From 48d1097b02b315fc0108dcf2a8121c7b5e4056e3 Mon Sep 17 00:00:00 2001 From: Scott Martens <70647348+scott-martens@users.noreply.github.com> Date: Tue, 18 Apr 2023 10:05:35 +0200 Subject: [PATCH] doc: Copy-edit README.md Signed-off-by: Scott Martens <70647348+scott-martens@users.noreply.github.com> --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 8ec6b053d9e..0ac3e743e4e 100644 --- a/README.md +++ b/README.md @@ -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: @@ -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. @@ -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. @@ -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 @@ -336,7 +336,7 @@ docs_pull = DocList[SimpleDoc].pull('file://simple_docs') ``` -**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: