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A dynamic and flexible AI agent framework for building intelligent, multi-modal AI agents

Project description

GRAMI-AI: Dynamic AI Agent Framework

Version Python Versions License GitHub Stars

Overview

GRAMI-AI is a revolutionary, async-first AI agent framework designed to create intelligent, collaborative, and highly customizable AI agents across multiple domains.

Key Features

  • Dynamic AI Agent Creation
  • Multi-LLM Support (Gemini, OpenAI, Anthropic, Ollama)
  • Extensible Tool Ecosystem
  • Multiple Communication Interfaces
  • Flexible Memory Management
  • Secure and Scalable Architecture

Installation

Using pip

pip install grami-ai

From Source

git clone https://github.com/YAFATEK/grami-ai.git
cd grami-ai
pip install -e .

Quick Start

Basic Agent Creation

from grami.agent import Agent
from grami.providers import GeminiProvider

# Initialize a Gemini-powered Agent
agent = Agent(
    name="AssistantAI",
    role="Helpful Digital Assistant",
    llm_provider=GeminiProvider(api_key="YOUR_API_KEY"),
    tools=[WebSearchTool(), CalculatorTool()]
)

# Send a message
response = await agent.send_message("Help me plan a trip to Paris")
print(response)

Examples

We provide a variety of example implementations to help you get started:

Available Examples

  1. Basic Agents

    • examples/gemini_example.py: Multi-tool Gemini Agent
    • examples/openai_example.py: OpenAI-powered Agent
    • examples/anthropic_example.py: Claude Agent Implementation
  2. Advanced Scenarios

    • examples/agent_crew_example.py: Multi-Agent Collaboration
    • examples/web_research_agent.py: Web Research Specialist
    • examples/content_creation_agent.py: Content Generation Agent
  3. Tool Integration

    • examples/custom_tool_example.py: Creating Custom Tools
    • examples/kafka_communication_example.py: Inter-Agent Communication

Development Checklist

Core Framework Design

  • Implement AsyncAgent base class with dynamic configuration
  • Create flexible system instruction definition mechanism
  • Design abstract LLM provider interface
  • Develop dynamic role and persona assignment system
  • Implement multi-modal agent capabilities (text, image, video)

LLM Provider Abstraction

  • Unified interface for diverse LLM providers
    • Google Gemini integration (start_chat(), send_message())
    • OpenAI ChatGPT integration
    • Anthropic Claude integration
    • Ollama local LLM support
  • Standardize function/tool calling across providers
  • Dynamic prompt engineering support
  • Provider-specific configuration handling

Communication Interfaces

  • WebSocket real-time communication
  • REST API endpoint design
  • Kafka inter-agent communication
  • gRPC support
  • Event-driven agent notification system
  • Secure communication protocols

Memory and State Management

  • Pluggable memory providers
    • In-memory state storage
    • Redis distributed memory
    • DynamoDB scalable storage
    • S3 content storage
  • Conversation and task history tracking
  • Global state management for agent crews
  • Persistent task and interaction logs

Tool and Function Ecosystem

  • Extensible tool integration framework
  • Default utility tools
    • Kafka message publisher
    • Web search utility
    • Content analysis tool
  • Provider-specific function calling support
  • Community tool marketplace
  • Easy custom tool development

Agent Crew Collaboration

  • Inter-agent communication protocol
  • Workflow and task delegation mechanisms
  • Approval and review workflows
  • Notification and escalation systems
  • Dynamic team composition
  • Shared context and memory management

Use Case Implementations

  • Digital Agency workflow template
    • Growth Manager agent
    • Content Creator agent
    • Trend Researcher agent
    • Media Creation agent
  • Customer interaction management
  • Approval and revision cycles

Security and Compliance

  • Secure credential management
  • Role-based access control
  • Audit logging
  • Compliance with data protection regulations

Performance and Scalability

  • Async-first design
  • Horizontal scaling support
  • Performance benchmarking
  • Resource optimization

Testing and Quality

  • Comprehensive unit testing
  • Integration testing for agent interactions
  • Mocking frameworks for LLM providers
  • Continuous integration setup

Documentation and Community

  • Detailed API documentation
  • Comprehensive developer guides
  • Example use case implementations
  • Contribution guidelines
  • Community tool submission process
  • Regular maintenance and updates

Future Roadmap

  • Payment integration solutions
  • Advanced context understanding
  • Multi-language support
  • Enterprise-grade security features
  • AI agent marketplace

Documentation

For detailed documentation, visit our Documentation Website

Contributing

We welcome contributions! Please see our Contribution Guidelines

License

MIT License - Empowering open-source innovation

About YAFATEK Solutions

Pioneering AI innovation through flexible, powerful frameworks.

Contact & Support


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