AgentBudget

What it does

AI agents can keep calling APIs until a task finishes. If something loops or goes wrong, the bill can grow very fast. There is usually no built in way to stop it. AgentBudget is an open source Python SDK that watches every LLM API call in real time and stops the agent the moment it reaches a set spending limit. You add one import, set a budget, and the agent cannot spend more than that.

Open-source Python SDK that puts a hard dollar limit on any AI agent session. One line to set a budget. Zero infrastructure to manage.

Set a hard dollar limit on any AI agent session with one line of code. Automatic tracking, circuit breaking, and cost reports across every LLM provider. Drop-in auto-tracking, manual wrapping, async agents, and nested budgets. import agentbudget import openai agentbudget. init ( "$ 5.00 " ) # Your existing code. Zero changes needed. client = openai. OpenAI () response = client.chat.completions. create ( model= "gpt-4o" , messages=[{ "role" : "user" , "content" : "Analyze this market..." }] ) # ^ Automatically tracked. Budget enforced. print (agentbudget. spent ()) # 0.0035 print (agentbudget. remaining ()) # 4.9965 print (agentbudget. report ()) # Full cost breakdown agentbudget. teardown…from agentbudget.dev

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  AgentBudget – Real-time dollar budgets for AI agentsFeb 2026 · github.com · ▲7

  Hey HN, I built AgentBudget after an AI agent loop cost me $187 in 10 minutes — GPT-4o retrying a failed analysis over and over. Existing tools (LangSmith, Langfuse) track costs after execution but don't prevent overspend. AgentBudget is a Python SDK that gives each agent session a hard dollar budget with real-time enforcement. Integration is two lines: import agentbudget agentbudget.init("$5.00") It monkey-patches the OpenAI and Anthropic SDKs (same pattern as Sentry/Datadog), so existing code works without changes. When the budget is hit, it raises BudgetExhausted before the next API…

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