grami-ai 0.3.112

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

GRAMI-AI: Dynamic AI Agent Framework

Vision and Purpose

GRAMI-AI is a revolutionary, async-first AI agent framework designed to solve complex computational challenges through intelligent, collaborative agent interactions. Our mission is to create a highly flexible, extensible platform that empowers developers to build sophisticated, context-aware AI systems capable of adapting and collaborating across diverse domains.

Framework Philosophy

The core philosophy of GRAMI-AI is to provide an abstraction layer that:

• Enables dynamic creation of AI agents with specific roles and capabilities
• Supports multiple Language Models (LLMs) with their unique interfaces
• Allows seamless integration of communication protocols
• Provides flexible memory management
• Supports extensible tool ecosystems

Key Architectural Goals

1. Dynamic Agent Creation

• Define agents with precise roles (e.g., Growth Manager, Content Creator)
• Customize system instructions and behavior
• Support multi-modal capabilities (text, image, video generation)

2. LLM Abstraction

• Unified interface for different LLMs (Gemini, OpenAI, Anthropic, Ollama)
• Handle provider-specific nuances (prompt building, chat interfaces)
• Flexible function/tool integration

3. Communication Interfaces

• Support multiple protocols (WebSocket, REST, Kafka)
• Enable inter-agent communication
• Implement global state management

4. Memory Management

• Pluggable memory providers (In-Memory, Redis, DynamoDB)
• Persistent conversation and task history
• Scalable state storage

5. Tool Ecosystem

• Default utility tools (Kafka publisher, web search)
• Easy custom tool development
• Provider-specific function handling

Roadmap and TODO List

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

Conceptual Agent Example

agent = AsyncAgent(
    llm=GeminiProvider(),            # LLM Provider
    memory=RedisMemoryProvider(),    # Memory Management
    tools=[                          # Extensible Tools
        KafkaPublisher(),
        WebSearchTool(),
        ContentAnalysisTool()
    ],
    system_instructions="You are a Growth Manager...",  # Role Definition
    communication_interface=WebSocketInterface(),
    storage=S3StorageProvider(),     # Optional Storage
    crew_config={                    # Optional Crew Configuration
        'team_members': ['ContentCreator', 'Researcher'],
        'communication_protocol': 'kafka'
    }
)

Community Contribution

We envision GRAMI-AI as a collaborative ecosystem where developers can:

• Create and share custom tools
• Develop new LLM integrations
• Build memory providers
• Implement communication interfaces
• Contribute to core framework development

Current Capabilities

• Async-first architecture
• Basic agent creation
• Gemini LLM integration
• Simple tool support
• Advanced inter-agent communication
• Multiple memory providers
• Comprehensive LLM support

Getting Started

pip install grami-ai

License

MIT License - Empowering open-source innovation

About YAFATEK Solutions

Pioneering AI innovation through flexible, powerful frameworks.

Contact & Support

• Email: [e-mail]
• GitHub: GRAMI-AI Issues

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