# How to Install the Graph Module in activeloopai/hivemind > Learn how easy it is to install the graph module for activeloopai hivemind. Discover that the graph component is built-in with the Hivemind npm module, requiring no separate installation. - Repository: [Activeloop/hivemind](https://github.com/activeloopai/hivemind) - Tags: how-to-guide - Published: 2026-06-11 --- **The graph component is a built-in part of the Hivemind package—there is no separate package to install.** When you install the Hivemind npm module, the graph command and its runtime are automatically included. The graph module in the `activeloopai/hivemind` repository provides code intelligence capabilities for analyzing and visualizing codebase structures. Unlike distributed tools that require separate installations, this module ships as an integrated component of the main Hivemind package. This guide walks you through installing the package and activating the graph functionality for your projects. ## Install the Hivemind Package Since the graph module is bundled with the core library, you only need to install the `@deeplake/hivemind` package. The graph dependencies, including the Graph VFS, are listed as optional dependencies in the repository’s [`package.json`](https://github.com/activeloopai/hivemind/blob/main/package.json) and are pulled automatically during installation. ```bash npm install @deeplake/hivemind ``` ## Verify the Graph Command After installation, the package’s `bin` field points to [`bundle/cli.js`](https://github.com/activeloopai/hivemind/blob/main/bundle/cli.js), making the `hivemind` executable available in your path. You can verify that the graph sub-command is registered by checking the help output. ```bash npx hivemind graph --help ``` This command confirms that the CLI entry point in [`src/commands/graph.ts`](https://github.com/activeloopai/hivemind/blob/main/src/commands/graph.ts) is properly loaded and ready to accept graph-specific instructions. ## Initialize a Graph for Your Repository To enable Hivemind to maintain a live code-graph for a specific project, run the initialization command from your project’s root directory. ```bash hivemind graph init ``` This creates a hidden directory at `~/.deeplake/memory/graph/...` where snapshots are stored, as implemented in [`src/graph/snapshot.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/snapshot.ts). The initialization sets up the `graphsRoot` and `repoDir` paths necessary for the module to track your codebase’s evolution. ## Working with the Graph Module Once initialized, you can interact with the codebase graph through several CLI commands that leverage the snapshot storage and session management logic. ### Query Symbols Search for specific functions or classes that agents have touched using the query command. This functionality relies on the graph snapshot data stored in your local repository directory. ```bash hivemind graph query "AuthService" ``` ### Render Visualizations Generate static visual representations of your codebase structure. The [`src/graph/session-context.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/session-context.ts) file handles the session state that enables these rendering operations. ```bash hivemind graph render --output graph.png ``` This outputs a PNG or HTML file showing the current graph state, as documented in the README.md "Codebase graph" section. ## Key Implementation Files Understanding the source structure helps when debugging or extending the graph functionality: - **[`src/commands/graph.ts`](https://github.com/activeloopai/hivemind/blob/main/src/commands/graph.ts)**: The CLI entry point that registers the `graph` sub-command and handles argument parsing for all graph operations. - **[`src/graph/snapshot.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/snapshot.ts)**: Manages storage paths and persistence logic for graph snapshots, including the `graphsRoot` and `repoDir` variables that determine where data lives on disk. - **[`src/graph/session-context.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/session-context.ts)**: Generates the shell prompt line that advertises graph endpoints during active sessions, enabling real-time code intelligence. ## Summary - The graph module requires no separate installation—it is bundled with the `@deeplake/hivemind` package. - Install the package via `npm install @deeplake/hivemind` to access the graph CLI and its optional dependencies. - Initialize project-specific graphs using `hivemind graph init`, which stores data in `~/.deeplake/memory/graph/`. - Query symbols with `hivemind graph query` and render visualizations with `hivemind graph render`. - Core logic resides in [`src/commands/graph.ts`](https://github.com/activeloopai/hivemind/blob/main/src/commands/graph.ts) and [`src/graph/snapshot.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/snapshot.ts). ## Frequently Asked Questions ### Is the graph module a separate package from Hivemind? No. According to the `activeloopai/hivemind` source code, the graph component is a built-in part of the Hivemind package. When you install `@deeplake/hivemind`, the graph command and its runtime dependencies are automatically included as optional dependencies in [`package.json`](https://github.com/activeloopai/hivemind/blob/main/package.json). ### Where does Hivemind store graph snapshots? Graph snapshots are stored in a hidden directory under `~/.deeplake/memory/graph/...`. The [`src/graph/snapshot.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/snapshot.ts) file handles these storage paths, specifically managing the `graphsRoot` and `repoDir` variables to organize snapshots by repository. ### How do I verify the graph module is installed correctly? Run `npx hivemind graph --help`. If the command returns usage information for the graph sub-command, the module is properly registered. This verifies that the CLI entry point in [`src/commands/graph.ts`](https://github.com/activeloopai/hivemind/blob/main/src/commands/graph.ts) is accessible and that the package’s `bin` field in [`package.json`](https://github.com/activeloopai/hivemind/blob/main/package.json) is correctly configured. ### Can I use the graph module without running `hivemind graph init`? While you can access the `hivemind graph` CLI commands immediately after installation, running `hivemind graph init` is required to create the local storage structure for a specific repository. Without initialization, commands like `query` and `render` may not have persistent snapshot data to work with, as the [`src/graph/snapshot.ts`](https://github.com/activeloopai/hivemind/blob/main/src/graph/snapshot.ts) logic depends on the initialized directory structure.