| """Configuration file for AgenticPayGym examples | |
| This file contains common configuration variables used across different | |
| negotiation examples, including reward weights, aggregation methods, and | |
| environment parameters. | |
| """ | |
| # Reward weights configuration | |
| # These weights control the relative importance of different reward components | |
| reward_weights = { | |
| "buyer_savings": 1.0, # Buyer savings weight | |
| "seller_profit": 1.0, # Seller profit weight | |
| "time_cost": 0.1, # Time cost weight (reduced impact) | |
| } | |
| # Reward aggregation methods | |
| # Options: "average", "max", "min" | |
| buyer_reward_aggregation = "average" # Buyer reward aggregation method | |
| seller_reward_aggregation = "average" # Seller reward aggregation method | |
| # Environment parameters | |
| max_rounds = 20 # Maximum negotiation rounds | |
| price_tolerance = 0.0 # Price tolerance (used to determine if prices match) | |
| # Model configuration | |
| # model_mode: "local" (local deployment) or "cloud" (cloud API) | |
| MODEL_MODE = "local" | |
| # MODEL_PATH: For local mode, use local model path; for cloud mode, use online model name (e.g. "gpt-4", "qwen-turbo") | |
| MODEL_PATH = "/path/to/local/model" | |
| # OpenAI API key and URL | |
| OPENAI_API_KEY = "your-api-key-here" | |
| OPENAI_URL = "your-url-here" | |