mirror of
https://github.com/meta-llama/llama-stack.git
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59 lines
1.7 KiB
Python
59 lines
1.7 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 argparse
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from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
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from llama_stack_client.types import UserMessage
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async def main(config_path: str):
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client = LlamaStackAsLibraryClient(config_path)
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await client.initialize()
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models = await client.models.list()
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print(models)
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if not models:
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print("No models found, skipping chat completion test")
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return
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model_id = models[0].identifier
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response = await client.inference.chat_completion(
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messages=[UserMessage(content="What is the capital of France?", role="user")],
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model_id=model_id,
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stream=False,
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)
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print("\nChat completion response:")
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print(response)
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response = await client.inference.chat_completion(
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messages=[UserMessage(content="What is the capital of France?", role="user")],
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model_id=model_id,
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stream=True,
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)
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print("\nChat completion stream response:")
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async for chunk in response:
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print(chunk)
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response = await client.memory_banks.register(
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memory_bank_id="memory_bank_id",
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params={
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"chunk_size_in_tokens": 0,
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"embedding_model": "embedding_model",
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"memory_bank_type": "vector",
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},
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)
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print("\nRegister memory bank response:")
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print(response)
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if __name__ == "__main__":
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import asyncio
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parser = argparse.ArgumentParser()
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parser.add_argument("config_path", help="Path to the config YAML file")
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args = parser.parse_args()
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asyncio.run(main(args.config_path))
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