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samsja merged 1 commit into from
Apr 18, 2023
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docs: Copy-edit README.md #1411

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Expand Up @@ -27,7 +27,7 @@ DocArray handles your data while integrating seamlessly with the rest of your **

- :fire: Native compatibility for **[NumPy](https://github.com/numpy/numpy)**, **[PyTorch](https://github.com/pytorch/pytorch)** and **[TensorFlow](https://github.com/tensorflow/tensorflow)**, including for **model training use cases**
- :zap: Built on **[Pydantic](https://github.com/pydantic/pydantic)** and out-of-the-box compatible with **[FastAPI](https://github.com/tiangolo/fastapi/)** and **[Jina](https://github.com/jina-ai/jina/)**
- :package: Support vector databases like **[Weaviate](https://weaviate.io/), [Qdrant](https://qdrant.tech/), [ElasticSearch](https://www.elastic.co/de/elasticsearch/)** and **[HNSWLib](https://github.com/nmslib/hnswlib)**
- :package: Support for vector databases like **[Weaviate](https://weaviate.io/), [Qdrant](https://qdrant.tech/), [ElasticSearch](https://www.elastic.co/de/elasticsearch/)** and **[HNSWLib](https://github.com/nmslib/hnswlib)**
- :chains: Send data as JSON over **HTTP** or as **[Protobuf](https://protobuf.dev/)** over **[gRPC](https://grpc.io/)**

> :bulb: **Where are you coming from?** Based on your use case and background, there are different ways to understand DocArray:
Expand All @@ -45,7 +45,7 @@ DocArray allows you to **represent your data**, in an ML-native way.

This is useful for different use cases:

- :woman_running: You are **training a model**: There are tensors of different shapes and sizes flying around, representing different _things_, and you want to keep a straight head about them.
- :running: You are **training a model**: There are tensors of different shapes and sizes flying around, representing different _things_, and you want to keep a straight head about them.
- :cloud: You are **serving a model**: For example through FastAPI, and you want to specify your API endpoints.
- :card_index_dividers: You are **parsing data**: For later use in your ML or data science applications.

Expand Down Expand Up @@ -256,7 +256,7 @@ assert isinstance(dl_2, DocList)

## Send

DocArray allows you to **send your data**, in an ML-native way.
DocArray allows you to **send your data** in an ML-native way.

This means there is native support for **Protobuf and gRPC**, on top of **HTTP** and serialization to JSON, JSONSchema, Base64, and Bytes.

Expand All @@ -270,7 +270,7 @@ This is useful for different use cases:
> that DocArray is fully compatible with FastAPI!
> Also, we have a [dedicated section](#coming-from-fastapi) just for you!

Whenever you want to send your data you need to serialize it, so let's take a look at how that works with DocArray:
Whenever you want to send your data, you need to serialize it, so let's take a look at how that works with DocArray:

```python
from docarray import BaseDoc
Expand Down Expand Up @@ -336,7 +336,7 @@ docs_pull = DocList[SimpleDoc].pull('file://simple_docs')
```
</details>

**Document Indexes** let you index your Documents into a **vector database**, for efficient similarity-based retrieval.
**Document Indexes** let you index your Documents in a **vector database** for efficient similarity-based retrieval.

This is useful for:

Expand Down