Merge pull request #48 from TigerGraph-DevLabs/feature/tigergraph_api

docs: modify installation.md

Author: xuanleilin

docs/getting_started/installation.md

@@ -6,23 +6,27 @@ Follow this guide to install and set up **TigerGraphX** in your environment.
 
 ## Requirements
 
-This project requires **Python 3.10, 3.11 or 3.12** and **TigerGraph**. Ensure you meet the following prerequisites before proceeding:
+This project requires **Python 3.10, 3.11, or 3.12** and **TigerGraph 4.1 or later**. Ensure you meet the following prerequisites before proceeding:
 
 ### **1. Python**
-- Please ensure Python 3.10, 3.11 or 3.12 is installed on your system.
+
+- Ensure Python 3.10, 3.11, or 3.12 is installed on your system.
 - You can download and install it from the [official Python website](https://www.python.org/downloads/).
 
 ### **2. TigerGraph**
 
-TigerGraph is required for this project and can be set up in one of the following ways:
+TigerGraph **version 4.1 or ** is required for this project. You can set up TigerGraph in one of the following ways:
 
 - **TigerGraph DB**: Install and configure a local instance of TigerGraph.
 - **TigerGraph Cloud**: Use a cloud-hosted instance of TigerGraph.
-- **TigerGraph Docker**: Use a Docker container to run TigerGraph.
+- **TigerGraph Docker**: Run TigerGraph using a Docker container.
+
+> ⚠️ **Minimum Required Version: TigerGraph 4.1**
+> ✅ **Recommended Version: TigerGraph 4.2+** to enable **TigerVector** support and advanced features such as hybrid retrieval.
 
-It is recommended to use **TigerGraph LTS (Long-Term Support) Versions**, which can be downloaded from the [TigerGraph Downloads page](https://dl.tigergraph.com/). To enable support for **TigerVector** and leverage advanced features like hybrid retrieval, ensure you are using **TigerGraph 4.2 or above**.
+We recommend using **TigerGraph LTS (Long-Term Support) versions**, available from the [TigerGraph Downloads page](https://dl.tigergraph.com/).
 
-Refer to the official [TigerGraph Documentation](https://docs.tigergraph.com/home/) for detailed installation and configuration instructions.
+For installation and configuration guidance, refer to the official [TigerGraph Documentation](https://docs.tigergraph.com/home/).
 
 ---
 
@@ -93,11 +97,22 @@ poetry show --with dev
 
 This ensures all required dependencies (including optional ones) are successfully installed.
 
+
+#### **Activate the Virtual Environment**
+
+Activate the environment using:
+
+```bash
+eval $(poetry env activate)
+```
+
+For more information about managing virtual environments in Poetry, please refer to the official documentation: [Managing Environments](https://python-poetry.org/docs/managing-environments/).
+
 ---
 
 ## Next Steps
 
-- [TigerGraphX Quick Start](quick_start_graph.ipynb): Learn how to build your first graph with TigerGraphX.
+- [TigerGraphX Quick Start](quick_start_graph.md): Learn how to build your first graph with TigerGraphX.
 
 ---
 

docs/getting_started/quick_start_vector.md

@@ -373,7 +373,7 @@ To clear the data and completely remove the graph—including schema, loading jo
 
 Now that you've learned how to use TigerGraph for storing both graph data and vectors, you can dive into more advanced features of TigerGraphX:
 
-- [GraphRAG Overview](../graphrag/graphrag_overview.md): Learn about integrating graphs with LLMs.
+- [TigerGraph Quick Start Guide for Graph and Vector Storage](quick_start_both.md): Quickly get started with TigerGraph for storing both graph and vector data.
 - [API Reference](../reference/introduction.md): Dive deeper into TigerGraphX APIs.
 
 ---

docs/reference/01_core/graph.md

@@ -157,7 +157,7 @@ Running the command will create a graph using the user-defined schema if it does
 
 ---
 
-**Alternative Connection Setup Methods**
+### Alternative Connection Setup Methods
 
 An alternative way to set up the connection is by directly assigning the `tigergraph_connection_config` parameter. Suppose we have already defined the same `graph_schema` as before. Now let's define the connection. Like the schema, the connection can be defined using a Python dictionary, YAML file, or JSON file. Below are examples of defining the same connection using all three approaches: