> ## Documentation Index > Fetch the complete documentation index at: https://praison.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Async Crew Kickoff > Run PraisonAI crews with native async execution — no thread offload required ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from praisonaiagents import Agent import asyncio agent = Agent(name="async-agent", instructions="Process tasks asynchronously.") async def main(): result = await agent.astart("Run this task asynchronously.") print(result) asyncio.run(main()) ``` Run PraisonAI crews with native async execution from FastAPI, Jupyter, Discord bots, and other event loop contexts. The user awaits `agent.astart()` from an async app; the crew kickoff runs natively on the event loop without thread offload. ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} graph LR subgraph "Native Async Flow" A[📋 Async Caller] --> B[🧠 praisonai.arun] B --> C[⚡ AgentsGenerator.agenerate_crew_and_kickoff] C --> D[🔧 FrameworkAdapter.arun] D --> E[🚀 AgentTeam.astart] E --> F[✅ Result] end classDef agent fill:#8B0000,color:#fff classDef tool fill:#189AB4,color:#fff class A agent class B,C,D,E,F tool ``` ## Quick Start Native async execution — no worker threads, true cooperative multitasking: ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} from fastapi import FastAPI import praisonai app = FastAPI() @app.post("/run") async def run_crew(): result = await praisonai.arun(agent_file="agents.yaml") return {"result": result} ``` Works directly in async cells without blocking: ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import praisonai result = await praisonai.arun(agent_file="agents.yaml") print(result) ``` *** ## How It Works ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} sequenceDiagram participant User participant praisonai participant AgentsGenerator participant Worker participant FrameworkAdapter participant AgentTeam participant Result User->>praisonai: await arun(agent_file) praisonai->>AgentsGenerator: agenerate_crew_and_kickoff() AgentsGenerator->>Worker: asyncio.to_thread(_aload_config) Worker-->>AgentsGenerator: config AgentsGenerator->>Worker: asyncio.to_thread(_aprepare_for_run) Worker-->>AgentsGenerator: prepared workflow AgentsGenerator->>FrameworkAdapter: arun(config, llm_config, topic) FrameworkAdapter->>AgentTeam: astart() AgentTeam-->>FrameworkAdapter: native async result FrameworkAdapter-->>AgentsGenerator: result AgentsGenerator-->>praisonai: result praisonai-->>User: result ``` ### Non-blocking startup Config loading, adapter setup, and workflow preparation run in a worker thread via `asyncio.to_thread`, so a slow disk read or heavy adapter import never stalls the event loop. The `_aload_config` and `_aprepare_for_run` helpers wrap the blocking `open()` / `yaml.safe_load` / adapter setup calls, keeping the loop free to serve other requests while startup work runs off-thread. **Sync/Async Parity:** As of PR #1870, sync and async kickoff paths share the same prep logic (AutoGen version selection, AgentOps init, cli\_backend validation), so behavior is identical between `generate_crew_and_kickoff()` and `agenerate_crew_and_kickoff()`. **Extended in [PR #2738](https://github.com/MervinPraison/PraisonAI/pull/2738):** Config validation, merge, and dump logic live in a single `_build_yaml_workflow` builder shared by both paths, so sync and async behavior can no longer drift apart. **PR #3252 (July 2026)** extended parity to the `process: workflow` path — observability, `cli_backend` validation, and `tool_timeout` diagnostics now fire on workflow YAML for both sync and async, matching the sequential / hierarchical treatment. As of [PR #3963](https://github.com/MervinPraison/PraisonAI/pull/3963), an **explicit** `tool_timeout` on `process: workflow` now **raises** on both paths rather than logging a warning — pick `sequential` or `hierarchical` if you need per-tool timeouts. See [tool\_timeout on workflow YAML](/docs/docs/features/yaml-workflows#tool_timeout-on-workflow-yaml). ### What's actually async | Adapter | Async path | Notes | | ----------------------------- | --------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | | `praisonai` (praisonaiagents) | Native — `AgentTeam.astart()` | True cooperative async | | `crewai` | Native — `crew.kickoff_async()` | Requires crewai ≥ 0.28; older installs transparently fall back to thread offload ([PR #4909](https://github.com/MervinPraison/PraisonAI/pull/4909)) | | `autogen` / `ag2` | Thread offload (default fallback) | AutoGen v0.2 is sync-only; v0.4 / ag2 are stubs | **PR #4909 (Sep 2026)** — `framework: crewai` gained a native async path. `CrewAIAdapter.arun()` now awaits `crew.kickoff_async()` directly (available since crewai 0.28) instead of pinning a worker thread. If an older crewai without `kickoff_async` is installed, the adapter transparently falls back to the base thread-offload path, so behaviour degrades instead of breaking. ### Workflow mode YAML files with `process: workflow` also run natively async via `YAMLWorkflowParser` + `workflow.astart()` — no extra configuration needed. *** ## Configuration Options | Option | Type | Default | Description | | --------------- | ------ | -------- | --------------------------------------------------------------------------------------------------------------- | | `agent_file` | `str` | Required | Path to the agent YAML file | | `framework` | `str` | `None` | Framework to use (auto-detected if None) | | `tools` | `list` | `None` | Additional tools to make available | | `agent_yaml` | `str` | `None` | Direct YAML content as string | | `cli_config` | `dict` | `None` | CLI configuration overrides (explicit keys win over `**kwargs`) | | `model` / `llm` | `str` | `None` | Selects the LLM — same as the CLI's `--llm` flag | | `session` | `str` | `None` | Resume a session — same as the CLI's `--resume` flag | | `**kwargs` | any | — | Any other keyword argument is forwarded through `cli_config` to the generator, mirroring the CLI's pass-through | See [Advanced CLI options from Python](/docs/developers/wrapper#advanced-cli-options-from-python) for the full alias table and precedence rules. *** ## Common Patterns ### FastAPI Background Task ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import asyncio import praisonai from fastapi import FastAPI, BackgroundTasks app = FastAPI() async def run_crew_background(): result = await praisonai.arun(agent_file="agents.yaml") # Store result in database, send notification, etc. print(f"Background crew completed: {result}") @app.post("/start-crew") async def start_crew(background_tasks: BackgroundTasks): background_tasks.add_task(run_crew_background) return {"message": "Crew started"} ``` ### Concurrent Crew Execution ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import asyncio import praisonai async def run_multiple_crews(): # Run all crews concurrently with true async results = await asyncio.gather( praisonai.arun(agent_file="research.yaml"), praisonai.arun(agent_file="analysis.yaml"), praisonai.arun(agent_file="summary.yaml") ) return results ``` ### CLI options from an async handler `arun()` (and `run()`) accept any extra keyword argument the CLI accepts. `model=`/`llm=` and `session=` get friendly Python aliases; everything else is forwarded through the same `cli_config` bridge the CLI already uses. ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import praisonai async def handler(): # model= is aliased to --llm; session= is aliased to --resume result = await praisonai.arun( "agents.yaml", model="gpt-4o", session="chat-42", ) return result ``` An explicit `cli_config=` still wins over loose kwargs — pass either, not both, for the same key. ```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} graph TB Start{How do you pass an option?} -->|Simple kwarg| Loose["praisonai.arun
model=gpt-4o"] Start -->|Need CLI-only key
or batch of values| Explicit["praisonai.arun
cli_config={...}"] Loose --> Merge[_merge_cli_config] Explicit --> Merge Merge --> Gen[AgentsGenerator] classDef question fill:#F59E0B,stroke:#7C90A0,color:#fff classDef choice fill:#189AB4,stroke:#7C90A0,color:#fff classDef merge fill:#6366F1,stroke:#7C90A0,color:#fff classDef gen fill:#10B981,stroke:#7C90A0,color:#fff class Start question class Loose,Explicit choice class Merge merge class Gen gen ``` *** ## Best Practices Under native async, `asyncio.CancelledError` and `asyncio.wait_for` now actually cancel SDK work instead of being trapped behind a worker thread: ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import asyncio import praisonai async def cancelable_crew(): try: # This will properly cancel if timeout is reached result = await asyncio.wait_for( praisonai.arun(agent_file="agents.yaml"), timeout=30.0 ) return result except asyncio.TimeoutError: print("Crew execution timed out and was cancelled") return None ``` When running multiple crews, use `asyncio.gather` for parallel execution: ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import asyncio import praisonai # ✅ Concurrent execution with native async crew1_task = praisonai.arun(agent_file="crew1.yaml") crew2_task = praisonai.arun(agent_file="crew2.yaml") results = await asyncio.gather(crew1_task, crew2_task) # ❌ Sequential execution (slower) result1 = await praisonai.arun(agent_file="crew1.yaml") result2 = await praisonai.arun(agent_file="crew2.yaml") ``` Both `praisonai` and `crewai` use native async — `AgentTeam.astart()` and `crew.kickoff_async()` respectively. AutoGen v0.2 still falls back to the bounded thread-offload pool because its `initiate_chats` is sync-only. ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import praisonai # Native async for both praisonai and crewai (crewai ≥ 0.28) result = await praisonai.arun(agent_file="agents.yaml", framework="crewai") ``` Wrap async crew execution in try-catch blocks: ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}} import asyncio import logging import praisonai logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) async def safe_crew_run(): try: result = await praisonai.arun(agent_file="agents.yaml") return {"success": True, "result": result} except Exception as e: logger.error(f"Crew execution failed: {e}") return {"success": False, "error": str(e)} ``` *** ## Related Use {topic} placeholders safely alongside JSON literals Custom framework adapters with async support