chore: update related descriptions

README.md

@@ -7,20 +7,22 @@ sdk: docker
 app_file: app.py
 ---
 
-# 🌍 LightweightEmbeddings: Multilingual, Fast, and Lightweight
+# 🌍 LightweightEmbeddings: Multilingual, Fast, and Unlimited
 
-**LightweightEmbeddings** is a high-performance framework designed for generating embeddings from **text** or **image-text inputs** across multiple languages. Engineered for efficiency and adaptability, it offers a perfect balance between speed and accuracy, making it ideal for **real-time applications** and **resource-constrained environments**.
+**LightweightEmbeddings** is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.
 
 ## ✨ Key Features
 
-- **Multilingual Support**: Seamlessly process text in over 100+ languages for truly global applications.
-- **Text and Image Embeddings**: Generate embeddings from text or image-text pairs using state-of-the-art models.
-- **Optimized for Speed**: Built with lightweight transformer models and efficient backends to ensure rapid inference, even on low-resource systems.
-- **Flexibility**: Supports multiple transformer models for diverse use cases:
+- **Free and Unlimited**: A completely free API service with no limits on usage, making it accessible for everyone.
+- **Multilingual Support**: Seamlessly process text in over 100+ languages for global applications.
+- **Text and Image Embeddings**: Generate high-quality embeddings from text or image-text pairs using state-of-the-art models.
+- **Reranking Support**: Includes powerful reranking capabilities for both text and image inputs.
+- **Optimized for Speed**: Built with lightweight transformer models and efficient backends for rapid inference, even on low-resource systems.
+- **Flexible Model Support**: Use a range of transformer models tailored to diverse use cases:
   - Text models: `multilingual-e5-small`, `paraphrase-multilingual-MiniLM-L12-v2`, `bge-m3`
   - Image model: `google/siglip-base-patch16-256-multilingual`
-- **Dockerized**: Deploy anywhere with ease using Docker, making it production-ready out of the box.
-- **Interactive API**: Comes with a **Gradio-powered playground** and detailed REST API documentation.
+- **Production-Ready**: Easily deploy anywhere with Docker for hassle-free setup.
+- **Interactive Playground**: Test embeddings and reranking directly via a **Gradio-powered interface** alongside detailed REST API documentation.
 
 ## 🚀 Use Cases
 

lightweight_embeddings/__init__.py

@@ -111,10 +111,9 @@ def create_main_interface():
         # Project Info
         gr.Markdown(
             """
-            ## 🚀 **Lightweight Embeddings** 
-            
-            Welcome to the **Lightweight Embeddings** API, a blazing-fast and flexible service 
-            supporting **text** and **image** embeddings. Below you'll find key project details:
+            ## 🚀 **Lightweight Embeddings API**  
+
+            Welcome to the **Lightweight Embeddings API**, a fast, free, and unlimited service for generating multilingual embeddings and reranking, supporting both **text** and **image** inputs. Discover its key features and capabilities below:
             """
         )
         gr.Markdown(
@@ -124,7 +123,7 @@ def create_main_interface():
             - **Description**: {root_data["description"]}
             
             ### 🔗 Links
-            - [Documentation]({root_data["docs"]}) | [GitHub]({root_data["github"]}) | [Demo]({root_data["spaces"]})
+            - [Documentation]({root_data["docs"]}) | [GitHub]({root_data["github"]}) | [Playground]({root_data["spaces"]})
 
             ### 💡 How to Use
             Visit **/docs** for API documentation or try the playground below! 🌏

pyproject.toml

@@ -1,7 +1,8 @@
 [tool.poetry]
 name = "lightweight-embeddings"
 version = "0.1.0"
-description = "Fast, lightweight, multilingual embeddings solution."
+short_description = "A fast, free, unlimited APIs service for multilingual embeddings and reranking, supporting text and image inputs."
+description = "LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime."
 authors = ["Hieu Lam <lamhieu.vk@gmail.com>"]
 readme = "README.md"