scenario-go is an open-source Go SDK that enables developers to build AI-driven conversational agents by defining scenarios with multi-step workflows. It offers prompt template management, context handling, memory storage, and seamless integration with LLM APIs. Developers can orchestrate complex chains of AI tasks, monitor execution, and reuse scenario components, streamlining the creation of sophisticated chatbots, virtual assistants, and automation scripts in Go projects.
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scenario-go
scenario-go is an open-source Go SDK that enables developers to build AI-driven conversational agents by defining scenarios with multi-step workflows. It offers prompt template management, context handling, memory storage, and seamless integration with LLM APIs. Developers can orchestrate complex chains of AI tasks, monitor execution, and reuse scenario components, streamlining the creation of sophisticated chatbots, virtual assistants, and automation scripts in Go projects.
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What is scenario-go?
scenario-go serves as a robust framework for constructing AI agents in Go by allowing developers to author scenario definitions that specify step-by-step interactions with large language models. Each scenario can incorporate prompt templates, custom functions, and memory storage to maintain conversational state across multiple turns. The toolkit integrates with leading LLM providers via RESTful APIs, enabling dynamic input-output cycles and conditional branching based on AI responses. With built-in logging and error handling, scenario-go simplifies debugging and monitoring of AI workflows. Developers can compose reusable scenario components, chain multiple AI tasks, and extend functionality through plugins. The result is a streamlined development experience for building chatbots, data extraction pipelines, virtual assistants, and automated customer support agents fully in Go.
Who will use scenario-go?
- Go developers
- AI researchers
- Software engineers building chatbots
- DevOps engineers automating workflows
- Customer support teams integrating AI
How to use the scenario-go?
- Step1: Install scenario-go module using `go get github.com/langwatch/scenario-go`
- Step2: Define a scenario struct and steps with prompts and handlers
- Step3: Configure LLM provider credentials and API endpoints
- Step4: Initialize the scenario engine and load scenarios
- Step5: Execute scenarios by calling Run functions
- Step6: Handle responses, manage memory, and implement custom logic
- Step7: Monitor logs and iterate on prompt templates for optimization
Platform
- Linux
- Mac
- Windows
scenario-go's Core Features & Benefits
The Core Features
- Scenario definition with step-by-step workflows
- Prompt template management
- LLM API integration
- Memory and context handling
- Conditional branching and custom functions
- Logging and error handling
- Plugin extension support
The Benefits
- Accelerates development of AI agents
- Ensures structured conversational flows
- Simplifies integration with LLM providers
- Enhances maintainability with reusable components
- Supports complex multi-step AI tasks
scenario-go's Main Use Cases & Applications
- Building AI-driven chatbots for websites and apps
- Automating customer support conversations
- Creating interactive virtual assistants
- Extracting structured data from text via AI
- Orchestrating multi-step AI workflows in backend services
FAQs of scenario-go
scenario-go Company Information
- Website:
- Company Name: LangWatch
- Support Email:
- Facebook:
- X(Twitter):
- YouTube:
- Instagram:
- Tiktok:
- LinkedIn:
scenario-go Reviews
5/5
scenario-go's Main Competitors and alternatives?
LangChain-Go
BobSwift AI Framework
GPT-Forge
Weaviate Scenario Engine
Botpress
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