Moved llama-stack-as-library client to llama-stack

llama_stack/distribution/tests/library_client_test.py

@@ -0,0 +1,59 @@
+# 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
+
+from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
+from llama_stack_client.types import UserMessage
+
+
+async def main(config_path: str):
+    client = LlamaStackAsLibraryClient(config_path)
+    await client.initialize()
+
+    models = await client.models.list()
+    print(models)
+    if not models:
+        print("No models found, skipping chat completion test")
+        return
+
+    model_id = models[0].identifier
+    response = await 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:")
+    print(response)
+
+    response = await client.inference.chat_completion(
+        messages=[UserMessage(content="What is the capital of France?", role="user")],
+        model_id=model_id,
+        stream=True,
+    )
+    print("\nChat completion stream response:")
+    async for chunk in response:
+        print(chunk)
+
+    response = await client.memory_banks.register(
+        memory_bank_id="memory_bank_id",
+        params={
+            "chunk_size_in_tokens": 0,
+            "embedding_model": "embedding_model",
+            "memory_bank_type": "vector",
+        },
+    )
+    print("\nRegister memory bank response:")
+    print(response)
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("config_path", help="Path to the config YAML file")
+    args = parser.parse_args()
+    asyncio.run(main(args.config_path))