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chore: remove openai dependency from providers (#3398)

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# What does this PR do?

The openai package is already a dependency of the llama-stack project
itself, so let's the project dictate which openai version we need and
avoid potential breakage with unsatisfiable dependency resolution.

Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han 2025-09-11 10:19:59 +02:00 • committed by GitHub
parent 0c7f49490c
commit 8e05c68d15
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GPG key ID: B5690EEEBB952194
5 changed files with 13 additions and 23 deletions
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20
llama_stack/providers/registry/inference.py
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@ -75,7 +75,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="vllm",
pip_packages=["openai"],
pip_packages=[],
module="llama_stack.providers.remote.inference.vllm",
config_class="llama_stack.providers.remote.inference.vllm.VLLMInferenceAdapterConfig",
description="Remote vLLM inference provider for connecting to vLLM servers.",
@ -151,9 +151,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="databricks",
pip_packages=[
"openai",
],
pip_packages=[],
module="llama_stack.providers.remote.inference.databricks",
config_class="llama_stack.providers.remote.inference.databricks.DatabricksImplConfig",
description="Databricks inference provider for running models on Databricks' unified analytics platform.",
@ -163,9 +161,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="nvidia",
pip_packages=[
"openai",
],
pip_packages=[],
module="llama_stack.providers.remote.inference.nvidia",
config_class="llama_stack.providers.remote.inference.nvidia.NVIDIAConfig",
description="NVIDIA inference provider for accessing NVIDIA NIM models and AI services.",
@ -175,7 +171,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="runpod",
pip_packages=["openai"],
pip_packages=[],
module="llama_stack.providers.remote.inference.runpod",
config_class="llama_stack.providers.remote.inference.runpod.RunpodImplConfig",
description="RunPod inference provider for running models on RunPod's cloud GPU platform.",
@ -207,7 +203,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="gemini",
pip_packages=["litellm", "openai"],
pip_packages=["litellm"],
module="llama_stack.providers.remote.inference.gemini",
config_class="llama_stack.providers.remote.inference.gemini.GeminiConfig",
provider_data_validator="llama_stack.providers.remote.inference.gemini.config.GeminiProviderDataValidator",
@ -218,7 +214,7 @@ def available_providers() -> list[ProviderSpec]:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="vertexai",
pip_packages=["litellm", "google-cloud-aiplatform", "openai"],
pip_packages=["litellm", "google-cloud-aiplatform"],
module="llama_stack.providers.remote.inference.vertexai",
config_class="llama_stack.providers.remote.inference.vertexai.VertexAIConfig",
provider_data_validator="llama_stack.providers.remote.inference.vertexai.config.VertexAIProviderDataValidator",
@ -248,7 +244,7 @@ Available Models:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="groq",
pip_packages=["litellm", "openai"],
pip_packages=["litellm"],
module="llama_stack.providers.remote.inference.groq",
config_class="llama_stack.providers.remote.inference.groq.GroqConfig",
provider_data_validator="llama_stack.providers.remote.inference.groq.config.GroqProviderDataValidator",
@ -270,7 +266,7 @@ Available Models:
api=Api.inference,
adapter=AdapterSpec(
adapter_type="sambanova",
pip_packages=["litellm", "openai"],
pip_packages=["litellm"],
module="llama_stack.providers.remote.inference.sambanova",
config_class="llama_stack.providers.remote.inference.sambanova.SambaNovaImplConfig",
provider_data_validator="llama_stack.providers.remote.inference.sambanova.config.SambaNovaProviderDataValidator",