From b2b82d4a9035ec40348505ca65b1d05381119939 Mon Sep 17 00:00:00 2001
From: Hardik Shah <hjshah@fb.com>
Date: Tue, 14 Jan 2025 17:54:22 -0800
Subject: [PATCH] removing unused script file

---
 .../distribution/tests/library_client_test.py | 129 ------------------
 1 file changed, 129 deletions(-)
 delete mode 100644 llama_stack/distribution/tests/library_client_test.py

diff --git a/llama_stack/distribution/tests/library_client_test.py b/llama_stack/distribution/tests/library_client_test.py
deleted file mode 100644
index a919ab223..000000000
--- a/llama_stack/distribution/tests/library_client_test.py
+++ /dev/null
@@ -1,129 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import argparse
-import os
-
-from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
-from llama_stack_client.lib.agents.agent import Agent
-from llama_stack_client.lib.agents.event_logger import EventLogger as AgentEventLogger
-from llama_stack_client.lib.inference.event_logger import EventLogger
-from llama_stack_client.types import Attachment, UserMessage
-from llama_stack_client.types.agent_create_params import AgentConfig
-
-
-def main(config_path: str):
-    client = LlamaStackAsLibraryClient(config_path)
-    if not client.initialize():
-        return
-
-    models = client.models.list()
-    print("\nModels:")
-    for model in models:
-        print(model)
-
-    if not models:
-        print("No models found, skipping chat completion test")
-        return
-
-    model_id = next(m.identifier for m in models if "8b" in m.identifier.lower())
-    print(f"Using model: {model_id}")
-    response = client.inference.chat_completion(
-        messages=[UserMessage(content="What is the capital of France?", role="user")],
-        model_id=model_id,
-        stream=False,
-    )
-    print("\nChat completion response (non-stream):")
-    print(response)
-
-    response = client.inference.chat_completion(
-        messages=[UserMessage(content="What is the capital of France?", role="user")],
-        model_id=model_id,
-        stream=True,
-    )
-
-    print("\nChat completion response (stream):")
-    for log in EventLogger().log(response):
-        log.print()
-
-    print("\nAgent test:")
-    agent_config = AgentConfig(
-        model=model_id,
-        instructions="You are a helpful assistant",
-        sampling_params={
-            "strategy": "greedy",
-            "temperature": 1.0,
-            "top_p": 0.9,
-        },
-        tools=(
-            [
-                {
-                    "type": "brave_search",
-                    "engine": "brave",
-                    "api_key": os.getenv("BRAVE_SEARCH_API_KEY"),
-                }
-            ]
-            if os.getenv("BRAVE_SEARCH_API_KEY")
-            else []
-        )
-        + (
-            [
-                {
-                    "type": "code_interpreter",
-                }
-            ]
-        ),
-        tool_choice="required",
-        input_shields=[],
-        output_shields=[],
-        enable_session_persistence=False,
-    )
-    agent = Agent(client, agent_config)
-    user_prompts = [
-        "Hello",
-        "Which players played in the winning team of the NBA western conference semifinals of 2024, please use tools",
-    ]
-    user_prompts = [
-        (
-            "Here is a csv, can you describe it ?",
-            [
-                Attachment(
-                    content="https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv",
-                    mime_type="test/csv",
-                )
-            ],
-        ),
-        ("Which year ended with the highest inflation ?", None),
-        (
-            "What macro economic situations that led to such high inflation in that period?",
-            None,
-        ),
-        ("Plot average yearly inflation as a time series", None),
-    ]
-
-    session_id = agent.create_session("test-session")
-
-    for prompt, attachments in user_prompts:
-        response = agent.create_turn(
-            messages=[
-                {
-                    "role": "user",
-                    "content": prompt,
-                }
-            ],
-            attachments=attachments,
-            session_id=session_id,
-        )
-
-        for log in AgentEventLogger().log(response):
-            log.print()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("config_path", help="Path to the config YAML file")
-    args = parser.parse_args()
-    main(args.config_path)