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ai-agent-book/chapter2/context-compression/config.py
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ai-agent-book 精选快照(<2MB 代码与文档,来自 github.com/bojieli/ai-agent-book)
2026-08-20 13:12:50 +00:00

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"""
Configuration module for Context Compression Experiment
"""
import os
from typing import Optional
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
class Config:
"""Configuration settings for the context compression experiment"""
# API Configuration
LLM_PROVIDER: str = os.getenv("LLM_PROVIDER", "kimi").lower()
LLM_PROVIDER = {"qwen": "dashscope", "bailian": "dashscope"}.get(
LLM_PROVIDER, LLM_PROVIDER
)
DASHSCOPE_API_KEY: str = os.getenv("DASHSCOPE_API_KEY", "")
DASHSCOPE_BASE_URL: str = os.getenv(
"DASHSCOPE_BASE_URL", "https://dashscope.aliyuncs.com/compatible-mode/v1"
)
MOONSHOT_API_KEY: str = os.getenv("MOONSHOT_API_KEY", "")
MOONSHOT_BASE_URL: str = "https://api.moonshot.cn/v1"
# Universal fallback: 当 MOONSHOT_API_KEY 缺失但设置了 OPENROUTER_API_KEY 时,
# 自动改走 OpenRouterkimi-* 模型名映射为 moonshotai/kimi-k2)。
OPENROUTER_API_KEY: str = os.getenv("OPENROUTER_API_KEY", "")
SERPER_API_KEY: str = os.getenv("SERPER_API_KEY", "")
SERPER_BASE_URL: str = "https://google.serper.dev"
# Model Configuration
MODEL_NAME: str = os.getenv(
"MODEL_NAME", "qwen3.7-plus" if LLM_PROVIDER == "dashscope" else "kimi-k3"
)
MODEL_TEMPERATURE: float = float(os.getenv("MODEL_TEMPERATURE", "0.3"))
MODEL_MAX_TOKENS: int = int(os.getenv("MODEL_MAX_TOKENS", "8192"))
# Agent Configuration
MAX_ITERATIONS: int = int(os.getenv("MAX_ITERATIONS", "50"))
ENABLE_VERBOSE: bool = os.getenv("ENABLE_VERBOSE", "false").lower() == "true"
# Compression Configuration
MAX_WEBPAGE_LENGTH: int = int(os.getenv("MAX_WEBPAGE_LENGTH", "50000"))
SUMMARY_MAX_TOKENS: int = int(os.getenv("SUMMARY_MAX_TOKENS", "500"))
# Context Window Configuration
CONTEXT_WINDOW_SIZE: int = 128000 # 128K context budget for the compression demo (K3 supports up to 1M)
# Logging Configuration
LOG_LEVEL: str = os.getenv("LOG_LEVEL", "INFO")
LOG_FORMAT: str = "%(asctime)s - %(levelname)s - %(name)s - %(message)s"
# File paths
RESULTS_DIR: str = "results"
CACHE_DIR: str = "cache"
@classmethod
def validate(cls) -> bool:
"""
Validate required configuration
Returns:
True if configuration is valid
"""
try:
cls.resolve_llm()
except ValueError as exc:
print(f"ERROR: {exc}")
return False
if not cls.SERPER_API_KEY:
print("WARNING: SERPER_API_KEY is not set")
print("Web search functionality will be limited")
print("Get a free API key at: https://serper.dev")
return True
@classmethod
def resolve_llm(cls):
"""Return ``(api_key, base_url, model)`` for the configured provider.
Computed at call time so a runtime override of ``Config.MODEL_NAME``
(e.g. via ``--model``) is respected.
端点、接受的 key 变量与模型名映射由 agentbook 的 provider 注册表统一
维护。此处保持三元组返回值:调用方按 3 个字段解包,测试也按这个形状
打桩。
"""
from agentbook.providers import resolve_backend
backend = resolve_backend(cls.LLM_PROVIDER, model=cls.MODEL_NAME)
return backend.api_key, backend.base_url, backend.model
@classmethod
def create_directories(cls):
"""Create necessary directories if they don't exist"""
os.makedirs(cls.RESULTS_DIR, exist_ok=True)
os.makedirs(cls.CACHE_DIR, exist_ok=True)
@classmethod
def print_config(cls):
"""Print current configuration (hiding sensitive data)"""
print("\n" + "="*50)
print("CONFIGURATION")
print("="*50)
print(f"Model: {cls.MODEL_NAME}")
print(f"Temperature: {cls.MODEL_TEMPERATURE}")
print(f"Max Tokens: {cls.MODEL_MAX_TOKENS}")
print(f"Max Iterations: {cls.MAX_ITERATIONS}")
print(f"Context Window: {cls.CONTEXT_WINDOW_SIZE:,} tokens")
print(f"Max Webpage Length: {cls.MAX_WEBPAGE_LENGTH:,} chars")
print(f"Summary Max Tokens: {cls.SUMMARY_MAX_TOKENS}")
print(f"Provider: {cls.LLM_PROVIDER}")
print(f"DashScope API Key Set: {'Yes' if cls.DASHSCOPE_API_KEY else 'No'}")
print(f"Kimi API Key Set: {'Yes' if cls.MOONSHOT_API_KEY else 'No'}")
print(f"Serper API Key Set: {'Yes' if cls.SERPER_API_KEY else 'No'}")
print("="*50 + "\n")