Friday Platform: Getting Started with Agentic Workflows Using the FAST Framework

The official example repository for the FAST (Friday Agent Studio & Toolkit) framework provides out-of-the-box Agentic workflow templates to help developers quickly get started building autonomous AI agent applications.

Against the backdrop of the rapid evolution of Agentic Workflow (autonomous agent workflow) technology, various development frameworks and tools have emerged one after another. Among them, FAST (Friday Agent Studio & Toolkit) is a comprehensive framework focused on simplifying Agentic application development, aiming to lower the barrier for developers to build autonomous AI agent systems.

The examples repository of Friday Platform is the official example collection of the FAST framework, providing multiple out-of-the-box workflow templates covering typical application scenarios from basic conversations to complex multi-step tasks. These examples are not only learning materials but also starter templates that can be directly used in production environments.

The design goal of the FAST framework is to enable developers to quickly build fully functional Agentic applications without needing to deeply understand the underlying LLM principles. Its core design principles include:

• Declarative Configuration: Define agent behavior via YAML/JSON configuration files to reduce boilerplate code
• Modular Components: Prebuilt common tools and capability modules for on-demand combination
• Visual Debugging: Provide visual tracking of workflow execution
• Progressive Complexity: A smooth learning curve from simple examples to complex systems

The FAST framework is not developed in isolation but actively integrates with existing ecosystems:

• Model Compatibility: Supports multiple LLM backends such as OpenAI, Anthropic, and local models
• Tool Integration: Built-in common tools (search, database, API calls, etc.)
• Framework Interoperability: Can be used in collaboration with frameworks like LangChain and LlamaIndex
• Deployment-Friendly: Supports multiple modes including local development, containerized deployment, and Serverless

The examples repository is organized by application scenario and complexity, and mainly includes the following categories of examples:

Hello Agent The simplest Agentic Workflow example, demonstrating:

• Basic agent configuration
• Single-turn conversation handling
• System prompt setting

Tool Calling Demo Demonstrates how agents call external tools:

• Tool definition and registration
• Parameter parsing and validation
• Tool execution and result processing

Memory Basics Introduces the use of the agent memory system:

• Short-term memory (conversation context)
• Long-term memory (vector storage)
• Memory retrieval and update

ReAct Pattern Implements the classic Reasoning + Acting agent pattern:

• Observe-Think-Act loop
• Multi-step task decomposition
• Accumulation and utilization of intermediate results

Plan-and-Execute The plan-first-then-execute pattern:

• Task decomposition and plan generation
• Step-by-step execution and monitoring
• Trigger conditions for plan adjustment

Multi-Agent Collaboration Multi-agent collaboration scenarios:

• Agent role definition
• Inter-agent communication mechanism
• Task assignment and result aggregation

Research Assistant Intelligent research assistant:

• Multi-source information retrieval
• Content summarization and integration
• Structured report generation

Code Review Agent Code review agent:

• Code analysis and understanding
• Potential issue identification
• Improvement suggestion generation

Customer Support Bot Customer service bot:

• Intent recognition and classification
• Knowledge base retrieval
• Ticket creation and escalation

Data Processing Pipeline Data processing pipeline:

• Multi-step data transformation
• Error handling and retries
• Result validation and reporting