update readme

Author: rejojer

README.md

@@ -6,9 +6,8 @@
 
 # ConDB: The KV-Cache Native Context Database
 
-<p align="center">
-  A new type of database optimized for reasoning-driven tree search — fast, context-aware retrieval at scale with up to 70% less token cost.
-</p>
+<p align="center"><i>A new context database for reasoning-driven retrieval via tree search.<br/>
+Fast, context-aware retrieval at scale with up to 70% less token cost.</i></p>
 
 </div>
 
@@ -47,7 +46,7 @@ Evolving, runtime context — agent memory, long conversations (via [ChatIndex](
 
 ---
 
-## ⚡ Quick Start
+## 🚀 Getting Started
 
 ### Install
 
@@ -92,9 +91,7 @@ tree_id = ct.index_markdown_file("doc.md", tree_builder=build_markdown_tree)
 ct.close()
 ```
 
----
-
-## ⚙️ Configuration
+### Configuration
 
 Create a `.env` file:
 
@@ -120,8 +117,8 @@ ConDB automatically selects the best retrieval strategy based on tree size:
 
 | Strategy | Best for | How it works |
 |----------|----------|--------------|
-| **Beam** | Small trees (< 50 nodes) | LLM evaluates and selects promising branches at each depth level |
-| **Block** | Large documents (50+ nodes) | Splits tree into token-bounded blocks, LLM reasons over each block. KV-cache native — caches intermediate block results to cut token usage by up to 70% |
+| **Beam** | Small trees <br/> (< 50 nodes) | LLM evaluates and selects promising branches at each depth level |
+| **Block** | Large documents <br/> (50+ nodes) | Splits tree into token-bounded blocks, LLM reasons over each block. KV-cache native — caches intermediate block results to cut token usage by up to 70% |
 
 You can also specify a strategy explicitly:
 
@@ -151,7 +148,9 @@ These numbers are benchmark snapshots, not hard guarantees; exact cost and laten
 
 ---
 
-## 🧩 Architecture
+## 🧩 Learn More
+
+### Architecture
 
 ```
 contextdb/
@@ -170,12 +169,9 @@ contextdb/
 └── prompts/              # Jinja2 prompt templates
 ```
 
----
-
-## 🔌 Extending
+### Extending
 
-<details>
-<summary><b>Custom Storage Backend</b></summary>
+**Custom Storage Backend**
 
 ```python
 from contextdb import StorageProtocol
@@ -187,10 +183,8 @@ class MyStorage:
 
 ct = ContextTree(storage=MyStorage())
 ```
-</details>
 
-<details>
-<summary><b>Custom LLM Provider</b></summary>
+**Custom LLM Provider**
 
 ```python
 from contextdb import LLMProtocol
@@ -201,43 +195,32 @@ class MyLLM:
 
 ct = ContextTree("db.sqlite", llm=MyLLM())
 ```
-</details>
 
----
-
-## 🧪 Testing
+### Testing
 
 ```bash
 ./run_tests.sh all
 ```
 
 ---
 
-## 🧭 Related Projects
+## 💬 Community
+
+### Related Projects
 
 - [**PageIndex**](https://github.com/VectifyAI/PageIndex) — vectorless, reasoning-based RAG that builds hierarchical tree indexes from long documents
 - [**ChatIndex**](https://github.com/VectifyAI/ChatIndex) — tree indexing for long conversations, enabling reasoning-based retrieval over chat histories
 - [**AgentFS**](https://github.com/anthropics/agentfs) — filesystem for AI agents
 
----
-
-## 📄 License
-
-Apache-2.0
-
----
-
 ### Connect with Us
 
-<div align="center">
-
 [![Twitter](https://img.shields.io/badge/Twitter-000000?style=for-the-badge&logo=x&logoColor=white)](https://x.com/PageIndexAI)&ensp;
 [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/company/vectify-ai/)&ensp;
 [![Discord](https://img.shields.io/badge/Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.com/invite/VuXuf29EUj)&ensp;
 [![Contact Us](https://img.shields.io/badge/Contact_Us-3B82F6?style=for-the-badge&logo=envelope&logoColor=white)](https://ii2abc2jejf.typeform.com/to/tK3AXl8T)
 
-</div>
-
 ---
 
+Licensed under [Apache 2.0](LICENSE).
+
 © 2026 [Vectify AI](https://vectify.ai)