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DashScopeCloudRetriever

DashScopeCloudRetriever is a software development kit (SDK) from Alibaba Cloud Model Studio. It lets you initialize a LlamaIndex retriever in the LlamaIndex framework.

Get started

Prerequisites

Log on to https://bailian.console.aliyun.com/cn-beijing/ and obtain your API key. To specify a workspace, obtain the workspace ID. Then, install the DashScopeCloudIndex package, which requires Python versions 3.9 to 3.12.
pip install llama-index-core
pip install llama-index-indices-managed-dashscope
import os
from llama_index.indices.managed.dashscope.retriever import DashScopeCloudRetriever

os.environ["DASHSCOPE_API_KEY"] = "your_api_key_here"
os.environ["DASHSCOPE_WORKSPACE_ID"] = "your_workspace_here"

retriever = DashScopeCloudRetriever("your index name")
nodes = retriever.retrieve("test query")
print(nodes)

Parameter descriptions

Input parameters

Parameter

Type

Default value

Description

index_name

str

None

The index name.

dense_similarity_top_k

int

100

The number of items to retrieve from vector search.

sparse_similarity_top_k

int

100

The number of items to retrieve from text search.

enable_reranking

bool

True

Specifies whether to use a reranking model.

rerank_model_name

str

gte-rerank-hybrid

The name of the reranking model. Supported models include the following:

  • gte-rerank-hybrid

  • gte-rerank

rerank_min_score

float

0.0

The score threshold for filtering retriever nodes. The retriever returns only nodes with a score higher than rerank_min_score. This parameter takes effect only when enable_reranking is set to True.

rerank_top_n

int

5

The number of nodes that the retriever returns. If the specified value exceeds the number of candidate nodes, all candidate nodes are returned.

workspace_id

str

None

The ID of the DashScope workspace. You can set this using an environment variable or other methods.

api_key

str

None

The DashScope API key. You can set this using an environment variable or other methods.

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