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feat: add (openai, anthropic, gemini) providers via litellm (#1267)
# What does this PR do?
This PR introduces more non-llama model support to llama stack.
Providers introduced: openai, anthropic and gemini. All of these
providers use essentially the same piece of code -- the implementation
works via the `litellm` library.
We will expose only specific models for providers we enable making sure
they all work well and pass tests. This setup (instead of automatically
enabling _all_ providers and models allowed by LiteLLM) ensures we can
also perform any needed prompt tuning on a per-model basis as needed
(just like we do it for llama models.)
## Test Plan
```bash
#!/bin/bash
args=("$@")
for model in openai/gpt-4o anthropic/claude-3-5-sonnet-latest gemini/gemini-1.5-flash; do
LLAMA_STACK_CONFIG=dev pytest -s -v tests/client-sdk/inference/test_text_inference.py \
--embedding-model=all-MiniLM-L6-v2 \
--vision-inference-model="" \
--inference-model=$model "${args[@]}"
done
```
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parent
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25 changed files with 1048 additions and 33 deletions
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@ -207,6 +207,33 @@ def available_providers() -> List[ProviderSpec]:
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config_class="llama_stack.providers.remote.inference.runpod.RunpodImplConfig",
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),
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),
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remote_provider_spec(
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api=Api.inference,
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adapter=AdapterSpec(
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adapter_type="openai",
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pip_packages=["litellm"],
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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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),
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),
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remote_provider_spec(
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api=Api.inference,
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adapter=AdapterSpec(
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adapter_type="anthropic",
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pip_packages=["litellm"],
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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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),
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),
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remote_provider_spec(
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api=Api.inference,
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adapter=AdapterSpec(
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adapter_type="gemini",
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pip_packages=["litellm"],
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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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),
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),
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remote_provider_spec(
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api=Api.inference,
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adapter=AdapterSpec(
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