Operations Analyst

operations_analyst/
├── main.py                         # Two-task pipeline (~40 lines)
├── requirements.txt                # upsonic, anthropic, matplotlib, pandas
└── workspace/
    ├── AGENTS.md                   # Agent behavior: task definitions, rules, memory
    ├── SOUL.md                     # Agent identity and personality
    ├── shipment_data.csv           # Input data (80 shipment records)
    └── memory/                     # Agent writes session logs here

workspace/
├── KPI_REPORT.md                   # Generated report with tables and commentary
├── charts/                         # Generated PNG charts (one per metric)
│   ├── ontime_performance.png
│   ├── carrier_comparison.png
│   └── ...
└── memory/
    └── YYYY-MM-DD.md

ANTHROPIC_API_KEY=your-api-key

cd examples/autonomous_agents/operations_analyst
uv venv && source .venv/bin/activate
uv pip install -r requirements.txt

python main.py

"""
Operations Analysis — Upsonic AutonomousAgent (two-task pipeline)

Task 1 (Analyst):    reads shipment_data.csv → decides KPIs → writes KPI_REPORT.md
Task 2 (Visualizer): reads KPI_REPORT.md → runs matplotlib code directly via run_python → produces charts

One agent. Two shots. Fully autonomous.
"""

import os
from upsonic import AutonomousAgent, Task

WORKSPACE = os.path.join(os.path.dirname(os.path.abspath(__file__)), "workspace")

print(f"Workspace: {WORKSPACE}")

agent = AutonomousAgent(
    model="anthropic/claude-sonnet-4-5",
    workspace=WORKSPACE,
)

analyst_task = Task(
    "Read shipment_data.csv. Identify the KPIs that matter most for delivery operations — "
    "on-time rate, carrier performance, route delays, cost efficiency. Compute each from the raw data. "
    "Write KPI_REPORT.md with a summary table, per-carrier breakdown, and a "
    "## Agent Commentary section with your analysis and recommendations."
)

visualizer_task = Task(
    "Read KPI_REPORT.md and shipment_data.csv. Based on the KPIs in the report, use run_python "
    "to execute matplotlib code that creates one chart per key metric. "
    "Use a white background with dark text for readability. Save all charts as PNGs to the charts/ directory. "
    "Do not write a .py file — run the code directly."
)

if __name__ == "__main__":
    print("\n── Task 1: Analyst ────────────────────────────")
    agent.print_do(analyst_task)

    print("\n── Task 2: Visualizer ─────────────────────────")
    agent.print_do(visualizer_task)