newDocumentTransformer component initialization function of node 'MarkdownSplitter' in graph 'KnowledgeIndexing'

newIndexer component initialization function of node 'RedisIndexer' in graph 'KnowledgeIndexing'

newLambda1 component initialization function of node 'ReactAgent' in graph 'EinoAgent'

newLoader component initialization function of node 'FileLoader' in graph 'KnowledgeIndexing'

newRetriever component initialization function of node 'RedisRetriever' in graph 'EinoAgent'

newScoreWorkflow builds the single-node inner workflow used by each BatchNode task. It is intentionally trivial: BatchNode provides the parallelism, n

演示【方式2】ProcessState：在 Lambda 内部主动获取 State

processMessageFuture reads from the MessageFuture and prints intermediate results. Each iteration of the ReAct loop produces multiple message streams:

register registers all routers.

renderGraph builds a Mermaid diagram section for the given GraphInfo. It: 1) Collects and sorts node keys for deterministic output 2) Renders nodes (i

Scenario 1: Basic Sequential Processing Demonstrates: MaxConcurrency=0 for sequential execution

Scenario 2: Concurrent Processing Demonstrates: MaxConcurrency>0 for parallel execution with limit

Scenario 6: Interrupt & Resume Demonstrates: Human-in-the-loop workflow using compose.Interrupt and compose.BatchResumeWithData Flow: 1. First invoca

runOneTurn executes a single agent turn via Runner and returns the concatenated text output from the agent.

Scenario 7: Parent Graph with Reduce Node Demonstrates: - BatchNode as a node in a larger pipeline - WithInnerOptions for passing runtime options (cal

Scenario 3: With Compile Options Demonstrates: InnerCompileOptions for configuring inner workflow at compile time

Scenario 5: Normal Error Handling Demonstrates: How BatchNode handles errors from individual tasks

Scenario 4: With Invoke Options (Callbacks) Demonstrates: Callbacks for batch-level monitoring via context

safeWrapReader proxies chunks from sr; on a stream error it emits the error as a final chunk instead of propagating it, so the model sees a complete (

scoreOneChunk asks the model to rate the relevance of a single chunk (0–10) and extract the most relevant excerpt. Parse errors are treated as score 0

seedBuggyProject pre-populates the InMemoryBackend with a URL shortener project that has multiple intentional bugs and missing features. The Ralph Loo

slowAgent returns a mock that delays before replying, respecting context cancellation.

splitIntoChunks splits text into chunks of at most chunkSize characters, breaking on paragraph boundaries (\n\n) where possible, then on newlines.

synthesize builds a prompt from the top-k chunks and generates a cited answer.

transcribeLive simulates a live transcription service that emits tokens over time. It may emit an error mid-stream for demonstration when encountering