forked from phoenix-oss/llama-stack-mirror
63e6acd0c3
# 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 "${args[@]}"
done
```
30 lines
902 B
Python
30 lines
902 B
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, Field, SecretStr
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from llama_stack.schema_utils import json_schema_type
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@json_schema_type
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class FireworksImplConfig(BaseModel):
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url: str = Field(
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default="https://api.fireworks.ai/inference/v1",
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description="The URL for the Fireworks server",
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)
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api_key: Optional[SecretStr] = Field(
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default=None,
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description="The Fireworks.ai API Key",
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)
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@classmethod
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def sample_run_config(cls, api_key: str = "${env.FIREWORKS_API_KEY}", **kwargs) -> Dict[str, Any]:
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return {
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"url": "https://api.fireworks.ai/inference/v1",
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"api_key": api_key,
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}
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