import os

# 必填参数
# API Settings
BACKEND_HOST = os.getenv("BACKEND_HOST", "https://api-dev.gptbase.ai")
MASTERKEY = os.getenv("MASTERKEY", "master")
FASTAPI_URL = os.getenv('FASTAPI_URL', 'http://127.0.0.1:8001')

# LLM Token Settings
MAX_CONTEXT_TOKENS = int(os.getenv("MAX_CONTEXT_TOKENS", 262144))
MAX_OUTPUT_TOKENS = int(os.getenv("MAX_OUTPUT_TOKENS", 8000))

# 可选参数
# Summarization Settings
SUMMARIZATION_MAX_TOKENS = MAX_CONTEXT_TOKENS - MAX_OUTPUT_TOKENS - 1000
SUMMARIZATION_MESSAGES_TO_KEEP = int(os.getenv("SUMMARIZATION_MESSAGES_TO_KEEP", 20))

# Agent Cache Settings
TOOL_CACHE_MAX_SIZE = int(os.getenv("TOOL_CACHE_MAX_SIZE", 20))
TOOL_CACHE_TTL = int(os.getenv("TOOL_CACHE_TTL", 180))
TOOL_CACHE_AUTO_RENEW = os.getenv("TOOL_CACHE_AUTO_RENEW", "true") == "true"

# Project Settings
PROJECT_DATA_DIR = os.getenv("PROJECT_DATA_DIR", "./projects/data")
SKILLS_DIR = os.getenv("SKILLS_DIR", "./skills")

# Tokenizer Settings
TOKENIZERS_PARALLELISM = os.getenv("TOKENIZERS_PARALLELISM", "true")

# Embedding Model Settings
SENTENCE_TRANSFORMER_MODEL = os.getenv("SENTENCE_TRANSFORMER_MODEL", "TaylorAI/gte-tiny")

# Tool Output Length Control Settings
TOOL_OUTPUT_MAX_LENGTH = int(SUMMARIZATION_MAX_TOKENS/4)
TOOL_OUTPUT_TRUNCATION_STRATEGY = os.getenv("TOOL_OUTPUT_TRUNCATION_STRATEGY", "smart")

# THINKING ENABLE
DEFAULT_THINKING_ENABLE = os.getenv("DEFAULT_THINKING_ENABLE", "true") == "true"


# MCP Tool Timeout Settings
MCP_HTTP_TIMEOUT = int(os.getenv("MCP_HTTP_TIMEOUT", 60))  # HTTP 请求超时（秒）
MCP_SSE_READ_TIMEOUT = int(os.getenv("MCP_SSE_READ_TIMEOUT", 300))  # SSE 读取超时（秒）

# ============================================================
# PostgreSQL Checkpoint Configuration
# ============================================================

# PostgreSQL 连接字符串
# 格式: postgresql://user:password@host:port/database
#CHECKPOINT_DB_URL = os.getenv("CHECKPOINT_DB_URL", "postgresql://postgres:AeEGDB0b7Z5GK0E2tblt@dev-circleo-pg.celp3nik7oaq.ap-northeast-1.rds.amazonaws.com:5432/gptbase")
CHECKPOINT_DB_URL = os.getenv("CHECKPOINT_DB_URL", "postgresql://moshui:@localhost:5432/moshui")

# 连接池大小
# 同时可以持有的最大连接数
CHECKPOINT_POOL_SIZE = int(os.getenv("CHECKPOINT_POOL_SIZE", "20"))

# Checkpoint 自动清理配置
# 是否启用自动清理旧 session
CHECKPOINT_CLEANUP_ENABLED = os.getenv("CHECKPOINT_CLEANUP_ENABLED", "true") == "true"

# 清理多少天前未活动的 thread（天数）
CHECKPOINT_CLEANUP_INACTIVE_DAYS = int(os.getenv("CHECKPOINT_CLEANUP_INACTIVE_DAYS", "3"))

# 清理间隔（小时）
# 每隔多少小时执行一次清理任务
CHECKPOINT_CLEANUP_INTERVAL_HOURS = int(os.getenv("CHECKPOINT_CLEANUP_INTERVAL_HOURS", "24"))


# ============================================================
# Memori 长期记忆配置
# ============================================================

# Memori 功能开关（全局）
MEMORI_ENABLED = os.getenv("MEMORI_ENABLED", "true") == "true"

# Memori API 密钥（用于高级增强功能）
MEMORI_API_KEY = os.getenv("MEMORI_API_KEY", "")

# 语义搜索配置
# 召回记忆数量
MEMORI_SEMANTIC_SEARCH_TOP_K = int(os.getenv("MEMORI_SEMANTIC_SEARCH_TOP_K", "5"))
# 相关性阈值（0.0 - 1.0）
MEMORI_SEMANTIC_SEARCH_THRESHOLD = float(os.getenv("MEMORI_SEMANTIC_SEARCH_THRESHOLD", "0.7"))
# 搜索嵌入限制
MEMORI_SEMANTIC_SEARCH_EMBEDDINGS_LIMIT = int(os.getenv("MEMORI_SEMANTIC_SEARCH_EMBEDDINGS_LIMIT", "1000"))

# 记忆注入配置
# 是否将记忆注入到系统提示
MEMORI_INJECT_TO_SYSTEM_PROMPT = os.getenv("MEMORI_INJECT_TO_SYSTEM_PROMPT", "true") == "true"

# 增强配置
# 是否启用后台增强
MEMORI_AUGMENTATION_ENABLED = os.getenv("MEMORI_AUGMENTATION_ENABLED", "true") == "true"
# 增强等待超时（秒），None 表示后台异步执行
MEMORI_AUGMENTATION_WAIT_TIMEOUT = os.getenv("MEMORI_AUGMENTATION_WAIT_TIMEOUT")
if MEMORI_AUGMENTATION_WAIT_TIMEOUT:
    MEMORI_AUGMENTATION_WAIT_TIMEOUT = float(MEMORI_AUGMENTATION_WAIT_TIMEOUT)
else:
    MEMORI_AUGMENTATION_WAIT_TIMEOUT = None

# 嵌入模型（多语言支持）
MEMORI_EMBEDDING_MODEL = os.getenv(
    "MEMORI_EMBEDDING_MODEL",
    "paraphrase-multilingual-MiniLM-L12-v2"
)