Pipeline architecture 

Core classes 

Madj2k\AiCore\Assistant\Pipeline\Pipeline

Executes configured steps.

Madj2k\AiCore\Assistant\Pipeline\Processor\ProcessorInterface

Common interface for all pipeline processors.

Madj2k\AiCore\Assistant\Pipeline\Registry\ProcessorRegistry

Resolves processors by identifier.

Madj2k\AiCore\Assistant\Prompt\PromptBuilder

Builds LLM messages from profile prompts, step prompts, history and context.

Madj2k\AiCore\Assistant\Context\Context

Shared state object for one assistant request.

Processor responsibilities 

Processors must stay generic. Project-specific instructions belong into database records. A processor should read step configuration and context, execute its technical task and write results back into context.

LLM processors 

LLM-based processors should call the AI provider through the configured AiConnection and AiConnectorRegistry. They should not instantiate provider clients directly.

Streaming execution 

Madj2k\AiCore\Assistant\Pipeline\Pipeline can run in synchronous mode through run() or in streaming mode through runStream(). In streaming mode the pipeline forwards streamed chunks to the callback passed by the caller.

A processor can participate in streaming by implementing Madj2k\AiCore\Assistant\Pipeline\Processor\ProcessorStreamingInterface in addition to ProcessorInterface. If a streaming callback is available and the processor implements that interface, the pipeline calls processStream(). Otherwise it falls back to the regular process() method.

Prompt context builders 

Prompt context is assembled through Madj2k\AiCore\Assistant\Prompt\Context\Registry\ContextBuilderRegistry. The registry collects all tagged context builders that support the current processor type and returns sorted PromptSection objects. This keeps prompt context construction extensible without hard-coding every section in one processor.

Pipeline tracing 

Processors can emit trace events for started steps, finished steps, LLM requests, LLM responses, retrieval results and errors. Traces are essential for debugging pipeline behaviour.