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840ad75fe9
# What does this PR do? Extract API definitions and provider specifications into a standalone llama-stack-api package that can be published to PyPI independently of the main llama-stack server. see: https://github.com/llamastack/llama-stack/pull/2978 and https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942 Motivation External providers currently import from llama-stack, which overrides the installed version and causes dependency conflicts. This separation allows external providers to: - Install only the type definitions they need without server dependencies - Avoid version conflicts with the installed llama-stack package - Be versioned and released independently This enables us to re-enable external provider module tests that were previously blocked by these import conflicts. Changes - Created llama-stack-api package with minimal dependencies (pydantic, jsonschema) - Moved APIs, providers datatypes, strong_typing, and schema_utils - Updated all imports from llama_stack.* to llama_stack_api.* - Configured local editable install for development workflow - Updated linting and type-checking configuration for both packages Next Steps - Publish llama-stack-api to PyPI - Update external provider dependencies - Re-enable external provider module tests Pre-cursor PRs to this one: - #4093 - #3954 - #4064 These PRs moved key pieces _out_ of the Api pkg, limiting the scope of change here. relates to #3237 ## Test Plan Package builds successfully and can be imported independently. All pre-commit hooks pass with expected exclusions maintained. --------- Signed-off-by: Charlie Doern <cdoern@redhat.com>
316 lines
16 KiB
Python
316 lines
16 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 llama_stack_api import (
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Api,
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InlineProviderSpec,
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ProviderSpec,
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RemoteProviderSpec,
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)
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META_REFERENCE_DEPS = [
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"accelerate",
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"fairscale",
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"torch",
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"torchvision",
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"transformers",
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"zmq",
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"lm-format-enforcer",
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"sentence-transformers",
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"torchao==0.8.0",
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"fbgemm-gpu-genai==1.1.2",
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]
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def available_providers() -> list[ProviderSpec]:
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return [
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InlineProviderSpec(
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api=Api.inference,
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provider_type="inline::meta-reference",
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pip_packages=META_REFERENCE_DEPS,
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module="llama_stack.providers.inline.inference.meta_reference",
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config_class="llama_stack.providers.inline.inference.meta_reference.MetaReferenceInferenceConfig",
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description="Meta's reference implementation of inference with support for various model formats and optimization techniques.",
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),
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InlineProviderSpec(
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api=Api.inference,
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provider_type="inline::sentence-transformers",
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# CrossEncoder depends on torchao.quantization
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pip_packages=[
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"torch torchvision torchao>=0.12.0 --extra-index-url https://download.pytorch.org/whl/cpu",
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"sentence-transformers --no-deps",
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# required by some SentenceTransformers architectures for tensor rearrange/merge ops
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"einops",
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# fast HF tokenization backend used by SentenceTransformers models
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"tokenizers",
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# safe and fast file format for storing and loading tensors
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"safetensors",
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],
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module="llama_stack.providers.inline.inference.sentence_transformers",
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config_class="llama_stack.providers.inline.inference.sentence_transformers.config.SentenceTransformersInferenceConfig",
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description="Sentence Transformers inference provider for text embeddings and similarity search.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="cerebras",
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provider_type="remote::cerebras",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.cerebras",
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config_class="llama_stack.providers.remote.inference.cerebras.CerebrasImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.cerebras.config.CerebrasProviderDataValidator",
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description="Cerebras inference provider for running models on Cerebras Cloud platform.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="ollama",
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provider_type="remote::ollama",
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pip_packages=["ollama", "aiohttp", "h11>=0.16.0"],
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config_class="llama_stack.providers.remote.inference.ollama.OllamaImplConfig",
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module="llama_stack.providers.remote.inference.ollama",
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description="Ollama inference provider for running local models through the Ollama runtime.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="vllm",
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provider_type="remote::vllm",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.vllm",
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config_class="llama_stack.providers.remote.inference.vllm.VLLMInferenceAdapterConfig",
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provider_data_validator="llama_stack.providers.remote.inference.vllm.VLLMProviderDataValidator",
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description="Remote vLLM inference provider for connecting to vLLM servers.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="tgi",
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provider_type="remote::tgi",
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pip_packages=["huggingface_hub", "aiohttp"],
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module="llama_stack.providers.remote.inference.tgi",
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config_class="llama_stack.providers.remote.inference.tgi.TGIImplConfig",
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description="Text Generation Inference (TGI) provider for HuggingFace model serving.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="hf::serverless",
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provider_type="remote::hf::serverless",
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pip_packages=["huggingface_hub", "aiohttp"],
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module="llama_stack.providers.remote.inference.tgi",
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config_class="llama_stack.providers.remote.inference.tgi.InferenceAPIImplConfig",
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description="HuggingFace Inference API serverless provider for on-demand model inference.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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provider_type="remote::hf::endpoint",
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adapter_type="hf::endpoint",
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pip_packages=["huggingface_hub", "aiohttp"],
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module="llama_stack.providers.remote.inference.tgi",
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config_class="llama_stack.providers.remote.inference.tgi.InferenceEndpointImplConfig",
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description="HuggingFace Inference Endpoints provider for dedicated model serving.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="fireworks",
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provider_type="remote::fireworks",
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pip_packages=[
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"fireworks-ai<=0.17.16",
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],
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module="llama_stack.providers.remote.inference.fireworks",
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config_class="llama_stack.providers.remote.inference.fireworks.FireworksImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.fireworks.FireworksProviderDataValidator",
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description="Fireworks AI inference provider for Llama models and other AI models on the Fireworks platform.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="together",
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provider_type="remote::together",
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pip_packages=[
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"together",
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],
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module="llama_stack.providers.remote.inference.together",
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config_class="llama_stack.providers.remote.inference.together.TogetherImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.together.TogetherProviderDataValidator",
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description="Together AI inference provider for open-source models and collaborative AI development.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="bedrock",
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provider_type="remote::bedrock",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.bedrock",
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config_class="llama_stack.providers.remote.inference.bedrock.BedrockConfig",
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provider_data_validator="llama_stack.providers.remote.inference.bedrock.config.BedrockProviderDataValidator",
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description="AWS Bedrock inference provider using OpenAI compatible endpoint.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="databricks",
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provider_type="remote::databricks",
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pip_packages=["databricks-sdk"],
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module="llama_stack.providers.remote.inference.databricks",
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config_class="llama_stack.providers.remote.inference.databricks.DatabricksImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.databricks.config.DatabricksProviderDataValidator",
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description="Databricks inference provider for running models on Databricks' unified analytics platform.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="nvidia",
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provider_type="remote::nvidia",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.nvidia",
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config_class="llama_stack.providers.remote.inference.nvidia.NVIDIAConfig",
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provider_data_validator="llama_stack.providers.remote.inference.nvidia.config.NVIDIAProviderDataValidator",
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description="NVIDIA inference provider for accessing NVIDIA NIM models and AI services.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="runpod",
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provider_type="remote::runpod",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.runpod",
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config_class="llama_stack.providers.remote.inference.runpod.RunpodImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.runpod.config.RunpodProviderDataValidator",
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description="RunPod inference provider for running models on RunPod's cloud GPU platform.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="openai",
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provider_type="remote::openai",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.openai",
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config_class="llama_stack.providers.remote.inference.openai.OpenAIConfig",
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provider_data_validator="llama_stack.providers.remote.inference.openai.config.OpenAIProviderDataValidator",
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description="OpenAI inference provider for accessing GPT models and other OpenAI services.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="anthropic",
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provider_type="remote::anthropic",
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pip_packages=["anthropic"],
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module="llama_stack.providers.remote.inference.anthropic",
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config_class="llama_stack.providers.remote.inference.anthropic.AnthropicConfig",
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provider_data_validator="llama_stack.providers.remote.inference.anthropic.config.AnthropicProviderDataValidator",
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description="Anthropic inference provider for accessing Claude models and Anthropic's AI services.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="gemini",
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provider_type="remote::gemini",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.gemini",
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config_class="llama_stack.providers.remote.inference.gemini.GeminiConfig",
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provider_data_validator="llama_stack.providers.remote.inference.gemini.config.GeminiProviderDataValidator",
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description="Google Gemini inference provider for accessing Gemini models and Google's AI services.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="vertexai",
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provider_type="remote::vertexai",
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pip_packages=[
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"google-cloud-aiplatform",
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],
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module="llama_stack.providers.remote.inference.vertexai",
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config_class="llama_stack.providers.remote.inference.vertexai.VertexAIConfig",
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provider_data_validator="llama_stack.providers.remote.inference.vertexai.config.VertexAIProviderDataValidator",
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description="""Google Vertex AI inference provider enables you to use Google's Gemini models through Google Cloud's Vertex AI platform, providing several advantages:
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• Enterprise-grade security: Uses Google Cloud's security controls and IAM
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• Better integration: Seamless integration with other Google Cloud services
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• Advanced features: Access to additional Vertex AI features like model tuning and monitoring
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• Authentication: Uses Google Cloud Application Default Credentials (ADC) instead of API keys
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Configuration:
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- Set VERTEX_AI_PROJECT environment variable (required)
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- Set VERTEX_AI_LOCATION environment variable (optional, defaults to us-central1)
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- Use Google Cloud Application Default Credentials or service account key
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Authentication Setup:
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Option 1 (Recommended): gcloud auth application-default login
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Option 2: Set GOOGLE_APPLICATION_CREDENTIALS to service account key path
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Available Models:
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- vertex_ai/gemini-2.0-flash
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- vertex_ai/gemini-2.5-flash
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- vertex_ai/gemini-2.5-pro""",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="groq",
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provider_type="remote::groq",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.groq",
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config_class="llama_stack.providers.remote.inference.groq.GroqConfig",
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provider_data_validator="llama_stack.providers.remote.inference.groq.config.GroqProviderDataValidator",
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description="Groq inference provider for ultra-fast inference using Groq's LPU technology.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="llama-openai-compat",
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provider_type="remote::llama-openai-compat",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.llama_openai_compat",
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config_class="llama_stack.providers.remote.inference.llama_openai_compat.config.LlamaCompatConfig",
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provider_data_validator="llama_stack.providers.remote.inference.llama_openai_compat.config.LlamaProviderDataValidator",
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description="Llama OpenAI-compatible provider for using Llama models with OpenAI API format.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="sambanova",
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provider_type="remote::sambanova",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.sambanova",
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config_class="llama_stack.providers.remote.inference.sambanova.SambaNovaImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.sambanova.config.SambaNovaProviderDataValidator",
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description="SambaNova inference provider for running models on SambaNova's dataflow architecture.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="passthrough",
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provider_type="remote::passthrough",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.passthrough",
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config_class="llama_stack.providers.remote.inference.passthrough.PassthroughImplConfig",
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provider_data_validator="llama_stack.providers.remote.inference.passthrough.PassthroughProviderDataValidator",
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description="Passthrough inference provider for connecting to any external inference service not directly supported.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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adapter_type="watsonx",
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provider_type="remote::watsonx",
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pip_packages=["litellm"],
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module="llama_stack.providers.remote.inference.watsonx",
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config_class="llama_stack.providers.remote.inference.watsonx.WatsonXConfig",
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provider_data_validator="llama_stack.providers.remote.inference.watsonx.config.WatsonXProviderDataValidator",
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description="IBM WatsonX inference provider for accessing AI models on IBM's WatsonX platform.",
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),
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RemoteProviderSpec(
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api=Api.inference,
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provider_type="remote::azure",
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adapter_type="azure",
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pip_packages=[],
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module="llama_stack.providers.remote.inference.azure",
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config_class="llama_stack.providers.remote.inference.azure.AzureConfig",
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provider_data_validator="llama_stack.providers.remote.inference.azure.config.AzureProviderDataValidator",
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description="""
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Azure OpenAI inference provider for accessing GPT models and other Azure services.
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Provider documentation
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https://learn.microsoft.com/en-us/azure/ai-foundry/openai/overview
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""",
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),
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RemoteProviderSpec(
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api=Api.inference,
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provider_type="remote::oci",
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adapter_type="oci",
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pip_packages=["oci"],
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module="llama_stack.providers.remote.inference.oci",
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config_class="llama_stack.providers.remote.inference.oci.config.OCIConfig",
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provider_data_validator="llama_stack.providers.remote.inference.oci.config.OCIProviderDataValidator",
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description="""
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Oracle Cloud Infrastructure (OCI) Generative AI inference provider for accessing OCI's Generative AI Platform-as-a-Service models.
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Provider documentation
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https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm
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""",
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),
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]
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