forked from phoenix-oss/llama-stack-mirror
330cc9d09d
# What does this PR do? See https://github.com/meta-llama/llama-stack/pull/1171 which is the original PR. Author: @zc277584121 feat: add [Milvus](https://milvus.io/) vectorDB note: I use the MilvusClient to implement it instead of AsyncMilvusClient, because when I tested AsyncMilvusClient, it would raise issues about evenloop, which I think AsyncMilvusClient SDK is not robust enough to be compatible with llama_stack framework. ## Test Plan have passed the unit test and ene2end test Here is my end2end test logs, including the client code, client log, server logs from inline and remote settings [test_end2end_logs.zip](https://github.com/user-attachments/files/18964391/test_end2end_logs.zip) --------- Signed-off-by: ChengZi <chen.zhang@zilliz.com> Co-authored-by: Cheney Zhang <chen.zhang@zilliz.com>
22 lines
654 B
Python
22 lines
654 B
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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from typing import Any, Dict, Optional
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from pydantic import BaseModel
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from llama_stack.schema_utils import json_schema_type
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@json_schema_type
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class MilvusVectorIOConfig(BaseModel):
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uri: str
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token: Optional[str] = None
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consistency_level: str = "Strong"
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@classmethod
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def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> Dict[str, Any]:
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return {"uri": "${env.MILVUS_ENDPOINT}", "token": "${env.MILVUS_TOKEN}"}
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