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Drop-in cost intelligence for Python AI agent frameworks.

Project description

RunCost ๐Ÿ’ธ

Run a 1,000-agent simulation for $2 instead of $200. Drop-in cost intelligence for Python AI agent frameworks.

License: AGPL v3 PyPI version GitHub Stars


The Problem

You built a multi-agent system. It works beautifully in testing.

Then you ran it for real and saw the bill.

A 500-agent simulation on GPT-4o costs $40โ€“$80 per run. A recursive loop that nobody catches costs $200 before you notice. An overnight batch job you forgot about costs $600 by morning.

Nobody warns you. No framework stops it.

Multi-agent AI is the future. Uncontrolled spend is the tax on building it.


The Fix: One Line

# Before RunCost
from openai import OpenAI
client = OpenAI()

# After RunCost โ€” nothing else changes
from runcost import OpenAI
client = OpenAI()

Drop it in. That's it. Your existing code works exactly as before โ€” except now every API call is intercepted, measured, and intelligently routed before it costs you money.


What Happens When You Run It

RunCost  //  Live Agent Cost Monitor          cost.run
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
  โœ“  researcher_01  โ†’  llama-3-8b   $0.001    11ms
  โœ“  analyst_04     โ†’  gpt-4o       $0.047   780ms
  โœ“  writer_02      โ†’  mistral-7b   $0.002    43ms
  โœ—  crawler_07     โ†’  BLOCKED      $0.000  loop@13
  โœ“  researcher_14  โ†’  llama-3-8b   $0.001     9ms
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€
  Spent:    $1.82 / $5.00   [====      ]  36%
  Saved:   $41.30            Efficiency: 95.7%
  Blocked:  3 loops          Calls:       847
โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€

RunCost intercepts every LLM call and:

  • Estimates the cost before spending a dollar
  • Routes simple tasks to cheap models (Groq, Llama 3, Mistral) automatically
  • Routes reasoning-heavy tasks to GPT-4o or Claude only when needed
  • Detects recursive loops and kills them before they drain your account
  • Enforces hard spending limits โ€” when you hit your cap, everything stops
  • Logs every call to a local SQLite database
  • Shows a live terminal dashboard of spend vs. savings in real time

The Numbers

Same simulation. Same output quality. 10x cheaper.

Workload Without RunCost With RunCost Saved
1,000-agent simulation ~$180-$200 ~$2-$4 ~98%
500-agent CrewAI workflow ~$40-$80 ~$4-$8 ~90%
AutoGen research pipeline ~$15-$20 ~$1-$2 ~90%
Recursive loop (caught) $200+ $0.00 100%

Install

pip install runcost

Supported frameworks: OpenAI SDK ยท CrewAI ยท LangGraph ยท AutoGen ยท LangChain ยท MiroFish ยท any OpenAI-compatible client


Quick Start

from runcost import OpenAI, BudgetConfig

config = BudgetConfig(
    hard_limit_usd=5.00,     # Hard stop โ€” never exceed this per run
    warn_at_usd=2.00,        # Alert when approaching limit
    auto_route=True,          # Auto-route cheap tasks to Llama/Groq
    block_loops=True,         # Kill recursive agent loops instantly
    log_to_db=True            # Save full history to runcost.db
)

client = OpenAI(budget=config)

# Use exactly as normal โ€” RunCost works silently underneath
response = client.chat.completions.create(
    model="gpt-4o",
    messages=[{"role": "user", "content": "Analyze these 500 documents"}]
)

How Routing Works

RunCost classifies each call by complexity before sending it:

Complexity Model Used Typical Cost
Simple: formatting, lookup, summarization Groq Llama-3 8B ~$0.001
Medium: research, extraction, classification Mistral 7B ~$0.002
Complex: reasoning, code, multi-step logic GPT-4o / Claude ~$0.04โ€“0.09
Detected loop / budget exceeded BLOCKED $0.000

You can override routing per agent, per task type, or per model preference.


The Dashboard

runcost dashboard

Opens a live terminal view showing real-time spend, savings, active agents, blocked loops, and full call history. Dark mode. No browser required.


Why Open Source?

Because every developer deserves to see exactly what their agents are spending โ€” before it's too late.

The core engine is AGPL-3.0. Run it yourself, audit it, fork it, build on it.

RunCost Pro (coming soon): team dashboards ยท multi-project tracking ยท SSO ยท compliance exports ยท Slack/Discord alerts ยท SLA support


Roadmap

โœ… OpenAI SDK wrapper โœ… Real-time cost tracking per call โœ… Hard budget limits with BudgetExceededError โœ… SQLite call logging โœ… Terminal dashboard (runcost dashboard) โœ… Web dashboard (runcost server) โœ… Pre-flight cost calculator โœ… DeepSeek support โœ… Grok / xAI support โœ… Auto-routing (automatic cheap model selection) โœ… Recursive loop detection โœ… Slack / Discord spend alerts ๐Ÿ”œ Claude (Anthropic SDK) support ๐Ÿ”œ Gemini (Google SDK) support ๐Ÿ”œ CrewAI native plugin ๐Ÿ”œ LangGraph native plugin

๐Ÿ”œ AgentLedger โ€” audit trail for every agent action


If RunCost saved you money, a โญ on GitHub costs nothing and means everything.


License

AGPL-3.0 โ€” free for individuals and open source projects.

Commercial license available for enterprise deployments.


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