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LM Studio inference integration
Co-authored-by: Rugved Somwanshi <rugved@lmstudio.ai>
This commit is contained in:
parent
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commit
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16 changed files with 1096 additions and 0 deletions
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@ -344,6 +344,38 @@
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"sentence-transformers --no-deps",
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"torch torchvision --index-url https://download.pytorch.org/whl/cpu"
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],
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"lmstudio": [
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"aiosqlite",
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"autoevals",
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"blobfile",
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"chardet",
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"chromadb-client",
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"datasets",
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"faiss-cpu",
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"fastapi",
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"fire",
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"httpx",
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"lmstudio",
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"matplotlib",
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"nltk",
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"numpy",
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"openai",
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"opentelemetry-exporter-otlp-proto-http",
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"opentelemetry-sdk",
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"pandas",
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"pillow",
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"psycopg2-binary",
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"pymongo",
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"pypdf",
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"redis",
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"requests",
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"scikit-learn",
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"scipy",
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"sentencepiece",
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"tqdm",
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"transformers",
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"uvicorn"
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],
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"meta-reference-gpu": [
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"accelerate",
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"aiosqlite",
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7
llama_stack/templates/lmstudio/__init__.py
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7
llama_stack/templates/lmstudio/__init__.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from .lmstudio import get_distribution_template # noqa: F401
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31
llama_stack/templates/lmstudio/build.yaml
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31
llama_stack/templates/lmstudio/build.yaml
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version: '2'
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distribution_spec:
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description: Use LM Studio for running LLM inference
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providers:
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inference:
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- remote::lmstudio
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safety:
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- inline::llama-guard
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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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agents:
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- 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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telemetry:
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- inline::meta-reference
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tool_runtime:
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- remote::brave-search
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- remote::tavily-search
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- inline::code-interpreter
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- inline::rag-runtime
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image_type: conda
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58
llama_stack/templates/lmstudio/doc_template.md
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58
llama_stack/templates/lmstudio/doc_template.md
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# LM Studio Distribution
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The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
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{{ providers_table }}
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{% if run_config_env_vars %}
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### Environment Variables
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The following environment variables can be configured:
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{% for var, (default_value, description) in run_config_env_vars.items() %}
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- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
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{% endfor %}
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{% endif %}
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{% if default_models %}
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### Models
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The following models are available by default:
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{% for model in default_models %}
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- `{{ model.model_id }} {{ model.doc_string }}`
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{% endfor %}
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{% endif %}
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## Set up LM Studio
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Download LM Studio from [https://lmstudio.ai/download](https://lmstudio.ai/download). Start the server by opening LM Studio and navigating to the `Developer` Tab, or, run the CLI command `lms server start`.
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## Running Llama Stack with LM Studio
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You can do this via Conda (build code) or Docker which has a pre-built image.
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### Via Docker
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This method allows you to get started quickly without having to build the distribution code.
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```bash
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LLAMA_STACK_PORT=5001
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docker run \
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-it \
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-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
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-v ./run.yaml:/root/my-run.yaml \
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llamastack/distribution-{{ name }} \
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--yaml-config /root/my-run.yaml \
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--port $LLAMA_STACK_PORT
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```
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### Via Conda
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```bash
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llama stack build --template lmstudio --image-type conda
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llama stack run ./run.yaml \
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--port 5001
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```
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89
llama_stack/templates/lmstudio/lmstudio.py
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89
llama_stack/templates/lmstudio/lmstudio.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from pathlib import Path
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from llama_stack.distribution.datatypes import Provider, ToolGroupInput
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from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig
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from llama_stack.providers.remote.inference.lmstudio import LMStudioImplConfig
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from llama_stack.providers.remote.inference.lmstudio.models import MODEL_ENTRIES
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from llama_stack.templates.template import DistributionTemplate, RunConfigSettings, get_model_registry
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def get_distribution_template() -> DistributionTemplate:
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providers = {
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"inference": ["remote::lmstudio"],
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"safety": ["inline::llama-guard"],
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"vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
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"agents": ["inline::meta-reference"],
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"eval": ["inline::meta-reference"],
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"datasetio": ["remote::huggingface", "inline::localfs"],
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"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
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"telemetry": ["inline::meta-reference"],
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"tool_runtime": [
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"remote::tavily-search",
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"inline::code-interpreter",
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"inline::rag-runtime",
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],
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}
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name = "lmstudio"
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lmstudio_provider = Provider(
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provider_id="lmstudio",
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provider_type="remote::lmstudio",
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config=LMStudioImplConfig.sample_run_config(),
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)
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available_models = {
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"lmstudio": MODEL_ENTRIES,
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}
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default_models = get_model_registry(available_models)
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vector_io_provider = Provider(
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provider_id="faiss",
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provider_type="inline::faiss",
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config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
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)
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default_tool_groups = [
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ToolGroupInput(
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toolgroup_id="builtin::websearch",
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provider_id="tavily-search",
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),
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ToolGroupInput(
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toolgroup_id="builtin::rag",
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provider_id="rag-runtime",
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),
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ToolGroupInput(
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toolgroup_id="builtin::code_interpreter",
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provider_id="code-interpreter",
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),
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]
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return DistributionTemplate(
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name="lmstudio",
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distro_type="self_hosted",
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description="Use LM Studio for running LLM inference",
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container_image=None,
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template_path=Path(__file__).parent / "doc_template.md",
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providers=providers,
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available_models_by_provider=available_models,
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run_configs={
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"run.yaml": RunConfigSettings(
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provider_overrides={
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"inference": [lmstudio_provider],
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"vector_io": [vector_io_provider],
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},
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default_models=default_models,
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default_shields=[],
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default_tool_groups=default_tool_groups,
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),
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},
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run_config_env_vars={
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"LLAMA_STACK_PORT": (
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"5001",
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"Port for the Llama Stack distribution server",
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),
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},
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)
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44
llama_stack/templates/lmstudio/report.md
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44
llama_stack/templates/lmstudio/report.md
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# Report for cerebras distribution
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## Supported Models
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| Model Descriptor | cerebras |
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|:---|:---|
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| meta-llama/Llama-3-8B-Instruct | ✅ |
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| meta-llama/Llama-3-70B-Instruct | ✅ |
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| meta-llama/Llama-3.1-8B-Instruct | ✅ |
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| meta-llama/Llama-3.1-70B-Instruct | ✅ |
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| meta-llama/Llama-3.1-405B-Instruct-FP8 | ✅ |
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| meta-llama/Llama-3.2-1B-Instruct | ✅ |
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| meta-llama/Llama-3.2-3B-Instruct | ✅ |
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| meta-llama/Llama-3.2-11B-Vision-Instruct | ❌ |
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| meta-llama/Llama-3.2-90B-Vision-Instruct | ❌ |
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| meta-llama/Llama-3.3-70B-Instruct | ✅ |
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| meta-llama/Llama-Guard-3-11B-Vision | ❌ |
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| meta-llama/Llama-Guard-3-1B | ❌ |
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| meta-llama/Llama-Guard-3-8B | ❌ |
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| meta-llama/Llama-Guard-2-8B | ❌ |
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## Inference
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| Model | API | Capability | Test | Status |
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|:----- |:-----|:-----|:-----|:-----|
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| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
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| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ❌ |
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| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ❌ |
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| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
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| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
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| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
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| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
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| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
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| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ❌ |
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## Vector IO
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| API | Capability | Test | Status |
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|:-----|:-----|:-----|:-----|
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| /retrieve | | test_vector_db_retrieve | ✅ |
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## Agents
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| API | Capability | Test | Status |
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|:-----|:-----|:-----|:-----|
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| /create_agent_turn | rag | test_rag_agent | ❓ |
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| /create_agent_turn | custom_tool | test_custom_tool | ❓ |
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| /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ❓ |
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158
llama_stack/templates/lmstudio/run.yaml
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158
llama_stack/templates/lmstudio/run.yaml
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version: '2'
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image_name: lmstudio
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apis:
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- agents
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- datasetio
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- eval
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- inference
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- safety
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- scoring
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- telemetry
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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: lmstudio
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provider_type: remote::lmstudio
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config:
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url: localhost:1234
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config:
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excluded_categories: []
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vector_io:
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- provider_id: faiss
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provider_type: inline::faiss
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/faiss_store.db
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence_store:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/agents_store.db
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eval:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/meta_reference_eval.db
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datasetio:
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- provider_id: huggingface
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provider_type: remote::huggingface
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/huggingface_datasetio.db
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- provider_id: localfs
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provider_type: inline::localfs
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/localfs_datasetio.db
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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config: {}
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- provider_id: llm-as-judge
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provider_type: inline::llm-as-judge
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config: {}
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- provider_id: braintrust
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provider_type: inline::braintrust
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config:
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openai_api_key: ${env.OPENAI_API_KEY:}
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
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sinks: ${env.TELEMETRY_SINKS:console,sqlite}
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sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/lmstudio/trace_store.db}
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tool_runtime:
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- provider_id: tavily-search
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provider_type: remote::tavily-search
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config:
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api_key: ${env.TAVILY_SEARCH_API_KEY:}
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max_results: 3
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- provider_id: code-interpreter
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provider_type: inline::code-interpreter
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config: {}
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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config: {}
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/lmstudio}/registry.db
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models:
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- metadata: {}
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model_id: meta-llama-3-8b-instruct
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provider_id: lmstudio
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provider_model_id: meta-llama-3-8b-instruct
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model_type: llm
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- metadata: {}
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model_id: meta-llama-3-70b-instruct
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provider_id: lmstudio
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provider_model_id: meta-llama-3-70b-instruct
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model_type: llm
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- metadata: {}
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model_id: meta-llama-3.1-8b-instruct
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provider_id: lmstudio
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provider_model_id: meta-llama-3.1-8b-instruct
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model_type: llm
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- metadata: {}
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model_id: meta-llama-3.1-70b-instruct
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provider_id: lmstudio
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provider_model_id: meta-llama-3.1-70b-instruct
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model_type: llm
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- metadata: {}
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model_id: llama-3.2-1b-instruct
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provider_id: lmstudio
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provider_model_id: llama-3.2-1b-instruct
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model_type: llm
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- metadata: {}
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model_id: llama-3.2-3b-instruct
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provider_id: lmstudio
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provider_model_id: llama-3.2-3b-instruct
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model_type: llm
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- metadata: {}
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model_id: llama-3.2-70b-instruct
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provider_id: lmstudio
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provider_model_id: llama-3.2-70b-instruct
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model_type: llm
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- metadata:
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embedding_dimension: 768
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context_length: 2048
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model_id: nomic-embed-text-v1.5
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provider_id: lmstudio
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provider_model_id: nomic-embed-text-v1.5
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model_type: embedding
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- metadata:
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embedding_dimension: 384
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model_id: all-minilm-l6-v2
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provider_id: lmstudio
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provider_model_id: all-minilm-l6-v2
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model_type: embedding
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shields: []
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vector_dbs: []
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datasets: []
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scoring_fns: []
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benchmarks: []
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tool_groups:
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- toolgroup_id: builtin::websearch
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provider_id: tavily-search
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- toolgroup_id: builtin::rag
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provider_id: rag-runtime
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- toolgroup_id: builtin::code_interpreter
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provider_id: code-interpreter
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server:
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port: 8321
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