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## Test Plan `LLAMA_STACK_CONFIG=inference=sentence-transformers,vector_io=sqlite-vec pytest -s -v test_vector_io.py --embedding-model all-miniLM-L6-V2 --inference-model='' --vision-inference-model=''` ``` test_vector_io.py::test_vector_db_retrieve[txt=:vis=:emb=all-miniLM-L6-V2] PASSED test_vector_io.py::test_vector_db_register[txt=:vis=:emb=all-miniLM-L6-V2] PASSED test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case0] PASSED test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case1] PASSED test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case2] PASSED test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case3] PASSED test_vector_io.py::test_insert_chunks[txt=:vis=:emb=all-miniLM-L6-V2-test_case4] PASSED ``` Same thing with: - LLAMA_STACK_CONFIG=inference=sentence-transformers,vector_io=faiss - LLAMA_STACK_CONFIG=fireworks (Note that ergonomics will soon be improved re: cmd-line options and env variables)
116 lines
3.9 KiB
Python
116 lines
3.9 KiB
Python
# 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 (
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Provider,
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ShieldInput,
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ToolGroupInput,
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)
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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.sambanova import SambaNovaImplConfig
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from llama_stack.providers.remote.inference.sambanova.models import MODEL_ENTRIES
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from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig
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from llama_stack.providers.remote.vector_io.pgvector.config import PGVectorVectorIOConfig
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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::sambanova"],
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"vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
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"safety": ["inline::llama-guard"],
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"agents": ["inline::meta-reference"],
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"telemetry": ["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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],
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}
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name = "sambanova"
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inference_provider = Provider(
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provider_id=name,
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provider_type=f"remote::{name}",
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config=SambaNovaImplConfig.sample_run_config(),
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)
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vector_io_providers = [
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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(
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__distro_dir__=f"~/.llama/distributions/{name}",
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),
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),
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Provider(
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provider_id="${env.ENABLE_CHROMADB+chromadb}",
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provider_type="remote::chromadb",
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config=ChromaVectorIOConfig.sample_run_config(url="${env.CHROMADB_URL:}"),
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),
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Provider(
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provider_id="${env.ENABLE_PGVECTOR+pgvector}",
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provider_type="remote::pgvector",
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config=PGVectorVectorIOConfig.sample_run_config(
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db="${env.PGVECTOR_DB:}",
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user="${env.PGVECTOR_USER:}",
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password="${env.PGVECTOR_PASSWORD:}",
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),
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),
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]
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available_models = {
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name: MODEL_ENTRIES,
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}
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default_models = get_model_registry(available_models)
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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=name,
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distro_type="self_hosted",
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description="Use SambaNova.AI for running LLM inference",
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docker_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": [inference_provider],
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"vector_io": vector_io_providers,
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},
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default_models=default_models,
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default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
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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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"LLAMASTACK_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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"SAMBANOVA_API_KEY": (
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"",
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"SambaNova.AI API Key",
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),
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},
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)
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