Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

add utm for arm #1445

Closed
wants to merge 1 commit into from
Closed

add utm for arm #1445

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions bootcamp/tutorials/integration/build_rag_on_arm.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -37,11 +37,11 @@ pip install --upgrade pymilvus openai requests langchain-huggingface huggingface


### Create the Collection
We use [Zilliz Cloud](https://zilliz.com/cloud) deployed on AWS with Arm-based machines to store and retrieve the vector data. To quick start, simply [register an account](https://docs.zilliz.com/docs/register-with-zilliz-cloud) on Zilliz Cloud for free.
We use [Zilliz Cloud](https://zilliz.com/cloud?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm) deployed on AWS with Arm-based machines to store and retrieve the vector data. To quick start, simply [register an account](https://docs.zilliz.com/docs/register-with-zilliz-cloud?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm) on Zilliz Cloud for free.

> In addition to Zilliz Cloud, self-hosted Milvus is also a (more complicated to set up) option. We can also deploy [Milvus Standalone](https://milvus.io/docs/install_standalone-docker-compose.md) and [Kubernetes](https://milvus.io/docs/install_cluster-milvusoperator.md) on ARM-based machines. For more information about Milvus installation, please refer to the [installation documentation](https://milvus.io/docs/install-overview.md).
> In addition to Zilliz Cloud, self-hosted Milvus is also a (more complicated to set up) option. We can also deploy [Milvus Standalone](https://milvus.io/docs/install_standalone-docker-compose.md?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm) and [Kubernetes](https://milvus.io/docs/install_cluster-milvusoperator.md?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm) on ARM-based machines. For more information about Milvus installation, please refer to the [installation documentation](https://milvus.io/docs/install-overview.md?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm).

We set the `uri` and `token` as the [Public Endpoint and Api key](https://docs.zilliz.com/docs/on-zilliz-cloud-console#free-cluster-details) in Zilliz Cloud.
We set the `uri` and `token` as the [Public Endpoint and Api key](https://docs.zilliz.com/docs/on-zilliz-cloud-console#free-cluster-details?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm) in Zilliz Cloud.
```python
from pymilvus import MilvusClient

Expand All @@ -68,7 +68,7 @@ milvus_client.create_collection(
consistency_level="Strong", # Strong consistency level
)
```
We use inner product distance as the default metric type. For more information about distance types, you can refer to [Similarity Metrics page](https://milvus.io/docs/metric.md?tab=floating)
We use inner product distance as the default metric type. For more information about distance types, you can refer to [Similarity Metrics page](https://milvus.io/docs/metric.md?tab=floating?utm_source=partner&utm_medium=referral&utm_campaign=2024-10-24_web_arm-dev-hub-data-loading_arm)

### Prepare the data

Expand Down