",
url.pulsar,
"-x",
std.toString($["bedrock-max-output-tokens"]),
"-t",
"%0.3f" % $["bedrock-temperature"],
"-m",
$["bedrock-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

63
templates/components/claude-rag.jsonnet Normal file
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@ -0,0 +1,63 @@
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 + {
["claude-rag-" + key]:: value,
},
"claude-rag-model":: "claude-3-sonnet-20240229",
"claude-rag-max-output-tokens":: 4096,
"claude-rag-temperature":: 0.0,
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("claude-credentials")
.with_env_var("CLAUDE_KEY", "claude-key");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-claude",
"-p",
url.pulsar,
"-x",
std.toString($["claude-rag-max-output-tokens"]),
"-m",
$["claude-rag-model"],
"-t",
"%0.3f" % $["claude-rag-temperature"],
"-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

38
templates/components/claude.jsonnet
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@ -5,6 +5,12 @@ local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["claude-" + key]:: value,
},
"claude-model":: "claude-3-sonnet-20240229",
"claude-max-output-tokens":: 4096,
"claude-temperature":: 0.0,
@ -24,6 +30,8 @@ local prompts = import "prompts/mixtral.jsonnet";
url.pulsar,
"-x",
std.toString($["claude-max-output-tokens"]),
"-m",
$["claude-model"],
"-t",
"%0.3f" % $["claude-temperature"],
])
@ -31,48 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-claude",
"-p",
url.pulsar,
"-x",
std.toString($["claude-max-output-tokens"]),
"-t",
"%0.3f" % $["claude-temperature"],
"-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

56
templates/components/cohere-rag.jsonnet Normal file
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@ -0,0 +1,56 @@
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 + {
["cohere-rag-" + key]:: value,
},
"cohere-rag-temperature":: 0.0,
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("cohere-credentials")
.with_env_var("COHERE_KEY", "cohere-key");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-cohere",
"-p",
url.pulsar,
"-t",
"%0.3f" % $["cohere-rag-temperature"],
"-i",
"non-persistent://tg/request/text-completion-rag",
"-o",
"non-persistent://tg/response/text-completion-rag",
])
.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

34
templates/components/cohere.jsonnet
View file

@ -5,9 +5,10 @@ local prompts = import "prompts/mixtral.jsonnet";
{
// Override chunking
"chunk-size":: 150,
"chunk-overlap":: 10,
with:: function(key, value)
self + {
["cohere-" + key]:: value,
},
"cohere-temperature":: 0.0,
@ -31,45 +32,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-cohere",
"-p",
url.pulsar,
"-t",
"%0.3f" % $["cohere-temperature"],
"-i",
"non-persistent://tg/request/text-completion-rag",
"-o",
"non-persistent://tg/response/text-completion-rag",
])
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

65
templates/components/googleaistudio-rag.jsonnet Normal file
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@ -0,0 +1,65 @@
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

32
templates/components/googleaistudio.jsonnet
View file

@ -34,50 +34,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-googleaistudio",
"-p",
url.pulsar,
"-x",
std.toString($["googleaistudio-max-output-tokens"]),
"-t",
"%0.3f" % $["googleaistudio-temperature"],
"-m",
$["googleaistudio-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8000, 8000, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

57
templates/components/llamafile-rag.jsonnet Normal file
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@ -0,0 +1,57 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/slm.jsonnet";
{
with:: function(key, value)
self + {
["llamafile-rag-" + key]:: value,
},
"llamafile-rag-model":: "LLaMA_CPP",
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("llamafile-credentials")
.with_env_var("LLAMAFILE_URL", "llamafile-url");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-llamafile",
"-p",
url.pulsar,
"-m",
$["llamafile-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(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSetRag,
serviceRag,
])
},
} + prompts

33
templates/components/llamafile.jsonnet
View file

@ -5,6 +5,11 @@ local prompts = import "prompts/slm.jsonnet";
{
with:: function(key, value)
self + {
["llamafile-" + key]:: value,
},
"llamafile-model":: "LLaMA_CPP",
"text-completion" +: {
@ -28,46 +33,18 @@ local prompts = import "prompts/slm.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-llamafile",
"-p",
url.pulsar,
"-m",
$["llamafile-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8080, 8080, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

57
templates/components/ollama-rag.jsonnet Normal file
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@ -0,0 +1,57 @@
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 + {
["ollama-rag-" + key]:: value,
},
"ollama-rag-model":: "gemma2:9b",
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("ollama-credentials")
.with_env_var("OLLAMA_HOST", "ollama-host");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-ollama",
"-p",
url.pulsar,
"-m",
$["ollama-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(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSetRag,
serviceRag,
])
},
} + prompts

33
templates/components/ollama.jsonnet
View file

@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["ollama-" + key]:: value,
},
"ollama-model":: "gemma2:9b",
"text-completion" +: {
@ -28,46 +33,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-ollama",
"-p",
url.pulsar,
"-m",
$["ollama-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8080, 8080, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

63
templates/components/openai-rag.jsonnet Normal file
View file

@ -0,0 +1,63 @@
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 + {
["openai-rag-" + key]:: value,
},
"openai-rag-max-output-tokens":: 4096,
"openai-rag-temperature":: 0.0,
"openai-rag-model":: "GPT-3.5-Turbo",
"text-completion-rag" +: {
create:: function(engine)
local envSecrets = engine.envSecrets("openai-credentials")
.with_env_var("OPENAI_TOKEN", "openai-token");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-openai",
"-p",
url.pulsar,
"-x",
std.toString($["openai-rag-max-output-tokens"]),
"-t",
"%0.3f" % $["openai-rag-temperature"],
"-m",
$["openai-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(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSetRag,
serviceRag,
])
},
} + prompts

37
templates/components/openai.jsonnet
View file

@ -5,6 +5,11 @@ local prompts = import "prompts/mixtral.jsonnet";
{
with:: function(key, value)
self + {
["openai-" + key]:: value,
},
"openai-max-output-tokens":: 4096,
"openai-temperature":: 0.0,
"openai-model":: "GPT-3.5-Turbo",
@ -34,50 +39,18 @@ local prompts = import "prompts/mixtral.jsonnet";
.with_limits("0.5", "128M")
.with_reservations("0.1", "128M");
local containerRag =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-openai",
"-p",
url.pulsar,
"-x",
std.toString($["openai-max-output-tokens"]),
"-t",
"%0.3f" % $["openai-temperature"],
"-m",
$["openai-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 containerSet = engine.containers(
"text-completion", [ container ]
);
local containerSetRag = engine.containers(
"text-completion-rag", [ containerRag ]
);
local service =
engine.internalService(containerSet)
.with_port(8080, 8080, "metrics");
local serviceRag =
engine.internalService(containerSetRag)
.with_port(8080, 8080, "metrics");
engine.resources([
envSecrets,
containerSet,
containerSetRag,
service,
serviceRag,
])
},

4
templates/components/prompt-overrides.jsonnet
View file

@ -1,7 +1,3 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompts = import "prompts/mixtral.jsonnet";
local default_prompts = import "prompts/default-prompts.jsonnet";
{

3
templates/components/trustgraph.jsonnet
View file

@ -1,7 +1,6 @@
local base = import "base/base.jsonnet";
local images = import "values/images.jsonnet";
local url = import "values/url.jsonnet";
local prompt = import "prompt-template.jsonnet";
{
@ -181,5 +180,5 @@ local prompt = import "prompt-template.jsonnet";
},
} + prompt
}

74
templates/components/vertexai-rag.jsonnet Normal file
View file

@ -0,0 +1,74 @@
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 + {
["vertexai-rag-" + key]:: value,
},
"vertexai-rag-model":: "gemini-1.0-pro-001",
"vertexai-rag-private-key":: "/vertexai/private.json",
"vertexai-rag-region":: "us-central1",
"vertexai-rag-max-output-tokens":: 4096,
"vertexai-rag-temperature":: 0.0,
"text-completion-rag" +: {
create:: function(engine)
local cfgVol = engine.secretVolume(
"vertexai-creds",
"./vertexai",
{
"private.json": importstr "vertexai/private.json",
}
);
local container =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-vertexai",
"-p",
url.pulsar,
"-k",
$["vertexai-rag-private-key"],
"-r",
$["vertexai-rag-region"],
"-x",
std.toString($["vertexai-rag-max-output-tokens"]),
"-t",
"%0.3f" % $["vertexai-rag-temperature"],
"-m",
$["vertexai-rag-model"],
"-i",
"non-persistent://tg/request/text-completion-rag",
"-o",
"non-persistent://tg/response/text-completion-rag",
])
.with_limits("0.5", "256M")
.with_reservations("0.1", "256M")
.with_volume_mount(cfgVol, "/vertexai");
local containerSet = engine.containers(
"text-completion-rag", [ container ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
engine.resources([
cfgVol,
containerSet,
service,
])
}
} + prompts

54
templates/components/vertexai.jsonnet
View file

@ -61,59 +61,5 @@ local prompts = import "prompts/mixtral.jsonnet";
},
"text-completion-rag" +: {
create:: function(engine)
local cfgVol = engine.secretVolume(
"vertexai-creds",
"./vertexai",
{
"private.json": importstr "vertexai/private.json",
}
);
local container =
engine.container("text-completion-rag")
.with_image(images.trustgraph)
.with_command([
"text-completion-vertexai",
"-p",
url.pulsar,
"-k",
$["vertexai-private-key"],
"-r",
$["vertexai-region"],
"-x",
std.toString($["vertexai-max-output-tokens"]),
"-t",
"%0.3f" % $["vertexai-temperature"],
"-m",
$["vertexai-model"],
"-i",
"non-persistent://tg/request/text-completion-rag",
"-o",
"non-persistent://tg/response/text-completion-rag",
])
.with_limits("0.5", "256M")
.with_reservations("0.1", "256M")
.with_volume_mount(cfgVol, "/vertexai");
local containerSet = engine.containers(
"text-completion-rag", [ container ]
);
local service =
engine.internalService(containerSet)
.with_port(8000, 8000, "metrics");
engine.resources([
cfgVol,
containerSet,
service,
])
}
} + prompts