A lightweight Python framework for building and orchestrating AI pipelines with message-based workflows.
Project description
Cyforge
A lightweight Python framework for building and orchestrating AI pipelines with message-based workflows.
Key Features
Modular Block Architecture: Build complex AI workflows using composable blocks including Responders, Schemas, and Switches, each of which takes function objects (ResponseGenerators) to specify how to handle messages within the workflow
Multi-Model Support: Integrate with OpenAI GPT models (gpt-4o, gpt-4o-mini) and extensible for other AI providers
Message-Based Flow Control: Manage conversation history and pipeline state through a ledger system with group policies
Flexible Response Generators: Create custom responders or use built-in ones (Echo, TextInput, MachineModel, CountLedger)
Conditional Routing: Direct message flow with Switch components for dynamic pipeline behavior
Parallel & Sequential Execution: Support for both parallel flows and dependency-based scheduling
Component Composition: Nest schemas within schemas to build hierarchical, reusable pipeline components
Group-Based Messaging: Filter and route messages using group tags for fine-grained control of visibility for models, external API, and UI
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