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Eino Framework Guide
Eino (pronounced "i know") is a Go framework for building LLM applications.
Core Concepts
Component
Standardized interfaces for AI capabilities. Each interface has multiple interchangeable implementations.
| Component | What It Does | Key Interface |
|---|---|---|
| ChatModel | LLM inference (generate / stream) | model.BaseChatModel, model.ToolCallingChatModel |
| Tool | Functions the model can call | tool.InvokableTool, tool.EnhancedInvokableTool |
| Embedding | Text to vector | embedding.Embedder |
| Retriever | Vector/keyword search | retriever.Retriever |
| Indexer | Store documents with vectors | indexer.Indexer |
| ChatTemplate | Prompt formatting with variables | prompt.ChatTemplate |
| Document Loader/Transformer | Load and process documents | document.Loader, document.Transformer |
| Callback Handler | Observability and tracing | callbacks.Handler |
Implementations live in eino-ext (OpenAI, Claude, Gemini, Ark, Ollama, Milvus, Redis, Elasticsearch, etc.).
-> Use /eino-component for selecting, configuring, and using components.
Orchestration (Compose)
Three APIs for wiring components into executable pipelines. All compile to a Runnable[I, O] with four execution modes (Invoke, Stream, Collect, Transform).
| API | Topology | When to Use |
|---|---|---|
| Graph | Directed graph, supports cycles | Complex flows with branching, loops (e.g., ReAct pattern) |
| Chain | Linear sequential | Simple pipelines (e.g., template -> model) |
| Workflow | DAG with field-level mapping | Parallel branches with struct field routing |
The compose layer handles type checking, stream conversion between nodes, concurrency, callback injection, and option distribution automatically.
-> Use /eino-compose for building graphs, chains, workflows, streaming, callbacks, and state management.
ADK (Agent Development Kit)
High-level abstractions for building AI agents. Encapsulates the model-tool-loop pattern.
| Concept | What It Does |
|---|---|
| ChatModelAgent | ReAct-style agent: model generates, calls tools, loops until done |
| DeepAgent | Pre-built agent with filesystem backend, tool search, summarization |
| Runner | Executes agents, manages checkpoints, emits event streams |
| Middleware (Handlers) | Intercept and extend agent behavior (filesystem, summarization, plan-task, etc.) |
| Interrupt/Resume | Human-in-the-loop: pause agent, get user input, resume from checkpoint |
| AgentTool | Wrap an agent as a tool callable by another agent |
-> Use /eino-agent for building agents, configuring middleware, runners, and human-in-the-loop.
Schema
Shared data types used across all layers:
schema.Message-- Conversation message (system/user/assistant/tool roles, content, tool calls)schema.Document-- Document with content, metadata, and vector embeddingsschema.ToolInfo-- Tool description with JSON schema parametersschema.StreamReader[T]-- Generic streaming reader (alwaysdefer stream.Close())
Repositories
| Repository | Role |
|---|---|
github.com/cloudwego/eino | Core: interfaces, schema, compose engine, ADK, callbacks |
github.com/cloudwego/eino-ext | Implementations: model providers, vector stores, tools, callback handlers |
Packages at a Glance
eino (core):
| Package | Contains |
|---|---|
schema | Message, Document, ToolInfo, StreamReader |
components/model | ChatModel and AgenticModel interfaces |
components/tool | Tool interfaces (BaseTool, InvokableTool, StreamableTool, Enhanced variants) |
components/embedding | Embedder interface |
components/retriever | Retriever interface |
components/indexer | Indexer interface |
components/document | Loader, Transformer interfaces |
components/prompt | ChatTemplate interface |
compose | Graph, Chain, Workflow, ToolsNode, Runnable, state, checkpoint |
callbacks | Handler interface, global/per-run registration |
adk | Agent, Runner, ChatModelAgent, middleware, interrupt/resume |
adk/prebuilt/deep | DeepAgent preset |
eino-ext (implementations):
| Package | Contains |
|---|---|
components/model/{provider} | ChatModel implementations (openai, claude, gemini, ark, ollama, deepseek, qwen, etc.) |
components/embedding/{provider} | Embedding implementations (openai, ark, ollama, etc.) |
components/retriever/{backend} | Retriever implementations (redis, milvus2, es8, qdrant) |
components/indexer/{backend} | Indexer implementations (redis, milvus2, es8, qdrant) |
components/tool/{type} | Tool implementations (mcp, googlesearch, duckduckgo, bingsearch, etc.) |
callbacks/{provider} | Callback handlers (cozeloop, apmplus, langfuse, langsmith) |
adk/backend/local | Local filesystem Backend for DeepAgent |
Choosing Your Approach
| Scenario | Approach | Skill |
|---|---|---|
| Single model call (generate or stream) | Use ChatModel directly | /eino-component |
| Multi-turn agent with tools | ChatModelAgent + Runner | /eino-agent |
| Production agent with filesystem, tool search | DeepAgent | /eino-agent |
| Linear pipeline (template -> model) | Chain | /eino-compose |
| Complex flow with branching or loops | Graph | /eino-compose |
| Parallel branches with field mapping | Workflow | /eino-compose |
| RAG (embed + index + retrieve) | Indexer + Retriever + Embedding | /eino-component |
| Agent with human approval | Interrupt/Resume + Runner | /eino-agent |
| Observability and tracing | Callback handlers | /eino-component |
Reference Files
reference/schema.md-- Core data types shared across all layers: Message, Document, ToolInfo, StreamReaderreference/runnable.md-- Runnable[I, O] interface, four execution modes, runtime optionsreference/quick-start.md-- Three complete working examples (ChatModel, Agent+Runner, Chain)
Instructions to Agent
- Route to the appropriate skill (
/eino-component,/eino-compose,/eino-agent) when the question is specific. Consult the "Choosing Your Approach" table. - Always provide Go code examples using real import paths from
github.com/cloudwego/einoandgithub.com/cloudwego/eino-ext. - For component implementation details, always read the provider's reference file before generating code. Do not assume constructor or config naming conventions.
- Prefer ADK (ChatModelAgent + Runner) for agent use cases over manually building ReAct loops with compose graphs. For interactive multi-turn applications needing preemption and lifecycle management, recommend TurnLoop.
- When showing streaming code, always include
defer stream.Close().
