forked from phoenix-oss/llama-stack-mirror
129 lines
3.9 KiB
Python
129 lines
3.9 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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import os
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from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
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from llama_stack_client.lib.agents.agent import Agent
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from llama_stack_client.lib.agents.event_logger import EventLogger as AgentEventLogger
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from llama_stack_client.lib.inference.event_logger import EventLogger
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from llama_stack_client.types import Attachment, UserMessage
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from llama_stack_client.types.agent_create_params import AgentConfig
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def main(config_path: str):
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client = LlamaStackAsLibraryClient(config_path)
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if not client.initialize():
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return
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models = client.models.list()
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print("\nModels:")
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for model in models:
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print(model)
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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 = next(m.identifier for m in models if "8b" in m.identifier.lower())
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print(f"Using model: {model_id}")
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response = 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 (non-stream):")
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print(response)
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response = 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 response (stream):")
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for log in EventLogger().log(response):
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log.print()
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print("\nAgent test:")
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agent_config = AgentConfig(
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model=model_id,
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instructions="You are a helpful assistant",
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sampling_params={
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"strategy": "greedy",
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"temperature": 1.0,
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"top_p": 0.9,
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},
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tools=(
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[
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{
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"type": "brave_search",
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"engine": "brave",
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"api_key": os.getenv("BRAVE_SEARCH_API_KEY"),
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}
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]
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if os.getenv("BRAVE_SEARCH_API_KEY")
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else []
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)
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+ (
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[
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{
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"type": "code_interpreter",
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}
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]
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),
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tool_choice="required",
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input_shields=[],
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output_shields=[],
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enable_session_persistence=False,
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)
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agent = Agent(client, agent_config)
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user_prompts = [
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"Hello",
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"Which players played in the winning team of the NBA western conference semifinals of 2024, please use tools",
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]
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user_prompts = [
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(
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"Here is a csv, can you describe it ?",
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[
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Attachment(
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content="https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv",
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mime_type="test/csv",
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)
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],
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),
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("Which year ended with the highest inflation ?", None),
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(
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"What macro economic situations that led to such high inflation in that period?",
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None,
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),
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("Plot average yearly inflation as a time series", None),
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]
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session_id = agent.create_session("test-session")
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for prompt, attachments in user_prompts:
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response = agent.create_turn(
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messages=[
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{
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"role": "user",
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"content": prompt,
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}
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],
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attachments=attachments,
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session_id=session_id,
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)
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for log in AgentEventLogger().log(response):
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log.print()
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if __name__ == "__main__":
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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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main(args.config_path)
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