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@@ -3,6 +3,7 @@ AOF
 AST
 Aldis
 Analytics
+APIs
 BFS
 BLAS
 Benchmarking
@@ -189,6 +190,7 @@ percentileDisc
 performant
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+prem
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diff --git a/getting_started.md b/getting_started.md
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+---
+title: "Getting Started"
+nav_order: 2
+description: >
+    Getting Started with FalkorDB Graph Database.
+---
+
+
+# Getting Started with FalkorDB
+
+This guide will walk you through setting up FalkorDB, modeling a social network as a graph, 
+and accessing it using the [FalkorDB Python client](/clients) with [Cypher](/cypher).
+
+---
+
+## Prerequisites
+
+1. **FalkorDB Instance**: Set up FalkorDB (on-prem or cloud). 
+   - [Run FalkorDB Docker](https://hub.docker.com/r/falkordb/falkordb/)
+   - [Create a FalkorDB Cloud Instance](https://app.falkordb.cloud/signup)
+2. **Python Installed**: Ensure you have Python 3.8+ installed.  
+3. **Install FalkorDB Python Client**:
+   
+   ```bash
+   pip install falkordb
+   ```
+   
+---
+
+## Step 1: Model a Social Network as a Graph
+
+Let's create a simple graph for a social network where:  
+- **Nodes** represent `User` and `Post`.
+- **Relationships** connect `User`s with a `FRIENDS_WITH` relationship, and `User`s are connected via a `CREATED` relationship to `Post`s
+
+### Graph Schema
+
+| Node Type | Properties               |
+|-----------|--------------------------|
+| User      | `id`, `name`, `email`    |
+| Post      | `id`, `content`, `date`  |
+
+| Relationship Type | Start Node | End Node | Properties   |
+|-------------------|------------|----------|--------------|
+| FRIENDS_WITH      | User       | User     | `since`      |
+| CREATED           | User       | Post     | `time`       |
+
+![FalkorDB-Model a Social Network as a Graph](https://github.com/user-attachments/assets/57d9b837-661e-4500-a9f2-88e754382d29)
+
+---
+
+## Step 2: Load Data into FalkorDB
+
+Here’s how you can model and load the data.
+
+### Cypher Query to Create the Data
+
+```cypher
+CREATE (alice:User {id: 1, name: "Alice", email: "alice@example.com"})
+CREATE (bob:User {id: 2, name: "Bob", email: "bob@example.com"})
+CREATE (charlie:User {id: 3, name: "Charlie", email: "charlie@example.com"})
+
+CREATE (post1:Post {id: 101, content: "Hello World!", date: 1701388800})
+CREATE (post2:Post {id: 102, content: "Graph Databases are awesome!", date: 1701475200})
+
+CREATE (alice)-[:FRIENDS_WITH {since: 1640995200}]->(bob)
+CREATE (bob)-[:FRIENDS_WITH {since: 1684108800}]->(charlie)
+CREATE (alice)-[:CREATED {time: 1701388800}]->(post1)
+CREATE (bob)-[:CREATED {time: 1701475200}]->(post2)
+```
+
+You can execute these commands using the FalkorDB Python client.
+
+---
+
+## Step 3: Access Your Data
+
+### Connect to FalkorDB
+
+```python
+from falkordb import FalkorDB
+
+# Connect to FalkorDB
+client = FalkorDB(host="localhost", port=6379, password="your-password")
+graph = client.select_graph('social')
+```
+
+### Execute Cypher Queries
+
+#### Create the Graph
+
+```python
+create_query = """
+CREATE (alice:User {id: 1, name: "Alice", email: "alice@example.com"})
+CREATE (bob:User {id: 2, name: "Bob", email: "bob@example.com"})
+CREATE (charlie:User {id: 3, name: "Charlie", email: "charlie@example.com"})
+
+CREATE (post1:Post {id: 101, content: "Hello World!", date: 1701388800})
+CREATE (post2:Post {id: 102, content: "Graph Databases are awesome!", date: 1701475200})
+
+CREATE (alice)-[:FRIENDS_WITH {since: 1640995200}]->(bob)
+CREATE (bob)-[:FRIENDS_WITH {since: 1684108800}]->(charlie)
+CREATE (alice)-[:CREATED {time: 1701388800}]->(post1)
+CREATE (bob)-[:CREATED {time: 1701475200}]->(post2)
+"""
+
+graph.query(create_query)
+print("Graph created successfully!")
+```
+
+![image](https://github.com/user-attachments/assets/f67c9a1d-4b80-435d-9038-b7e1f931da74)
+
+#### Query the Graph
+
+```python
+# Find all friends of Alice
+query = """
+
+date and time as they are right now can be confusing, either use Python to create timestamps from actual dates or consider changing the attribute to something else which doesn't require time / date datatype
+
+MATCH (alice:User {name: "Alice"})-[:FRIENDS_WITH]->(friend)
+RETURN friend.name AS Friend
+"""
+result = graph.ro_query(query)
+
+print("Alice's friends:")
+for record in result:
+    print(record["Friend"])
+```
+
+#### Query Relationships
+
+```python
+# Find posts created by Bob
+query = """
+MATCH (bob:User {name: "Bob"})-[:CREATED]->(post:Post)
+RETURN post.content AS PostContent
+"""
+result = graph.ro_query(query)
+
+print("Posts created by Bob:")
+for record in result:
+    print(record["PostContent"])
+```
+
+---
+
+## Step 4: Explore Further
+
+Congratulations! 🎉 You have successfully modeled, loaded, and queried a social network graph with FalkorDB.
+
+Next, dive deeper into FalkorDB's powerful features:
+- [Advanced Cypher](/cypher)
+- [Database Operations](/operations)
+- [Integration with ML Workflows](/llm_support)
+
+For questions or support, visit our [community forums](https://www.falkordb.com/contact-us/)