docs(i18n): translate chinese docstrings/comments in backend root, api init, simulation_ipc, simulation_manager, zep_entity_reader
This commit is contained in:
Dominik Seemann
parent
e3f7defefc
commit
e1019d91cb
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@ -1,12 +1,10 @@
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"""
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MiroFish Backend - Flask应用工厂
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"""
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"""MiroFish backend Flask application factory."""
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import os
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import warnings
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# 抑制 multiprocessing resource_tracker 的警告（来自第三方库如 transformers）
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# 需要在所有其他导入之前设置
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# Silence multiprocessing.resource_tracker warnings emitted by some third-party
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# libraries (e.g. transformers); must run before those modules are imported.
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warnings.filterwarnings("ignore", message=".*resource_tracker.*")
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from flask import Flask, request
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@ -18,62 +16,65 @@ from .utils.locale import t
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def create_app(config_class=Config):
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"""Flask应用工厂函数"""
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"""Flask application factory."""
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app = Flask(__name__)
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app.config.from_object(config_class)
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# 设置JSON编码：确保中文直接显示（而不是 \uXXXX 格式）
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# Flask >= 2.3 使用 app.json.ensure_ascii，旧版本使用 JSON_AS_ASCII 配置
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# Configure JSON encoding so non-ASCII characters render literally
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# rather than as \uXXXX escape sequences. Flask >= 2.3 exposes
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# ``app.json.ensure_ascii``; older versions use ``JSON_AS_ASCII``.
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if hasattr(app, 'json') and hasattr(app.json, 'ensure_ascii'):
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app.json.ensure_ascii = False
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# 设置日志
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# Configure logging.
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logger = setup_logger('mirofish')
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# 只在 reloader 子进程中打印启动信息（避免 debug 模式下打印两次）
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# Only print startup banners in the reloader child process to avoid
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# double-printing in debug mode.
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is_reloader_process = os.environ.get('WERKZEUG_RUN_MAIN') == 'true'
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debug_mode = app.config.get('DEBUG', False)
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should_log_startup = not debug_mode or is_reloader_process
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if should_log_startup:
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logger.info("=" * 50)
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logger.info(t("log.bootstrap.m001"))
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logger.info("=" * 50)
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# 启用CORS
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# Enable CORS.
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CORS(app, resources={r"/api/*": {"origins": "*"}})
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# 注册模拟进程清理函数（确保服务器关闭时终止所有模拟进程）
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# Register simulation-process cleanup so all child processes are torn down
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# when the Flask server shuts down.
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from .services.simulation_runner import SimulationRunner
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SimulationRunner.register_cleanup()
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if should_log_startup:
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logger.info(t("log.bootstrap.m002"))
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# 请求日志中间件
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# Request-logging middleware.
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@app.before_request
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def log_request():
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logger = get_logger('mirofish.request')
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logger.debug(t("log.bootstrap.m003", request=request.method, request_2=request.path))
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if request.content_type and 'json' in request.content_type:
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logger.debug(t("log.bootstrap.m004", request=request.get_json(silent=True)))
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@app.after_request
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def log_response(response):
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logger = get_logger('mirofish.request')
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logger.debug(t("log.bootstrap.m005", response=response.status_code))
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return response
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# 注册蓝图
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# Register API blueprints.
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from .api import graph_bp, simulation_bp, report_bp
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app.register_blueprint(graph_bp, url_prefix='/api/graph')
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app.register_blueprint(simulation_bp, url_prefix='/api/simulation')
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app.register_blueprint(report_bp, url_prefix='/api/report')
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# 健康检查
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# Health-check endpoint.
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@app.route('/health')
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def health():
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return {'status': 'ok', 'service': 'MiroFish Backend'}
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# On startup: recover any projects stuck in graph_building (task was killed by restart)
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if should_log_startup:
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_recover_stuck_projects()
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@ -1,6 +1,4 @@
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"""
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API路由模块
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"""
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"""API blueprints package."""
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from flask import Blueprint
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@ -1,38 +1,40 @@
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"""
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配置管理
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统一从项目根目录的 .env 文件加载配置
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"""Configuration management.
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Loads configuration values from the project-root ``.env`` file.
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"""
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import os
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from dotenv import load_dotenv
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# 加载项目根目录的 .env 文件
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# 路径: MiroFish/.env (相对于 backend/app/config.py)
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# Load the project-root .env file.
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# Path: MiroFish/.env (relative to backend/app/config.py).
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project_root_env = os.path.join(os.path.dirname(__file__), '../../.env')
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if os.path.exists(project_root_env):
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load_dotenv(project_root_env, override=True)
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else:
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# 如果根目录没有 .env，尝试加载环境变量（用于生产环境）
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# If the project root has no .env, fall back to the process environment
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# (used in production deployments).
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load_dotenv(override=True)
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class Config:
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"""Flask配置类"""
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# Flask配置
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"""Flask configuration class."""
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# Flask settings.
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SECRET_KEY = os.environ.get('SECRET_KEY', 'mirofish-secret-key')
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DEBUG = os.environ.get('FLASK_DEBUG', 'True').lower() == 'true'
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# JSON配置 - 禁用ASCII转义，让中文直接显示（而不是 \uXXXX 格式）
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# JSON settings: disable ASCII escaping so non-ASCII output renders literally
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# rather than as \uXXXX escape sequences.
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JSON_AS_ASCII = False
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# LLM配置（统一使用OpenAI格式）
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# LLM settings (called via the OpenAI-compatible API surface).
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LLM_API_KEY = os.environ.get('LLM_API_KEY')
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LLM_BASE_URL = os.environ.get('LLM_BASE_URL', 'https://api.openai.com/v1')
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LLM_MODEL_NAME = os.environ.get('LLM_MODEL_NAME', 'gpt-4o-mini')
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# Neo4j + Graphiti配置（替代 Zep Cloud）
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# Neo4j + Graphiti settings (replacement for Zep Cloud).
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NEO4J_URI = os.environ.get('NEO4J_URI', 'bolt://localhost:7687')
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NEO4J_USER = os.environ.get('NEO4J_USER', 'neo4j')
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NEO4J_PASSWORD = os.environ.get('NEO4J_PASSWORD', 'mirofish123')
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@ -50,23 +52,23 @@ class Config:
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EMBEDDING_API_KEY = os.environ.get('EMBEDDING_API_KEY')
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EMBEDDING_BASE_URL = os.environ.get('EMBEDDING_BASE_URL')
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# Zep配置（保留兼容性，已废弃）
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# Zep settings (kept for backwards compatibility; deprecated).
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ZEP_API_KEY = os.environ.get('ZEP_API_KEY', '')
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# 文件上传配置
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# File upload settings.
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MAX_CONTENT_LENGTH = 50 * 1024 * 1024 # 50MB
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UPLOAD_FOLDER = os.path.join(os.path.dirname(__file__), '../uploads')
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ALLOWED_EXTENSIONS = {'pdf', 'md', 'txt', 'markdown'}
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# 文本处理配置
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DEFAULT_CHUNK_SIZE = 500 # 默认切块大小
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DEFAULT_CHUNK_OVERLAP = 50 # 默认重叠大小
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# OASIS模拟配置
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# Text processing settings.
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DEFAULT_CHUNK_SIZE = 500 # default chunk size in characters
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DEFAULT_CHUNK_OVERLAP = 50 # default overlap in characters
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# OASIS simulation settings.
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OASIS_DEFAULT_MAX_ROUNDS = int(os.environ.get('OASIS_DEFAULT_MAX_ROUNDS', '10'))
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OASIS_SIMULATION_DATA_DIR = os.path.join(os.path.dirname(__file__), '../uploads/simulations')
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# OASIS平台可用动作配置
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# OASIS per-platform allowed action lists.
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OASIS_TWITTER_ACTIONS = [
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'CREATE_POST', 'LIKE_POST', 'REPOST', 'FOLLOW', 'DO_NOTHING', 'QUOTE_POST'
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]
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@ -76,14 +78,14 @@ class Config:
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'TREND', 'REFRESH', 'DO_NOTHING', 'FOLLOW', 'MUTE'
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]
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# Report Agent配置
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# Report agent settings.
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REPORT_AGENT_MAX_TOOL_CALLS = int(os.environ.get('REPORT_AGENT_MAX_TOOL_CALLS', '5'))
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REPORT_AGENT_MAX_REFLECTION_ROUNDS = int(os.environ.get('REPORT_AGENT_MAX_REFLECTION_ROUNDS', '2'))
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REPORT_AGENT_TEMPERATURE = float(os.environ.get('REPORT_AGENT_TEMPERATURE', '0.5'))
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@classmethod
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def validate(cls):
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"""验证必要配置"""
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"""Validate that required configuration values are present."""
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errors = []
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if not cls.LLM_API_KEY:
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errors.append("LLM_API_KEY 未配置")
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@ -1,11 +1,12 @@
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"""
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模拟IPC通信模块
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用于Flask后端和模拟脚本之间的进程间通信
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"""Simulation IPC module.
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通过文件系统实现简单的命令/响应模式：
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1. Flask写入命令到 commands/ 目录
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2. 模拟脚本轮询命令目录，执行命令并写入响应到 responses/ 目录
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3. Flask轮询响应目录获取结果
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Inter-process communication between the Flask backend and the simulation
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subprocess. Implements a simple file-system command/response pattern:
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1. Flask writes commands into ``commands/``.
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2. The simulation script polls for commands, executes them, and writes
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responses into ``responses/``.
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3. Flask polls the responses directory for results.
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"""
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import os
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@ -24,14 +25,14 @@ logger = get_logger('mirofish.simulation_ipc')
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class CommandType(str, Enum):
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"""命令类型"""
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INTERVIEW = "interview" # 单个Agent采访
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BATCH_INTERVIEW = "batch_interview" # 批量采访
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CLOSE_ENV = "close_env" # 关闭环境
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"""IPC command types."""
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INTERVIEW = "interview" # interview a single agent
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BATCH_INTERVIEW = "batch_interview" # interview multiple agents at once
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CLOSE_ENV = "close_env" # tear down the environment
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class CommandStatus(str, Enum):
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"""命令状态"""
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"""IPC command status."""
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PENDING = "pending"
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PROCESSING = "processing"
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COMPLETED = "completed"
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@ -40,12 +41,12 @@ class CommandStatus(str, Enum):
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@dataclass
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class IPCCommand:
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"""IPC命令"""
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"""A command sent over the IPC channel."""
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command_id: str
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command_type: CommandType
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args: Dict[str, Any]
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timestamp: str = field(default_factory=lambda: datetime.now().isoformat())
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def to_dict(self) -> Dict[str, Any]:
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return {
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"command_id": self.command_id,
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@ -53,7 +54,7 @@ class IPCCommand:
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"args": self.args,
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"timestamp": self.timestamp
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}
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> 'IPCCommand':
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return cls(
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@ -66,13 +67,13 @@ class IPCCommand:
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@dataclass
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class IPCResponse:
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"""IPC响应"""
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"""A response returned over the IPC channel."""
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command_id: str
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status: CommandStatus
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result: Optional[Dict[str, Any]] = None
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error: Optional[str] = None
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timestamp: str = field(default_factory=lambda: datetime.now().isoformat())
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def to_dict(self) -> Dict[str, Any]:
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return {
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"command_id": self.command_id,
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@ -81,7 +82,7 @@ class IPCResponse:
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"error": self.error,
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"timestamp": self.timestamp
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}
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@classmethod
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def from_dict(cls, data: Dict[str, Any]) -> 'IPCResponse':
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return cls(
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@ -94,27 +95,25 @@ class IPCResponse:
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class SimulationIPCClient:
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"""IPC client used by the Flask side.
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Sends commands to the simulation process and waits for responses.
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"""
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模拟IPC客户端（Flask端使用）
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用于向模拟进程发送命令并等待响应
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"""
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def __init__(self, simulation_dir: str):
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"""
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初始化IPC客户端
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"""Initialize the IPC client.
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Args:
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simulation_dir: 模拟数据目录
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simulation_dir: Directory holding the simulation's IPC files.
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"""
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self.simulation_dir = simulation_dir
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self.commands_dir = os.path.join(simulation_dir, "ipc_commands")
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self.responses_dir = os.path.join(simulation_dir, "ipc_responses")
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# 确保目录存在
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# Ensure both directories exist before use.
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os.makedirs(self.commands_dir, exist_ok=True)
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os.makedirs(self.responses_dir, exist_ok=True)
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def send_command(
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self,
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command_type: CommandType,
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@ -122,20 +121,19 @@ class SimulationIPCClient:
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timeout: float = 60.0,
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poll_interval: float = 0.5
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) -> IPCResponse:
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"""
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发送命令并等待响应
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"""Send a command and wait for the response.
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Args:
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command_type: 命令类型
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args: 命令参数
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timeout: 超时时间（秒）
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poll_interval: 轮询间隔（秒）
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command_type: Command type to send.
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args: Command arguments.
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timeout: Timeout in seconds.
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poll_interval: Polling interval in seconds.
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Returns:
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IPCResponse
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The ``IPCResponse``.
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Raises:
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TimeoutError: 等待响应超时
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TimeoutError: When no response arrives before ``timeout``.
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"""
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command_id = str(uuid.uuid4())
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command = IPCCommand(
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@ -143,50 +141,50 @@ class SimulationIPCClient:
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command_type=command_type,
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args=args
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)
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# 写入命令文件
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# Write the command file.
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command_file = os.path.join(self.commands_dir, f"{command_id}.json")
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with open(command_file, 'w', encoding='utf-8') as f:
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json.dump(command.to_dict(), f, ensure_ascii=False, indent=2)
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logger.info(t("log.simulation_ipc.m001", command_type=command_type.value, command_id=command_id))
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# 等待响应
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# Poll for the response file.
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response_file = os.path.join(self.responses_dir, f"{command_id}.json")
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start_time = time.time()
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while time.time() - start_time < timeout:
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if os.path.exists(response_file):
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try:
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with open(response_file, 'r', encoding='utf-8') as f:
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response_data = json.load(f)
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response = IPCResponse.from_dict(response_data)
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# 清理命令和响应文件
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# Clean up command and response files after successful read.
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try:
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os.remove(command_file)
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os.remove(response_file)
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except OSError:
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pass
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logger.info(t("log.simulation_ipc.m002", command_id=command_id, response=response.status.value))
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return response
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except (json.JSONDecodeError, KeyError) as e:
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logger.warning(t("log.simulation_ipc.m003", e=e))
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time.sleep(poll_interval)
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# 超时
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# Timed out waiting for the response.
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logger.error(t("log.simulation_ipc.m004", command_id=command_id))
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# 清理命令文件
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# Clean up the unanswered command file.
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try:
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os.remove(command_file)
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except OSError:
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pass
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raise TimeoutError(f"等待命令响应超时 ({timeout}秒)")
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def send_interview(
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self,
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agent_id: int,
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@ -194,20 +192,19 @@ class SimulationIPCClient:
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platform: str = None,
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timeout: float = 60.0
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) -> IPCResponse:
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"""
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发送单个Agent采访命令
|
||||
|
||||
"""Send a single-agent interview command.
|
||||
|
||||
Args:
|
||||
agent_id: Agent ID
|
||||
prompt: 采访问题
|
||||
platform: 指定平台（可选）
|
||||
- "twitter": 只采访Twitter平台
|
||||
- "reddit": 只采访Reddit平台
|
||||
- None: 双平台模拟时同时采访两个平台，单平台模拟时采访该平台
|
||||
timeout: 超时时间
|
||||
|
||||
agent_id: Agent id to interview.
|
||||
prompt: Interview question.
|
||||
platform: Optional platform selector.
|
||||
- ``"twitter"``: interview only on Twitter.
|
||||
- ``"reddit"``: interview only on Reddit.
|
||||
- ``None``: dual-platform if applicable, else the single active platform.
|
||||
timeout: Timeout in seconds.
|
||||
|
||||
Returns:
|
||||
IPCResponse，result字段包含采访结果
|
||||
``IPCResponse`` whose ``result`` carries the interview response.
|
||||
"""
|
||||
args = {
|
||||
"agent_id": agent_id,
|
||||
|
|
@ -215,69 +212,66 @@ class SimulationIPCClient:
|
|||
}
|
||||
if platform:
|
||||
args["platform"] = platform
|
||||
|
||||
|
||||
return self.send_command(
|
||||
command_type=CommandType.INTERVIEW,
|
||||
args=args,
|
||||
timeout=timeout
|
||||
)
|
||||
|
||||
|
||||
def send_batch_interview(
|
||||
self,
|
||||
interviews: List[Dict[str, Any]],
|
||||
platform: str = None,
|
||||
timeout: float = 120.0
|
||||
) -> IPCResponse:
|
||||
"""
|
||||
发送批量采访命令
|
||||
|
||||
"""Send a batched interview command.
|
||||
|
||||
Args:
|
||||
interviews: 采访列表，每个元素包含 {"agent_id": int, "prompt": str, "platform": str(可选)}
|
||||
platform: 默认平台（可选，会被每个采访项的platform覆盖）
|
||||
- "twitter": 默认只采访Twitter平台
|
||||
- "reddit": 默认只采访Reddit平台
|
||||
- None: 双平台模拟时每个Agent同时采访两个平台
|
||||
timeout: 超时时间
|
||||
|
||||
interviews: List of items shaped ``{"agent_id": int, "prompt": str, "platform": str?}``.
|
||||
platform: Default platform; per-item ``platform`` overrides this.
|
||||
- ``"twitter"``: default to Twitter.
|
||||
- ``"reddit"``: default to Reddit.
|
||||
- ``None``: dual-platform interview when applicable.
|
||||
timeout: Timeout in seconds.
|
||||
|
||||
Returns:
|
||||
IPCResponse，result字段包含所有采访结果
|
||||
``IPCResponse`` whose ``result`` carries every interview response.
|
||||
"""
|
||||
args = {"interviews": interviews}
|
||||
if platform:
|
||||
args["platform"] = platform
|
||||
|
||||
|
||||
return self.send_command(
|
||||
command_type=CommandType.BATCH_INTERVIEW,
|
||||
args=args,
|
||||
timeout=timeout
|
||||
)
|
||||
|
||||
|
||||
def send_close_env(self, timeout: float = 30.0) -> IPCResponse:
|
||||
"""
|
||||
发送关闭环境命令
|
||||
|
||||
"""Send a tear-down-environment command.
|
||||
|
||||
Args:
|
||||
timeout: 超时时间
|
||||
|
||||
timeout: Timeout in seconds.
|
||||
|
||||
Returns:
|
||||
IPCResponse
|
||||
``IPCResponse``.
|
||||
"""
|
||||
return self.send_command(
|
||||
command_type=CommandType.CLOSE_ENV,
|
||||
args={},
|
||||
timeout=timeout
|
||||
)
|
||||
|
||||
|
||||
def check_env_alive(self) -> bool:
|
||||
"""
|
||||
检查模拟环境是否存活
|
||||
|
||||
通过检查 env_status.json 文件来判断
|
||||
"""Return ``True`` if the simulation environment reports as alive.
|
||||
|
||||
Reads ``env_status.json`` written by the IPC server side.
|
||||
"""
|
||||
status_file = os.path.join(self.simulation_dir, "env_status.json")
|
||||
if not os.path.exists(status_file):
|
||||
return False
|
||||
|
||||
|
||||
try:
|
||||
with open(status_file, 'r', encoding='utf-8') as f:
|
||||
status = json.load(f)
|
||||
|
|
@ -287,68 +281,65 @@ class SimulationIPCClient:
|
|||
|
||||
|
||||
class SimulationIPCServer:
|
||||
"""IPC server used by the simulation script.
|
||||
|
||||
Polls the commands directory, executes commands, and writes responses.
|
||||
"""
|
||||
模拟IPC服务器（模拟脚本端使用）
|
||||
|
||||
轮询命令目录，执行命令并返回响应
|
||||
"""
|
||||
|
||||
|
||||
def __init__(self, simulation_dir: str):
|
||||
"""
|
||||
初始化IPC服务器
|
||||
|
||||
"""Initialize the IPC server.
|
||||
|
||||
Args:
|
||||
simulation_dir: 模拟数据目录
|
||||
simulation_dir: Directory holding the simulation's IPC files.
|
||||
"""
|
||||
self.simulation_dir = simulation_dir
|
||||
self.commands_dir = os.path.join(simulation_dir, "ipc_commands")
|
||||
self.responses_dir = os.path.join(simulation_dir, "ipc_responses")
|
||||
|
||||
# 确保目录存在
|
||||
|
||||
# Ensure both directories exist before use.
|
||||
os.makedirs(self.commands_dir, exist_ok=True)
|
||||
os.makedirs(self.responses_dir, exist_ok=True)
|
||||
|
||||
# 环境状态
|
||||
|
||||
# Server-running flag.
|
||||
self._running = False
|
||||
|
||||
|
||||
def start(self):
|
||||
"""标记服务器为运行状态"""
|
||||
"""Mark the server as alive and persist the state."""
|
||||
self._running = True
|
||||
self._update_env_status("alive")
|
||||
|
||||
|
||||
def stop(self):
|
||||
"""标记服务器为停止状态"""
|
||||
"""Mark the server as stopped and persist the state."""
|
||||
self._running = False
|
||||
self._update_env_status("stopped")
|
||||
|
||||
|
||||
def _update_env_status(self, status: str):
|
||||
"""更新环境状态文件"""
|
||||
"""Update the persistent environment-status file."""
|
||||
status_file = os.path.join(self.simulation_dir, "env_status.json")
|
||||
with open(status_file, 'w', encoding='utf-8') as f:
|
||||
json.dump({
|
||||
"status": status,
|
||||
"timestamp": datetime.now().isoformat()
|
||||
}, f, ensure_ascii=False, indent=2)
|
||||
|
||||
|
||||
def poll_commands(self) -> Optional[IPCCommand]:
|
||||
"""
|
||||
轮询命令目录，返回第一个待处理的命令
|
||||
|
||||
"""Poll the commands directory and return the next pending command.
|
||||
|
||||
Returns:
|
||||
IPCCommand 或 None
|
||||
``IPCCommand`` or ``None`` if no pending commands remain.
|
||||
"""
|
||||
if not os.path.exists(self.commands_dir):
|
||||
return None
|
||||
|
||||
# 按时间排序获取命令文件
|
||||
|
||||
# Sort by mtime so we process commands in arrival order.
|
||||
command_files = []
|
||||
for filename in os.listdir(self.commands_dir):
|
||||
if filename.endswith('.json'):
|
||||
filepath = os.path.join(self.commands_dir, filename)
|
||||
command_files.append((filepath, os.path.getmtime(filepath)))
|
||||
|
||||
|
||||
command_files.sort(key=lambda x: x[1])
|
||||
|
||||
|
||||
for filepath, _ in command_files:
|
||||
try:
|
||||
with open(filepath, 'r', encoding='utf-8') as f:
|
||||
|
|
@ -357,37 +348,36 @@ class SimulationIPCServer:
|
|||
except (json.JSONDecodeError, KeyError, OSError) as e:
|
||||
logger.warning(t("log.simulation_ipc.m005", filepath=filepath, e=e))
|
||||
continue
|
||||
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def send_response(self, response: IPCResponse):
|
||||
"""
|
||||
发送响应
|
||||
|
||||
"""Write a response file.
|
||||
|
||||
Args:
|
||||
response: IPC响应
|
||||
response: The response to send.
|
||||
"""
|
||||
response_file = os.path.join(self.responses_dir, f"{response.command_id}.json")
|
||||
with open(response_file, 'w', encoding='utf-8') as f:
|
||||
json.dump(response.to_dict(), f, ensure_ascii=False, indent=2)
|
||||
|
||||
# 删除命令文件
|
||||
|
||||
# Delete the matching command file.
|
||||
command_file = os.path.join(self.commands_dir, f"{response.command_id}.json")
|
||||
try:
|
||||
os.remove(command_file)
|
||||
except OSError:
|
||||
pass
|
||||
|
||||
|
||||
def send_success(self, command_id: str, result: Dict[str, Any]):
|
||||
"""发送成功响应"""
|
||||
"""Send a success response."""
|
||||
self.send_response(IPCResponse(
|
||||
command_id=command_id,
|
||||
status=CommandStatus.COMPLETED,
|
||||
result=result
|
||||
))
|
||||
|
||||
|
||||
def send_error(self, command_id: str, error: str):
|
||||
"""发送错误响应"""
|
||||
"""Send a failure response."""
|
||||
self.send_response(IPCResponse(
|
||||
command_id=command_id,
|
||||
status=CommandStatus.FAILED,
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
"""
|
||||
OASIS模拟管理器
|
||||
管理Twitter和Reddit双平台并行模拟
|
||||
使用预设脚本 + LLM智能生成配置参数
|
||||
"""OASIS simulation manager.
|
||||
|
||||
Drives parallel Twitter + Reddit simulations using preset scripts plus
|
||||
LLM-generated configuration parameters.
|
||||
"""
|
||||
|
||||
import os
|
||||
|
|
@ -23,60 +23,60 @@ logger = get_logger('mirofish.simulation')
|
|||
|
||||
|
||||
class SimulationStatus(str, Enum):
|
||||
"""模拟状态"""
|
||||
"""Simulation lifecycle status."""
|
||||
CREATED = "created"
|
||||
PREPARING = "preparing"
|
||||
READY = "ready"
|
||||
RUNNING = "running"
|
||||
PAUSED = "paused"
|
||||
STOPPED = "stopped" # 模拟被手动停止
|
||||
COMPLETED = "completed" # 模拟自然完成
|
||||
STOPPED = "stopped" # manually stopped
|
||||
COMPLETED = "completed" # finished naturally
|
||||
FAILED = "failed"
|
||||
|
||||
|
||||
class PlatformType(str, Enum):
|
||||
"""平台类型"""
|
||||
"""Simulated platform types."""
|
||||
TWITTER = "twitter"
|
||||
REDDIT = "reddit"
|
||||
|
||||
|
||||
@dataclass
|
||||
class SimulationState:
|
||||
"""模拟状态"""
|
||||
"""In-memory + persisted state for a single simulation."""
|
||||
simulation_id: str
|
||||
project_id: str
|
||||
graph_id: str
|
||||
|
||||
# 平台启用状态
|
||||
|
||||
# Per-platform enable flags.
|
||||
enable_twitter: bool = True
|
||||
enable_reddit: bool = True
|
||||
|
||||
# 状态
|
||||
|
||||
# Lifecycle status.
|
||||
status: SimulationStatus = SimulationStatus.CREATED
|
||||
|
||||
# 准备阶段数据
|
||||
|
||||
# Counters captured during the prepare phase.
|
||||
entities_count: int = 0
|
||||
profiles_count: int = 0
|
||||
entity_types: List[str] = field(default_factory=list)
|
||||
|
||||
# 配置生成信息
|
||||
|
||||
# Information about the auto-generated config.
|
||||
config_generated: bool = False
|
||||
config_reasoning: str = ""
|
||||
|
||||
# 运行时数据
|
||||
|
||||
# Runtime data.
|
||||
current_round: int = 0
|
||||
twitter_status: str = "not_started"
|
||||
reddit_status: str = "not_started"
|
||||
|
||||
# 时间戳
|
||||
|
||||
# Timestamps.
|
||||
created_at: str = field(default_factory=lambda: datetime.now().isoformat())
|
||||
updated_at: str = field(default_factory=lambda: datetime.now().isoformat())
|
||||
|
||||
# 错误信息
|
||||
|
||||
# Error message when status == FAILED.
|
||||
error: Optional[str] = None
|
||||
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""完整状态字典（内部使用）"""
|
||||
"""Full state dict (used for persistence and internal callers)."""
|
||||
return {
|
||||
"simulation_id": self.simulation_id,
|
||||
"project_id": self.project_id,
|
||||
|
|
@ -96,9 +96,9 @@ class SimulationState:
|
|||
"updated_at": self.updated_at,
|
||||
"error": self.error,
|
||||
}
|
||||
|
||||
|
||||
def to_simple_dict(self) -> Dict[str, Any]:
|
||||
"""简化状态字典（API返回使用）"""
|
||||
"""Simplified state dict (used for API responses)."""
|
||||
return {
|
||||
"simulation_id": self.simulation_id,
|
||||
"project_id": self.project_id,
|
||||
|
|
@ -113,61 +113,60 @@ class SimulationState:
|
|||
|
||||
|
||||
class SimulationManager:
|
||||
"""Simulation manager.
|
||||
|
||||
Core responsibilities:
|
||||
1. Read entities from the Zep graph and filter to the configured types.
|
||||
2. Generate OASIS agent profiles per entity.
|
||||
3. Use the LLM to generate simulation configuration parameters.
|
||||
4. Materialize the files the preset scripts expect.
|
||||
"""
|
||||
模拟管理器
|
||||
|
||||
核心功能：
|
||||
1. 从Zep图谱读取实体并过滤
|
||||
2. 生成OASIS Agent Profile
|
||||
3. 使用LLM智能生成模拟配置参数
|
||||
4. 准备预设脚本所需的所有文件
|
||||
"""
|
||||
|
||||
# 模拟数据存储目录
|
||||
|
||||
# Root directory for persisted simulation data.
|
||||
SIMULATION_DATA_DIR = os.path.join(
|
||||
os.path.dirname(__file__),
|
||||
os.path.dirname(__file__),
|
||||
'../../uploads/simulations'
|
||||
)
|
||||
|
||||
|
||||
def __init__(self):
|
||||
# 确保目录存在
|
||||
# Ensure the simulation data directory exists.
|
||||
os.makedirs(self.SIMULATION_DATA_DIR, exist_ok=True)
|
||||
|
||||
# 内存中的模拟状态缓存
|
||||
|
||||
# In-memory cache of simulation state objects.
|
||||
self._simulations: Dict[str, SimulationState] = {}
|
||||
|
||||
|
||||
def _get_simulation_dir(self, simulation_id: str) -> str:
|
||||
"""获取模拟数据目录"""
|
||||
"""Return the on-disk directory for a simulation, creating if missing."""
|
||||
sim_dir = os.path.join(self.SIMULATION_DATA_DIR, simulation_id)
|
||||
os.makedirs(sim_dir, exist_ok=True)
|
||||
return sim_dir
|
||||
|
||||
|
||||
def _save_simulation_state(self, state: SimulationState):
|
||||
"""保存模拟状态到文件"""
|
||||
"""Persist a simulation state to disk and update the cache."""
|
||||
sim_dir = self._get_simulation_dir(state.simulation_id)
|
||||
state_file = os.path.join(sim_dir, "state.json")
|
||||
|
||||
|
||||
state.updated_at = datetime.now().isoformat()
|
||||
|
||||
|
||||
with open(state_file, 'w', encoding='utf-8') as f:
|
||||
json.dump(state.to_dict(), f, ensure_ascii=False, indent=2)
|
||||
|
||||
|
||||
self._simulations[state.simulation_id] = state
|
||||
|
||||
|
||||
def _load_simulation_state(self, simulation_id: str) -> Optional[SimulationState]:
|
||||
"""从文件加载模拟状态"""
|
||||
"""Load a simulation state from disk (or cache) by id."""
|
||||
if simulation_id in self._simulations:
|
||||
return self._simulations[simulation_id]
|
||||
|
||||
|
||||
sim_dir = self._get_simulation_dir(simulation_id)
|
||||
state_file = os.path.join(sim_dir, "state.json")
|
||||
|
||||
|
||||
if not os.path.exists(state_file):
|
||||
return None
|
||||
|
||||
|
||||
with open(state_file, 'r', encoding='utf-8') as f:
|
||||
data = json.load(f)
|
||||
|
||||
|
||||
state = SimulationState(
|
||||
simulation_id=simulation_id,
|
||||
project_id=data.get("project_id", ""),
|
||||
|
|
@ -187,10 +186,10 @@ class SimulationManager:
|
|||
updated_at=data.get("updated_at", datetime.now().isoformat()),
|
||||
error=data.get("error"),
|
||||
)
|
||||
|
||||
|
||||
self._simulations[simulation_id] = state
|
||||
return state
|
||||
|
||||
|
||||
def create_simulation(
|
||||
self,
|
||||
project_id: str,
|
||||
|
|
@ -198,21 +197,20 @@ class SimulationManager:
|
|||
enable_twitter: bool = True,
|
||||
enable_reddit: bool = True,
|
||||
) -> SimulationState:
|
||||
"""
|
||||
创建新的模拟
|
||||
|
||||
"""Create a new simulation in the ``CREATED`` state.
|
||||
|
||||
Args:
|
||||
project_id: 项目ID
|
||||
graph_id: Zep图谱ID
|
||||
enable_twitter: 是否启用Twitter模拟
|
||||
enable_reddit: 是否启用Reddit模拟
|
||||
|
||||
project_id: Owning project id.
|
||||
graph_id: Source Zep graph id.
|
||||
enable_twitter: When ``True``, the Twitter simulation runs.
|
||||
enable_reddit: When ``True``, the Reddit simulation runs.
|
||||
|
||||
Returns:
|
||||
SimulationState
|
||||
The created ``SimulationState``.
|
||||
"""
|
||||
import uuid
|
||||
simulation_id = f"sim_{uuid.uuid4().hex[:12]}"
|
||||
|
||||
|
||||
state = SimulationState(
|
||||
simulation_id=simulation_id,
|
||||
project_id=project_id,
|
||||
|
|
@ -221,12 +219,12 @@ class SimulationManager:
|
|||
enable_reddit=enable_reddit,
|
||||
status=SimulationStatus.CREATED,
|
||||
)
|
||||
|
||||
|
||||
self._save_simulation_state(state)
|
||||
logger.info(t("log.simulation_manager.m001", simulation_id=simulation_id, project_id=project_id, graph_id=graph_id))
|
||||
|
||||
|
||||
return state
|
||||
|
||||
|
||||
def prepare_simulation(
|
||||
self,
|
||||
simulation_id: str,
|
||||
|
|
@ -237,56 +235,55 @@ class SimulationManager:
|
|||
progress_callback: Optional[callable] = None,
|
||||
parallel_profile_count: int = 3
|
||||
) -> SimulationState:
|
||||
"""
|
||||
准备模拟环境（全程自动化）
|
||||
|
||||
步骤：
|
||||
1. 从Zep图谱读取并过滤实体
|
||||
2. 为每个实体生成OASIS Agent Profile（可选LLM增强，支持并行）
|
||||
3. 使用LLM智能生成模拟配置参数（时间、活跃度、发言频率等）
|
||||
4. 保存配置文件和Profile文件
|
||||
5. 复制预设脚本到模拟目录
|
||||
|
||||
"""Prepare the simulation environment end-to-end.
|
||||
|
||||
Steps:
|
||||
1. Read and filter entities from the graph.
|
||||
2. Generate OASIS agent profiles (optional LLM enrichment, parallel-capable).
|
||||
3. Use the LLM to produce simulation parameters (timing, activity, posting frequency).
|
||||
4. Save the configuration and profile files.
|
||||
5. Copy preset scripts into the simulation directory.
|
||||
|
||||
Args:
|
||||
simulation_id: 模拟ID
|
||||
simulation_requirement: 模拟需求描述（用于LLM生成配置）
|
||||
document_text: 原始文档内容（用于LLM理解背景）
|
||||
defined_entity_types: 预定义的实体类型（可选）
|
||||
use_llm_for_profiles: 是否使用LLM生成详细人设
|
||||
progress_callback: 进度回调函数 (stage, progress, message)
|
||||
parallel_profile_count: 并行生成人设的数量，默认3
|
||||
|
||||
simulation_id: Simulation id.
|
||||
simulation_requirement: Free-text description of the simulation goal.
|
||||
document_text: Raw source document text passed to the LLM for context.
|
||||
defined_entity_types: Optional list of allowed entity types.
|
||||
use_llm_for_profiles: When ``True``, enrich profiles via the LLM.
|
||||
progress_callback: Optional callback ``(stage, progress, message, **extras)``.
|
||||
parallel_profile_count: Number of profile generations to run in parallel.
|
||||
|
||||
Returns:
|
||||
SimulationState
|
||||
The updated ``SimulationState``.
|
||||
"""
|
||||
state = self._load_simulation_state(simulation_id)
|
||||
if not state:
|
||||
raise ValueError(f"模拟不存在: {simulation_id}")
|
||||
|
||||
|
||||
try:
|
||||
state.status = SimulationStatus.PREPARING
|
||||
self._save_simulation_state(state)
|
||||
|
||||
|
||||
sim_dir = self._get_simulation_dir(simulation_id)
|
||||
|
||||
# ========== 阶段1: 读取并过滤实体 ==========
|
||||
|
||||
# ========== Stage 1: read and filter entities ==========
|
||||
if progress_callback:
|
||||
progress_callback("reading", 0, t('progress.connectingZepGraph'))
|
||||
|
||||
|
||||
reader = ZepEntityReader()
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback("reading", 30, t('progress.readingNodeData'))
|
||||
|
||||
|
||||
filtered = reader.filter_defined_entities(
|
||||
graph_id=state.graph_id,
|
||||
defined_entity_types=defined_entity_types,
|
||||
enrich_with_edges=True
|
||||
)
|
||||
|
||||
|
||||
state.entities_count = filtered.filtered_count
|
||||
state.entity_types = list(filtered.entity_types)
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"reading", 100,
|
||||
|
|
@ -294,16 +291,16 @@ class SimulationManager:
|
|||
current=filtered.filtered_count,
|
||||
total=filtered.filtered_count
|
||||
)
|
||||
|
||||
|
||||
if filtered.filtered_count == 0:
|
||||
state.status = SimulationStatus.FAILED
|
||||
state.error = "没有找到符合条件的实体，请检查图谱是否正确构建"
|
||||
self._save_simulation_state(state)
|
||||
return state
|
||||
|
||||
# ========== 阶段2: 生成Agent Profile ==========
|
||||
|
||||
# ========== Stage 2: generate agent profiles ==========
|
||||
total_entities = len(filtered.entities)
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_profiles", 0,
|
||||
|
|
@ -311,22 +308,22 @@ class SimulationManager:
|
|||
current=0,
|
||||
total=total_entities
|
||||
)
|
||||
|
||||
# 传入graph_id以启用Zep检索功能，获取更丰富的上下文
|
||||
|
||||
# Pass the graph_id so the generator can use Zep retrieval for richer context.
|
||||
generator = OasisProfileGenerator(graph_id=state.graph_id)
|
||||
|
||||
|
||||
def profile_progress(current, total, msg):
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_profiles",
|
||||
int(current / total * 100),
|
||||
"generating_profiles",
|
||||
int(current / total * 100),
|
||||
msg,
|
||||
current=current,
|
||||
total=total,
|
||||
item_name=msg
|
||||
)
|
||||
|
||||
# 设置实时保存的文件路径（优先使用 Reddit JSON 格式）
|
||||
|
||||
# Configure the realtime save target (prefer Reddit JSON if Reddit is enabled).
|
||||
realtime_output_path = None
|
||||
realtime_platform = "reddit"
|
||||
if state.enable_reddit:
|
||||
|
|
@ -335,21 +332,21 @@ class SimulationManager:
|
|||
elif state.enable_twitter:
|
||||
realtime_output_path = os.path.join(sim_dir, "twitter_profiles.csv")
|
||||
realtime_platform = "twitter"
|
||||
|
||||
|
||||
profiles = generator.generate_profiles_from_entities(
|
||||
entities=filtered.entities,
|
||||
use_llm=use_llm_for_profiles,
|
||||
progress_callback=profile_progress,
|
||||
graph_id=state.graph_id, # 传入graph_id用于Zep检索
|
||||
parallel_count=parallel_profile_count, # 并行生成数量
|
||||
realtime_output_path=realtime_output_path, # 实时保存路径
|
||||
output_platform=realtime_platform # 输出格式
|
||||
graph_id=state.graph_id, # used for Zep retrieval enrichment
|
||||
parallel_count=parallel_profile_count,
|
||||
realtime_output_path=realtime_output_path,
|
||||
output_platform=realtime_platform
|
||||
)
|
||||
|
||||
|
||||
state.profiles_count = len(profiles)
|
||||
|
||||
# 保存Profile文件（注意：Twitter使用CSV格式，Reddit使用JSON格式）
|
||||
# Reddit 已经在生成过程中实时保存了，这里再保存一次确保完整性
|
||||
|
||||
# Save profile files. Reddit also writes JSON during generation; this is
|
||||
# a final consistency write. Twitter requires CSV per OASIS conventions.
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_profiles", 95,
|
||||
|
|
@ -357,22 +354,22 @@ class SimulationManager:
|
|||
current=total_entities,
|
||||
total=total_entities
|
||||
)
|
||||
|
||||
|
||||
if state.enable_reddit:
|
||||
generator.save_profiles(
|
||||
profiles=profiles,
|
||||
file_path=os.path.join(sim_dir, "reddit_profiles.json"),
|
||||
platform="reddit"
|
||||
)
|
||||
|
||||
|
||||
if state.enable_twitter:
|
||||
# Twitter使用CSV格式！这是OASIS的要求
|
||||
# Twitter uses CSV format — required by OASIS.
|
||||
generator.save_profiles(
|
||||
profiles=profiles,
|
||||
file_path=os.path.join(sim_dir, "twitter_profiles.csv"),
|
||||
platform="twitter"
|
||||
)
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_profiles", 100,
|
||||
|
|
@ -380,8 +377,8 @@ class SimulationManager:
|
|||
current=len(profiles),
|
||||
total=len(profiles)
|
||||
)
|
||||
|
||||
# ========== 阶段3: LLM智能生成模拟配置 ==========
|
||||
|
||||
# ========== Stage 3: LLM-driven simulation config ==========
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_config", 0,
|
||||
|
|
@ -389,9 +386,9 @@ class SimulationManager:
|
|||
current=0,
|
||||
total=3
|
||||
)
|
||||
|
||||
|
||||
config_generator = SimulationConfigGenerator()
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_config", 30,
|
||||
|
|
@ -399,7 +396,7 @@ class SimulationManager:
|
|||
current=1,
|
||||
total=3
|
||||
)
|
||||
|
||||
|
||||
sim_params = config_generator.generate_config(
|
||||
simulation_id=simulation_id,
|
||||
project_id=state.project_id,
|
||||
|
|
@ -410,7 +407,7 @@ class SimulationManager:
|
|||
enable_twitter=state.enable_twitter,
|
||||
enable_reddit=state.enable_reddit
|
||||
)
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_config", 70,
|
||||
|
|
@ -418,15 +415,15 @@ class SimulationManager:
|
|||
current=2,
|
||||
total=3
|
||||
)
|
||||
|
||||
# 保存配置文件
|
||||
|
||||
# Save the configuration file.
|
||||
config_path = os.path.join(sim_dir, "simulation_config.json")
|
||||
with open(config_path, 'w', encoding='utf-8') as f:
|
||||
f.write(sim_params.to_json())
|
||||
|
||||
|
||||
state.config_generated = True
|
||||
state.config_reasoning = sim_params.generation_reasoning
|
||||
|
||||
|
||||
if progress_callback:
|
||||
progress_callback(
|
||||
"generating_config", 100,
|
||||
|
|
@ -434,18 +431,17 @@ class SimulationManager:
|
|||
current=3,
|
||||
total=3
|
||||
)
|
||||
|
||||
# 注意：运行脚本保留在 backend/scripts/ 目录，不再复制到模拟目录
|
||||
# 启动模拟时，simulation_runner 会从 scripts/ 目录运行脚本
|
||||
|
||||
# 更新状态
|
||||
|
||||
# The runtime scripts now live under backend/scripts/; we no longer copy
|
||||
# them per-simulation. simulation_runner invokes them in place.
|
||||
|
||||
state.status = SimulationStatus.READY
|
||||
self._save_simulation_state(state)
|
||||
|
||||
|
||||
logger.info(t("log.simulation_manager.m002", simulation_id=simulation_id, state=state.entities_count, state_2=state.profiles_count))
|
||||
|
||||
|
||||
return state
|
||||
|
||||
|
||||
except Exception as e:
|
||||
logger.error(t("log.simulation_manager.m003", simulation_id=simulation_id, str=str(e)))
|
||||
import traceback
|
||||
|
|
@ -454,61 +450,61 @@ class SimulationManager:
|
|||
state.error = str(e)
|
||||
self._save_simulation_state(state)
|
||||
raise
|
||||
|
||||
|
||||
def get_simulation(self, simulation_id: str) -> Optional[SimulationState]:
|
||||
"""获取模拟状态"""
|
||||
"""Return the simulation's state, or ``None`` if unknown."""
|
||||
return self._load_simulation_state(simulation_id)
|
||||
|
||||
|
||||
def list_simulations(self, project_id: Optional[str] = None) -> List[SimulationState]:
|
||||
"""列出所有模拟"""
|
||||
"""List all simulations, optionally filtered by ``project_id``."""
|
||||
simulations = []
|
||||
|
||||
|
||||
if os.path.exists(self.SIMULATION_DATA_DIR):
|
||||
for sim_id in os.listdir(self.SIMULATION_DATA_DIR):
|
||||
# 跳过隐藏文件（如 .DS_Store）和非目录文件
|
||||
# Skip dotfiles (e.g. .DS_Store) and non-directories.
|
||||
sim_path = os.path.join(self.SIMULATION_DATA_DIR, sim_id)
|
||||
if sim_id.startswith('.') or not os.path.isdir(sim_path):
|
||||
continue
|
||||
|
||||
|
||||
state = self._load_simulation_state(sim_id)
|
||||
if state:
|
||||
if project_id is None or state.project_id == project_id:
|
||||
simulations.append(state)
|
||||
|
||||
|
||||
return simulations
|
||||
|
||||
|
||||
def get_profiles(self, simulation_id: str, platform: str = "reddit") -> List[Dict[str, Any]]:
|
||||
"""获取模拟的Agent Profile"""
|
||||
"""Return the persisted agent profiles for a platform."""
|
||||
state = self._load_simulation_state(simulation_id)
|
||||
if not state:
|
||||
raise ValueError(f"模拟不存在: {simulation_id}")
|
||||
|
||||
|
||||
sim_dir = self._get_simulation_dir(simulation_id)
|
||||
profile_path = os.path.join(sim_dir, f"{platform}_profiles.json")
|
||||
|
||||
|
||||
if not os.path.exists(profile_path):
|
||||
return []
|
||||
|
||||
|
||||
with open(profile_path, 'r', encoding='utf-8') as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
def get_simulation_config(self, simulation_id: str) -> Optional[Dict[str, Any]]:
|
||||
"""获取模拟配置"""
|
||||
"""Return the persisted simulation config dict, or ``None`` if absent."""
|
||||
sim_dir = self._get_simulation_dir(simulation_id)
|
||||
config_path = os.path.join(sim_dir, "simulation_config.json")
|
||||
|
||||
|
||||
if not os.path.exists(config_path):
|
||||
return None
|
||||
|
||||
|
||||
with open(config_path, 'r', encoding='utf-8') as f:
|
||||
return json.load(f)
|
||||
|
||||
|
||||
def get_run_instructions(self, simulation_id: str) -> Dict[str, str]:
|
||||
"""获取运行说明"""
|
||||
"""Return shell commands and instructions to launch the simulation manually."""
|
||||
sim_dir = self._get_simulation_dir(simulation_id)
|
||||
config_path = os.path.join(sim_dir, "simulation_config.json")
|
||||
scripts_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '../../scripts'))
|
||||
|
||||
|
||||
return {
|
||||
"simulation_dir": sim_dir,
|
||||
"scripts_dir": scripts_dir,
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
"""
|
||||
Zep实体读取与过滤服务
|
||||
从Zep图谱中读取节点，筛选出符合预定义实体类型的节点
|
||||
"""Zep entity reader and filter service.
|
||||
|
||||
Reads nodes from a Zep graph and filters down to those that match a
|
||||
predefined ontology of entity types.
|
||||
"""
|
||||
|
||||
import time
|
||||
|
|
@ -16,23 +17,23 @@ from ..utils.locale import t
|
|||
|
||||
logger = get_logger('mirofish.zep_entity_reader')
|
||||
|
||||
# 用于泛型返回类型
|
||||
# Generic return-type variable.
|
||||
T = TypeVar('T')
|
||||
|
||||
|
||||
@dataclass
|
||||
class EntityNode:
|
||||
"""实体节点数据结构"""
|
||||
"""In-memory representation of an entity node from the graph."""
|
||||
uuid: str
|
||||
name: str
|
||||
labels: List[str]
|
||||
summary: str
|
||||
attributes: Dict[str, Any]
|
||||
# 相关的边信息
|
||||
# Edges connected to this entity.
|
||||
related_edges: List[Dict[str, Any]] = field(default_factory=list)
|
||||
# 相关的其他节点信息
|
||||
# Other nodes connected through related edges.
|
||||
related_nodes: List[Dict[str, Any]] = field(default_factory=list)
|
||||
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"uuid": self.uuid,
|
||||
|
|
@ -43,9 +44,9 @@ class EntityNode:
|
|||
"related_edges": self.related_edges,
|
||||
"related_nodes": self.related_nodes,
|
||||
}
|
||||
|
||||
|
||||
def get_entity_type(self) -> Optional[str]:
|
||||
"""获取实体类型（排除默认的Entity标签）"""
|
||||
"""Return the first non-default label, or ``None`` if only defaults are present."""
|
||||
for label in self.labels:
|
||||
if label not in ["Entity", "Node"]:
|
||||
return label
|
||||
|
|
@ -54,12 +55,12 @@ class EntityNode:
|
|||
|
||||
@dataclass
|
||||
class FilteredEntities:
|
||||
"""过滤后的实体集合"""
|
||||
"""Result of a filter pass over the graph: matching entities + counts."""
|
||||
entities: List[EntityNode]
|
||||
entity_types: Set[str]
|
||||
total_count: int
|
||||
filtered_count: int
|
||||
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"entities": [e.to_dict() for e in self.entities],
|
||||
|
|
@ -70,40 +71,38 @@ class FilteredEntities:
|
|||
|
||||
|
||||
class ZepEntityReader:
|
||||
"""Read entities from a Zep graph and filter to ontology-defined types.
|
||||
|
||||
Capabilities:
|
||||
1. Read all nodes from the graph.
|
||||
2. Keep nodes whose labels include something other than the default ``Entity``.
|
||||
3. Optionally enrich each entity with its connected edges and neighboring nodes.
|
||||
"""
|
||||
Zep实体读取与过滤服务
|
||||
|
||||
主要功能：
|
||||
1. 从Zep图谱读取所有节点
|
||||
2. 筛选出符合预定义实体类型的节点（Labels不只是Entity的节点）
|
||||
3. 获取每个实体的相关边和关联节点信息
|
||||
"""
|
||||
|
||||
|
||||
def __init__(self, api_key: Optional[str] = None):
|
||||
self.client = GraphitiAdapter()
|
||||
|
||||
|
||||
def _call_with_retry(
|
||||
self,
|
||||
func: Callable[[], T],
|
||||
self,
|
||||
func: Callable[[], T],
|
||||
operation_name: str,
|
||||
max_retries: int = 3,
|
||||
initial_delay: float = 2.0
|
||||
) -> T:
|
||||
"""
|
||||
带重试机制的Zep API调用
|
||||
|
||||
"""Call a Zep API function with retry on failure.
|
||||
|
||||
Args:
|
||||
func: 要执行的函数（无参数的lambda或callable）
|
||||
operation_name: 操作名称，用于日志
|
||||
max_retries: 最大重试次数（默认3次，即最多尝试3次）
|
||||
initial_delay: 初始延迟秒数
|
||||
|
||||
func: A zero-argument callable performing the request.
|
||||
operation_name: Operation label used in log output.
|
||||
max_retries: Maximum number of attempts (default 3 — i.e. up to 3 tries total).
|
||||
initial_delay: Initial delay between retries in seconds.
|
||||
|
||||
Returns:
|
||||
API调用结果
|
||||
The return value of ``func``.
|
||||
"""
|
||||
last_exception = None
|
||||
delay = initial_delay
|
||||
|
||||
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
return func()
|
||||
|
|
@ -114,21 +113,20 @@ class ZepEntityReader:
|
|||
t("log.zep_entity_reader.m001", operation_name=operation_name, attempt=attempt + 1, str=str(e)[:100], delay=delay)
|
||||
)
|
||||
time.sleep(delay)
|
||||
delay *= 2 # 指数退避
|
||||
delay *= 2 # exponential backoff
|
||||
else:
|
||||
logger.error(t("log.zep_entity_reader.m002", operation_name=operation_name, max_retries=max_retries, str=str(e)))
|
||||
|
||||
|
||||
raise last_exception
|
||||
|
||||
|
||||
def get_all_nodes(self, graph_id: str) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取图谱的所有节点（分页获取）
|
||||
"""Return every node in the graph (paginated under the hood).
|
||||
|
||||
Args:
|
||||
graph_id: 图谱ID
|
||||
graph_id: Graph identifier.
|
||||
|
||||
Returns:
|
||||
节点列表
|
||||
A list of node dicts.
|
||||
"""
|
||||
logger.info(t("log.zep_entity_reader.m003", graph_id=graph_id))
|
||||
|
||||
|
|
@ -148,14 +146,13 @@ class ZepEntityReader:
|
|||
return nodes_data
|
||||
|
||||
def get_all_edges(self, graph_id: str) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取图谱的所有边（分页获取）
|
||||
"""Return every edge in the graph (paginated under the hood).
|
||||
|
||||
Args:
|
||||
graph_id: 图谱ID
|
||||
graph_id: Graph identifier.
|
||||
|
||||
Returns:
|
||||
边列表
|
||||
A list of edge dicts.
|
||||
"""
|
||||
logger.info(t("log.zep_entity_reader.m005", graph_id=graph_id))
|
||||
|
||||
|
|
@ -174,24 +171,23 @@ class ZepEntityReader:
|
|||
|
||||
logger.info(t("log.zep_entity_reader.m006", len=len(edges_data)))
|
||||
return edges_data
|
||||
|
||||
|
||||
def get_node_edges(self, node_uuid: str) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
获取指定节点的所有相关边（带重试机制）
|
||||
|
||||
"""Return every edge connected to the given node (with retry).
|
||||
|
||||
Args:
|
||||
node_uuid: 节点UUID
|
||||
|
||||
node_uuid: Node UUID.
|
||||
|
||||
Returns:
|
||||
边列表
|
||||
A list of edge dicts.
|
||||
"""
|
||||
try:
|
||||
# 使用重试机制调用Zep API
|
||||
# Wrap the API call in retry logic.
|
||||
edges = self._call_with_retry(
|
||||
func=lambda: self.client.graph.node.get_entity_edges(node_uuid=node_uuid),
|
||||
operation_name=f"获取节点边(node={node_uuid[:8]}...)"
|
||||
)
|
||||
|
||||
|
||||
edges_data = []
|
||||
for edge in edges:
|
||||
edges_data.append({
|
||||
|
|
@ -202,32 +198,31 @@ class ZepEntityReader:
|
|||
"target_node_uuid": edge.target_node_uuid,
|
||||
"attributes": edge.attributes or {},
|
||||
})
|
||||
|
||||
|
||||
return edges_data
|
||||
except Exception as e:
|
||||
logger.warning(t("log.zep_entity_reader.m007", node_uuid=node_uuid, str=str(e)))
|
||||
return []
|
||||
|
||||
|
||||
def filter_defined_entities(
|
||||
self,
|
||||
self,
|
||||
graph_id: str,
|
||||
defined_entity_types: Optional[List[str]] = None,
|
||||
enrich_with_edges: bool = True
|
||||
) -> FilteredEntities:
|
||||
"""
|
||||
筛选出符合预定义实体类型的节点
|
||||
|
||||
筛选逻辑：
|
||||
- 如果节点的Labels只有一个"Entity"，说明这个实体不符合我们预定义的类型，跳过
|
||||
- 如果节点的Labels包含除"Entity"和"Node"之外的标签，说明符合预定义类型，保留
|
||||
|
||||
"""Filter nodes down to entities matching the predefined ontology types.
|
||||
|
||||
Filtering rules:
|
||||
- Skip nodes whose only label is ``Entity`` (uncategorized).
|
||||
- Keep nodes whose labels include anything other than ``Entity`` and ``Node``.
|
||||
|
||||
Args:
|
||||
graph_id: 图谱ID
|
||||
defined_entity_types: 预定义的实体类型列表（可选，如果提供则只保留这些类型）
|
||||
enrich_with_edges: 是否获取每个实体的相关边信息
|
||||
|
||||
graph_id: Graph identifier.
|
||||
defined_entity_types: Optional allow-list; when provided, only matching types are kept.
|
||||
enrich_with_edges: When ``True``, populate related_edges and related_nodes.
|
||||
|
||||
Returns:
|
||||
FilteredEntities: 过滤后的实体集合
|
||||
A ``FilteredEntities`` summary.
|
||||
"""
|
||||
logger.info(t("log.zep_entity_reader.m008", graph_id=graph_id))
|
||||
|
||||
|
|
@ -243,7 +238,7 @@ class ZepEntityReader:
|
|||
except Exception:
|
||||
pass
|
||||
|
||||
# 获取所有节点
|
||||
# Read every node from the graph.
|
||||
all_nodes = self.get_all_nodes(graph_id)
|
||||
total_count = len(all_nodes)
|
||||
|
||||
|
|
@ -259,27 +254,27 @@ class ZepEntityReader:
|
|||
if entity_type != "Entity":
|
||||
node["labels"] = [entity_type] + labels
|
||||
|
||||
# 获取所有边（用于后续关联查找）
|
||||
# Read every edge so we can enrich entities later.
|
||||
all_edges = self.get_all_edges(graph_id) if enrich_with_edges else []
|
||||
|
||||
# 构建节点UUID到节点数据的映射
|
||||
# uuid -> node-data map for fast lookup.
|
||||
node_map = {n["uuid"]: n for n in all_nodes}
|
||||
|
||||
# 筛选符合条件的实体
|
||||
# Filter to entities that match the criteria.
|
||||
filtered_entities = []
|
||||
entity_types_found = set()
|
||||
|
||||
for node in all_nodes:
|
||||
labels = node.get("labels", [])
|
||||
|
||||
# 筛选逻辑：Labels必须包含除"Entity"和"Node"之外的标签
|
||||
# Filtering rule: labels must contain something other than the defaults.
|
||||
custom_labels = [l for l in labels if l not in ["Entity", "Node"]]
|
||||
|
||||
if not custom_labels:
|
||||
# 只有默认标签，跳过
|
||||
# Only default labels — skip.
|
||||
continue
|
||||
|
||||
# 如果指定了预定义类型，检查是否匹配
|
||||
|
||||
# When a predefined-type list is supplied, require a match against it.
|
||||
if defined_entity_types:
|
||||
matching_labels = [l for l in custom_labels if l in defined_entity_types]
|
||||
if not matching_labels:
|
||||
|
|
@ -287,10 +282,9 @@ class ZepEntityReader:
|
|||
entity_type = matching_labels[0]
|
||||
else:
|
||||
entity_type = custom_labels[0]
|
||||
|
||||
|
||||
entity_types_found.add(entity_type)
|
||||
|
||||
# 创建实体节点对象
|
||||
|
||||
entity = EntityNode(
|
||||
uuid=node["uuid"],
|
||||
name=node["name"],
|
||||
|
|
@ -298,12 +292,12 @@ class ZepEntityReader:
|
|||
summary=node["summary"],
|
||||
attributes=node["attributes"],
|
||||
)
|
||||
|
||||
# 获取相关边和节点
|
||||
|
||||
# Enrich with related edges and neighboring nodes.
|
||||
if enrich_with_edges:
|
||||
related_edges = []
|
||||
related_node_uuids = set()
|
||||
|
||||
|
||||
for edge in all_edges:
|
||||
if edge["source_node_uuid"] == node["uuid"]:
|
||||
related_edges.append({
|
||||
|
|
@ -321,10 +315,10 @@ class ZepEntityReader:
|
|||
"source_node_uuid": edge["source_node_uuid"],
|
||||
})
|
||||
related_node_uuids.add(edge["source_node_uuid"])
|
||||
|
||||
|
||||
entity.related_edges = related_edges
|
||||
|
||||
# 获取关联节点的基本信息
|
||||
|
||||
# Populate basic info for each neighboring node.
|
||||
related_nodes = []
|
||||
for related_uuid in related_node_uuids:
|
||||
if related_uuid in node_map:
|
||||
|
|
@ -335,56 +329,55 @@ class ZepEntityReader:
|
|||
"labels": related_node["labels"],
|
||||
"summary": related_node.get("summary", ""),
|
||||
})
|
||||
|
||||
|
||||
entity.related_nodes = related_nodes
|
||||
|
||||
|
||||
filtered_entities.append(entity)
|
||||
|
||||
|
||||
logger.info(t("log.zep_entity_reader.m009", total_count=total_count, len=len(filtered_entities), entity_types_found=entity_types_found))
|
||||
|
||||
|
||||
return FilteredEntities(
|
||||
entities=filtered_entities,
|
||||
entity_types=entity_types_found,
|
||||
total_count=total_count,
|
||||
filtered_count=len(filtered_entities),
|
||||
)
|
||||
|
||||
|
||||
def get_entity_with_context(
|
||||
self,
|
||||
graph_id: str,
|
||||
self,
|
||||
graph_id: str,
|
||||
entity_uuid: str
|
||||
) -> Optional[EntityNode]:
|
||||
"""
|
||||
获取单个实体及其完整上下文（边和关联节点，带重试机制）
|
||||
|
||||
"""Fetch a single entity with its full context (edges + neighbors), with retry.
|
||||
|
||||
Args:
|
||||
graph_id: 图谱ID
|
||||
entity_uuid: 实体UUID
|
||||
|
||||
graph_id: Graph identifier.
|
||||
entity_uuid: Entity UUID.
|
||||
|
||||
Returns:
|
||||
EntityNode或None
|
||||
``EntityNode`` or ``None`` if not found.
|
||||
"""
|
||||
try:
|
||||
# 使用重试机制获取节点
|
||||
# Fetch the node with retry.
|
||||
node = self._call_with_retry(
|
||||
func=lambda: self.client.graph.node.get(uuid_=entity_uuid),
|
||||
operation_name=f"获取节点详情(uuid={entity_uuid[:8]}...)"
|
||||
)
|
||||
|
||||
|
||||
if not node:
|
||||
return None
|
||||
|
||||
# 获取节点的边
|
||||
|
||||
# Edges connected to this node.
|
||||
edges = self.get_node_edges(entity_uuid)
|
||||
|
||||
# 获取所有节点用于关联查找
|
||||
|
||||
# All graph nodes, used for neighbor lookup.
|
||||
all_nodes = self.get_all_nodes(graph_id)
|
||||
node_map = {n["uuid"]: n for n in all_nodes}
|
||||
|
||||
# 处理相关边和节点
|
||||
|
||||
# Collect related edges and neighboring uuids.
|
||||
related_edges = []
|
||||
related_node_uuids = set()
|
||||
|
||||
|
||||
for edge in edges:
|
||||
if edge["source_node_uuid"] == entity_uuid:
|
||||
related_edges.append({
|
||||
|
|
@ -402,8 +395,8 @@ class ZepEntityReader:
|
|||
"source_node_uuid": edge["source_node_uuid"],
|
||||
})
|
||||
related_node_uuids.add(edge["source_node_uuid"])
|
||||
|
||||
# 获取关联节点信息
|
||||
|
||||
# Populate basic info for each neighboring node.
|
||||
related_nodes = []
|
||||
for related_uuid in related_node_uuids:
|
||||
if related_uuid in node_map:
|
||||
|
|
@ -414,7 +407,7 @@ class ZepEntityReader:
|
|||
"labels": related_node["labels"],
|
||||
"summary": related_node.get("summary", ""),
|
||||
})
|
||||
|
||||
|
||||
return EntityNode(
|
||||
uuid=getattr(node, 'uuid_', None) or getattr(node, 'uuid', ''),
|
||||
name=node.name or "",
|
||||
|
|
@ -424,27 +417,26 @@ class ZepEntityReader:
|
|||
related_edges=related_edges,
|
||||
related_nodes=related_nodes,
|
||||
)
|
||||
|
||||
|
||||
except Exception as e:
|
||||
logger.error(t("log.zep_entity_reader.m010", entity_uuid=entity_uuid, str=str(e)))
|
||||
return None
|
||||
|
||||
|
||||
def get_entities_by_type(
|
||||
self,
|
||||
graph_id: str,
|
||||
self,
|
||||
graph_id: str,
|
||||
entity_type: str,
|
||||
enrich_with_edges: bool = True
|
||||
) -> List[EntityNode]:
|
||||
"""
|
||||
获取指定类型的所有实体
|
||||
|
||||
"""Return every entity matching the given type.
|
||||
|
||||
Args:
|
||||
graph_id: 图谱ID
|
||||
entity_type: 实体类型（如 "Student", "PublicFigure" 等）
|
||||
enrich_with_edges: 是否获取相关边信息
|
||||
|
||||
graph_id: Graph identifier.
|
||||
entity_type: Entity type label (e.g. ``Student``, ``PublicFigure``).
|
||||
enrich_with_edges: When ``True``, populate related edges/nodes.
|
||||
|
||||
Returns:
|
||||
实体列表
|
||||
A list of matching ``EntityNode`` instances.
|
||||
"""
|
||||
result = self.filter_defined_entities(
|
||||
graph_id=graph_id,
|
||||
|
|
|
|||
|
|
@ -1,21 +1,20 @@
|
|||
"""
|
||||
MiroFish Backend 启动入口
|
||||
"""
|
||||
"""MiroFish backend entry point."""
|
||||
|
||||
import os
|
||||
import sys
|
||||
|
||||
# 解决 Windows 控制台中文乱码问题：在所有导入之前设置 UTF-8 编码
|
||||
# Force UTF-8 on Windows console before importing anything that might write to
|
||||
# stdout/stderr; otherwise non-ASCII characters render as mojibake.
|
||||
if sys.platform == 'win32':
|
||||
# 设置环境变量确保 Python 使用 UTF-8
|
||||
# Make sure Python itself uses UTF-8.
|
||||
os.environ.setdefault('PYTHONIOENCODING', 'utf-8')
|
||||
# 重新配置标准输出流为 UTF-8
|
||||
# Reconfigure the standard streams to UTF-8.
|
||||
if hasattr(sys.stdout, 'reconfigure'):
|
||||
sys.stdout.reconfigure(encoding='utf-8', errors='replace')
|
||||
if hasattr(sys.stderr, 'reconfigure'):
|
||||
sys.stderr.reconfigure(encoding='utf-8', errors='replace')
|
||||
|
||||
# 添加项目根目录到路径
|
||||
# Add the project root to sys.path so the ``app`` package resolves.
|
||||
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
|
||||
|
||||
from app import create_app
|
||||
|
|
@ -23,8 +22,7 @@ from app.config import Config
|
|||
|
||||
|
||||
def main():
|
||||
"""主函数"""
|
||||
# 验证配置
|
||||
"""Validate configuration and start the Flask development server."""
|
||||
errors = Config.validate()
|
||||
if errors:
|
||||
print("配置错误:")
|
||||
|
|
@ -32,19 +30,16 @@ def main():
|
|||
print(f" - {err}")
|
||||
print("\n请检查 .env 文件中的配置")
|
||||
sys.exit(1)
|
||||
|
||||
# 创建应用
|
||||
|
||||
app = create_app()
|
||||
|
||||
# 获取运行配置
|
||||
|
||||
# Resolve runtime host/port from the environment.
|
||||
host = os.environ.get('FLASK_HOST', '0.0.0.0')
|
||||
port = int(os.environ.get('FLASK_PORT', 5001))
|
||||
debug = Config.DEBUG
|
||||
|
||||
# 启动服务
|
||||
|
||||
app.run(host=host, port=port, debug=debug, threaded=True)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue