Add readme

Signed-off-by: junjiejiangjjj <[email protected]>

Author: junjiejiangjjj

CONTRIBUTING.md

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+# Contributing Guide
+
+Welcome contributors! This guide will help you get started with contributing to Milvus-lite.
+
+Please always find the latest version of this guide at [CONTRIBUTING.md:main](https://github.com/milvus-io/milvus-lite/blob/main/CONTRIBUTING.md)
+
+## How to set up the development environment
+The Milvus-lite project is written in Python. To set up the development environment, you need to install Python 3.8 or later. We recommend that you use a virtual environment to install the dependencies, although the Milvus-lite project requires a very small number of external packages.
+
+The main dependencies for build Milvus-lite is to install dependencies of milvis, so generally you could refer to Milvus's [install_deps.sh](https://github.com/milvus-io/milvus/blob/master/scripts/install_deps.sh) as a reference. Please note, you should follow the related branch of Milvus. For example, if you want to build Milvus-lite with Milvus 2.4.0, you should checkout the branch of Milvus 2.4.0.
+
+For python3 build wheel, we use the build module and requires newer version of setuptools. So you should install the latest version of setuptools and build.
+
+## Build Milvus-lite
+```bash
+python3 setup.py bdist_wheel
+```
+
+After build, you shoud have wheel package under dist folder.

README.md

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+# Introduction
+Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment.
+Milvus Lite is a lightweight version of Milvus that can be embedded into your Python application, integrating the core vector search functionality of Milvus.
+Please note that it is not suggested to use Milvus Lite in a production environment. Consider using Milvus clustered or the fully managed Milvus on Cloud.
+
+# Requirements
+Milvus Lite is available in:
+- Google Colab
+- Jupyter Notebook
+
+Here's also a list of verified OS types where Milvus Lite can successfully build and run:
+- Ubuntu >= 20.04 (x86_64)
+- MacOS >= 11.0 (Apple Silicon)
+
+# Installation
+```shell
+pip install pymilvus
+```
+
+# Usage
+In `pymilvus`, specify a local file name as uri parameter of MilvusClient to use Milvus Lite.
+```python
+from pymilvus import MilvusClient
+client = MilvusClient("./milvus_demo.db")
+```
+Or with old `connections.connect` API (not recommended):
+```python
+from pymilvus import connections
+connections.connect(uri="./milvus_demo.db")
+```
+
+# Examples
+
+```python
+from pymilvus import MilvusClient
+import numpy as np
+
+client = MilvusClient("./milvus_demo.db")
+client.create_collection(
+    collection_name="demo_collection",
+    dimension=384  # The vectors we will use in this demo has 384 dimensions
+)
+
+# Text strings to search from.
+docs = [
+    "Artificial intelligence was founded as an academic discipline in 1956.",
+    "Alan Turing was the first person to conduct substantial research in AI.",
+    "Born in Maida Vale, London, Turing was raised in southern England.",
+]
+# For illustration, here we use fake vectors with random numbers (384 dimension).
+
+vectors = [[ np.random.uniform(-1, 1) for _ in range(384) ] for _ in range(len(docs)) ]
+data = [ {"id": i, "vector": vectors[i], "text": docs[i], "subject": "history"} for i in range(len(vectors)) ]
+res = client.insert(
+    collection_name="demo_collection",
+    data=data
+)
+
+# This will exclude any text in "history" subject despite close to the query vector.
+res = client.search(
+    collection_name="demo_collection",
+    data=[vectors[0]],
+    filter="subject == 'history'",
+    limit=2,
+    output_fields=["text", "subject"],
+)
+print(res)
+
+# a query that retrieves all entities matching filter expressions.
+res = client.query(
+    collection_name="demo_collection",
+    filter="subject == 'history'",
+    output_fields=["text", "subject"],
+)
+print(res)
+
+# delete
+res = client.delete(
+    collection_name="demo_collection",
+    filter="subject == 'history'",
+)
+print(res)
+```
+
+# Contributing
+If you want to contribute to Milvus Lite, please read the [Contributing Guide](https://github.com/milvus-io/milvus-lite/blob/main/CONTRIBUTING.md) first.
+
+# Report a bug
+When you use or develop milvus-lite, if you find any bug, please report it to us. You could submit an issue in [milvus-lite](https://github.com/milvus-io/milvus-lite/issues/new/choose) or report you [milvus](https://github.com/milvus-io/milvus/issues/new/choose) repo if you think it is a Milvus issue.
+
+# License
+Milvus Lite is under the Apache 2.0 license. See the [LICENSE](https://github.com/milvus-io/milvus-lite/blob/main/LICENSE) file for details.