chore:doc

README.md

@@ -1,3 +1,48 @@
 # embedbase-qdrant
 
-Embedbase + Qdrant - Advanced and high-performant vector similarity search technology in your AI applications
+<div align="center">
+
+[Embedbase](https://github.com/different-ai/embedbase) + [Qdrant](https://qdrant.tech) - Advanced and high-performant vector similarity search technology in your AI applications 
+    <br>
+    <br>
+    ⚠️ Status: Alpha release ⚠️
+    <br>
+    <br>
+    <a href="https://discord.gg/pMNeuGrDky"><img alt="Discord" src="https://img.shields.io/discord/ 1066022656845025310?color=black&style=for-the-badge"></a>
+    <a href="https://badge.fury.io/py/embedbase-qdrant"><img alt="PyPI" src="https://img.shields.io/pypi/v/embedbase-qdrant?color=black&style=for-the-badge"></a>
+
+
+</div>
+
+If you have any feedback or issues, please let us know by opening an issue or contacting us on [discord](https://discord.gg/pMNeuGrDky).
+
+Please refer to the [documentation](https://docs.embedbase.xyz/sdk).
+
+## Getting started
+
+To install the Embedbase Qdrant library, run the following command:
+
+```bash
+pip install embedbase-qdrant
+```
+
+## Usage
+
+```python
+import os
+import uvicorn
+from embedbase import get_app
+from embedbase.embedding.openai import Openai
+from sentence_transformers import SentenceTransformer
+from embedbase_qdrant import Qdrant
+
+app = get_app().use_embedder(Openai(
+    os.environ["OPENAI_API_KEY"],
+)).use_db(Qdrant()).run()
+
+if __name__ == "__main__":
+    uvicorn.run(app, reload=True)
+```
+
+Check out other [examples](./examples/main.py) and [documentation](https://docs.embedbase.xyz/sdk) for more details.
+