425f3c5bb4
Convert all Chinese comments, docstrings, logger/print output, HTTPException detail messages, and API response messages to English across the entire codebase. Functional zh/ja localized strings (e.g. prompt templates, timezone display names, date formats) are preserved as-is. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
110 lines
4.5 KiB
Python
110 lines
4.5 KiB
Python
import os
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# Required parameters
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# API Settings
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BACKEND_HOST = os.getenv("BACKEND_HOST", "https://api-dev.gptbase.ai")
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MASTERKEY = os.getenv("MASTERKEY", "master")
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FASTAPI_URL = os.getenv('FASTAPI_URL', 'http://127.0.0.1:8001')
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# LLM Token Settings
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MAX_CONTEXT_TOKENS = int(os.getenv("MAX_CONTEXT_TOKENS", 200000))
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MAX_OUTPUT_TOKENS = int(os.getenv("MAX_OUTPUT_TOKENS", 8000))
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# Optional parameters
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# Summarization Settings
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SUMMARIZATION_MAX_TOKENS = int(MAX_CONTEXT_TOKENS/2)
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SUMMARIZATION_TOKENS_TO_KEEP = int(SUMMARIZATION_MAX_TOKENS/3)
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DEFAULT_TRIM_TOKEN_LIMIT = SUMMARIZATION_MAX_TOKENS - SUMMARIZATION_TOKENS_TO_KEEP + 5000
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# Agent Cache Settings
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TOOL_CACHE_MAX_SIZE = int(os.getenv("TOOL_CACHE_MAX_SIZE", 20))
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TOOL_CACHE_TTL = int(os.getenv("TOOL_CACHE_TTL", 180))
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TOOL_CACHE_AUTO_RENEW = os.getenv("TOOL_CACHE_AUTO_RENEW", "true") == "true"
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# Project Settings
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PROJECT_DATA_DIR = os.getenv("PROJECT_DATA_DIR", "./projects/data")
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SKILLS_DIR = os.getenv("SKILLS_DIR", "./skills")
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PROJECT_NAME = os.getenv("PROJECT_NAME", "support")
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# Tokenizer Settings
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TOKENIZERS_PARALLELISM = os.getenv("TOKENIZERS_PARALLELISM", "true")
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# Embedding Model Settings
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SENTENCE_TRANSFORMER_MODEL = os.getenv("SENTENCE_TRANSFORMER_MODEL", "TaylorAI/gte-tiny")
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# Tool Output Length Control Settings
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TOOL_OUTPUT_MAX_LENGTH = SUMMARIZATION_MAX_TOKENS
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TOOL_OUTPUT_TRUNCATION_STRATEGY = os.getenv("TOOL_OUTPUT_TRUNCATION_STRATEGY", "smart")
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# WebDAV Authentication
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WEBDAV_USERNAME = os.getenv("WEBDAV_USERNAME", "admin")
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WEBDAV_PASSWORD = os.getenv("WEBDAV_PASSWORD", "MmL85TjjxZC97hk9rsYfhQ")
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# MCP Tool Timeout Settings
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MCP_HTTP_TIMEOUT = int(os.getenv("MCP_HTTP_TIMEOUT", 60)) # HTTP request timeout (seconds)
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MCP_SSE_READ_TIMEOUT = int(os.getenv("MCP_SSE_READ_TIMEOUT", 300)) # SSE read timeout (seconds)
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# ============================================================
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# PostgreSQL Checkpoint Configuration
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# ============================================================
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# PostgreSQL connection string
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# Format: postgresql://user:password@host:port/database
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#CHECKPOINT_DB_URL = os.getenv("CHECKPOINT_DB_URL", "postgresql://postgres:AeEGDB0b7Z5GK0E2tblt@dev-circleo-pg.celp3nik7oaq.ap-northeast-1.rds.amazonaws.com:5432/gptbase")
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CHECKPOINT_DB_URL = os.getenv("CHECKPOINT_DB_URL", "postgresql://moshui:@localhost:5432/moshui")
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# Connection pool size
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# Maximum number of simultaneous connections
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CHECKPOINT_POOL_SIZE = int(os.getenv("CHECKPOINT_POOL_SIZE", "20"))
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MEM0_POOL_SIZE = int(os.getenv("MEM0_POOL_SIZE", "50"))
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# Checkpoint auto-cleanup configuration
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# Whether to enable automatic cleanup of old sessions
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CHECKPOINT_CLEANUP_ENABLED = os.getenv("CHECKPOINT_CLEANUP_ENABLED", "true") == "true"
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# Number of days after which inactive threads are cleaned up
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CHECKPOINT_CLEANUP_INACTIVE_DAYS = int(os.getenv("CHECKPOINT_CLEANUP_INACTIVE_DAYS", "3"))
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# Cleanup interval (hours)
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# How many hours between cleanup runs
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CHECKPOINT_CLEANUP_INTERVAL_HOURS = int(os.getenv("CHECKPOINT_CLEANUP_INTERVAL_HOURS", "24"))
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# ============================================================
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# Mem0 long-term memory configuration
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# ============================================================
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# Mem0 feature toggle (global)
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MEM0_ENABLED = os.getenv("MEM0_ENABLED", "true") == "true"
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# Semantic search configuration
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# Number of memories to recall
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MEM0_SEMANTIC_SEARCH_TOP_K = int(os.getenv("MEM0_SEMANTIC_SEARCH_TOP_K", "20"))
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# ============================================================
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# Schedule job configuration
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# ============================================================
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# Whether to enable the scheduled job runner
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SCHEDULE_ENABLED = os.getenv("SCHEDULE_ENABLED", "true") == "true"
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# Scheduler scan interval (seconds)
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SCHEDULE_SCAN_INTERVAL = int(os.getenv("SCHEDULE_SCAN_INTERVAL", "60"))
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# Maximum number of concurrent scheduled jobs
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SCHEDULE_MAX_CONCURRENT = int(os.getenv("SCHEDULE_MAX_CONCURRENT", "5"))
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# ============================================================
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# Daytona sandbox configuration
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# ============================================================
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DAYTONA_API_KEY = os.getenv("DAYTONA_API_KEY", "dtn_ccf86acd5b13a3069a8369d12d8cb26a9a184d07451374dfc325955fc2d8331c")
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DAYTONA_SERVER_URL = os.getenv("DAYTONA_SERVER_URL", "https://daytona-dev.gbase.ai/api")
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# DAYTONA_API_KEY = os.getenv("DAYTONA_API_KEY", "dtn_696a914ff54e45bb97132c32fba10995a4cab8ebef0cd8dea18129d447f805a3")
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# DAYTONA_SERVER_URL = os.getenv("DAYTONA_SERVER_URL", "https://app.daytona.io/api")
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DAYTONA_ENABLED = os.getenv("DAYTONA_ENABLED", "false") == "true"
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os.environ["OPENAI_API_KEY"] = "your_api_key"
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