llama-stack-mirror/llama_stack/templates/ollama/ollama.py
Ashwin Bharambe abfbaf3c1b
refactor(test): move tools, evals, datasetio, scoring and post training tests (#1401)
All of the tests from `llama_stack/providers/tests/` are now moved to
`tests/integration`.

I converted the `tools`, `scoring` and `datasetio` tests to use API.
However, `eval` and `post_training` proved to be a bit challenging to
leaving those. I think `post_training` should be relatively
straightforward also.

As part of this, I noticed that `wolfram_alpha` tool wasn't added to
some of our commonly used distros so I added it. I am going to remove a
lot of code duplication from distros next so while this looks like a
one-off right now, it will go away and be there uniformly for all
distros.
2025-03-04 14:53:47 -08:00

157 lines
5.4 KiB
Python

# 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 pathlib import Path
from llama_stack.apis.models.models import ModelType
from llama_stack.distribution.datatypes import (
ModelInput,
Provider,
ShieldInput,
ToolGroupInput,
)
from llama_stack.providers.inline.vector_io.sqlite_vec.config import SQLiteVectorIOConfig
from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
def get_distribution_template() -> DistributionTemplate:
providers = {
"inference": ["remote::ollama"],
"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",
"remote::wolfram-alpha",
],
}
name = "ollama"
inference_provider = Provider(
provider_id="ollama",
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}"),
)
inference_model = ModelInput(
model_id="${env.INFERENCE_MODEL}",
provider_id="ollama",
)
safety_model = ModelInput(
model_id="${env.SAFETY_MODEL}",
provider_id="ollama",
)
embedding_model = ModelInput(
model_id="all-MiniLM-L6-v2",
provider_id="ollama",
provider_model_id="all-minilm:latest",
model_type=ModelType.embedding,
metadata={
"embedding_dimension": 384,
},
)
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",
),
ToolGroupInput(
toolgroup_id="builtin::wolfram_alpha",
provider_id="wolfram-alpha",
),
]
return DistributionTemplate(
name=name,
distro_type="self_hosted",
description="Use (an external) Ollama server for running LLM inference",
container_image=None,
template_path=Path(__file__).parent / "doc_template.md",
providers=providers,
run_configs={
"run.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"vector_io": [vector_io_provider_sqlite],
},
default_models=[inference_model, embedding_model],
default_tool_groups=default_tool_groups,
),
"run-with-safety.yaml": RunConfigSettings(
provider_overrides={
"inference": [inference_provider],
"vector_io": [vector_io_provider_sqlite],
"safety": [
Provider(
provider_id="llama-guard",
provider_type="inline::llama-guard",
config={},
),
Provider(
provider_id="code-scanner",
provider_type="inline::code-scanner",
config={},
),
],
},
default_models=[
inference_model,
safety_model,
embedding_model,
],
default_shields=[
ShieldInput(
shield_id="${env.SAFETY_MODEL}",
provider_id="llama-guard",
),
ShieldInput(
shield_id="CodeScanner",
provider_id="code-scanner",
),
],
default_tool_groups=default_tool_groups,
),
},
run_config_env_vars={
"LLAMA_STACK_PORT": (
"5001",
"Port for the Llama Stack distribution server",
),
"OLLAMA_URL": (
"http://127.0.0.1:11434",
"URL of the Ollama server",
),
"INFERENCE_MODEL": (
"meta-llama/Llama-3.2-3B-Instruct",
"Inference model loaded into the Ollama server",
),
"SAFETY_MODEL": (
"meta-llama/Llama-Guard-3-1B",
"Safety model loaded into the Ollama server",
),
},
)