forked from phoenix-oss/llama-stack-mirror
22dc684da6
# What does this PR do? This PR adds SambaNova as one of the Provider - Add SambaNova as a provider ## Test Plan Test the functional command ``` pytest -s -v --providers inference=sambanova llama_stack/providers/tests/inference/test_embeddings.py llama_stack/providers/tests/inference/test_prompt_adapter.py llama_stack/providers/tests/inference/test_text_inference.py llama_stack/providers/tests/inference/test_vision_inference.py --env SAMBANOVA_API_KEY=<sambanova-api-key> ``` Test the distribution template: ``` # Docker LLAMA_STACK_PORT=5001 docker run -it -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \ llamastack/distribution-sambanova \ --port $LLAMA_STACK_PORT \ --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY # Conda llama stack build --template sambanova --image-type conda llama stack run ./run.yaml \ --port $LLAMA_STACK_PORT \ --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY ``` ## Source [SambaNova API Documentation](https://cloud.sambanova.ai/apis) ## Before submitting - [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [Y] Ran pre-commit to handle lint / formatting issues. - [Y] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [Y] Updated relevant documentation. - [Y ] Wrote necessary unit or integration tests. --------- Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
37 lines
1.2 KiB
Python
37 lines
1.2 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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import os
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from typing import Optional
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from llama_stack_client import LlamaStackClient
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class LlamaStackApi:
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def __init__(self):
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self.client = LlamaStackClient(
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base_url=os.environ.get("LLAMA_STACK_ENDPOINT", "http://localhost:8321"),
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provider_data={
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"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY", ""),
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"together_api_key": os.environ.get("TOGETHER_API_KEY", ""),
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"sambanova_api_key": os.environ.get("SAMBANOVA_API_KEY", ""),
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"openai_api_key": os.environ.get("OPENAI_API_KEY", ""),
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},
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)
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def run_scoring(
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self, row, scoring_function_ids: list[str], scoring_params: Optional[dict]
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):
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"""Run scoring on a single row"""
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if not scoring_params:
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scoring_params = {fn_id: None for fn_id in scoring_function_ids}
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return self.client.scoring.score(
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input_rows=[row], scoring_functions=scoring_params
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)
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llama_stack_api = LlamaStackApi()
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