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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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llama_stack/templates/dev/build.yaml
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llama_stack/templates/dev/build.yaml
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version: '2'
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distribution_spec:
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description: Distribution for running e2e tests in CI
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providers:
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inference:
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- remote::openai
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- remote::fireworks
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- remote::anthropic
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- remote::gemini
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- inline::sentence-transformers
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vector_io:
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- inline::sqlite-vec
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- remote::chromadb
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- remote::pgvector
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safety:
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- inline::llama-guard
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agents:
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- inline::meta-reference
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telemetry:
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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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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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- remote::model-context-protocol
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image_type: conda
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