Reasoning Agents for Hard Analytical Problems

pip install requests python-dotenv

import json
import os

import requests
from dotenv import load_dotenv

load_dotenv()

API_KEY = os.getenv("SWARMS_API_KEY")
BASE_URL = "https://api.swarms.world"

headers = {
    "x-api-key": API_KEY,
    "Content-Type": "application/json",
}

problem = """
A SaaS company sells a 24-month enterprise subscription on October 1, 2024 for
a total contract value of $480,000, billed annually in advance.

Contract terms:
- The first $240,000 is billed and collected on October 1, 2024, covering
  October 1, 2024 through September 30, 2025.
- The second $240,000 is billed and collected on October 1, 2025, covering
  October 1, 2025 through September 30, 2026.
- The customer is granted a one-time 5% discount that applies to the SECOND
  year only, reducing the second-year invoice (and cash collected) to
  $228,000. The discount is contractual at inception and is not a separate
  performance obligation.
- Revenue is recognized ratably on a straight-line basis under ASC 606.
- The company's fiscal year ends December 31.

Required:
1. What is the total transaction price under ASC 606 at contract inception?
2. What is the monthly revenue recognition amount?
3. As of December 31, 2024, what is (a) revenue recognized year-to-date,
   (b) deferred revenue on the balance sheet, and (c) contract asset or
   contract liability if any?
4. As of December 31, 2025, what is (a) revenue recognized in fiscal 2025,
   (b) deferred revenue on the balance sheet, and (c) accounts receivable
   if any?

Show every step of the calculation. Return a final JSON object with keys:
transaction_price, monthly_revenue, dec_2024 (with sub-keys revenue_ytd,
deferred_revenue, contract_asset_or_liability), and dec_2025 (with sub-keys
revenue_fy2025, deferred_revenue, accounts_receivable).
""".strip()

plain_payload = {
    "agent_config": {
        "agent_name": "Accounting-Plain",
        "description": "Standard accounting agent (single chain of thought).",
        "system_prompt": (
            "You are a CPA. Solve accounting problems carefully under ASC 606. "
            "Return the final answer as JSON."
        ),
        "model_name": "gpt-4.1",
        "max_loops": 1,
        "max_tokens": 4000,
    },
    "task": problem,
}

plain_response = requests.post(
    f"{BASE_URL}/v1/agent/completions",
    headers=headers,
    json=plain_payload,
    timeout=300,
)
plain_response.raise_for_status()
print("=" * 60)
print("PLAIN AGENT — single chain of thought")
print("=" * 60)
print(json.dumps(plain_response.json(), indent=2)[:1500])

reasoning_payload = {
    "agent_name": "Accrual-Reasoner",
    "description": (
        "ASC 606 revenue recognition specialist with self-consistency "
        "deliberation across multiple independent reasoning chains."
    ),
    "model_name": "anthropic/claude-opus-4-8",
    "system_prompt": (
        "You are a CPA specializing in ASC 606 revenue recognition. "
        "When solving a problem, derive the total transaction price first, "
        "then allocate ratably across the full performance period. Show every "
        "step. The final line of your response MUST be a single JSON object "
        "containing the requested fields."
    ),
    "swarm_type": "self-consistency",
    "num_samples": 5,
    "max_loops": 1,
    "output_type": "dict-final",
    "task": problem,
}

reasoning_response = requests.post(
    f"{BASE_URL}/v1/reasoning-agent/completions",
    headers=headers,
    json=reasoning_payload,
    timeout=600,
)
reasoning_response.raise_for_status()
result = reasoning_response.json()

print("=" * 60)
print("REASONING AGENT — self-consistency, 5 samples")
print("=" * 60)
print(json.dumps(result, indent=2)[:3000])

import re

outputs = result.get("outputs", {})
final = outputs.get("final_answer") if isinstance(outputs, dict) else None

if not final:
    # Some response shapes nest the JSON in a string — extract it
    blob = json.dumps(outputs)
    match = re.search(r"\{[^{}]*transaction_price[^{}]*\}", blob, re.DOTALL)
    if match:
        final = json.loads(match.group(0))

print("\nExtracted answer:")
print(json.dumps(final, indent=2))

# Sanity-check the structure
expected = {
    "transaction_price": 468_000,
    "monthly_revenue": 19_500,
    "dec_2024": {
        "revenue_ytd": 58_500,           # 3 months
        "deferred_revenue": 181_500,     # 240,000 cash - 58,500 recognized
        "contract_asset_or_liability": "contract liability (deferred revenue)",
    },
    "dec_2025": {
        "revenue_fy2025": 234_000,       # 12 months
        "deferred_revenue": 175_500,     # carry-forward math
    },
}
print("\nExpected key figures:")
print(json.dumps(expected, indent=2))