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How I built a terminal AI agent that never hits rate limits (open source, Python)

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A month ago I was building a side project and kept

hitting the same wall: I'd start a task with OpenAI,

hit the rate limit, manually switch to Anthropic,

hit a different limit, then open yet another tab to

configure Gemini. Three API dashboards open, three

different billing pages, and my actual project sitting

there waiting.



I didn't want to pay for multiple APIs just to keep

working. So I built something to fix it.





What I built



HelloChusquis is an open source terminal AI agent that automatically switches between 35+ AI providers when one hits rate limits or goes down.



One config file. Zero manual switching.




CODE
pip install hellochusquis
hellochusquis --quick






The agent tries your first provider, and if it fails or hits limits, silently falls back to the next one. You never see an error — the task just completes.






The hardest part



The trickiest bug was getting the agent to execute commands correctly during multi-step plans. The agent would generate a plan, start executing, and then lose access to its tools halfway through. Step 1 worked, steps 2-6 failed with "Unknown tool" errors.



The problem: tools were available in the initial context but weren't being passed through each step of the execution loop. Once I fixed the context propagation, multi-step tasks like "search the web for AI news and summarize the top 3 stories" started working end to end.






How the fallback works



The core is a ProviderPool class that tracks each provider's state:




CODE
@dataclass
class Provider:
name: str
base_url: str
api_key: str
model: str
exhausted: bool = False
exhausted_at: datetime = None

class ProviderPool:
def chat(self, messages, tools=None):
available = self._available()
for provider in available:
try:
return self._call(provider, messages, tools)
except Exception as e:
self._handle_error(provider, e)
raise RuntimeError("All providers failed")






When a provider returns a 429, 402, or 503, it gets marked as exhausted with a timestamp. After a configurable window (default 1 hour), it resets automatically. It's essentially a circuit breaker pattern applied to LLM providers.






What it can do



Beyond the fallback, HelloChusquis has grown into

a full terminal agent:




  • 128 integrations (Stripe, Supabase, AWS, Discord...)

  • Browser automation with human-like mouse movement

  • Web UI with voice I/O

  • Auto-Tool Builder: describe an integration, it generates the plugin

  • REST API mode

  • Persistent memory across sessions






Try it






CODE
pip install hellochusquis
hellochusquis --quick # 60 second setup






GitHub: github.com/aminoy77/HelloChusquis



Open source, MIT license, free forever.



If you've hit the same rate limit frustration, I'd

love to hear how you're handling it — or what you'd

want HelloChusquis to do that it doesn't yet.

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