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FastADK v0.2.0: Enterprise-Ready Agent Development Kit Latest

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Mathews-Tom released this 09 Jul 19:52

v0.2.0

27f735c

FastADK v0.2.0: Enterprise-Ready Agent Development Kit

Release Highlights

FastADK 0.2.0 is a major release that transforms the framework into an enterprise-ready agent development toolkit. This version introduces comprehensive token & cost tracking, advanced memory management, performance optimizations, extended integrations, improved developer experience, and robust observability features.

🚀 Major Features

💰 Token and Cost Management

Complete token usage tracking across all providers
Cost estimation based on provider-specific pricing
Configurable budgets with alerts and automatic cutoffs
Detailed metrics for token usage optimization

🧠 Advanced Context and Memory

Sliding window memory with automatic summarization
Vector store integration for semantic memory capabilities
Persistent storage backends (Redis, SQL) for production use
Customizable context policies for fine-grained control

⚡ Performance Optimizations

True async execution for all model and tool calls
Parallel workflow execution for complex operations
Intelligent caching to reduce redundant LLM calls
Lazy tool execution for improved efficiency
Batch processing utilities for high-throughput scenarios

🔌 Extensibility and Integrations

Pluggable model provider interface for custom backends
Dynamic plugin system for third-party extensions
Slack and Discord adapters for easy deployment
Multi-agent orchestration for complex scenarios
Fine-tuning helpers for specialized models

🛠️ Developer Experience

Interactive REPL mode for rapid prototyping
Enhanced CLI tools for project scaffolding and management
Comprehensive testing utilities with mocks and scenarios
VSCode integration with snippets and settings
Configuration validation and hot reload capabilities

📊 Observability and Monitoring

Structured logging for all agent events
OpenTelemetry integration for distributed tracing
Prometheus metrics for real-time monitoring
Sensitive data redaction for privacy compliance

📚 Documentation and Examples

Expanded cookbook with practical recipes
New example agents for real-world use cases
Streamlit UI example for web interfaces
Comprehensive API reference and conceptual guides

📋 Detailed Changelog

Added

Token and Cost Tracking

Added TokenUsage data class to record prompt, completion, and total tokens
Extended each provider client to capture usage from responses
Created CostCalculator utility for estimating costs based on token usage
Added TokenBudget component with configurable budgets and alerts
Added structured logging for token usage and costs
Added Prometheus metrics for token usage and cost estimation

Context Management and Memory Improvements

Added ContextPolicy abstract class with built-in policies (MostRecent, SummarizeOlder, HybridVectorRetrieval)
Implemented SummarizationService for LLM-based conversation summarization
Added vector store backend integration with VectorMemoryBackend
Implemented persistent memory backends for Redis and SQL
Added configuration options for memory policies

Scalability and Performance Optimizations

Improved async execution for all model and tool calls
Enhanced Workflow class to support concurrent sub-tasks
Implemented CacheManager with in-memory LRU and Redis options
Added lazy tool execution logic to improve efficiency
Created BatchUtils for common bulk operations

Extensibility and Integration

Defined ModelProviderABC interface for custom providers
Implemented PluginManager for discovering and loading custom modules
Added Slack and Discord adapters for integration
Added multi-agent orchestration API
Included fine-tuning helper module

Developer Experience and Tooling

Extended CLI with repl, init, and config validate commands
Added verbose debugging with chain-of-thought capture
Created MockLLM and MockTool classes for testing
Added test scenario decorators for structured testing
Added VSCode snippets and configuration support
Implemented config reload endpoint

Observability and Monitoring

Added structured JSON logging for all agent events
Integrated OpenTelemetry for traces and spans
Added Prometheus metrics endpoint
Implemented redaction filter for sensitive data

UI/UX and Documentation

Added cookbook, plugin guide, and performance tuning documentation
Expanded examples folder with new agent templates
Implemented project scaffolding with fastadk init
Added Streamlit chat UI example
Added community feedback links

Changed

Improved async performance and error handling
Enhanced memory management for long conversations
Optimized token usage and cost calculations
Upgraded provider integrations with the latest APIs

Fixed

Various bug fixes and stability improvements
Fixed memory leaks in long-running conversations
Addressed race conditions in async workflows
Improved error reporting and exception handling

🔧 Installation

pip install fastadk==0.2.0

Or using uv:

uv add fastadk==0.2.0

📖 Documentation

For comprehensive documentation, visit:
https://fastadk.dev

🎯 Example Usage

from fastadk.core import Agent, BaseAgent, tool

@Agent(
    model="gemini-1.5-pro",
    memory_backend="redis",
    cache_enabled=True
)
class WeatherAgent(BaseAgent):
    @tool
    def get_weather(self, location: str) -> str:
        """Get weather for a location."""
        # Implementation...
        return f"Weather for {location}: Sunny, 75°F"
    
    @tool
    def get_forecast(self, location: str, days: int = 5) -> list:
        """Get forecast for a location."""
        # Implementation...
        return [{"day": i, "forecast": "Sunny"} for i in range(1, days+1)]

# Create and run the agent
agent = WeatherAgent()
result = await agent.run("What's the weather in New York?")

❤️ Acknowledgements

Thank you to all contributors who helped make this release possible! Special thanks to our early adopters who provided valuable feedback and use cases.

🔜 What's Next

We're already planning the next release with:

Enhanced RAG capabilities
More third-party integrations
Function calling improvements
Multi-modal support

Stay tuned and join our community!

Assets 2

FastADK 0.1.0 Release Notes

Mathews-Tom released this 05 Jul 18:47

v0.1.0

78b6c77

FastADK 0.1.0 Release Notes

🚀 First Public Release

We're thrilled to announce the first public release of FastADK, now available on PyPI! FastADK is a developer-friendly framework for building AI agents with Google ADK, providing high-level abstractions, declarative APIs, and intuitive tooling to dramatically improve the agent development experience.

📦 Installation

FastADK can now be installed directly from PyPI:

## With pip
pip install fastadk

# With uv
uv add fastadk

✨ Key Features

Declarative Agent Creation: Create powerful AI agents with minimal boilerplate using the @agent decorator
Tool Management: Easily implement agent tools with the @tool decorator, with automatic type validation
Multi-Provider Support: Works with Gemini, OpenAI, and Anthropic models out of the box
Memory Integration: Built-in support for conversation memory with pluggable backends
Exception Handling: Comprehensive exception framework for robust error handling
HTTP API Integration: Serve agents via FastAPI with a few lines of code
Workflow Orchestration: Create complex agent workflows with sequential and parallel execution
Type Safety: Strong typing support throughout the framework for better IDE integration and runtime validation

📚 Examples

The package includes several examples demonstrating key features:

Basic Examples

Weather Agent: A simple agent that fetches real weather data and provides forecasts
Exception Demo: Demonstrates the comprehensive exception handling system

Advanced Examples

Travel Assistant: A fully-featured travel assistant with memory, multiple tools, and lifecycle hooks
Workflow Demo: Shows how to build complex workflows with conditional branching and parallel execution

API Examples

HTTP Agent: Multi-agent HTTP API server demonstrating how to serve agents via FastAPI

🛠️ Breaking Changes

This is the first public release, so there are no breaking changes to report.

🔜 Coming Soon

Enhanced vector memory support
More pre-built agent templates
Advanced caching mechanisms
Improved observability and monitoring
Fine-tuning integrations

🙏 Acknowledgments

We'd like to thank all the contributors who helped make this release possible. FastADK builds on the foundation provided by Google's Agent Development Kit and aims to bring a more developer-friendly experience to agent building.

Documentation

For complete documentation, visit our GitHub repository.

Issues and Feedback

If you encounter any issues or have feedback, please open an issue on our GitHub repository.

Contributors

tool and agent

Assets 2

Releases: Mathews-Tom/FastADK

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