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README.md

VeADK Examples

A hands-on tour of VeADK, from the smallest possible agent to a multi-agent workflow. Each folder is self-contained: a single main.py, an .env.example, and a bilingual README (English + 中文).

中文版见 README.zh.md

Learning path

# Example Level What you'll learn
01 Quickstart Simple Agent + Runner, one question
02 Custom tools Simple Let the agent call your Python functions
03 Short-term memory Medium Multi-turn conversation with a persistent session
04 Web search Medium Use a built-in Volcengine tool
05 Knowledgebase RAG Medium Ground answers in your own documents
06 Multi-agent workflow Complex Compose specialist agents with SequentialAgent
07 Structured output Medium Get schema-validated JSON with output_schema
08 Model config Simple Model fallbacks + model_extra_config per agent
09 Long-term memory Complex Recall facts across sessions (auto_save_session)
10 Agent routing Complex A coordinator that delegates to specialists dynamically
11 Tracing Complex Observe LLM/tool calls; dump or export spans

There is also a2ui_agent/ — a demo of agent-driven UI, run with veadk frontend --agents-dir examples.

For a deployable full app (web UI + agent API in one container, shipped to Volcengine AgentKit via veadk agentkit), see basic-app/.

The examples are grouped by concept: 01–02 basics, 03 & 09 memory, 04–05 tools & knowledge, 06 & 10 multi-agent, 07–08 model behavior, 11 observability.

Common setup

  1. Install VeADK (examples 05 needs the extensions extra):

    pip install veadk-python
# for the RAG example:
pip install "veadk-python[extensions]"

  2. In each example folder, copy the env template and add your keys:

    cd 01_quickstart
cp .env.example .env

    VeADK auto-loads .env from the current working directory. You can also use a config.yaml instead — see the configuration docs.

  3. Run:

    python main.py

Key concepts in one place

  • Agent — model + instruction + tools + memory/knowledge. Created once, reads model config from the environment.
  • Runner — drives a conversation; await runner.run(messages=..., session_id=...) returns the final text answer.
  • Tools — any Python function with type hints and a docstring; built-ins live under veadk.tools.builtin_tools.
  • Memory — short-term (conversation context, keyed by session_id) and long-term (across sessions).
  • KnowledgeBase — RAG over your documents; auto-adds a retrieval tool.
  • Workflow agents — SequentialAgent, ParallelAgent, LoopAgent to orchestrate multiple agents.

Learn more