Quickstart

export ANTHROPIC_API_KEY="your-api-key"

agent_config:
  agent_type: chat_completions
  agent_name: bank-insurance
  api_config:
    endpoint: https://api.anthropic.com/v1/messages
    headers:
      Content-Type: application/json
      x-api-key: "${ANTHROPIC_API_KEY}"
      anthropic-version: "2023-06-01"
    body:
      model: claude-opus-4-6
      max_tokens: 1024
      system: |
        You are a customer service chatbot for XYZ Bank insurance.
        XYZ Insurance—a core business within XYZ Bank Group—is one of
        Canada's leading providers of life, health, home, auto, and
        travel insurance.

        Rules:
        1. Do not flip roles.
        2. Avoid using bullet points or lists.
        3. Never exceed 80 words.

# ...

# LLM model
model: claude-opus-4-6

# LLM provider
provider: anthropic

export GEMINI_API_KEY="your-api-key"

agent_config:
  agent_type: chat_completions
  agent_name: e-commerce
  api_config:
    endpoint: https://generativelanguage.googleapis.com/v1beta/openai/chat/completions
    headers:
      Content-Type: application/json
      Authorization: "Bearer ${GEMINI_API_KEY}"
    body:
      model: gemini-2.5-flash
      messages:
        - role: system
          content: >-
            You are a shopping assistant. Please provide a complete answer
            to the user's question based on your knowledge. Response within
            50 words.

# ...

# LLM model
model: gemini-2.5-flash

# LLM provider
provider: google

import asyncio
from arksim.simulation_engine import run_simulation, SimulationInput
from arksim.evaluator import run_evaluation, EvaluationInput
from arksim.config import AgentConfig
from arksim.scenario import Scenarios

BANK_INSURANCE_DIR = "./examples/bank-insurance"

# Example agent config (OpenAI; match bank-insurance config.yaml)
agent_config = AgentConfig(
    agent_type="chat_completions",
    agent_name="bank-insurance",
    api_config={
        "endpoint": "https://api.openai.com/v1/chat/completions",
        "headers": {
            "Content-Type": "application/json",
            "Authorization": "Bearer ${OPENAI_API_KEY}",
        },
        "body": {
            "model": "gpt-5.1",
            "messages": [
                {"role": "system", "content": "You are a customer service chatbot for XYZ Bank insurance."}
            ],
        },
    },
)

scenarios = Scenarios.load(f"{BANK_INSURANCE_DIR}/scenarios.json")

simulation = asyncio.run(run_simulation(SimulationInput(
    agent_config=agent_config,
    num_conversations_per_scenario=1,
    max_turns=5,
    num_workers="50",
    output_file_path=f"{BANK_INSURANCE_DIR}/results/simulation.json",
)))

evaluation = run_evaluation(EvaluationInput(
    scenario_file_path=f"{BANK_INSURANCE_DIR}/scenarios.json",
    output_dir=f"{BANK_INSURANCE_DIR}/results",
    custom_metrics_file_paths=[f"{BANK_INSURANCE_DIR}/custom_metrics.py"],
    metrics_to_run=[
        "faithfulness",
        "helpfulness",
        "coherence",
        "relevance",
        "goal_completion",
        "agent_behavior_failure",
    ],
    model="gpt-5.1",
    provider="openai",
    num_workers=50,
    generate_html_report=True,
), simulation=simulation, scenarios=scenarios)

print("Simulation and evaluation complete.")
print(f"Simulated {len(simulation.conversations)} conversations.")
print(f"Evaluation results saved to {BANK_INSURANCE_DIR}/results")

arksim ui