docs: update README to include TypeScript implementation and installation

README.md

@@ -1,14 +1,14 @@
 # Distributed Deductive System Sorts (DDSS)
 
-DDSS is a distributed deductive system with a scalable architecture. It currently supports distributed engines including forward-chaining, E-graph, and more.
+DDSS is a distributed deductive system with a scalable architecture, providing identical implementations in both **Python** and **TypeScript**. It currently supports distributed engines including forward-chaining, E-graph, and more.
 
 ## Design Philosophy
 
 DDSS adopts a modular architecture that decomposes the deductive system into independent but collaborative sub-systems:
 
-1. **Separation of Concerns**: Each module focuses on a specific reasoning task
-2. **Concurrent Execution**: All modules collaborate asynchronously through a shared database, fully utilizing system resources
-3. **Persistent Storage**: Uses a database to store facts and ideas, ensuring data consistency
+1. **Separation of Concerns**: Each module focuses on a specific reasoning task.
+2. **Concurrent Execution**: All modules collaborate asynchronously through a shared database, fully utilizing system resources.
+3. **Persistent Storage**: Uses a database to store facts and ideas, ensuring data consistency.
 
 The system uses a database as the central hub, with two tables (`facts` and `ideas`) for interaction between sub-systems:
 
@@ -18,34 +18,49 @@ The system uses a database as the central hub, with two tables (`facts` and `ide
 
 ## Modules
 
-- **Input** (`ddss/input.py`): Interactive input interface with BNF syntax parsing
-- **Output** (`ddss/output.py`): Real-time display of facts and ideas from the database
-- **Load** (`ddss/load.py`): Batch import of facts from standard input
-- **Dump** (`ddss/dump.py`): Export all facts and ideas to output
-- **DS** (`ddss/ds.py`): Forward-chaining deductive search engine
-- **Egg** (`ddss/egg.py`): E-graph based equality reasoning engine
+The system consists of the following modules, implemented symmetrically in `ddss/*.py` and `ddss/*.ts`:
+
+- **Input** (`ddss/input.py`, `ddss/input.ts`): Interactive input interface with BNF syntax parsing
+- **Output** (`ddss/output.py`, `ddss/output.ts`): Real-time display of facts and ideas from the database
+- **Load** (`ddss/load.py`, `ddss/load.ts`): Batch import of facts from standard input
+- **Dump** (`ddss/dump.py`, `ddss/dump.ts`): Export all facts and ideas to output
+- **DS** (`ddss/ds.py`, `ddss/ds.ts`): Forward-chaining deductive search engine
+- **Egg** (`ddss/egg.py`, `ddss/egg.ts`): E-graph based equality reasoning engine
 
 ## Installation
 
-### Using uvx (Recommended)
+You can choose either the Python or TypeScript version. Both provide the same `ddss` command-line interface.
 
-The simplest way is to run with `uvx`:
+### Python Version
 
+#### Using uvx (Recommended)
 ```bash
 uvx ddss
 ```
 
-This automatically installs all dependencies and starts the DDSS system.
+#### Using pip
+```bash
+pip install ddss
+ddss
+```
+
+### TypeScript Version
 
-### Using pip
+#### Using npx (Recommended)
+```bash
+npx @hzhangxyz/ddss
+```
 
+#### Using npm
 ```bash
-pip install ddss
+npm install -g @hzhangxyz/ddss
 ddss
 ```
 
 ## Usage
 
+The usage, command-line options, and interactive syntax are identical regardless of the implementation language used.
+
 ### Basic Usage
 
 Run DDSS with a temporary SQLite database: