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Merge branch 'meta-llama:main' into feat/litellm_sambanova_usage

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Jorge Piedrahita Ortiz 2025-03-12 15:12:42 -05:00 • committed by GitHub
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90 changed files with 3142 additions and 586 deletions
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10
llama_stack/templates/ci-tests/run.yaml
View file

@ -120,16 +120,6 @@ models:
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p1-405b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.2-1B-Instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-3b-instruct
provider_id: fireworks

10
llama_stack/templates/dev/run.yaml
View file

@ -178,16 +178,6 @@ models:
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p1-405b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.2-1B-Instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-3b-instruct
provider_id: fireworks

10
llama_stack/templates/fireworks/run-with-safety.yaml
View file

@ -132,16 +132,6 @@ models:
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p1-405b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.2-1B-Instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-3b-instruct
provider_id: fireworks

10
llama_stack/templates/fireworks/run.yaml
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@ -126,16 +126,6 @@ models:
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p1-405b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.2-1B-Instruct
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama-v3p2-1b-instruct
model_type: llm
- metadata: {}
model_id: accounts/fireworks/models/llama-v3p2-3b-instruct
provider_id: fireworks

2
llama_stack/templates/ollama/build.yaml
View file

@ -5,7 +5,7 @@ distribution_spec:
inference:
- remote::ollama
vector_io:
- inline::sqlite-vec
- inline::faiss
- remote::chromadb
- remote::pgvector
safety:

2
llama_stack/templates/ollama/doc_template.md
View file

@ -119,7 +119,7 @@ llama stack run ./run-with-safety.yaml \
### (Optional) Update Model Serving Configuration
```{note}
Please check the [model_entries](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/ollama.py#L45) for the supported Ollama models.
Please check the [model_entries](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/inference/ollama/models.py) for the supported Ollama models.
```
To serve a new model with `ollama`

16
llama_stack/templates/ollama/ollama.py
View file

@ -13,7 +13,7 @@ from llama_stack.distribution.datatypes import (
ShieldInput,
ToolGroupInput,
)
from llama_stack.providers.inline.vector_io.sqlite_vec.config import SQLiteVectorIOConfig
from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@ -21,7 +21,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
def get_distribution_template() -> DistributionTemplate:
providers = {
"inference": ["remote::ollama"],
"vector_io": ["inline::sqlite-vec", "remote::chromadb", "remote::pgvector"],
"vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
"safety": ["inline::llama-guard"],
"agents": ["inline::meta-reference"],
"telemetry": ["inline::meta-reference"],
@ -43,10 +43,10 @@ def get_distribution_template() -> DistributionTemplate:
provider_type="remote::ollama",
config=OllamaImplConfig.sample_run_config(),
)
vector_io_provider_sqlite = Provider(
provider_id="sqlite-vec",
provider_type="inline::sqlite-vec",
config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
vector_io_provider_faiss = Provider(
provider_id="faiss",
provider_type="inline::faiss",
config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
)
inference_model = ModelInput(
@ -96,7 +96,7 @@ def get_distribution_template() -> DistributionTemplate:
"run.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"vector_io": [vector_io_provider_sqlite],
"vector_io": [vector_io_provider_faiss],
},
default_models=[inference_model, embedding_model],
default_tool_groups=default_tool_groups,
@ -104,7 +104,7 @@ def get_distribution_template() -> DistributionTemplate:
"run-with-safety.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"vector_io": [vector_io_provider_sqlite],
"vector_io": [vector_io_provider_faiss],
"safety": [
Provider(
provider_id="llama-guard",

9
llama_stack/templates/ollama/run-with-safety.yaml
View file

@ -17,10 +17,13 @@ providers:
config:
url: ${env.OLLAMA_URL:http://localhost:11434}
vector_io:
- provider_id: sqlite-vec
provider_type: inline::sqlite-vec
- provider_id: faiss
provider_type: inline::faiss
config:
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/faiss_store.db
safety:
- provider_id: llama-guard
provider_type: inline::llama-guard

9
llama_stack/templates/ollama/run.yaml
View file

@ -17,10 +17,13 @@ providers:
config:
url: ${env.OLLAMA_URL:http://localhost:11434}
vector_io:
- provider_id: sqlite-vec
provider_type: inline::sqlite-vec
- provider_id: faiss
provider_type: inline::faiss
config:
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/faiss_store.db
safety:
- provider_id: llama-guard
provider_type: inline::llama-guard

7
llama_stack/templates/open-benchmark/__init__.py Normal file
View file

@ -0,0 +1,7 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from .open_benchmark import get_distribution_template # noqa: F401

300
llama_stack/templates/open-benchmark/open_benchmark.py Normal file
View file

@ -0,0 +1,300 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Dict, List, Tuple
from llama_stack.apis.common.content_types import URL
from llama_stack.apis.models.models import ModelType
from llama_stack.distribution.datatypes import (
BenchmarkInput,
DatasetInput,
ModelInput,
Provider,
ShieldInput,
ToolGroupInput,
)
from llama_stack.providers.inline.vector_io.sqlite_vec.config import (
SQLiteVectorIOConfig,
)
from llama_stack.providers.remote.inference.anthropic.config import AnthropicConfig
from llama_stack.providers.remote.inference.gemini.config import GeminiConfig
from llama_stack.providers.remote.inference.groq.config import GroqConfig
from llama_stack.providers.remote.inference.openai.config import OpenAIConfig
from llama_stack.providers.remote.inference.together.config import TogetherImplConfig
from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
from llama_stack.providers.remote.vector_io.pgvector.config import (
PGVectorVectorIOConfig,
)
from llama_stack.providers.utils.inference.model_registry import ProviderModelEntry
from llama_stack.templates.template import (
DistributionTemplate,
RunConfigSettings,
get_model_registry,
)
def get_inference_providers() -> Tuple[List[Provider], Dict[str, List[ProviderModelEntry]]]:
# in this template, we allow each API key to be optional
providers = [
(
"openai",
[
ProviderModelEntry(
provider_model_id="openai/gpt-4o",
model_type=ModelType.llm,
)
],
OpenAIConfig.sample_run_config(api_key="${env.OPENAI_API_KEY:}"),
),
(
"anthropic",
[
ProviderModelEntry(
provider_model_id="anthropic/claude-3-5-sonnet-latest",
model_type=ModelType.llm,
)
],
AnthropicConfig.sample_run_config(api_key="${env.ANTHROPIC_API_KEY:}"),
),
(
"gemini",
[
ProviderModelEntry(
provider_model_id="gemini/gemini-1.5-flash",
model_type=ModelType.llm,
)
],
GeminiConfig.sample_run_config(api_key="${env.GEMINI_API_KEY:}"),
),
(
"groq",
[],
GroqConfig.sample_run_config(api_key="${env.GROQ_API_KEY:}"),
),
(
"together",
[],
TogetherImplConfig.sample_run_config(api_key="${env.TOGETHER_API_KEY:}"),
),
]
inference_providers = []
available_models = {}
for provider_id, model_entries, config in providers:
inference_providers.append(
Provider(
provider_id=provider_id,
provider_type=f"remote::{provider_id}",
config=config,
)
)
available_models[provider_id] = model_entries
return inference_providers, available_models
def get_distribution_template() -> DistributionTemplate:
inference_providers, available_models = get_inference_providers()
providers = {
"inference": [p.provider_type for p in inference_providers],
"vector_io": ["inline::sqlite-vec", "remote::chromadb", "remote::pgvector"],
"safety": ["inline::llama-guard"],
"agents": ["inline::meta-reference"],
"telemetry": ["inline::meta-reference"],
"eval": ["inline::meta-reference"],
"datasetio": ["remote::huggingface", "inline::localfs"],
"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
"tool_runtime": [
"remote::brave-search",
"remote::tavily-search",
"inline::code-interpreter",
"inline::rag-runtime",
"remote::model-context-protocol",
],
}
name = "open-benchmark"
vector_io_providers = [
Provider(
provider_id="sqlite-vec",
provider_type="inline::sqlite-vec",
config=SQLiteVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
),
Provider(
provider_id="${env.ENABLE_CHROMADB+chromadb}",
provider_type="remote::chromadb",
config=ChromaVectorIOConfig.sample_run_config(url="${env.CHROMADB_URL:}"),
),
Provider(
provider_id="${env.ENABLE_PGVECTOR+pgvector}",
provider_type="remote::pgvector",
config=PGVectorVectorIOConfig.sample_run_config(
db="${env.PGVECTOR_DB:}",
user="${env.PGVECTOR_USER:}",
password="${env.PGVECTOR_PASSWORD:}",
),
),
]
default_tool_groups = [
ToolGroupInput(
toolgroup_id="builtin::websearch",
provider_id="tavily-search",
),
ToolGroupInput(
toolgroup_id="builtin::rag",
provider_id="rag-runtime",
),
ToolGroupInput(
toolgroup_id="builtin::code_interpreter",
provider_id="code-interpreter",
),
]
default_models = get_model_registry(available_models) + [
ModelInput(
model_id="meta-llama/Llama-3.3-70B-Instruct",
provider_id="groq",
provider_model_id="groq/llama-3.3-70b-versatile",
model_type=ModelType.llm,
),
ModelInput(
model_id="meta-llama/Llama-3.1-405B-Instruct",
provider_id="together",
provider_model_id="meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
model_type=ModelType.llm,
),
]
default_datasets = [
DatasetInput(
dataset_id="simpleqa",
provider_id="huggingface",
url=URL(uri="https://huggingface.co/datasets/llamastack/simpleqa"),
metadata={
"path": "llamastack/simpleqa",
"split": "train",
},
dataset_schema={
"input_query": {"type": "string"},
"expected_answer": {"type": "string"},
"chat_completion_input": {"type": "string"},
},
),
DatasetInput(
dataset_id="mmlu_cot",
provider_id="huggingface",
url=URL(uri="https://huggingface.co/datasets/llamastack/mmlu_cot"),
metadata={
"path": "llamastack/mmlu_cot",
"name": "all",
"split": "test",
},
dataset_schema={
"input_query": {"type": "string"},
"expected_answer": {"type": "string"},
"chat_completion_input": {"type": "string"},
},
),
DatasetInput(
dataset_id="gpqa_cot",
provider_id="huggingface",
url=URL(uri="https://huggingface.co/datasets/llamastack/gpqa_0shot_cot"),
metadata={
"path": "llamastack/gpqa_0shot_cot",
"name": "gpqa_main",
"split": "train",
},
dataset_schema={
"input_query": {"type": "string"},
"expected_answer": {"type": "string"},
"chat_completion_input": {"type": "string"},
},
),
DatasetInput(
dataset_id="math_500",
provider_id="huggingface",
url=URL(uri="https://huggingface.co/datasets/llamastack/math_500"),
metadata={
"path": "llamastack/math_500",
"split": "test",
},
dataset_schema={
"input_query": {"type": "string"},
"expected_answer": {"type": "string"},
"chat_completion_input": {"type": "string"},
},
),
]
default_benchmarks = [
BenchmarkInput(
benchmark_id="meta-reference-simpleqa",
dataset_id="simpleqa",
scoring_functions=["llm-as-judge::405b-simpleqa"],
),
BenchmarkInput(
benchmark_id="meta-reference-mmlu-cot",
dataset_id="mmlu_cot",
scoring_functions=["basic::regex_parser_multiple_choice_answer"],
),
BenchmarkInput(
benchmark_id="meta-reference-gpqa-cot",
dataset_id="gpqa_cot",
scoring_functions=["basic::regex_parser_multiple_choice_answer"],
),
BenchmarkInput(
benchmark_id="meta-reference-math-500",
dataset_id="math_500",
scoring_functions=["basic::regex_parser_math_response"],
),
]
return DistributionTemplate(
name=name,
distro_type="self_hosted",
description="Distribution for running open benchmarks",
container_image=None,
template_path=None,
providers=providers,
available_models_by_provider=available_models,
run_configs={
"run.yaml": RunConfigSettings(
provider_overrides={
"inference": inference_providers,
"vector_io": vector_io_providers,
},
default_models=default_models,
default_tool_groups=default_tool_groups,
default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
default_datasets=default_datasets,
default_benchmarks=default_benchmarks,
),
},
run_config_env_vars={
"LLAMA_STACK_PORT": (
"5001",
"Port for the Llama Stack distribution server",
),
"TOGETHER_API_KEY": (
"",
"Together API Key",
),
"OPENAI_API_KEY": (
"",
"OpenAI API Key",
),
"GEMINI_API_KEY": (
"",
"Gemini API Key",
),
"ANTHROPIC_API_KEY": (
"",
"Anthropic API Key",
),
"GROQ_API_KEY": (
"",
"Groq API Key",
),
},
)

152
llama_stack/templates/open-benchmark/run.yaml
View file

@ -33,12 +33,12 @@ providers:
provider_type: remote::together
config:
url: https://api.together.xyz/v1
api_key: ${env.TOGETHER_API_KEY}
api_key: ${env.TOGETHER_API_KEY:}
vector_io:
- provider_id: sqlite-vec
provider_type: inline::sqlite-vec
config:
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/dev}/sqlite_vec.db
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/open-benchmark}/sqlite_vec.db
- provider_id: ${env.ENABLE_CHROMADB+chromadb}
provider_type: remote::chromadb
config:
@ -62,14 +62,14 @@ providers:
persistence_store:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/dev}/agents_store.db
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/open-benchmark}/agents_store.db
telemetry:
- provider_id: meta-reference
provider_type: inline::meta-reference
config:
service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
sinks: ${env.TELEMETRY_SINKS:console,sqlite}
sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/dev/trace_store.db}
sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/open-benchmark/trace_store.db}
eval:
- provider_id: meta-reference
provider_type: inline::meta-reference
@ -114,18 +114,13 @@ providers:
config: {}
metadata_store:
type: sqlite
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/dev}/registry.db
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/open-benchmark}/registry.db
models:
- metadata: {}
model_id: openai/gpt-4o
provider_id: openai
provider_model_id: openai/gpt-4o
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.1-405B-Instruct
provider_id: together
provider_model_id: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo
model_type: llm
- metadata: {}
model_id: anthropic/claude-3-5-sonnet-latest
provider_id: anthropic
@ -141,66 +136,95 @@ models:
provider_id: groq
provider_model_id: groq/llama-3.3-70b-versatile
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-3.1-405B-Instruct
provider_id: together
provider_model_id: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo
model_type: llm
shields:
- shield_id: meta-llama/Llama-Guard-3-8B
vector_dbs: []
datasets:
- dataset_id: simpleqa
provider_id: huggingface
url:
uri: https://huggingface.co/datasets/llamastack/simpleqa
metadata:
path: llamastack/simpleqa
name:
split: train
dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
- dataset_id: mmlu_cot
provider_id: huggingface
url:
uri: https://huggingface.co/datasets/llamastack/mmlu_cot
metadata:
path: llamastack/mmlu_cot
name: all
split: test
dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
- dataset_id: gpqa_cot
provider_id: huggingface
url:
uri: https://huggingface.co/datasets/llamastack/gpqa_0shot_cot
metadata:
path: llamastack/gpqa_0shot_cot
name: gpqa_main
split: train
dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
- dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
url:
uri: https://huggingface.co/datasets/llamastack/simpleqa
metadata:
path: llamastack/simpleqa
split: train
dataset_id: simpleqa
provider_id: huggingface
- dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
url:
uri: https://huggingface.co/datasets/llamastack/mmlu_cot
metadata:
path: llamastack/mmlu_cot
name: all
split: test
dataset_id: mmlu_cot
provider_id: huggingface
- dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
url:
uri: https://huggingface.co/datasets/llamastack/gpqa_0shot_cot
metadata:
path: llamastack/gpqa_0shot_cot
name: gpqa_main
split: train
dataset_id: gpqa_cot
provider_id: huggingface
- dataset_schema:
input_query:
type: string
expected_answer:
type: string
chat_completion_input:
type: string
url:
uri: https://huggingface.co/datasets/llamastack/math_500
metadata:
path: llamastack/math_500
split: test
dataset_id: math_500
provider_id: huggingface
scoring_fns: []
benchmarks:
- benchmark_id: meta-reference-simpleqa
dataset_id: simpleqa
scoring_functions: ["llm-as-judge::405b-simpleqa"]
- benchmark_id: meta-reference-mmlu-cot
dataset_id: mmlu_cot
scoring_functions: ["basic::regex_parser_multiple_choice_answer"]
- benchmark_id: meta-reference-gpqa-cot
dataset_id: gpqa_cot
scoring_functions: ["basic::regex_parser_multiple_choice_answer"]
- dataset_id: simpleqa
scoring_functions:
- llm-as-judge::405b-simpleqa
metadata: {}
benchmark_id: meta-reference-simpleqa
- dataset_id: mmlu_cot
scoring_functions:
- basic::regex_parser_multiple_choice_answer
metadata: {}
benchmark_id: meta-reference-mmlu-cot
- dataset_id: gpqa_cot
scoring_functions:
- basic::regex_parser_multiple_choice_answer
metadata: {}
benchmark_id: meta-reference-gpqa-cot
- dataset_id: math_500
scoring_functions:
- basic::regex_parser_math_response
metadata: {}
benchmark_id: meta-reference-math-500
tool_groups:
- toolgroup_id: builtin::websearch
provider_id: tavily-search

12
llama_stack/templates/template.py
View file

@ -14,7 +14,9 @@ from pydantic import BaseModel, Field
from llama_stack.apis.models.models import ModelType
from llama_stack.distribution.datatypes import (
Api,
BenchmarkInput,
BuildConfig,
DatasetInput,
DistributionSpec,
ModelInput,
Provider,
@ -28,7 +30,9 @@ from llama_stack.providers.utils.inference.model_registry import ProviderModelEn
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
def get_model_registry(available_models: Dict[str, List[ProviderModelEntry]]) -> List[ModelInput]:
def get_model_registry(
available_models: Dict[str, List[ProviderModelEntry]],
) -> List[ModelInput]:
models = []
for provider_id, entries in available_models.items():
for entry in entries:
@ -56,6 +60,8 @@ class RunConfigSettings(BaseModel):
default_models: Optional[List[ModelInput]] = None
default_shields: Optional[List[ShieldInput]] = None
default_tool_groups: Optional[List[ToolGroupInput]] = None
default_datasets: Optional[List[DatasetInput]] = None
default_benchmarks: Optional[List[BenchmarkInput]] = None
def run_config(
self,
@ -113,6 +119,8 @@ class RunConfigSettings(BaseModel):
models=self.default_models or [],
shields=self.default_shields or [],
tool_groups=self.default_tool_groups or [],
datasets=self.default_datasets or [],
benchmarks=self.default_benchmarks or [],
)
@ -187,7 +195,7 @@ class DistributionTemplate(BaseModel):
default_models.append(
DefaultModel(
model_id=model_entry.provider_model_id,
doc_string=f"({' -- '.join(doc_parts)})" if doc_parts else "",
doc_string=(f"({' -- '.join(doc_parts)})" if doc_parts else ""),
)
)

2
llama_stack/templates/together/run-with-safety.yaml
View file

@ -16,7 +16,7 @@ providers:
provider_type: remote::together
config:
url: https://api.together.xyz/v1
api_key: ${env.TOGETHER_API_KEY}
api_key: ${env.TOGETHER_API_KEY:}
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}

2
llama_stack/templates/together/run.yaml
View file

@ -16,7 +16,7 @@ providers:
provider_type: remote::together
config:
url: https://api.together.xyz/v1
api_key: ${env.TOGETHER_API_KEY}
api_key: ${env.TOGETHER_API_KEY:}
- provider_id: sentence-transformers
provider_type: inline::sentence-transformers
config: {}