Merge d0729722da into 96096ea0ff
This commit is contained in:
amaynez
GitHub
commit
3d84258ea4
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@ -58,3 +58,6 @@ backend/uploads/
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# Docker 数据
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data/
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# Personal configuration
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CLAUDE.md
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skills/
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@ -17,6 +17,7 @@ from ..utils.file_parser import FileParser
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from ..utils.logger import get_logger
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from ..utils.locale import t, get_locale, set_locale
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from ..models.task import TaskManager, TaskStatus
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from ..utils.zep_rate_limiter import graph_data_cache
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from ..models.project import ProjectManager, ProjectStatus
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# 获取日志器
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@ -564,12 +565,35 @@ def list_tasks():
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})
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# ============== 配置接口 ==============
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@graph_bp.route('/config', methods=['GET'])
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def get_graph_config():
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"""
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返回前端需要的图谱轮询配置。
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前端根据这些值决定是否自动轮询以及间隔。
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"""
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# 初始化缓存 TTL（确保与 Config 同步）
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graph_data_cache.ttl = Config.ZEP_CACHE_TTL
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return jsonify({
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"success": True,
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"data": {
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"poll_interval": Config.ZEP_GRAPH_POLL_INTERVAL, # 0 = 仅手动刷新
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"cache_ttl": Config.ZEP_CACHE_TTL,
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"rate_limit": Config.ZEP_RATE_LIMIT,
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"rate_limit_window": Config.ZEP_RATE_LIMIT_WINDOW,
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}
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})
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# ============== 图谱数据接口 ==============
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@graph_bp.route('/data/<graph_id>', methods=['GET'])
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def get_graph_data(graph_id: str):
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"""
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获取图谱数据（节点和边）
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获取图谱数据（节点和边）。
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使用响应缓存避免频繁调用 Zep API。
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"""
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try:
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if not Config.ZEP_API_KEY:
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@ -578,12 +602,28 @@ def get_graph_data(graph_id: str):
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"error": t('api.zepApiKeyMissing')
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}), 500
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# 检查缓存
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cache_key = f"graph_data:{graph_id}"
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cached = graph_data_cache.get(cache_key)
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if cached is not None:
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logger.debug(f"Serving cached graph data for {graph_id}")
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return jsonify({
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"success": True,
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"data": cached,
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"cached": True
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})
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# 缓存未命中，调用 Zep API
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builder = GraphBuilderService(api_key=Config.ZEP_API_KEY)
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graph_data = builder.get_graph_data(graph_id)
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# 缓存成功响应
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graph_data_cache.set(cache_key, graph_data)
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return jsonify({
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"success": True,
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"data": graph_data
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"data": graph_data,
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"cached": False
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})
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except Exception as e:
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@ -32,9 +32,20 @@ class Config:
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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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# Boost/Fallback LLM配置（可选，主 LLM 失败时自动回退）
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LLM_BOOST_API_KEY = os.environ.get('LLM_BOOST_API_KEY')
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LLM_BOOST_BASE_URL = os.environ.get('LLM_BOOST_BASE_URL')
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LLM_BOOST_MODEL_NAME = os.environ.get('LLM_BOOST_MODEL_NAME')
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# Zep配置
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ZEP_API_KEY = os.environ.get('ZEP_API_KEY')
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# Zep 速率限制配置（可通过 .env 调整，升级付费计划后放宽）
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ZEP_RATE_LIMIT = int(os.environ.get('ZEP_RATE_LIMIT', '5')) # 每个窗口期允许的请求数
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ZEP_RATE_LIMIT_WINDOW = int(os.environ.get('ZEP_RATE_LIMIT_WINDOW', '60')) # 窗口期（秒）
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ZEP_CACHE_TTL = int(os.environ.get('ZEP_CACHE_TTL', '30')) # graph data 缓存时间（秒），0=不缓存
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ZEP_GRAPH_POLL_INTERVAL = int(os.environ.get('ZEP_GRAPH_POLL_INTERVAL', '0')) # 前端自动轮询间隔（秒），0=仅手动刷新
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# 文件上传配置
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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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@ -18,6 +18,7 @@ from ..models.task import TaskManager, TaskStatus
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from ..utils.zep_paging import fetch_all_nodes, fetch_all_edges
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from .text_processor import TextProcessor
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from ..utils.locale import t, get_locale, set_locale
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from ..utils.zep_retry import with_zep_retry
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@dataclass
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@ -190,6 +191,7 @@ class GraphBuilderService:
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error_msg = f"{str(e)}\n{traceback.format_exc()}"
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self.task_manager.fail_task(task_id, error_msg)
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@with_zep_retry(max_retries=3, operation_name="create_graph")
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def create_graph(self, name: str) -> str:
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"""创建Zep图谱（公开方法）"""
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graph_id = f"mirofish_{uuid.uuid4().hex[:16]}"
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@ -285,11 +287,14 @@ class GraphBuilderService:
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# 调用Zep API设置本体
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if entity_types or edge_definitions:
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self.client.graph.set_ontology(
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graph_ids=[graph_id],
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entities=entity_types if entity_types else None,
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edges=edge_definitions if edge_definitions else None,
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)
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@with_zep_retry(max_retries=3, operation_name="set_ontology")
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def _set_ontology():
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self.client.graph.set_ontology(
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graph_ids=[graph_id],
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entities=entity_types if entity_types else None,
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edges=edge_definitions if edge_definitions else None,
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)
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_set_ontology()
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def add_text_batches(
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self,
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@ -322,10 +327,14 @@ class GraphBuilderService:
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# 发送到Zep
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try:
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batch_result = self.client.graph.add_batch(
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graph_id=graph_id,
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episodes=episodes
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)
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@with_zep_retry(max_retries=3, operation_name=f"add_batch {batch_num}/{total_batches}")
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def _add_batch():
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return self.client.graph.add_batch(
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graph_id=graph_id,
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episodes=episodes
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)
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batch_result = _add_batch()
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# 收集返回的 episode uuid
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if batch_result and isinstance(batch_result, list):
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@ -376,7 +385,11 @@ class GraphBuilderService:
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# 检查每个 episode 的处理状态
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for ep_uuid in list(pending_episodes):
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try:
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episode = self.client.graph.episode.get(uuid_=ep_uuid)
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@with_zep_retry(max_retries=2, initial_delay=1.0, operation_name="get_episode")
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def _get_episode():
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return self.client.graph.episode.get(uuid_=ep_uuid)
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episode = _get_episode()
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is_processed = getattr(episode, 'processed', False)
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if is_processed:
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@ -500,6 +513,7 @@ class GraphBuilderService:
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"edge_count": len(edges_data),
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}
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@with_zep_retry(max_retries=3, operation_name="delete_graph")
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def delete_graph(self, graph_id: str):
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"""删除图谱"""
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self.client.graph.delete(graph_id=graph_id)
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@ -21,6 +21,7 @@ from zep_cloud.client import Zep
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from ..config import Config
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from ..utils.logger import get_logger
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from ..utils.locale import get_language_instruction, get_locale, set_locale, t
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from ..utils.zep_retry import with_zep_retry
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from .zep_entity_reader import EntityNode, ZepEntityReader
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logger = get_logger('mirofish.oasis_profile')
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@ -316,55 +317,27 @@ class OasisProfileGenerator:
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comprehensive_query = t('progress.zepSearchQuery', name=entity_name)
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@with_zep_retry(max_retries=3, initial_delay=2.0, operation_name="Zep Edge Search")
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def search_edges():
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"""搜索边（事实/关系）- 带重试机制"""
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max_retries = 3
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last_exception = None
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delay = 2.0
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for attempt in range(max_retries):
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try:
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return self.zep_client.graph.search(
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query=comprehensive_query,
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graph_id=self.graph_id,
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limit=30,
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scope="edges",
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reranker="rrf"
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)
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except Exception as e:
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last_exception = e
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if attempt < max_retries - 1:
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logger.debug(f"Zep边搜索第 {attempt + 1} 次失败: {str(e)[:80]}, 重试中...")
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time.sleep(delay)
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delay *= 2
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else:
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logger.debug(f"Zep边搜索在 {max_retries} 次尝试后仍失败: {e}")
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return None
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return self.zep_client.graph.search(
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query=comprehensive_query,
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graph_id=self.graph_id,
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limit=30,
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scope="edges",
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reranker="rrf"
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)
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@with_zep_retry(max_retries=3, initial_delay=2.0, operation_name="Zep Node Search")
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def search_nodes():
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"""搜索节点（实体摘要）- 带重试机制"""
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max_retries = 3
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last_exception = None
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delay = 2.0
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for attempt in range(max_retries):
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try:
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return self.zep_client.graph.search(
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query=comprehensive_query,
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graph_id=self.graph_id,
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limit=20,
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scope="nodes",
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reranker="rrf"
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)
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except Exception as e:
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last_exception = e
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if attempt < max_retries - 1:
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logger.debug(f"Zep节点搜索第 {attempt + 1} 次失败: {str(e)[:80]}, 重试中...")
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time.sleep(delay)
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delay *= 2
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else:
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logger.debug(f"Zep节点搜索在 {max_retries} 次尝试后仍失败: {e}")
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return None
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return self.zep_client.graph.search(
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query=comprehensive_query,
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graph_id=self.graph_id,
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limit=20,
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scope="nodes",
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reranker="rrf"
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)
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try:
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# 并行执行edges和nodes搜索
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|
|
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@ -225,8 +225,9 @@ class OntologyGenerator:
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return result
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# 传给 LLM 的文本最大长度（5万字）
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MAX_TEXT_LENGTH_FOR_LLM = 50000
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# 传给 LLM 的文本最大长度（2万字）
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# 本体分析只需识别实体/关系类型，不需要完整文本；完整文本仍用于后续图谱构建
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MAX_TEXT_LENGTH_FOR_LLM = 20000
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def _build_user_message(
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self,
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|
|
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|
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@ -12,6 +12,7 @@ from zep_cloud.client import Zep
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from ..config import Config
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from ..utils.logger import get_logger
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from ..utils.zep_paging import fetch_all_nodes, fetch_all_edges
|
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from ..utils.zep_retry import with_zep_retry
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logger = get_logger('mirofish.zep_entity_reader')
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|
|
@ -104,25 +105,11 @@ class ZepEntityReader:
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|||
Returns:
|
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API调用结果
|
||||
"""
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last_exception = None
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||||
delay = initial_delay
|
||||
@with_zep_retry(max_retries=max_retries, initial_delay=initial_delay, operation_name=operation_name)
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def _execute():
|
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return func()
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|
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for attempt in range(max_retries):
|
||||
try:
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return func()
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except Exception as e:
|
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last_exception = e
|
||||
if attempt < max_retries - 1:
|
||||
logger.warning(
|
||||
f"Zep {operation_name} 第 {attempt + 1} 次尝试失败: {str(e)[:100]}, "
|
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f"{delay:.1f}秒后重试..."
|
||||
)
|
||||
time.sleep(delay)
|
||||
delay *= 2 # 指数退避
|
||||
else:
|
||||
logger.error(f"Zep {operation_name} 在 {max_retries} 次尝试后仍失败: {str(e)}")
|
||||
|
||||
raise last_exception
|
||||
return _execute()
|
||||
|
||||
def get_all_nodes(self, graph_id: str) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -1,18 +1,173 @@
|
|||
"""
|
||||
LLM客户端封装
|
||||
统一使用OpenAI格式调用
|
||||
|
||||
支持三层容错机制：
|
||||
1. 截断检测（finish_reason == 'length'）
|
||||
2. JSON修复（尝试关闭未闭合的括号）
|
||||
3. 级联回退（自动切换到 Boost LLM）
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
from typing import Optional, Dict, Any, List
|
||||
from typing import Optional, Dict, Any, List, Tuple
|
||||
from openai import OpenAI
|
||||
|
||||
from ..config import Config
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def repair_truncated_json(text: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
尝试修复被截断的JSON字符串。
|
||||
|
||||
两阶段策略：
|
||||
1. 精确修复：找到最后一个结构完整的安全截断点，关闭括号
|
||||
2. 激进修复：剥离末尾不完整的字符串/值，关闭所有括号
|
||||
|
||||
Args:
|
||||
text: 被截断的JSON字符串
|
||||
|
||||
Returns:
|
||||
修复后的字典，如果无法修复则返回 None
|
||||
"""
|
||||
if not text or not text.strip():
|
||||
return None
|
||||
|
||||
text = text.strip()
|
||||
|
||||
# 清理 markdown 代码块标记
|
||||
text = re.sub(r'^```(?:json)?\s*\n?', '', text, flags=re.IGNORECASE)
|
||||
text = re.sub(r'\n?```\s*$', '', text)
|
||||
text = text.strip()
|
||||
|
||||
# 先尝试直接解析（也许已经是有效JSON）
|
||||
try:
|
||||
return json.loads(text)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
# === 阶段1：精确安全点修复 ===
|
||||
# 扫描结构，找到 }, ] 或顶层逗号作为安全截断点
|
||||
safe_points = []
|
||||
depth_brace = 0
|
||||
depth_bracket = 0
|
||||
in_string = False
|
||||
escape_next = False
|
||||
|
||||
for i, ch in enumerate(text):
|
||||
if escape_next:
|
||||
escape_next = False
|
||||
continue
|
||||
if ch == '\\' and in_string:
|
||||
escape_next = True
|
||||
continue
|
||||
if ch == '"' and not escape_next:
|
||||
in_string = not in_string
|
||||
continue
|
||||
if in_string:
|
||||
continue
|
||||
|
||||
if ch == '{':
|
||||
depth_brace += 1
|
||||
elif ch == '}':
|
||||
depth_brace -= 1
|
||||
safe_points.append(i + 1)
|
||||
elif ch == '[':
|
||||
depth_bracket += 1
|
||||
elif ch == ']':
|
||||
depth_bracket -= 1
|
||||
safe_points.append(i + 1)
|
||||
elif ch == ',' and depth_brace >= 1:
|
||||
safe_points.append(i)
|
||||
|
||||
# 从最后一个安全点开始尝试
|
||||
for point in reversed(safe_points):
|
||||
candidate = text[:point].rstrip().rstrip(',')
|
||||
result = _try_close_and_parse(candidate)
|
||||
if result is not None:
|
||||
logger.info(f"JSON repair (phase 1) succeeded at position {point}/{len(text)}")
|
||||
return result
|
||||
|
||||
# === 阶段2：激进修复 ===
|
||||
# 处理截断发生在字符串值中间的情况（如 "description": "A）
|
||||
# 策略：从末尾向前找到最后一个完整的 }, 然后关闭括号
|
||||
|
||||
# 先尝试关闭可能未闭合的字符串
|
||||
# 用正则找到最后一个看起来像截断字符串值的位置
|
||||
# 模式：找最后一个 "key": "...（未闭合的字符串），截断到前一个完整的 }
|
||||
|
||||
# 逐步从末尾剥离，找到能解析的子串
|
||||
for strip_len in range(1, min(len(text), 500)):
|
||||
candidate = text[:len(text) - strip_len]
|
||||
|
||||
# 尝试在最后一个完整对象/数组闭合符处截断
|
||||
# 找最后一个 } 或 ]
|
||||
last_close = max(candidate.rfind('}'), candidate.rfind(']'))
|
||||
if last_close < 0:
|
||||
continue
|
||||
|
||||
truncated = candidate[:last_close + 1].rstrip().rstrip(',')
|
||||
result = _try_close_and_parse(truncated)
|
||||
if result is not None:
|
||||
logger.info(f"JSON repair (phase 2) succeeded, stripped {strip_len + len(text) - last_close - 1} chars")
|
||||
return result
|
||||
|
||||
logger.warning("JSON repair failed: no recoverable structure found")
|
||||
return None
|
||||
|
||||
|
||||
def _try_close_and_parse(candidate: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
使用栈追踪未闭合的括号，按正确顺序关闭它们，然后尝试解析。
|
||||
|
||||
JSON 关闭顺序很重要：{[{ }]} 而不是 {[{ ]}}
|
||||
|
||||
Returns:
|
||||
解析后的字典，或 None
|
||||
"""
|
||||
stack = [] # 记录开启的括号类型，用于按正确顺序关闭
|
||||
in_str = False
|
||||
esc = False
|
||||
|
||||
for ch in candidate:
|
||||
if esc:
|
||||
esc = False
|
||||
continue
|
||||
if ch == '\\' and in_str:
|
||||
esc = True
|
||||
continue
|
||||
if ch == '"':
|
||||
in_str = not in_str
|
||||
continue
|
||||
if in_str:
|
||||
continue
|
||||
if ch == '{':
|
||||
stack.append('}')
|
||||
elif ch == '[':
|
||||
stack.append(']')
|
||||
elif ch in ('}', ']'):
|
||||
if stack and stack[-1] == ch:
|
||||
stack.pop()
|
||||
|
||||
# 如果字符串未闭合，不尝试此候选
|
||||
if in_str:
|
||||
return None
|
||||
|
||||
# 按栈逆序关闭（LIFO）
|
||||
closing = ''.join(reversed(stack))
|
||||
repaired = candidate + closing
|
||||
|
||||
try:
|
||||
return json.loads(repaired)
|
||||
except json.JSONDecodeError:
|
||||
return None
|
||||
|
||||
|
||||
class LLMClient:
|
||||
"""LLM客户端"""
|
||||
"""LLM客户端，支持级联回退"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
|
|
@ -32,6 +187,54 @@ class LLMClient:
|
|||
base_url=self.base_url
|
||||
)
|
||||
|
||||
# 检查是否有 Boost LLM 配置可用于回退
|
||||
self._has_boost = bool(Config.LLM_BOOST_API_KEY)
|
||||
|
||||
def _chat_raw(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
temperature: float = 0.7,
|
||||
max_tokens: int = 4096,
|
||||
response_format: Optional[Dict] = None,
|
||||
client: Optional[OpenAI] = None,
|
||||
model: Optional[str] = None
|
||||
) -> Tuple[str, str]:
|
||||
"""
|
||||
底层聊天请求，返回 (content, finish_reason) 元组。
|
||||
|
||||
Args:
|
||||
messages: 消息列表
|
||||
temperature: 温度参数
|
||||
max_tokens: 最大token数
|
||||
response_format: 响应格式
|
||||
client: 可选的替代客户端（用于 Boost 回退）
|
||||
model: 可选的替代模型名
|
||||
|
||||
Returns:
|
||||
(content, finish_reason) 元组
|
||||
"""
|
||||
use_client = client or self.client
|
||||
use_model = model or self.model
|
||||
|
||||
kwargs = {
|
||||
"model": use_model,
|
||||
"messages": messages,
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
}
|
||||
|
||||
if response_format:
|
||||
kwargs["response_format"] = response_format
|
||||
|
||||
response = use_client.chat.completions.create(**kwargs)
|
||||
content = response.choices[0].message.content or ""
|
||||
finish_reason = response.choices[0].finish_reason or "unknown"
|
||||
|
||||
# 部分模型（如MiniMax M2.5）会在content中包含<think>思考内容，需要移除
|
||||
content = re.sub(r'<think>[\s\S]*?</think>', '', content).strip()
|
||||
|
||||
return content, finish_reason
|
||||
|
||||
def chat(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
|
|
@ -51,22 +254,24 @@ class LLMClient:
|
|||
Returns:
|
||||
模型响应文本
|
||||
"""
|
||||
kwargs = {
|
||||
"model": self.model,
|
||||
"messages": messages,
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
}
|
||||
|
||||
if response_format:
|
||||
kwargs["response_format"] = response_format
|
||||
|
||||
response = self.client.chat.completions.create(**kwargs)
|
||||
content = response.choices[0].message.content
|
||||
# 部分模型（如MiniMax M2.5）会在content中包含<think>思考内容，需要移除
|
||||
content = re.sub(r'<think>[\s\S]*?</think>', '', content).strip()
|
||||
content, _ = self._chat_raw(
|
||||
messages=messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
response_format=response_format
|
||||
)
|
||||
return content
|
||||
|
||||
def _create_boost_client(self) -> Tuple[OpenAI, str]:
|
||||
"""创建 Boost LLM 客户端（按需创建，不缓存）"""
|
||||
return (
|
||||
OpenAI(
|
||||
api_key=Config.LLM_BOOST_API_KEY,
|
||||
base_url=Config.LLM_BOOST_BASE_URL
|
||||
),
|
||||
Config.LLM_BOOST_MODEL_NAME
|
||||
)
|
||||
|
||||
def chat_json(
|
||||
self,
|
||||
messages: List[Dict[str, str]],
|
||||
|
|
@ -74,7 +279,9 @@ class LLMClient:
|
|||
max_tokens: int = 4096
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
发送聊天请求并返回JSON
|
||||
发送聊天请求并返回JSON，支持三层容错：
|
||||
1. 截断检测 + JSON修复
|
||||
2. 级联回退到 Boost LLM
|
||||
|
||||
Args:
|
||||
messages: 消息列表
|
||||
|
|
@ -84,20 +291,103 @@ class LLMClient:
|
|||
Returns:
|
||||
解析后的JSON对象
|
||||
"""
|
||||
response = self.chat(
|
||||
messages=messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
response_format={"type": "json_object"}
|
||||
)
|
||||
# 清理markdown代码块标记
|
||||
cleaned_response = response.strip()
|
||||
cleaned_response = re.sub(r'^```(?:json)?\s*\n?', '', cleaned_response, flags=re.IGNORECASE)
|
||||
cleaned_response = re.sub(r'\n?```\s*$', '', cleaned_response)
|
||||
cleaned_response = cleaned_response.strip()
|
||||
# === 第一层：尝试主 LLM ===
|
||||
try:
|
||||
content, finish_reason = self._chat_raw(
|
||||
messages=messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
response_format={"type": "json_object"}
|
||||
)
|
||||
|
||||
# 清理 markdown 代码块标记
|
||||
cleaned = self._clean_json_response(content)
|
||||
|
||||
# 正常完成 → 尝试解析
|
||||
if finish_reason == "stop":
|
||||
try:
|
||||
return json.loads(cleaned)
|
||||
except json.JSONDecodeError:
|
||||
logger.warning("Primary LLM returned invalid JSON despite finish_reason=stop, attempting repair")
|
||||
repaired = repair_truncated_json(content)
|
||||
if repaired is not None:
|
||||
return repaired
|
||||
# 回退到 Boost
|
||||
|
||||
# 截断 → 尝试修复
|
||||
elif finish_reason == "length":
|
||||
logger.warning(f"Primary LLM response truncated (finish_reason=length, {len(content)} chars)")
|
||||
repaired = repair_truncated_json(content)
|
||||
if repaired is not None:
|
||||
logger.info("Truncated JSON repaired successfully from primary LLM")
|
||||
return repaired
|
||||
logger.warning("JSON repair failed, falling back to Boost LLM")
|
||||
|
||||
else:
|
||||
logger.warning(f"Unexpected finish_reason='{finish_reason}', attempting parse")
|
||||
try:
|
||||
return json.loads(cleaned)
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
|
||||
except Exception as e:
|
||||
logger.warning(f"Primary LLM failed: {type(e).__name__}: {e}")
|
||||
|
||||
# === 第二层：回退到 Boost LLM ===
|
||||
if not self._has_boost:
|
||||
raise ValueError(
|
||||
f"Primary LLM failed and no Boost LLM configured. "
|
||||
f"Set LLM_BOOST_API_KEY, LLM_BOOST_BASE_URL, LLM_BOOST_MODEL_NAME in .env"
|
||||
)
|
||||
|
||||
logger.info(f"Falling back to Boost LLM: {Config.LLM_BOOST_BASE_URL} / {Config.LLM_BOOST_MODEL_NAME}")
|
||||
|
||||
try:
|
||||
return json.loads(cleaned_response)
|
||||
except json.JSONDecodeError:
|
||||
raise ValueError(f"LLM返回的JSON格式无效: {cleaned_response}")
|
||||
boost_client, boost_model = self._create_boost_client()
|
||||
content, finish_reason = self._chat_raw(
|
||||
messages=messages,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
response_format={"type": "json_object"},
|
||||
client=boost_client,
|
||||
model=boost_model
|
||||
)
|
||||
|
||||
cleaned = self._clean_json_response(content)
|
||||
|
||||
if finish_reason == "stop":
|
||||
try:
|
||||
return json.loads(cleaned)
|
||||
except json.JSONDecodeError:
|
||||
repaired = repair_truncated_json(content)
|
||||
if repaired is not None:
|
||||
logger.info("Boost LLM JSON repaired successfully")
|
||||
return repaired
|
||||
raise ValueError(f"Boost LLM returned invalid JSON: {cleaned[:200]}...")
|
||||
|
||||
elif finish_reason == "length":
|
||||
logger.warning(f"Boost LLM also truncated ({len(content)} chars), attempting repair")
|
||||
repaired = repair_truncated_json(content)
|
||||
if repaired is not None:
|
||||
logger.info("Truncated JSON from Boost LLM repaired successfully")
|
||||
return repaired
|
||||
raise ValueError(f"Boost LLM response truncated and repair failed: {cleaned[:200]}...")
|
||||
|
||||
else:
|
||||
try:
|
||||
return json.loads(cleaned)
|
||||
except json.JSONDecodeError:
|
||||
raise ValueError(f"Boost LLM returned unparseable response: {cleaned[:200]}...")
|
||||
|
||||
except ValueError:
|
||||
raise
|
||||
except Exception as e:
|
||||
raise ValueError(f"Both primary and Boost LLM failed. Boost error: {type(e).__name__}: {e}")
|
||||
|
||||
@staticmethod
|
||||
def _clean_json_response(content: str) -> str:
|
||||
"""清理 LLM 响应中的 markdown 代码块标记"""
|
||||
cleaned = content.strip()
|
||||
cleaned = re.sub(r'^```(?:json)?\s*\n?', '', cleaned, flags=re.IGNORECASE)
|
||||
cleaned = re.sub(r'\n?```\s*$', '', cleaned)
|
||||
return cleaned.strip()
|
||||
|
|
|
|||
|
|
@ -10,7 +10,6 @@ import time
|
|||
from collections.abc import Callable
|
||||
from typing import Any
|
||||
|
||||
from zep_cloud import InternalServerError
|
||||
from zep_cloud.client import Zep
|
||||
|
||||
from .logger import get_logger
|
||||
|
|
@ -23,6 +22,8 @@ _DEFAULT_MAX_RETRIES = 3
|
|||
_DEFAULT_RETRY_DELAY = 2.0 # seconds, doubles each retry
|
||||
|
||||
|
||||
from .zep_retry import with_zep_retry
|
||||
|
||||
def _fetch_page_with_retry(
|
||||
api_call: Callable[..., list[Any]],
|
||||
*args: Any,
|
||||
|
|
@ -32,28 +33,11 @@ def _fetch_page_with_retry(
|
|||
**kwargs: Any,
|
||||
) -> list[Any]:
|
||||
"""单页请求，失败时指数退避重试。仅重试网络/IO类瞬态错误。"""
|
||||
if max_retries < 1:
|
||||
raise ValueError("max_retries must be >= 1")
|
||||
@with_zep_retry(max_retries=max_retries, initial_delay=retry_delay, operation_name=f"Zep {page_description}")
|
||||
def execute_call():
|
||||
return api_call(*args, **kwargs)
|
||||
|
||||
last_exception: Exception | None = None
|
||||
delay = retry_delay
|
||||
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
return api_call(*args, **kwargs)
|
||||
except (ConnectionError, TimeoutError, OSError, InternalServerError) as e:
|
||||
last_exception = e
|
||||
if attempt < max_retries - 1:
|
||||
logger.warning(
|
||||
f"Zep {page_description} attempt {attempt + 1} failed: {str(e)[:100]}, retrying in {delay:.1f}s..."
|
||||
)
|
||||
time.sleep(delay)
|
||||
delay *= 2
|
||||
else:
|
||||
logger.error(f"Zep {page_description} failed after {max_retries} attempts: {str(e)}")
|
||||
|
||||
assert last_exception is not None
|
||||
raise last_exception
|
||||
return execute_call()
|
||||
|
||||
|
||||
def fetch_all_nodes(
|
||||
|
|
|
|||
|
|
@ -0,0 +1,95 @@
|
|||
"""
|
||||
Zep API 速率限制与响应缓存
|
||||
|
||||
为 Zep Cloud FREE 计划提供保护：
|
||||
- 响应缓存：graph data 请求在 TTL 内返回缓存结果，避免重复调用 Zep API
|
||||
- 可通过 .env 配置参数，升级付费计划后可放宽限制
|
||||
"""
|
||||
|
||||
import time
|
||||
import threading
|
||||
from typing import Any, Dict, Optional, Tuple
|
||||
|
||||
from .logger import get_logger
|
||||
|
||||
logger = get_logger('mirofish.zep_cache')
|
||||
|
||||
|
||||
class ZepResponseCache:
|
||||
"""
|
||||
线程安全的 Zep API 响应缓存。
|
||||
|
||||
缓存 graph data 的成功响应，在 TTL 内直接返回缓存数据，
|
||||
避免频繁调用 Zep API 导致 429 错误。
|
||||
"""
|
||||
|
||||
def __init__(self, default_ttl: int = 30):
|
||||
"""
|
||||
Args:
|
||||
default_ttl: 默认缓存生存时间（秒）。0 表示不缓存。
|
||||
"""
|
||||
self._cache: Dict[str, Tuple[float, Any]] = {} # key -> (expire_time, data)
|
||||
self._lock = threading.Lock()
|
||||
self._default_ttl = default_ttl
|
||||
|
||||
@property
|
||||
def ttl(self) -> int:
|
||||
return self._default_ttl
|
||||
|
||||
@ttl.setter
|
||||
def ttl(self, value: int):
|
||||
self._default_ttl = max(0, value)
|
||||
|
||||
def get(self, key: str) -> Optional[Any]:
|
||||
"""
|
||||
获取缓存数据。如果缓存存在且未过期，返回数据；否则返回 None。
|
||||
"""
|
||||
with self._lock:
|
||||
entry = self._cache.get(key)
|
||||
if entry is None:
|
||||
return None
|
||||
|
||||
expire_time, data = entry
|
||||
if time.time() > expire_time:
|
||||
# 缓存已过期
|
||||
del self._cache[key]
|
||||
logger.debug(f"Cache expired for key: {key}")
|
||||
return None
|
||||
|
||||
remaining = int(expire_time - time.time())
|
||||
logger.debug(f"Cache hit for key: {key} (expires in {remaining}s)")
|
||||
return data
|
||||
|
||||
def set(self, key: str, data: Any, ttl: Optional[int] = None):
|
||||
"""
|
||||
设置缓存数据。
|
||||
|
||||
Args:
|
||||
key: 缓存键
|
||||
data: 要缓存的数据
|
||||
ttl: 缓存生存时间（秒）。None 表示使用默认 TTL。
|
||||
"""
|
||||
effective_ttl = ttl if ttl is not None else self._default_ttl
|
||||
if effective_ttl <= 0:
|
||||
return # 不缓存
|
||||
|
||||
with self._lock:
|
||||
self._cache[key] = (time.time() + effective_ttl, data)
|
||||
logger.debug(f"Cache set for key: {key} (TTL={effective_ttl}s)")
|
||||
|
||||
def invalidate(self, key: str):
|
||||
"""删除指定缓存。"""
|
||||
with self._lock:
|
||||
if key in self._cache:
|
||||
del self._cache[key]
|
||||
logger.debug(f"Cache invalidated for key: {key}")
|
||||
|
||||
def clear(self):
|
||||
"""清除所有缓存。"""
|
||||
with self._lock:
|
||||
self._cache.clear()
|
||||
logger.debug("Cache cleared")
|
||||
|
||||
|
||||
# 全局缓存实例（在模块加载时创建，TTL 在 app 初始化时通过 Config 设置）
|
||||
graph_data_cache = ZepResponseCache(default_ttl=30)
|
||||
|
|
@ -0,0 +1,84 @@
|
|||
import time
|
||||
import functools
|
||||
from typing import Callable, Any, TypeVar, cast
|
||||
|
||||
from zep_cloud.core.api_error import ApiError
|
||||
from zep_cloud import InternalServerError
|
||||
|
||||
from .logger import get_logger
|
||||
from .locale import t
|
||||
|
||||
logger = get_logger('mirofish.zep_retry')
|
||||
|
||||
T = TypeVar('T', bound=Callable[..., Any])
|
||||
|
||||
|
||||
class ZepQuotaExceededError(Exception):
|
||||
"""Raised when Zep Account is over the episode usage limit (403 Quota limit)."""
|
||||
pass
|
||||
|
||||
|
||||
def with_zep_retry(
|
||||
max_retries: int = 3,
|
||||
initial_delay: float = 2.0,
|
||||
operation_name: str = "Zep API Call"
|
||||
) -> Callable[[T], T]:
|
||||
"""
|
||||
Decorator to wrap Zep API calls with retry logic.
|
||||
- Handles 429 Rate Limit by respecting 'Retry-After' headers.
|
||||
- Handles 403 Quota Limit by failing fast with a clear exception.
|
||||
- Retries other transient errors (ConnectionError, TimeoutError, etc) with exponential backoff.
|
||||
"""
|
||||
def decorator(func: T) -> T:
|
||||
@functools.wraps(func)
|
||||
def wrapper(*args: Any, **kwargs: Any) -> Any:
|
||||
last_exception = None
|
||||
delay = initial_delay
|
||||
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
return func(*args, **kwargs)
|
||||
except ApiError as e:
|
||||
# 403 Forbidden: Account is over the episode usage limit
|
||||
if e.status_code == 403 and hasattr(e, 'body') and 'forbidden: Account is over the episode usage limit' in str(e.body):
|
||||
logger.error(f"{operation_name} Failed: Zep Free Plan quota exceeded (403).")
|
||||
error_msg = t("api.zepQuotaExceeded")
|
||||
if not error_msg or error_msg == "api.zepQuotaExceeded":
|
||||
error_msg = "Zep Free Plan Quota Exceeded: Your account has reached the maximum allowed episode usage. Please upgrade your Zep plan or clear old data."
|
||||
raise ZepQuotaExceededError(error_msg) from e
|
||||
|
||||
# 429 Rate limit
|
||||
if e.status_code == 429:
|
||||
retry_after = 60 # Default fallback
|
||||
if hasattr(e, 'headers') and e.headers:
|
||||
retry_after = int(e.headers.get('retry-after', retry_after))
|
||||
elif hasattr(e, 'body') and 'retry-after' in str(e.body):
|
||||
retry_after = 60
|
||||
|
||||
logger.warning(
|
||||
f"Zep rate limit hit on {operation_name}, waiting {retry_after}s before retry (attempt {attempt + 1}/{max_retries})"
|
||||
)
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(retry_after + 1)
|
||||
continue
|
||||
else:
|
||||
logger.error(f"{operation_name} rate limited after {max_retries} attempts")
|
||||
raise
|
||||
|
||||
# Other ApiErrors should not be retried unless we want to, but normally we fail fast
|
||||
raise
|
||||
except (ConnectionError, TimeoutError, OSError, InternalServerError) as e:
|
||||
last_exception = e
|
||||
if attempt < max_retries - 1:
|
||||
logger.warning(
|
||||
f"{operation_name} attempt {attempt + 1} failed: {str(e)[:100]}, retrying in {delay:.1f}s..."
|
||||
)
|
||||
time.sleep(delay)
|
||||
delay *= 2
|
||||
else:
|
||||
logger.error(f"{operation_name} failed after {max_retries} attempts: {str(e)}")
|
||||
|
||||
if last_exception:
|
||||
raise last_exception
|
||||
return cast(T, wrapper)
|
||||
return decorator
|
||||
|
|
@ -51,5 +51,13 @@ dev = [
|
|||
"pytest-asyncio>=0.23.0",
|
||||
]
|
||||
|
||||
[tool.uv]
|
||||
override-dependencies = [
|
||||
"pillow>=11.0.0",
|
||||
"tiktoken>=0.8.0",
|
||||
]
|
||||
|
||||
[tool.uv.sources]
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["app"]
|
||||
|
|
|
|||
171
backend/uv.lock
171
backend/uv.lock
|
|
@ -6,6 +6,12 @@ resolution-markers = [
|
|||
"python_full_version < '3.12'",
|
||||
]
|
||||
|
||||
[manifest]
|
||||
overrides = [
|
||||
{ name = "pillow", specifier = ">=11.0.0" },
|
||||
{ name = "tiktoken", specifier = ">=0.8.0" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "aiofiles"
|
||||
version = "25.1.0"
|
||||
|
|
@ -1481,32 +1487,89 @@ wheels = [
|
|||
|
||||
[[package]]
|
||||
name = "pillow"
|
||||
version = "10.3.0"
|
||||
version = "12.2.0"
|
||||
source = { registry = "https://pypi.org/simple" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/ef/43/c50c17c5f7d438e836c169e343695534c38c77f60e7c90389bd77981bc21/pillow-10.3.0.tar.gz", hash = "sha256:9d2455fbf44c914840c793e89aa82d0e1763a14253a000743719ae5946814b2d", size = 46572854, upload-time = "2024-04-01T12:19:40.048Z" }
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||||
sdist = { url = "https://files.pythonhosted.org/packages/8c/21/c2bcdd5906101a30244eaffc1b6e6ce71a31bd0742a01eb89e660ebfac2d/pillow-12.2.0.tar.gz", hash = "sha256:a830b1a40919539d07806aa58e1b114df53ddd43213d9c8b75847eee6c0182b5", size = 46987819, upload-time = "2026-04-01T14:46:17.687Z" }
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||||
wheels = [
|
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[[package]]
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||||
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||||
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||||
{ url = "https://files.pythonhosted.org/packages/05/df/4f80030d44682235bdaecd7346c90f67ae87ec8f3df4a3442cb53834f7e4/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:06a9f4f49884139013b138920a4c393aa6556b2f8f536345f11819389c703ebb", size = 1151875, upload-time = "2025-10-06T20:22:14.559Z" },
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||||
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||||
{ url = "https://files.pythonhosted.org/packages/78/a7/f8ead382fce0243cb625c4f266e66c27f65ae65ee9e77f59ea1653b6d730/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0ee8f9ae00c41770b5f9b0bb1235474768884ae157de3beb5439ca0fd70f3e25", size = 1253794, upload-time = "2025-10-06T20:22:16.624Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/93/e0/6cc82a562bc6365785a3ff0af27a2a092d57c47d7a81d9e2295d8c36f011/tiktoken-0.12.0-cp313-cp313t-win_amd64.whl", hash = "sha256:dc2dd125a62cb2b3d858484d6c614d136b5b848976794edfb63688d539b8b93f", size = 878777, upload-time = "2025-10-06T20:22:18.036Z" },
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{ url = "https://files.pythonhosted.org/packages/72/05/3abc1db5d2c9aadc4d2c76fa5640134e475e58d9fbb82b5c535dc0de9b01/tiktoken-0.12.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a90388128df3b3abeb2bfd1895b0681412a8d7dc644142519e6f0a97c2111646", size = 1050188, upload-time = "2025-10-06T20:22:19.563Z" },
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{ url = "https://files.pythonhosted.org/packages/e3/7b/50c2f060412202d6c95f32b20755c7a6273543b125c0985d6fa9465105af/tiktoken-0.12.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:da900aa0ad52247d8794e307d6446bd3cdea8e192769b56276695d34d2c9aa88", size = 993978, upload-time = "2025-10-06T20:22:20.702Z" },
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{ url = "https://files.pythonhosted.org/packages/14/27/bf795595a2b897e271771cd31cb847d479073497344c637966bdf2853da1/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_aarch64.whl", hash = "sha256:285ba9d73ea0d6171e7f9407039a290ca77efcdb026be7769dccc01d2c8d7fff", size = 1129271, upload-time = "2025-10-06T20:22:22.06Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl", hash = "sha256:d186a5c60c6a0213f04a7a802264083dea1bbde92a2d4c7069e1a56630aef830", size = 1151216, upload-time = "2025-10-06T20:22:23.085Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/75/0d/881866647b8d1be4d67cb24e50d0c26f9f807f994aa1510cb9ba2fe5f612/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:604831189bd05480f2b885ecd2d1986dc7686f609de48208ebbbddeea071fc0b", size = 1194860, upload-time = "2025-10-06T20:22:24.602Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/b3/1e/b651ec3059474dab649b8d5b69f5c65cd8fcd8918568c1935bd4136c9392/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:8f317e8530bb3a222547b85a58583238c8f74fd7a7408305f9f63246d1a0958b", size = 1254567, upload-time = "2025-10-06T20:22:25.671Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/80/57/ce64fd16ac390fafde001268c364d559447ba09b509181b2808622420eec/tiktoken-0.12.0-cp314-cp314-win_amd64.whl", hash = "sha256:399c3dd672a6406719d84442299a490420b458c44d3ae65516302a99675888f3", size = 921067, upload-time = "2025-10-06T20:22:26.753Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/ac/a4/72eed53e8976a099539cdd5eb36f241987212c29629d0a52c305173e0a68/tiktoken-0.12.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c2c714c72bc00a38ca969dae79e8266ddec999c7ceccd603cc4f0d04ccd76365", size = 1050473, upload-time = "2025-10-06T20:22:27.775Z" },
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||||
{ url = "https://files.pythonhosted.org/packages/e6/d7/0110b8f54c008466b19672c615f2168896b83706a6611ba6e47313dbc6e9/tiktoken-0.12.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:cbb9a3ba275165a2cb0f9a83f5d7025afe6b9d0ab01a22b50f0e74fee2ad253e", size = 993855, upload-time = "2025-10-06T20:22:28.799Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/5f/77/4f268c41a3957c418b084dd576ea2fad2e95da0d8e1ab705372892c2ca22/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:dfdfaa5ffff8993a3af94d1125870b1d27aed7cb97aa7eb8c1cefdbc87dbee63", size = 1129022, upload-time = "2025-10-06T20:22:29.981Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/4e/2b/fc46c90fe5028bd094cd6ee25a7db321cb91d45dc87531e2bdbb26b4867a/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:584c3ad3d0c74f5269906eb8a659c8bfc6144a52895d9261cdaf90a0ae5f4de0", size = 1150736, upload-time = "2025-10-06T20:22:30.996Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/28/c0/3c7a39ff68022ddfd7d93f3337ad90389a342f761c4d71de99a3ccc57857/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:54c891b416a0e36b8e2045b12b33dd66fb34a4fe7965565f1b482da50da3e86a", size = 1194908, upload-time = "2025-10-06T20:22:32.073Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/ab/0d/c1ad6f4016a3968c048545f5d9b8ffebf577774b2ede3e2e352553b685fe/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5edb8743b88d5be814b1a8a8854494719080c28faaa1ccbef02e87354fe71ef0", size = 1253706, upload-time = "2025-10-06T20:22:33.385Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/af/df/c7891ef9d2712ad774777271d39fdef63941ffba0a9d59b7ad1fd2765e57/tiktoken-0.12.0-cp314-cp314t-win_amd64.whl", hash = "sha256:f61c0aea5565ac82e2ec50a05e02a6c44734e91b51c10510b084ea1b8e633a71", size = 920667, upload-time = "2025-10-06T20:22:34.444Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
|
|
|||
|
|
@ -1435,7 +1435,6 @@
|
|||
"resolved": "https://registry.npmjs.org/d3-selection/-/d3-selection-3.0.0.tgz",
|
||||
"integrity": "sha512-fmTRWbNMmsmWq6xJV8D19U/gw/bwrHfNXxrIN+HfZgnzqTHp9jOmKMhsTUjXOJnZOdZY9Q28y4yebKzqDKlxlQ==",
|
||||
"license": "ISC",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
}
|
||||
|
|
@ -1913,7 +1912,6 @@
|
|||
"integrity": "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=12"
|
||||
},
|
||||
|
|
@ -2053,7 +2051,6 @@
|
|||
"integrity": "sha512-ITcnkFeR3+fI8P1wMgItjGrR10170d8auB4EpMLPqmx6uxElH3a/hHGQabSHKdqd4FXWO1nFIp9rRn7JQ34ACQ==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"esbuild": "^0.25.0",
|
||||
"fdir": "^6.5.0",
|
||||
|
|
@ -2128,7 +2125,6 @@
|
|||
"resolved": "https://registry.npmjs.org/vue/-/vue-3.5.25.tgz",
|
||||
"integrity": "sha512-YLVdgv2K13WJ6n+kD5owehKtEXwdwXuj2TTyJMsO7pSeKw2bfRNZGjhB7YzrpbMYj5b5QsUebHpOqR3R3ziy/g==",
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"@vue/compiler-dom": "3.5.25",
|
||||
"@vue/compiler-sfc": "3.5.25",
|
||||
|
|
|
|||
|
|
@ -68,3 +68,14 @@ export function getProject(projectId) {
|
|||
method: 'get'
|
||||
})
|
||||
}
|
||||
|
||||
/**
|
||||
* 获取图谱轮询配置（速率限制参数）
|
||||
* @returns {Promise} { poll_interval, cache_ttl, rate_limit, rate_limit_window }
|
||||
*/
|
||||
export function getGraphConfig() {
|
||||
return service({
|
||||
url: '/api/graph/config',
|
||||
method: 'get'
|
||||
})
|
||||
}
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@
|
|||
</div>
|
||||
<div class="step-status">
|
||||
<span v-if="currentPhase > 0" class="badge success">{{ $t('step1.ontologyCompleted') }}</span>
|
||||
<span v-else-if="errorMsg && currentPhase === 0" class="badge error">FAILED</span>
|
||||
<span v-else-if="currentPhase === 0" class="badge processing">{{ $t('step1.ontologyGenerating') }}</span>
|
||||
<span v-else class="badge pending">{{ $t('step1.ontologyPending') }}</span>
|
||||
</div>
|
||||
|
|
@ -22,11 +23,17 @@
|
|||
</p>
|
||||
|
||||
<!-- Loading / Progress -->
|
||||
<div v-if="currentPhase === 0 && ontologyProgress" class="progress-section">
|
||||
<div v-if="currentPhase === 0 && ontologyProgress && !errorMsg" class="progress-section">
|
||||
<div class="spinner-sm"></div>
|
||||
<span>{{ ontologyProgress.message || $t('step1.analyzingDocs') }}</span>
|
||||
</div>
|
||||
|
||||
<!-- Error Alert for Phase 0 -->
|
||||
<div v-if="currentPhase === 0 && errorMsg" class="error-alert">
|
||||
<span class="error-icon">⚠️</span>
|
||||
<span class="error-text">{{ errorMsg }}</span>
|
||||
</div>
|
||||
|
||||
<!-- Detail Overlay -->
|
||||
<div v-if="selectedOntologyItem" class="ontology-detail-overlay">
|
||||
<div class="detail-header">
|
||||
|
|
@ -114,6 +121,7 @@
|
|||
</div>
|
||||
<div class="step-status">
|
||||
<span v-if="currentPhase > 1" class="badge success">{{ $t('step1.ontologyCompleted') }}</span>
|
||||
<span v-else-if="errorMsg && currentPhase === 1" class="badge error">FAILED</span>
|
||||
<span v-else-if="currentPhase === 1" class="badge processing">{{ buildProgress?.progress || 0 }}%</span>
|
||||
<span v-else class="badge pending">{{ $t('step1.ontologyPending') }}</span>
|
||||
</div>
|
||||
|
|
@ -125,6 +133,12 @@
|
|||
{{ $t('step1.graphRagDesc') }}
|
||||
</p>
|
||||
|
||||
<!-- Error Alert for Phase 1 -->
|
||||
<div v-if="currentPhase === 1 && errorMsg" class="error-alert" style="margin-bottom: 16px;">
|
||||
<span class="error-icon">⚠️</span>
|
||||
<span class="error-text">{{ errorMsg }}</span>
|
||||
</div>
|
||||
|
||||
<!-- Stats Cards -->
|
||||
<div class="stats-grid">
|
||||
<div class="stat-card">
|
||||
|
|
@ -201,7 +215,8 @@ const props = defineProps({
|
|||
ontologyProgress: Object,
|
||||
buildProgress: Object,
|
||||
graphData: Object,
|
||||
systemLogs: { type: Array, default: () => [] }
|
||||
systemLogs: { type: Array, default: () => [] },
|
||||
errorMsg: { type: String, default: '' }
|
||||
})
|
||||
|
||||
defineEmits(['next-step'])
|
||||
|
|
@ -349,6 +364,7 @@ watch(() => props.systemLogs.length, () => {
|
|||
.badge.processing { background: #FF5722; color: #FFF; }
|
||||
.badge.accent { background: #FF5722; color: #FFF; }
|
||||
.badge.pending { background: #F5F5F5; color: #999; }
|
||||
.badge.error { background: #FFEBEE; color: #D32F2F; }
|
||||
|
||||
.api-note {
|
||||
font-family: 'JetBrains Mono', monospace;
|
||||
|
|
@ -364,6 +380,28 @@ watch(() => props.systemLogs.length, () => {
|
|||
margin-bottom: 16px;
|
||||
}
|
||||
|
||||
.error-alert {
|
||||
display: flex;
|
||||
align-items: flex-start;
|
||||
gap: 8px;
|
||||
background: #FFF5F5;
|
||||
border: 1px solid #FFCDD2;
|
||||
border-radius: 6px;
|
||||
padding: 12px;
|
||||
margin-top: 8px;
|
||||
}
|
||||
|
||||
.error-icon {
|
||||
font-size: 14px;
|
||||
}
|
||||
|
||||
.error-text {
|
||||
font-size: 12px;
|
||||
color: #C62828;
|
||||
line-height: 1.4;
|
||||
word-break: break-word;
|
||||
}
|
||||
|
||||
/* Step 01 Tags */
|
||||
.tags-container {
|
||||
margin-top: 12px;
|
||||
|
|
|
|||
|
|
@ -59,6 +59,7 @@
|
|||
:buildProgress="buildProgress"
|
||||
:graphData="graphData"
|
||||
:systemLogs="systemLogs"
|
||||
:errorMsg="error"
|
||||
@next-step="handleNextStep"
|
||||
/>
|
||||
<!-- Step 2: 环境搭建 -->
|
||||
|
|
@ -83,7 +84,7 @@ import { useI18n } from 'vue-i18n'
|
|||
import GraphPanel from '../components/GraphPanel.vue'
|
||||
import Step1GraphBuild from '../components/Step1GraphBuild.vue'
|
||||
import Step2EnvSetup from '../components/Step2EnvSetup.vue'
|
||||
import { generateOntology, getProject, buildGraph, getTaskStatus, getGraphData } from '../api/graph'
|
||||
import { generateOntology, getProject, buildGraph, getTaskStatus, getGraphData, getGraphConfig } from '../api/graph'
|
||||
import { getPendingUpload, clearPendingUpload } from '../store/pendingUpload'
|
||||
import LanguageSwitcher from '../components/LanguageSwitcher.vue'
|
||||
|
||||
|
|
@ -114,6 +115,9 @@ const systemLogs = ref([])
|
|||
let pollTimer = null
|
||||
let graphPollTimer = null
|
||||
|
||||
// Graph polling config (fetched from backend)
|
||||
const graphPollInterval = ref(0) // 0 = manual only
|
||||
|
||||
// --- Computed Layout Styles ---
|
||||
const leftPanelStyle = computed(() => {
|
||||
if (viewMode.value === 'graph') return { width: '100%', opacity: 1, transform: 'translateX(0)' }
|
||||
|
|
@ -184,6 +188,19 @@ const handleGoBack = () => {
|
|||
|
||||
const initProject = async () => {
|
||||
addLog('Project view initialized.')
|
||||
|
||||
// Fetch graph polling config from backend
|
||||
try {
|
||||
const configRes = await getGraphConfig()
|
||||
if (configRes.success && configRes.data) {
|
||||
graphPollInterval.value = configRes.data.poll_interval || 0
|
||||
addLog(`Graph config loaded: poll_interval=${graphPollInterval.value}s, cache_ttl=${configRes.data.cache_ttl}s`)
|
||||
}
|
||||
} catch (err) {
|
||||
addLog('Could not load graph config, defaulting to manual refresh only.')
|
||||
graphPollInterval.value = 0
|
||||
}
|
||||
|
||||
if (currentProjectId.value === 'new') {
|
||||
await handleNewProject()
|
||||
} else {
|
||||
|
|
@ -295,9 +312,17 @@ const startBuildGraph = async () => {
|
|||
}
|
||||
|
||||
const startGraphPolling = () => {
|
||||
addLog('Started polling for graph data...')
|
||||
// Always do one immediate fetch
|
||||
fetchGraphData()
|
||||
graphPollTimer = setInterval(fetchGraphData, 10000)
|
||||
|
||||
// Only set up automatic polling if poll_interval > 0 (paid plan)
|
||||
if (graphPollInterval.value > 0) {
|
||||
const intervalMs = graphPollInterval.value * 1000
|
||||
addLog(`Started automatic graph polling (every ${graphPollInterval.value}s)...`)
|
||||
graphPollTimer = setInterval(fetchGraphData, intervalMs)
|
||||
} else {
|
||||
addLog('Automatic graph polling disabled (FREE plan). Use manual refresh.')
|
||||
}
|
||||
}
|
||||
|
||||
const fetchGraphData = async () => {
|
||||
|
|
|
|||
|
|
@ -414,7 +414,7 @@
|
|||
<script setup>
|
||||
import { ref, computed, onMounted, onUnmounted, watch, nextTick } from 'vue'
|
||||
import { useRoute, useRouter } from 'vue-router'
|
||||
import { generateOntology, getProject, buildGraph, getTaskStatus, getGraphData } from '../api/graph'
|
||||
import { generateOntology, getProject, buildGraph, getTaskStatus, getGraphData, getGraphConfig } from '../api/graph'
|
||||
import { getPendingUpload, clearPendingUpload } from '../store/pendingUpload'
|
||||
import * as d3 from 'd3'
|
||||
|
||||
|
|
@ -443,6 +443,9 @@ const graphSvg = ref(null)
|
|||
// 轮询定时器
|
||||
let pollTimer = null
|
||||
|
||||
// Graph polling config (fetched from backend)
|
||||
const graphPollInterval = ref(0) // 0 = manual only
|
||||
|
||||
// 计算属性
|
||||
const statusClass = computed(() => {
|
||||
if (error.value) return 'error'
|
||||
|
|
@ -554,6 +557,16 @@ const getPhaseStatusText = (phase) => {
|
|||
const initProject = async () => {
|
||||
const paramProjectId = route.params.projectId
|
||||
|
||||
// Fetch graph polling config from backend
|
||||
try {
|
||||
const configRes = await getGraphConfig()
|
||||
if (configRes.success && configRes.data) {
|
||||
graphPollInterval.value = configRes.data.poll_interval || 0
|
||||
}
|
||||
} catch (err) {
|
||||
graphPollInterval.value = 0
|
||||
}
|
||||
|
||||
if (paramProjectId === 'new') {
|
||||
// 新建项目：从 store 获取待上传的数据
|
||||
await handleNewProject()
|
||||
|
|
@ -715,10 +728,13 @@ const startGraphPolling = () => {
|
|||
// 立即获取一次
|
||||
fetchGraphData()
|
||||
|
||||
// 每 10 秒自动获取一次图谱数据
|
||||
graphPollTimer = setInterval(async () => {
|
||||
await fetchGraphData()
|
||||
}, 10000)
|
||||
// Only set up automatic polling if poll_interval > 0 (paid plan)
|
||||
if (graphPollInterval.value > 0) {
|
||||
const intervalMs = graphPollInterval.value * 1000
|
||||
graphPollTimer = setInterval(async () => {
|
||||
await fetchGraphData()
|
||||
}, intervalMs)
|
||||
}
|
||||
}
|
||||
|
||||
// 手动刷新图谱
|
||||
|
|
|
|||
|
|
@ -73,7 +73,7 @@ import { ref, computed, onMounted, onUnmounted, watch } from 'vue'
|
|||
import { useRoute, useRouter } from 'vue-router'
|
||||
import GraphPanel from '../components/GraphPanel.vue'
|
||||
import Step3Simulation from '../components/Step3Simulation.vue'
|
||||
import { getProject, getGraphData } from '../api/graph'
|
||||
import { getProject, getGraphData, getGraphConfig } from '../api/graph'
|
||||
import { getSimulation, getSimulationConfig, stopSimulation, closeSimulationEnv, getEnvStatus } from '../api/simulation'
|
||||
import LanguageSwitcher from '../components/LanguageSwitcher.vue'
|
||||
import { useI18n } from 'vue-i18n'
|
||||
|
|
@ -100,6 +100,7 @@ const graphData = ref(null)
|
|||
const graphLoading = ref(false)
|
||||
const systemLogs = ref([])
|
||||
const currentStatus = ref('processing') // processing | completed | error
|
||||
const graphPollInterval = ref(0) // 0 = manual only
|
||||
|
||||
// --- Computed Layout Styles ---
|
||||
const leftPanelStyle = computed(() => {
|
||||
|
|
@ -208,6 +209,16 @@ const loadSimulationData = async () => {
|
|||
try {
|
||||
addLog(t('log.loadingSimData', { id: currentSimulationId.value }))
|
||||
|
||||
// Fetch graph polling config from backend
|
||||
try {
|
||||
const configRes = await getGraphConfig()
|
||||
if (configRes.success && configRes.data) {
|
||||
graphPollInterval.value = configRes.data.poll_interval || 0
|
||||
}
|
||||
} catch (err) {
|
||||
graphPollInterval.value = 0
|
||||
}
|
||||
|
||||
// 获取 simulation 信息
|
||||
const simRes = await getSimulation(currentSimulationId.value)
|
||||
if (simRes.success && simRes.data) {
|
||||
|
|
@ -278,9 +289,15 @@ let graphRefreshTimer = null
|
|||
|
||||
const startGraphRefresh = () => {
|
||||
if (graphRefreshTimer) return
|
||||
addLog(t('log.graphRealtimeRefreshStart'))
|
||||
// 立即刷新一次，然后每30秒刷新
|
||||
graphRefreshTimer = setInterval(refreshGraph, 30000)
|
||||
|
||||
// Only set up automatic refresh if poll_interval > 0 (paid plan)
|
||||
if (graphPollInterval.value > 0) {
|
||||
const intervalMs = Math.max(graphPollInterval.value * 1000, 30000) // At least 30s during simulation
|
||||
addLog(t('log.graphRealtimeRefreshStart'))
|
||||
graphRefreshTimer = setInterval(refreshGraph, intervalMs)
|
||||
} else {
|
||||
addLog('Automatic graph refresh disabled (FREE plan). Use manual refresh.')
|
||||
}
|
||||
}
|
||||
|
||||
const stopGraphRefresh = () => {
|
||||
|
|
|
|||
|
|
@ -339,6 +339,7 @@
|
|||
"taskNotFound": "Task not found: {id}",
|
||||
"graphDeleted": "Graph deleted: {id}",
|
||||
"entityNotFound": "Entity not found: {id}",
|
||||
"zepQuotaExceeded": "Zep Free Plan Quota Exceeded: Your account has reached the maximum allowed episode usage. Please upgrade your Zep plan or clear old data.",
|
||||
"graphNotBuilt": "Graph not yet built. Please call /api/graph/build first.",
|
||||
"requireSimulationId": "Please provide simulation_id",
|
||||
"simulationNotFound": "Simulation not found: {id}",
|
||||
|
|
|
|||
|
|
@ -339,6 +339,7 @@
|
|||
"taskNotFound": "任务不存在: {id}",
|
||||
"graphDeleted": "图谱已删除: {id}",
|
||||
"entityNotFound": "实体不存在: {id}",
|
||||
"zepQuotaExceeded": "Zep 免费计划配额已用完：您的账户已达到最大 episode 数量限制，请升级 Zep 计划或清理旧数据。",
|
||||
"graphNotBuilt": "项目尚未构建图谱，请先调用 /api/graph/build",
|
||||
"requireSimulationId": "请提供 simulation_id",
|
||||
"simulationNotFound": "模拟不存在: {id}",
|
||||
|
|
|
|||
Loading…
Reference in New Issue