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https://github.com/meta-llama/llama-stack.git
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Merge 407c3e3bad
into 632cf9eb72
This commit is contained in:
commit
172d578b20
50 changed files with 5611 additions and 508 deletions
7
llama_stack/templates/ollama/__init__.py
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7
llama_stack/templates/ollama/__init__.py
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|||
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
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# All rights reserved.
|
||||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
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||||
|
||||
from .ollama import get_distribution_template # noqa: F401
|
39
llama_stack/templates/ollama/build.yaml
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39
llama_stack/templates/ollama/build.yaml
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version: 2
|
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distribution_spec:
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description: Use (an external) Ollama server for running LLM inference
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providers:
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inference:
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- remote::ollama
|
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vector_io:
|
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- inline::faiss
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- remote::chromadb
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- remote::pgvector
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||||
safety:
|
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- inline::llama-guard
|
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agents:
|
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- inline::meta-reference
|
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telemetry:
|
||||
- inline::meta-reference
|
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eval:
|
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- inline::meta-reference
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datasetio:
|
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- remote::huggingface
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- inline::localfs
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scoring:
|
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- inline::basic
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- inline::llm-as-judge
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- inline::braintrust
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files:
|
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- inline::localfs
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post_training:
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- inline::huggingface
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tool_runtime:
|
||||
- remote::brave-search
|
||||
- remote::tavily-search
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||||
- inline::rag-runtime
|
||||
- remote::model-context-protocol
|
||||
- remote::wolfram-alpha
|
||||
image_type: conda
|
||||
additional_pip_packages:
|
||||
- aiosqlite
|
||||
- sqlalchemy[asyncio]
|
168
llama_stack/templates/ollama/doc_template.md
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168
llama_stack/templates/ollama/doc_template.md
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|
|||
# Ollama Distribution
|
||||
|
||||
The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
|
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|
||||
{{ providers_table }}
|
||||
|
||||
{% if run_config_env_vars %}
|
||||
### Environment Variables
|
||||
|
||||
The following environment variables can be configured:
|
||||
|
||||
{% for var, (default_value, description) in run_config_env_vars.items() %}
|
||||
- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
|
||||
{% endfor %}
|
||||
{% endif %}
|
||||
|
||||
{% if default_models %}
|
||||
### Models
|
||||
|
||||
The following models are available by default:
|
||||
|
||||
{% for model in default_models %}
|
||||
- `{{ model.model_id }} {{ model.doc_string }}`
|
||||
{% endfor %}
|
||||
{% endif %}
|
||||
|
||||
## Prerequisites
|
||||
|
||||
### Ollama Server
|
||||
|
||||
This distribution requires an external Ollama server to be running. You can install and run Ollama by following these steps:
|
||||
|
||||
1. **Install Ollama**: Download and install Ollama from [https://ollama.ai/](https://ollama.ai/)
|
||||
|
||||
2. **Start the Ollama server**:
|
||||
```bash
|
||||
ollama serve
|
||||
```
|
||||
By default, Ollama serves on `http://127.0.0.1:11434`
|
||||
|
||||
3. **Pull the required models**:
|
||||
```bash
|
||||
# Pull the inference model
|
||||
ollama pull meta-llama/Llama-3.2-3B-Instruct
|
||||
|
||||
# Pull the embedding model
|
||||
ollama pull all-minilm:latest
|
||||
|
||||
# (Optional) Pull the safety model for run-with-safety.yaml
|
||||
ollama pull meta-llama/Llama-Guard-3-1B
|
||||
```
|
||||
|
||||
## Supported Services
|
||||
|
||||
### Inference: Ollama
|
||||
Uses an external Ollama server for running LLM inference. The server should be accessible at the URL specified in the `OLLAMA_URL` environment variable.
|
||||
|
||||
### Vector IO: FAISS
|
||||
Provides vector storage capabilities using FAISS for embeddings and similarity search operations.
|
||||
|
||||
### Safety: Llama Guard (Optional)
|
||||
When using the `run-with-safety.yaml` configuration, provides safety checks using Llama Guard models running on the Ollama server.
|
||||
|
||||
### Agents: Meta Reference
|
||||
Provides agent execution capabilities using the meta-reference implementation.
|
||||
|
||||
### Post-Training: Hugging Face
|
||||
Supports model fine-tuning using Hugging Face integration.
|
||||
|
||||
### Tool Runtime
|
||||
Supports various external tools including:
|
||||
- Brave Search
|
||||
- Tavily Search
|
||||
- RAG Runtime
|
||||
- Model Context Protocol
|
||||
- Wolfram Alpha
|
||||
|
||||
## Running Llama Stack with Ollama
|
||||
|
||||
You can do this via Conda or venv (build code), or Docker which has a pre-built image.
|
||||
|
||||
### Via Docker
|
||||
|
||||
This method allows you to get started quickly without having to build the distribution code.
|
||||
|
||||
```bash
|
||||
LLAMA_STACK_PORT=8321
|
||||
docker run \
|
||||
-it \
|
||||
--pull always \
|
||||
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
|
||||
-v ./run.yaml:/root/my-run.yaml \
|
||||
llamastack/distribution-{{ name }} \
|
||||
--config /root/my-run.yaml \
|
||||
--port $LLAMA_STACK_PORT \
|
||||
--env OLLAMA_URL=$OLLAMA_URL \
|
||||
--env INFERENCE_MODEL=$INFERENCE_MODEL
|
||||
```
|
||||
|
||||
### Via Conda
|
||||
|
||||
```bash
|
||||
llama stack build --template ollama --image-type conda
|
||||
llama stack run ./run.yaml \
|
||||
--port 8321 \
|
||||
--env OLLAMA_URL=$OLLAMA_URL \
|
||||
--env INFERENCE_MODEL=$INFERENCE_MODEL
|
||||
```
|
||||
|
||||
### Via venv
|
||||
|
||||
If you've set up your local development environment, you can also build the image using your local virtual environment.
|
||||
|
||||
```bash
|
||||
llama stack build --template ollama --image-type venv
|
||||
llama stack run ./run.yaml \
|
||||
--port 8321 \
|
||||
--env OLLAMA_URL=$OLLAMA_URL \
|
||||
--env INFERENCE_MODEL=$INFERENCE_MODEL
|
||||
```
|
||||
|
||||
### Running with Safety
|
||||
|
||||
To enable safety checks, use the `run-with-safety.yaml` configuration:
|
||||
|
||||
```bash
|
||||
llama stack run ./run-with-safety.yaml \
|
||||
--port 8321 \
|
||||
--env OLLAMA_URL=$OLLAMA_URL \
|
||||
--env INFERENCE_MODEL=$INFERENCE_MODEL \
|
||||
--env SAFETY_MODEL=$SAFETY_MODEL
|
||||
```
|
||||
|
||||
## Example Usage
|
||||
|
||||
Once your Llama Stack server is running with Ollama, you can interact with it using the Llama Stack client:
|
||||
|
||||
```python
|
||||
from llama_stack_client import LlamaStackClient
|
||||
|
||||
client = LlamaStackClient(base_url="http://localhost:8321")
|
||||
|
||||
# Run inference
|
||||
response = client.inference.chat_completion(
|
||||
model_id="meta-llama/Llama-3.2-3B-Instruct",
|
||||
messages=[{"role": "user", "content": "Hello, how are you?"}],
|
||||
)
|
||||
print(response.completion_message.content)
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Common Issues
|
||||
|
||||
1. **Connection refused errors**: Ensure your Ollama server is running and accessible at the configured URL.
|
||||
|
||||
2. **Model not found errors**: Make sure you've pulled the required models using `ollama pull <model-name>`.
|
||||
|
||||
3. **Performance issues**: Consider using more powerful models or adjusting the Ollama server configuration for better performance.
|
||||
|
||||
### Logs
|
||||
|
||||
Check the Ollama server logs for any issues:
|
||||
```bash
|
||||
# Ollama logs are typically available in:
|
||||
# - macOS: ~/Library/Logs/Ollama/
|
||||
# - Linux: ~/.ollama/logs/
|
||||
```
|
180
llama_stack/templates/ollama/ollama.py
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180
llama_stack/templates/ollama/ollama.py
Normal file
|
@ -0,0 +1,180 @@
|
|||
# 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.
|
||||
|
||||
# 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 import ModelType
|
||||
from llama_stack.distribution.datatypes import (
|
||||
ModelInput,
|
||||
Provider,
|
||||
ShieldInput,
|
||||
ToolGroupInput,
|
||||
)
|
||||
from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
|
||||
from llama_stack.providers.inline.post_training.huggingface import HuggingFacePostTrainingConfig
|
||||
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
|
||||
|
||||
|
||||
def get_distribution_template() -> DistributionTemplate:
|
||||
providers = {
|
||||
"inference": ["remote::ollama"],
|
||||
"vector_io": ["inline::faiss", "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"],
|
||||
"files": ["inline::localfs"],
|
||||
"post_training": ["inline::huggingface"],
|
||||
"tool_runtime": [
|
||||
"remote::brave-search",
|
||||
"remote::tavily-search",
|
||||
"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_faiss = Provider(
|
||||
provider_id="faiss",
|
||||
provider_type="inline::faiss",
|
||||
config=FaissVectorIOConfig.sample_run_config(
|
||||
f"${{env.XDG_STATE_HOME:-~/.local/state}}/llama-stack/distributions/{name}"
|
||||
),
|
||||
)
|
||||
files_provider = Provider(
|
||||
provider_id="meta-reference-files",
|
||||
provider_type="inline::localfs",
|
||||
config=LocalfsFilesImplConfig.sample_run_config(
|
||||
f"${{env.XDG_DATA_HOME:-~/.local/share}}/llama-stack/distributions/{name}"
|
||||
),
|
||||
)
|
||||
posttraining_provider = Provider(
|
||||
provider_id="huggingface",
|
||||
provider_type="inline::huggingface",
|
||||
config=HuggingFacePostTrainingConfig.sample_run_config(
|
||||
f"${{env.XDG_DATA_HOME:-~/.local/share}}/llama-stack/distributions/{name}"
|
||||
),
|
||||
)
|
||||
inference_model = ModelInput(
|
||||
model_id="${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::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_faiss],
|
||||
"files": [files_provider],
|
||||
"post_training": [posttraining_provider],
|
||||
},
|
||||
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_faiss],
|
||||
"files": [files_provider],
|
||||
"post_training": [posttraining_provider],
|
||||
"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": (
|
||||
"8321",
|
||||
"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",
|
||||
),
|
||||
},
|
||||
)
|
158
llama_stack/templates/ollama/run-with-safety.yaml
Normal file
158
llama_stack/templates/ollama/run-with-safety.yaml
Normal file
|
@ -0,0 +1,158 @@
|
|||
version: 2
|
||||
image_name: ollama
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- files
|
||||
- inference
|
||||
- post_training
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: ollama
|
||||
provider_type: remote::ollama
|
||||
config:
|
||||
url: ${env.OLLAMA_URL:=http://localhost:11434}
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=${env.XDG_STATE_HOME:-~/.local/state}/llama-stack/distributions/ollama}/faiss_store.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config: {}
|
||||
- provider_id: code-scanner
|
||||
provider_type: inline::code-scanner
|
||||
config: {}
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
config: {}
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
config: {}
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
files:
|
||||
- provider_id: meta-reference-files
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
storage_dir: ${env.FILES_STORAGE_DIR:=${env.XDG_DATA_HOME:-~/.local/share}/llama-stack/distributions/ollama/files}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=${env.XDG_DATA_HOME:-~/.local/share}/llama-stack/distributions/ollama}/files_metadata.db
|
||||
post_training:
|
||||
- provider_id: huggingface
|
||||
provider_type: inline::huggingface
|
||||
config:
|
||||
checkpoint_format: huggingface
|
||||
distributed_backend: null
|
||||
device: cpu
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
config: {}
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
config: {}
|
||||
- provider_id: wolfram-alpha
|
||||
provider_type: remote::wolfram-alpha
|
||||
config:
|
||||
api_key: ${env.WOLFRAM_ALPHA_API_KEY:=}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: ${env.INFERENCE_MODEL}
|
||||
provider_id: ollama
|
||||
model_type: llm
|
||||
- metadata: {}
|
||||
model_id: ${env.SAFETY_MODEL}
|
||||
provider_id: ollama
|
||||
model_type: llm
|
||||
- metadata:
|
||||
embedding_dimension: 384
|
||||
model_id: all-MiniLM-L6-v2
|
||||
provider_id: ollama
|
||||
provider_model_id: all-minilm:latest
|
||||
model_type: embedding
|
||||
shields:
|
||||
- shield_id: ${env.SAFETY_MODEL}
|
||||
provider_id: llama-guard
|
||||
- shield_id: CodeScanner
|
||||
provider_id: code-scanner
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
- toolgroup_id: builtin::wolfram_alpha
|
||||
provider_id: wolfram-alpha
|
||||
server:
|
||||
port: 8321
|
148
llama_stack/templates/ollama/run.yaml
Normal file
148
llama_stack/templates/ollama/run.yaml
Normal file
|
@ -0,0 +1,148 @@
|
|||
version: 2
|
||||
image_name: ollama
|
||||
apis:
|
||||
- agents
|
||||
- datasetio
|
||||
- eval
|
||||
- files
|
||||
- inference
|
||||
- post_training
|
||||
- safety
|
||||
- scoring
|
||||
- telemetry
|
||||
- tool_runtime
|
||||
- vector_io
|
||||
providers:
|
||||
inference:
|
||||
- provider_id: ollama
|
||||
provider_type: remote::ollama
|
||||
config:
|
||||
url: ${env.OLLAMA_URL:=http://localhost:11434}
|
||||
vector_io:
|
||||
- provider_id: faiss
|
||||
provider_type: inline::faiss
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=${env.XDG_STATE_HOME:-~/.local/state}/llama-stack/distributions/ollama}/faiss_store.db
|
||||
safety:
|
||||
- provider_id: llama-guard
|
||||
provider_type: inline::llama-guard
|
||||
config:
|
||||
excluded_categories: []
|
||||
agents:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
persistence_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/agents_store.db
|
||||
responses_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/responses_store.db
|
||||
telemetry:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
service_name: "${env.OTEL_SERVICE_NAME:=\u200B}"
|
||||
sinks: ${env.TELEMETRY_SINKS:=console,sqlite}
|
||||
sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/trace_store.db
|
||||
otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=}
|
||||
eval:
|
||||
- provider_id: meta-reference
|
||||
provider_type: inline::meta-reference
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/meta_reference_eval.db
|
||||
datasetio:
|
||||
- provider_id: huggingface
|
||||
provider_type: remote::huggingface
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/huggingface_datasetio.db
|
||||
- provider_id: localfs
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
kvstore:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/localfs_datasetio.db
|
||||
scoring:
|
||||
- provider_id: basic
|
||||
provider_type: inline::basic
|
||||
config: {}
|
||||
- provider_id: llm-as-judge
|
||||
provider_type: inline::llm-as-judge
|
||||
config: {}
|
||||
- provider_id: braintrust
|
||||
provider_type: inline::braintrust
|
||||
config:
|
||||
openai_api_key: ${env.OPENAI_API_KEY:=}
|
||||
files:
|
||||
- provider_id: meta-reference-files
|
||||
provider_type: inline::localfs
|
||||
config:
|
||||
storage_dir: ${env.FILES_STORAGE_DIR:=${env.XDG_DATA_HOME:-~/.local/share}/llama-stack/distributions/ollama/files}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=${env.XDG_DATA_HOME:-~/.local/share}/llama-stack/distributions/ollama}/files_metadata.db
|
||||
post_training:
|
||||
- provider_id: huggingface
|
||||
provider_type: inline::huggingface
|
||||
config:
|
||||
checkpoint_format: huggingface
|
||||
distributed_backend: null
|
||||
device: cpu
|
||||
tool_runtime:
|
||||
- provider_id: brave-search
|
||||
provider_type: remote::brave-search
|
||||
config:
|
||||
api_key: ${env.BRAVE_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: tavily-search
|
||||
provider_type: remote::tavily-search
|
||||
config:
|
||||
api_key: ${env.TAVILY_SEARCH_API_KEY:=}
|
||||
max_results: 3
|
||||
- provider_id: rag-runtime
|
||||
provider_type: inline::rag-runtime
|
||||
config: {}
|
||||
- provider_id: model-context-protocol
|
||||
provider_type: remote::model-context-protocol
|
||||
config: {}
|
||||
- provider_id: wolfram-alpha
|
||||
provider_type: remote::wolfram-alpha
|
||||
config:
|
||||
api_key: ${env.WOLFRAM_ALPHA_API_KEY:=}
|
||||
metadata_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/registry.db
|
||||
inference_store:
|
||||
type: sqlite
|
||||
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ollama}/inference_store.db
|
||||
models:
|
||||
- metadata: {}
|
||||
model_id: ${env.INFERENCE_MODEL}
|
||||
provider_id: ollama
|
||||
model_type: llm
|
||||
- metadata:
|
||||
embedding_dimension: 384
|
||||
model_id: all-MiniLM-L6-v2
|
||||
provider_id: ollama
|
||||
provider_model_id: all-minilm:latest
|
||||
model_type: embedding
|
||||
shields: []
|
||||
vector_dbs: []
|
||||
datasets: []
|
||||
scoring_fns: []
|
||||
benchmarks: []
|
||||
tool_groups:
|
||||
- toolgroup_id: builtin::websearch
|
||||
provider_id: tavily-search
|
||||
- toolgroup_id: builtin::rag
|
||||
provider_id: rag-runtime
|
||||
- toolgroup_id: builtin::wolfram_alpha
|
||||
provider_id: wolfram-alpha
|
||||
server:
|
||||
port: 8321
|
Loading…
Add table
Add a link
Reference in a new issue