FastAIAgent SDK¶
Build, debug, evaluate, and operate AI agents.
The only SDK with Agent Replay — fork-and-rerun debugging for AI agents.
Works standalone or connected to the FastAIAgent Platform for visual editing, production monitoring, and team collaboration.
What Makes FastAIAgent Different¶
| Feature | FastAIAgent | LangSmith | Langfuse |
|---|---|---|---|
| Agent Replay (fork-and-rerun) | Yes | No | No |
| Durable HITL — pause for days, resume from any process | Yes | No | No |
@idempotent side-effect protection |
Yes | No | No |
| Build agents in code | Yes | No | No |
| Cyclic chain workflows | Yes | LangGraph | No |
| Multi-turn agent simulation | Yes | No | No |
| Built-in guardrails | Yes | No | No |
| Safety library (PII, prompt-injection, moderation) | Yes | No | No |
| OTel-native tracing | Yes | Proprietary | Proprietary |
| Fragment prompt composition | Yes | No | No |
| Visual editor sync | Yes | No | No |
Quick Start¶
from fastaiagent import Agent, LLMClient
from fastaiagent.tools import FunctionTool
agent = Agent(
name="assistant",
system_prompt="You are a helpful assistant.",
llm=LLMClient(provider="openai", model="gpt-4o-mini"),
tools=[FunctionTool(name="greet", fn=lambda name: f"Hello, {name}!")]
)
result = agent.run("Say hello to World", trace=True)
print(result.output)
print(result.trace.summary())
Core Features¶
- Agents — Build agents with tools, memory, and multi-agent teams
- Durability — Pause for human approval, survive crashes, resume from any process. SQLite locally, Postgres in production.
- Streaming — Real-time token delivery from LLM to your app
- Structured Output — Force LLM responses into typed JSON schemas
- Chains — Directed graph workflows with cycles, typed state, and checkpointing
- Guardrails — Input/output/tool validation (code, regex, LLM judge)
- Tracing — OTel-native tracing with local SQLite storage
- Agent Replay — Fork-and-rerun debugging at any execution step
- Evaluation — Scorers, datasets, LLM-as-judge, trajectory eval
- Prompts — Registry with versioning and fragment composition
- Knowledge Base — Local file ingestion with embedding search, or
PlatformKBfor hosted KBs - Platform Connection — Connect for traces, prompts, eval, and replay
- Integrations — Auto-tracing for OpenAI, Anthropic, LangChain, CrewAI