Geers AI Lang Graph is an open-source toolkit enabling developers to build graph-based AI agents that chain large language model calls, maintain structured memory nodes, and visualize conversational workflows. It supports multiple LLM providers and customizable prompt templates for complex agent orchestration.
Geers AI Lang Graph is an open-source toolkit enabling developers to build graph-based AI agents that chain large language model calls, maintain structured memory nodes, and visualize conversational workflows. It supports multiple LLM providers and customizable prompt templates for complex agent orchestration.
Geers AI Lang Graph provides a graph-based abstraction layer for building AI agents that coordinate multiple LLM calls and manage structured knowledge. By defining nodes and edges representing prompts, data, and memory, developers can create dynamic workflows, track context across interactions, and visualize execution flows. The framework supports plugin integrations for various LLM providers, custom prompt templating, and exportable graphs. It simplifies iterative agent design, improves context retention, and accelerates prototyping of conversational assistants, decision-support bots, and research pipelines.
Who will use Geers AI Lang Graph?
AI researchers
Developers building AI agents
Data scientists
Software engineers
How to use the Geers AI Lang Graph?
Step1: Clone the repository from GitHub.
Step2: Install dependencies via pip or poetry.
Step3: Configure your LLM provider API keys in the settings file.
Step4: Define nodes and edges in a language graph schema file.
Step5: Write a driver script to execute and visualize the agent workflow.
Step6: Run examples and extend with custom prompt templates.
Platform
mac
windows
linux
Geers AI Lang Graph's Core Features & Benefits
The Core Features
Graph-based chaining of LLM prompts
Structured memory nodes and edges
Support for multiple LLM providers
Customizable prompt templating
Workflow visualization and export
The Benefits
Modular, reusable agent flows
Improved context retention
Rapid prototyping of conversational agents
Open-source extensibility
Clear visualization of execution paths
Geers AI Lang Graph's Main Use Cases & Applications