feat: add local SQLite graph storage fallback

- Add local graph store for running without Zep Cloud
- Allow graph, simulation and memory flows to work in sqlite mode
- Preserve Zep integration when API credentials are configured

backend/app/api/graph.py

@@ -285,7 +285,7 @@ def build_graph():
         
         # 检查配置
         errors = []
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             errors.append(t('api.zepApiKeyMissing'))
         if errors:
             logger.error(f"配置错误: {errors}")
@@ -387,7 +387,7 @@ def build_graph():
                 )
                 
                 # 创建图谱构建服务
-                builder = GraphBuilderService(api_key=Config.ZEP_API_KEY)
+                builder = GraphBuilderService()
                 
                 # 分块
                 task_manager.update_task(
@@ -572,13 +572,13 @@ def get_graph_data(graph_id: str):
     获取图谱数据（节点和边）
     """
     try:
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             return jsonify({
                 "success": False,
                 "error": t('api.zepApiKeyMissing')
             }), 500
         
-        builder = GraphBuilderService(api_key=Config.ZEP_API_KEY)
+        builder = GraphBuilderService()
         graph_data = builder.get_graph_data(graph_id)
         
         return jsonify({
@@ -600,13 +600,13 @@ def delete_graph(graph_id: str):
     删除Zep图谱
     """
     try:
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             return jsonify({
                 "success": False,
                 "error": t('api.zepApiKeyMissing')
             }), 500
         
-        builder = GraphBuilderService(api_key=Config.ZEP_API_KEY)
+        builder = GraphBuilderService()
         builder.delete_graph(graph_id)
         
         return jsonify({

backend/app/api/simulation.py

@@ -57,7 +57,7 @@ def get_graph_entities(graph_id: str):
         enrich: 是否获取相关边信息（默认true）
     """
     try:
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             return jsonify({
                 "success": False,
                 "error": t('api.zepApiKeyMissing')
@@ -94,7 +94,7 @@ def get_graph_entities(graph_id: str):
 def get_entity_detail(graph_id: str, entity_uuid: str):
     """获取单个实体的详细信息"""
     try:
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             return jsonify({
                 "success": False,
                 "error": t('api.zepApiKeyMissing')
@@ -127,7 +127,7 @@ def get_entity_detail(graph_id: str, entity_uuid: str):
 def get_entities_by_type(graph_id: str, entity_type: str):
     """获取指定类型的所有实体"""
     try:
-        if not Config.ZEP_API_KEY:
+        if Config.GRAPH_STORAGE_BACKEND != 'sqlite' and not Config.ZEP_API_KEY:
             return jsonify({
                 "success": False,
                 "error": t('api.zepApiKeyMissing')

backend/app/config.py

@@ -32,9 +32,18 @@ class Config:
     LLM_BASE_URL = os.environ.get('LLM_BASE_URL', 'https://api.openai.com/v1')
     LLM_MODEL_NAME = os.environ.get('LLM_MODEL_NAME', 'gpt-4o-mini')
     
-    # Zep配置
+    # 图谱存储配置
+    # 默认优先使用 SQLite 本地存储；如果显式提供 ZEP_API_KEY，也可以继续走远端 Zep。
     ZEP_API_KEY = os.environ.get('ZEP_API_KEY')
-    
+    GRAPH_STORAGE_BACKEND = os.environ.get(
+        'MIROFISH_GRAPH_STORAGE',
+        'sqlite' if not os.environ.get('ZEP_API_KEY') else 'zep'
+    ).strip().lower()
+    LOCAL_GRAPH_DB_PATH = os.environ.get(
+        'MIROFISH_GRAPH_DB_PATH',
+        os.path.join(os.path.dirname(__file__), '../uploads/local_graphs.sqlite3')
+    )
+
     # 文件上传配置
     MAX_CONTENT_LENGTH = 50 * 1024 * 1024  # 50MB
     UPLOAD_FOLDER = os.path.join(os.path.dirname(__file__), '../uploads')
@@ -69,7 +78,6 @@ class Config:
         errors: list[str] = []
         if not cls.LLM_API_KEY:
             errors.append("LLM_API_KEY 未配置")
-        if not cls.ZEP_API_KEY:
-            errors.append("ZEP_API_KEY 未配置")
+        # 图谱存储现在默认可以使用 SQLite，本地模式下不再强制要求 ZEP_API_KEY。
         return errors
 

backend/app/services/graph_builder.py

@@ -15,7 +15,9 @@ from zep_cloud import EpisodeData, EntityEdgeSourceTarget
 
 from ..config import Config
 from ..models.task import TaskManager, TaskStatus
+from ..utils.llm_client import LLMClient
 from ..utils.zep_paging import fetch_all_nodes, fetch_all_edges
+from .local_graph_store import LocalGraphStore
 from .text_processor import TextProcessor
 from ..utils.locale import t, get_locale, set_locale
 
@@ -45,11 +47,23 @@ class GraphBuilderService:
     
     def __init__(self, api_key: Optional[str] = None):
         self.api_key = api_key or Config.ZEP_API_KEY
-        if not self.api_key:
-            raise ValueError("ZEP_API_KEY 未配置")
-        
-        self.client = Zep(api_key=self.api_key)
+        self.use_local_storage = Config.GRAPH_STORAGE_BACKEND == 'sqlite' or not self.api_key
         self.task_manager = TaskManager()
+        self.local_store = LocalGraphStore() if self.use_local_storage else None
+        self.llm_client = None
+
+        if self.use_local_storage:
+            # Local SQLite mode: no Zep client needed.
+            if Config.LLM_API_KEY:
+                try:
+                    self.llm_client = LLMClient()
+                except Exception:
+                    self.llm_client = None
+            self.client = None
+        else:
+            if not self.api_key:
+                raise ValueError("ZEP_API_KEY 未配置")
+            self.client = Zep(api_key=self.api_key)
     
     def build_graph_async(
         self,
@@ -191,19 +205,31 @@ class GraphBuilderService:
             self.task_manager.fail_task(task_id, error_msg)
     
     def create_graph(self, name: str) -> str:
-        """创建Zep图谱（公开方法）"""
+        """创建图谱（公开方法）"""
         graph_id = f"mirofish_{uuid.uuid4().hex[:16]}"
-        
+
+        if self.use_local_storage:
+            self.local_store.create_graph(
+                graph_id=graph_id,
+                name=name,
+                description="MiroFish Social Simulation Graph",
+            )
+            return graph_id
+
         self.client.graph.create(
             graph_id=graph_id,
             name=name,
             description="MiroFish Social Simulation Graph"
         )
-        
+
         return graph_id
     
     def set_ontology(self, graph_id: str, ontology: Dict[str, Any]):
         """设置图谱本体（公开方法）"""
+        if self.use_local_storage:
+            self.local_store.set_ontology(graph_id, ontology)
+            return
+
         import warnings
         from typing import Optional
         from pydantic import Field
@@ -290,7 +316,6 @@ class GraphBuilderService:
                 entities=entity_types if entity_types else None,
                 edges=edge_definitions if edge_definitions else None,
             )
-    
     def add_text_batches(
         self,
         graph_id: str,
@@ -299,6 +324,25 @@ class GraphBuilderService:
         progress_callback: Optional[Callable] = None
     ) -> List[str]:
         """分批添加文本到图谱，返回所有 episode 的 uuid 列表"""
+        if self.use_local_storage:
+            total = len(chunks)
+            if total == 0:
+                return []
+            if progress_callback:
+                progress_callback(t('progress.sendingBatch', current=1, total=1, chunks=total), 0.0)
+
+            episode_uuids = self.local_store.extract_and_store_chunks(
+                graph_id=graph_id,
+                chunks=chunks,
+                ontology=(self.local_store.get_graph(graph_id) or {}).get('ontology', {}),
+                llm_client=self.llm_client,
+                progress_callback=None,
+                batch_size=batch_size,
+            )
+            if progress_callback:
+                progress_callback(t('progress.processingComplete', completed=len(episode_uuids), total=len(episode_uuids)), 1.0)
+            return episode_uuids
+
         episode_uuids = []
         total_chunks = len(chunks)
         
@@ -351,6 +395,11 @@ class GraphBuilderService:
         timeout: int = 600
     ):
         """等待所有 episode 处理完成（通过查询每个 episode 的 processed 状态）"""
+        if self.use_local_storage:
+            if progress_callback:
+                progress_callback(t('progress.processingComplete', completed=len(episode_uuids), total=len(episode_uuids)), 1.0)
+            return
+
         if not episode_uuids:
             if progress_callback:
                 progress_callback(t('progress.noEpisodesWait'), 1.0)
@@ -402,11 +451,29 @@ class GraphBuilderService:
     
     def _get_graph_info(self, graph_id: str) -> GraphInfo:
         """获取图谱信息"""
+        if self.use_local_storage:
+            graph = self.local_store.get_graph(graph_id) or {}
+            nodes = graph.get("nodes", [])
+            edges = graph.get("edges", [])
+            entity_types = set()
+            for node in nodes:
+                for label in node.get("labels", []):
+                    if label not in ["Entity", "Node"]:
+                        entity_types.add(label)
+            return GraphInfo(
+                graph_id=graph_id,
+                node_count=len(nodes),
+                edge_count=len(edges),
+                entity_types=list(entity_types),
+            )
+
         # 获取节点（分页）
-        nodes = fetch_all_nodes(self.client, graph_id)
+        client = self.client
+        assert client is not None
+        nodes = fetch_all_nodes(client, graph_id)
 
         # 获取边（分页）
-        edges = fetch_all_edges(self.client, graph_id)
+        edges = fetch_all_edges(client, graph_id)
 
         # 统计实体类型
         entity_types = set()
@@ -433,8 +500,22 @@ class GraphBuilderService:
         Returns:
             包含nodes和edges的字典，包括时间信息、属性等详细数据
         """
-        nodes = fetch_all_nodes(self.client, graph_id)
-        edges = fetch_all_edges(self.client, graph_id)
+        if self.use_local_storage:
+            graph = self.local_store.get_graph(graph_id) or {}
+            nodes_data = graph.get("nodes", [])
+            edges_data = graph.get("edges", [])
+            return {
+                "graph_id": graph_id,
+                "nodes": nodes_data,
+                "edges": edges_data,
+                "node_count": len(nodes_data),
+                "edge_count": len(edges_data),
+            }
+
+        client = self.client
+        assert client is not None
+        nodes = fetch_all_nodes(client, graph_id)
+        edges = fetch_all_edges(client, graph_id)
 
         # 创建节点映射用于获取节点名称
         node_map = {}
@@ -502,5 +583,8 @@ class GraphBuilderService:
     
     def delete_graph(self, graph_id: str):
         """删除图谱"""
+        if self.use_local_storage:
+            self.local_store.delete_graph(graph_id)
+            return
         self.client.graph.delete(graph_id=graph_id)
 

backend/app/services/local_graph_store.py

@@ -0,0 +1,869 @@
+"""SQLite-backed local graph store used when Zep is disabled.
+
+This is a pragmatic replacement layer that keeps the app bootable and lets the
+main graph/profile/report flows use local persistence instead of Zep Cloud.
+It intentionally stores raw chunks, extracted nodes, extracted edges, and
+lightweight episode metadata in SQLite.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import re
+import sqlite3
+import threading
+import uuid
+from dataclasses import dataclass
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple
+
+from ..config import Config
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ExtractedChunk:
+    episode_uuid: str
+    nodes: List[Dict[str, Any]]
+    edges: List[Dict[str, Any]]
+
+
+def _utcnow() -> str:
+    return datetime.now(timezone.utc).isoformat()
+
+
+def _json_loads(value: Optional[str], default: Any) -> Any:
+    if not value:
+        return default
+    try:
+        return json.loads(value)
+    except Exception:
+        return default
+
+
+def _json_dumps(value: Any) -> str:
+    return json.dumps(value, ensure_ascii=False, sort_keys=True)
+
+
+def _stable_uuid(*parts: str) -> str:
+    payload = "::".join(part.strip().lower() for part in parts if part is not None)
+    return str(uuid.uuid5(uuid.NAMESPACE_URL, payload))
+
+
+class LocalGraphStore:
+    def __init__(self, db_path: Optional[str] = None):
+        self.db_path = Path(db_path or getattr(Config, "LOCAL_GRAPH_DB_PATH", "") or self._default_db_path())
+        self.db_path.parent.mkdir(parents=True, exist_ok=True)
+        self._lock = threading.Lock()
+        self._ensure_schema()
+
+    @staticmethod
+    def _default_db_path() -> str:
+        return str(Path(__file__).resolve().parents[2] / "uploads" / "local_graphs.sqlite3")
+
+    def _connect(self) -> sqlite3.Connection:
+        conn = sqlite3.connect(self.db_path)
+        conn.row_factory = sqlite3.Row
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA foreign_keys=ON")
+        return conn
+
+    def _ensure_schema(self) -> None:
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.executescript(
+                    """
+                    CREATE TABLE IF NOT EXISTS graphs (
+                        graph_id TEXT PRIMARY KEY,
+                        name TEXT NOT NULL,
+                        description TEXT DEFAULT '',
+                        ontology_json TEXT NOT NULL DEFAULT '{}',
+                        source_text TEXT NOT NULL DEFAULT '',
+                        created_at TEXT NOT NULL,
+                        updated_at TEXT NOT NULL,
+                        mode TEXT NOT NULL DEFAULT 'sqlite'
+                    );
+
+                    CREATE TABLE IF NOT EXISTS graph_chunks (
+                        id INTEGER PRIMARY KEY AUTOINCREMENT,
+                        graph_id TEXT NOT NULL,
+                        chunk_index INTEGER NOT NULL,
+                        content TEXT NOT NULL,
+                        created_at TEXT NOT NULL,
+                        FOREIGN KEY(graph_id) REFERENCES graphs(graph_id) ON DELETE CASCADE
+                    );
+
+                    CREATE TABLE IF NOT EXISTS graph_episodes (
+                        uuid TEXT PRIMARY KEY,
+                        graph_id TEXT NOT NULL,
+                        kind TEXT NOT NULL DEFAULT 'chunk',
+                        data TEXT NOT NULL,
+                        processed INTEGER NOT NULL DEFAULT 1,
+                        created_at TEXT NOT NULL,
+                        FOREIGN KEY(graph_id) REFERENCES graphs(graph_id) ON DELETE CASCADE
+                    );
+
+                    CREATE TABLE IF NOT EXISTS graph_nodes (
+                        uuid TEXT PRIMARY KEY,
+                        graph_id TEXT NOT NULL,
+                        name TEXT NOT NULL,
+                        labels_json TEXT NOT NULL DEFAULT '[]',
+                        summary TEXT NOT NULL DEFAULT '',
+                        attributes_json TEXT NOT NULL DEFAULT '{}',
+                        created_at TEXT NOT NULL,
+                        updated_at TEXT NOT NULL,
+                        FOREIGN KEY(graph_id) REFERENCES graphs(graph_id) ON DELETE CASCADE
+                    );
+
+                    CREATE TABLE IF NOT EXISTS graph_edges (
+                        uuid TEXT PRIMARY KEY,
+                        graph_id TEXT NOT NULL,
+                        name TEXT NOT NULL DEFAULT '',
+                        fact TEXT NOT NULL DEFAULT '',
+                        fact_type TEXT NOT NULL DEFAULT '',
+                        source_node_uuid TEXT NOT NULL,
+                        target_node_uuid TEXT NOT NULL,
+                        source_node_name TEXT NOT NULL DEFAULT '',
+                        target_node_name TEXT NOT NULL DEFAULT '',
+                        attributes_json TEXT NOT NULL DEFAULT '{}',
+                        episodes_json TEXT NOT NULL DEFAULT '[]',
+                        created_at TEXT NOT NULL,
+                        valid_at TEXT,
+                        invalid_at TEXT,
+                        expired_at TEXT,
+                        updated_at TEXT NOT NULL,
+                        FOREIGN KEY(graph_id) REFERENCES graphs(graph_id) ON DELETE CASCADE
+                    );
+
+                    CREATE INDEX IF NOT EXISTS idx_graph_chunks_graph_id ON graph_chunks(graph_id);
+                    CREATE INDEX IF NOT EXISTS idx_graph_episodes_graph_id ON graph_episodes(graph_id);
+                    CREATE INDEX IF NOT EXISTS idx_graph_nodes_graph_id ON graph_nodes(graph_id);
+                    CREATE INDEX IF NOT EXISTS idx_graph_edges_graph_id ON graph_edges(graph_id);
+                    CREATE INDEX IF NOT EXISTS idx_graph_edges_source ON graph_edges(source_node_uuid);
+                    CREATE INDEX IF NOT EXISTS idx_graph_edges_target ON graph_edges(target_node_uuid);
+                    """
+                )
+                conn.commit()
+            finally:
+                conn.close()
+
+    def create_graph(self, graph_id: str, name: str, description: str = "") -> str:
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    """
+                    INSERT INTO graphs (graph_id, name, description, ontology_json, source_text, created_at, updated_at, mode)
+                    VALUES (?, ?, ?, ?, ?, ?, ?, 'sqlite')
+                    ON CONFLICT(graph_id) DO UPDATE SET
+                        name=excluded.name,
+                        description=excluded.description,
+                        updated_at=excluded.updated_at
+                    """,
+                    (graph_id, name, description, "{}", "", now, now),
+                )
+                conn.commit()
+                return graph_id
+            finally:
+                conn.close()
+
+    def set_ontology(self, graph_id: str, ontology: Dict[str, Any]) -> None:
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    "UPDATE graphs SET ontology_json = ?, updated_at = ? WHERE graph_id = ?",
+                    (_json_dumps(ontology or {}), now, graph_id),
+                )
+                conn.commit()
+            finally:
+                conn.close()
+
+    def append_source_text(self, graph_id: str, source_text: str) -> None:
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    "UPDATE graphs SET source_text = COALESCE(source_text, '') || ?, updated_at = ? WHERE graph_id = ?",
+                    (source_text or "", now, graph_id),
+                )
+                conn.commit()
+            finally:
+                conn.close()
+
+    def store_episode(self, graph_id: str, chunk_index: int, content: str, kind: str = "chunk") -> str:
+        episode_uuid = str(uuid.uuid4())
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    """
+                    INSERT INTO graph_episodes (uuid, graph_id, kind, data, processed, created_at)
+                    VALUES (?, ?, ?, ?, 1, ?)
+                    """,
+                    (episode_uuid, graph_id, kind, content, now),
+                )
+                conn.execute(
+                    """
+                    INSERT INTO graph_chunks (graph_id, chunk_index, content, created_at)
+                    VALUES (?, ?, ?, ?)
+                    """,
+                    (graph_id, chunk_index, content, now),
+                )
+                conn.commit()
+                return episode_uuid
+            finally:
+                conn.close()
+
+    def upsert_node(
+        self,
+        graph_id: str,
+        name: str,
+        labels: Sequence[str],
+        summary: str = "",
+        attributes: Optional[Dict[str, Any]] = None,
+        node_uuid: Optional[str] = None,
+    ) -> str:
+        node_uuid = node_uuid or _stable_uuid(graph_id, "node", name, ",".join(labels or []))
+        now = _utcnow()
+        payload = (
+            node_uuid,
+            graph_id,
+            name.strip(),
+            _json_dumps(list(labels or [])),
+            summary or "",
+            _json_dumps(attributes or {}),
+            now,
+            now,
+        )
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    """
+                    INSERT INTO graph_nodes (uuid, graph_id, name, labels_json, summary, attributes_json, created_at, updated_at)
+                    VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+                    ON CONFLICT(uuid) DO UPDATE SET
+                        name=excluded.name,
+                        labels_json=excluded.labels_json,
+                        summary=excluded.summary,
+                        attributes_json=excluded.attributes_json,
+                        updated_at=excluded.updated_at
+                    """,
+                    payload,
+                )
+                conn.commit()
+                return node_uuid
+            finally:
+                conn.close()
+
+    def upsert_edge(
+        self,
+        graph_id: str,
+        name: str,
+        fact: str,
+        source_node_uuid: str,
+        target_node_uuid: str,
+        source_node_name: str,
+        target_node_name: str,
+        attributes: Optional[Dict[str, Any]] = None,
+        episodes: Optional[Sequence[str]] = None,
+        fact_type: Optional[str] = None,
+        edge_uuid: Optional[str] = None,
+        created_at: Optional[str] = None,
+        valid_at: Optional[str] = None,
+        invalid_at: Optional[str] = None,
+        expired_at: Optional[str] = None,
+    ) -> str:
+        edge_uuid = edge_uuid or _stable_uuid(
+            graph_id,
+            "edge",
+            name,
+            source_node_uuid,
+            target_node_uuid,
+            fact[:160],
+        )
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                existing = conn.execute(
+                    "SELECT episodes_json, created_at FROM graph_edges WHERE uuid = ?",
+                    (edge_uuid,),
+                ).fetchone()
+                merged_episodes = list(episodes or [])
+                if existing:
+                    prev_episodes = _json_loads(existing["episodes_json"], [])
+                    if isinstance(prev_episodes, list):
+                        merged_episodes = list(dict.fromkeys([*prev_episodes, *merged_episodes]))
+                    if not created_at:
+                        created_at = existing["created_at"]
+                conn.execute(
+                    """
+                    INSERT INTO graph_edges (
+                        uuid, graph_id, name, fact, fact_type, source_node_uuid, target_node_uuid,
+                        source_node_name, target_node_name, attributes_json, episodes_json,
+                        created_at, valid_at, invalid_at, expired_at, updated_at
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                    ON CONFLICT(uuid) DO UPDATE SET
+                        name=excluded.name,
+                        fact=excluded.fact,
+                        fact_type=excluded.fact_type,
+                        source_node_uuid=excluded.source_node_uuid,
+                        target_node_uuid=excluded.target_node_uuid,
+                        source_node_name=excluded.source_node_name,
+                        target_node_name=excluded.target_node_name,
+                        attributes_json=excluded.attributes_json,
+                        episodes_json=excluded.episodes_json,
+                        valid_at=excluded.valid_at,
+                        invalid_at=excluded.invalid_at,
+                        expired_at=excluded.expired_at,
+                        updated_at=excluded.updated_at
+                    """,
+                    (
+                        edge_uuid,
+                        graph_id,
+                        name or "",
+                        fact or "",
+                        fact_type or name or "",
+                        source_node_uuid,
+                        target_node_uuid,
+                        source_node_name or "",
+                        target_node_name or "",
+                        _json_dumps(attributes or {}),
+                        _json_dumps(merged_episodes),
+                        created_at or now,
+                        valid_at,
+                        invalid_at,
+                        expired_at,
+                        now,
+                    ),
+                )
+                conn.commit()
+                return edge_uuid
+            finally:
+                conn.close()
+
+    def _load_graph(self, conn: sqlite3.Connection, graph_id: str) -> Optional[sqlite3.Row]:
+        return conn.execute("SELECT * FROM graphs WHERE graph_id = ?", (graph_id,)).fetchone()
+
+    def get_graph(self, graph_id: str) -> Optional[Dict[str, Any]]:
+        with self._lock:
+            conn = self._connect()
+            try:
+                graph = self._load_graph(conn, graph_id)
+                if not graph:
+                    return None
+                nodes = self.list_nodes(graph_id, conn=conn)
+                edges = self.list_edges(graph_id, conn=conn)
+                chunks = conn.execute(
+                    "SELECT chunk_index, content, created_at FROM graph_chunks WHERE graph_id = ? ORDER BY chunk_index, id",
+                    (graph_id,),
+                ).fetchall()
+                return {
+                    "graph_id": graph_id,
+                    "name": graph["name"],
+                    "description": graph["description"],
+                    "ontology": _json_loads(graph["ontology_json"], {}),
+                    "source_text": graph["source_text"],
+                    "created_at": graph["created_at"],
+                    "updated_at": graph["updated_at"],
+                    "nodes": nodes,
+                    "edges": edges,
+                    "chunks": [dict(row) for row in chunks],
+                }
+            finally:
+                conn.close()
+
+    def list_graphs(self) -> List[Dict[str, Any]]:
+        with self._lock:
+            conn = self._connect()
+            try:
+                rows = conn.execute(
+                    "SELECT graph_id, name, description, ontology_json, created_at, updated_at FROM graphs ORDER BY updated_at DESC"
+                ).fetchall()
+                return [
+                    {
+                        "graph_id": row["graph_id"],
+                        "name": row["name"],
+                        "description": row["description"],
+                        "ontology": _json_loads(row["ontology_json"], {}),
+                        "created_at": row["created_at"],
+                        "updated_at": row["updated_at"],
+                    }
+                    for row in rows
+                ]
+            finally:
+                conn.close()
+
+    def list_nodes(self, graph_id: str, conn: Optional[sqlite3.Connection] = None) -> List[Dict[str, Any]]:
+        own_conn = None
+        if conn is None:
+            own_conn = self._connect()
+            conn = own_conn
+        try:
+            rows = conn.execute(
+                "SELECT * FROM graph_nodes WHERE graph_id = ? ORDER BY updated_at DESC, created_at DESC, name",
+                (graph_id,),
+            ).fetchall()
+            return [self._row_to_node(row) for row in rows]
+        finally:
+            if own_conn is not None:
+                own_conn.close()
+
+    def list_edges(self, graph_id: str, conn: Optional[sqlite3.Connection] = None) -> List[Dict[str, Any]]:
+        own_conn = None
+        if conn is None:
+            own_conn = self._connect()
+            conn = own_conn
+        try:
+            rows = conn.execute(
+                "SELECT * FROM graph_edges WHERE graph_id = ? ORDER BY updated_at DESC, created_at DESC",
+                (graph_id,),
+            ).fetchall()
+            return [self._row_to_edge(row) for row in rows]
+        finally:
+            if own_conn is not None:
+                own_conn.close()
+
+    def get_node(self, graph_id: str, node_uuid: str) -> Optional[Dict[str, Any]]:
+        with self._lock:
+            conn = self._connect()
+            try:
+                row = conn.execute(
+                    "SELECT * FROM graph_nodes WHERE graph_id = ? AND uuid = ?",
+                    (graph_id, node_uuid),
+                ).fetchone()
+                return self._row_to_node(row) if row else None
+            finally:
+                conn.close()
+
+    def get_edges_for_node(self, graph_id: str, node_uuid: str) -> List[Dict[str, Any]]:
+        with self._lock:
+            conn = self._connect()
+            try:
+                rows = conn.execute(
+                    """
+                    SELECT * FROM graph_edges
+                    WHERE graph_id = ? AND (source_node_uuid = ? OR target_node_uuid = ?)
+                    ORDER BY updated_at DESC, created_at DESC
+                    """,
+                    (graph_id, node_uuid, node_uuid),
+                ).fetchall()
+                return [self._row_to_edge(row) for row in rows]
+            finally:
+                conn.close()
+
+    def get_edges_for_node_any(self, node_uuid: str) -> List[Dict[str, Any]]:
+        with self._lock:
+            conn = self._connect()
+            try:
+                rows = conn.execute(
+                    """
+                    SELECT * FROM graph_edges
+                    WHERE source_node_uuid = ? OR target_node_uuid = ?
+                    ORDER BY updated_at DESC, created_at DESC
+                    """,
+                    (node_uuid, node_uuid),
+                ).fetchall()
+                return [self._row_to_edge(row) for row in rows]
+            finally:
+                conn.close()
+
+    def get_graph_statistics(self, graph_id: str) -> Dict[str, Any]:
+        nodes = self.list_nodes(graph_id)
+        edges = self.list_edges(graph_id)
+        entity_types: Dict[str, int] = {}
+        relation_types: Dict[str, int] = {}
+        for node in nodes:
+            for label in node.get("labels", []):
+                if label not in ["Entity", "Node"]:
+                    entity_types[label] = entity_types.get(label, 0) + 1
+        for edge in edges:
+            relation_types[edge.get("name", "")] = relation_types.get(edge.get("name", ""), 0) + 1
+        return {
+            "graph_id": graph_id,
+            "total_nodes": len(nodes),
+            "total_edges": len(edges),
+            "entity_types": entity_types,
+            "relation_types": relation_types,
+        }
+
+    def delete_graph(self, graph_id: str) -> None:
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute("DELETE FROM graphs WHERE graph_id = ?", (graph_id,))
+                conn.commit()
+            finally:
+                conn.close()
+
+    def append_activity(self, graph_id: str, payload: Dict[str, Any]) -> str:
+        episode_uuid = str(uuid.uuid4())
+        now = _utcnow()
+        with self._lock:
+            conn = self._connect()
+            try:
+                conn.execute(
+                    """
+                    INSERT INTO graph_episodes (uuid, graph_id, kind, data, processed, created_at)
+                    VALUES (?, ?, ?, ?, 1, ?)
+                    """,
+                    (episode_uuid, graph_id, "activity", _json_dumps(payload), now),
+                )
+                conn.commit()
+                return episode_uuid
+            finally:
+                conn.close()
+
+    def search(self, graph_id: str, query: str, scope: str = "edges", limit: int = 10) -> Dict[str, Any]:
+        query_lower = (query or "").lower()
+        keywords = [w.strip() for w in re.split(r"[\s,，]+", query_lower) if len(w.strip()) > 1]
+
+        def score_text(text: str) -> int:
+            if not text:
+                return 0
+            text_lower = text.lower()
+            score = 0
+            if query_lower and query_lower in text_lower:
+                score += 100
+            for kw in keywords:
+                if kw in text_lower:
+                    score += 10
+            return score
+
+        nodes = self.list_nodes(graph_id) if scope in ["nodes", "both"] else []
+        edges = self.list_edges(graph_id) if scope in ["edges", "both"] else []
+        facts: List[str] = []
+        scored_nodes: List[Tuple[int, Dict[str, Any]]] = []
+        scored_edges: List[Tuple[int, Dict[str, Any]]] = []
+
+        for node in nodes:
+            text = " ".join([
+                node.get("name", ""),
+                node.get("summary", ""),
+                _json_dumps(node.get("attributes", {})),
+            ])
+            score = score_text(text)
+            if score > 0:
+                scored_nodes.append((score, node))
+
+        for edge in edges:
+            text = " ".join([
+                edge.get("name", ""),
+                edge.get("fact", ""),
+                edge.get("source_node_name", ""),
+                edge.get("target_node_name", ""),
+                _json_dumps(edge.get("attributes", {})),
+            ])
+            score = score_text(text)
+            if score > 0:
+                scored_edges.append((score, edge))
+
+        scored_nodes.sort(key=lambda item: item[0], reverse=True)
+        scored_edges.sort(key=lambda item: item[0], reverse=True)
+
+        node_results = [node for _, node in scored_nodes[:limit]]
+        edge_results = [edge for _, edge in scored_edges[:limit]]
+
+        for node in node_results:
+            if node.get("summary"):
+                facts.append(f"[{node['name']}]: {node['summary']}")
+        for edge in edge_results:
+            if edge.get("fact"):
+                facts.append(edge["fact"])
+
+        return {
+            "facts": facts[:limit],
+            "nodes": node_results,
+            "edges": edge_results,
+            "total_count": len(facts),
+        }
+
+    def extract_and_store_chunks(
+        self,
+        graph_id: str,
+        chunks: Sequence[str],
+        ontology: Optional[Dict[str, Any]] = None,
+        llm_client: Optional[Any] = None,
+        progress_callback: Optional[Any] = None,
+        batch_size: int = 1,
+    ) -> List[str]:
+        episode_uuids: List[str] = []
+        ontology = ontology or {}
+
+        existing_nodes = {node["name"].strip().lower(): node for node in self.list_nodes(graph_id)}
+        total = len(chunks)
+        for idx, chunk in enumerate(chunks):
+            if progress_callback:
+                progress_callback(idx + 1, total)
+            episode_uuid = self.store_episode(graph_id, idx, chunk, kind="text")
+            episode_uuids.append(episode_uuid)
+            extracted = self._extract_chunk(chunk, ontology, llm_client)
+            node_map = self._store_extracted_chunk(graph_id, extracted, episode_uuid, existing_nodes)
+            existing_nodes.update(node_map)
+        return episode_uuids
+
+    def _extract_chunk(self, chunk: str, ontology: Dict[str, Any], llm_client: Optional[Any]) -> ExtractedChunk:
+        if llm_client is not None:
+            try:
+                payload = self._extract_with_llm(chunk, ontology, llm_client)
+                return ExtractedChunk(
+                    episode_uuid="",
+                    nodes=payload.get("nodes", []),
+                    edges=payload.get("edges", []),
+                )
+            except Exception as exc:
+                logger.warning("Local graph extraction via LLM failed, falling back to heuristics: %s", exc)
+        nodes = self._heuristic_extract_nodes(chunk, ontology)
+        edges = self._heuristic_extract_edges(chunk, nodes, ontology)
+        return ExtractedChunk(episode_uuid="", nodes=nodes, edges=edges)
+
+    def _extract_with_llm(self, chunk: str, ontology: Dict[str, Any], llm_client: Any) -> Dict[str, Any]:
+        entity_types = [e.get("name", "Entity") for e in ontology.get("entity_types", []) if isinstance(e, dict)]
+        edge_types = [e.get("name", "RELATED_TO") for e in ontology.get("edge_types", []) if isinstance(e, dict)]
+        system = (
+            "You extract graph nodes and edges from source text for a social-simulation knowledge graph. "
+            "Return only JSON with keys nodes and edges. "
+            "Each node must have name, labels, summary, attributes. "
+            "Each edge must have name, fact, source_node_name, target_node_name, attributes."
+        )
+        if entity_types:
+            system += " Allowed entity types: " + ", ".join(entity_types)
+        if edge_types:
+            system += " Allowed relation types: " + ", ".join(edge_types)
+        user = (
+            f"Ontology:\n{_json_dumps(ontology)}\n\n"
+            f"Text chunk:\n{chunk}\n\n"
+            "Rules:\n"
+            "- Prefer real-world entities that can act on social media\n"
+            "- If the text mentions organizations or people, use those as nodes\n"
+            "- Use labels like ['Entity', '<Type>']\n"
+            "- Facts should be concise natural language statements\n"
+            "- If you cannot infer a relationship, return an empty edges list\n"
+        )
+        result = llm_client.chat_json(
+            messages=[
+                {"role": "system", "content": system},
+                {"role": "user", "content": user},
+            ],
+            temperature=0.1,
+            max_tokens=2500,
+        )
+        if not isinstance(result, dict):
+            raise ValueError("Invalid extraction payload")
+        return result
+
+    def _heuristic_extract_nodes(self, chunk: str, ontology: Dict[str, Any]) -> List[Dict[str, Any]]:
+        entity_types = [e.get("name", "Entity") for e in ontology.get("entity_types", []) if isinstance(e, dict)]
+        fallback_type = entity_types[0] if entity_types else "Entity"
+        candidates = self._guess_entities(chunk)
+        nodes: List[Dict[str, Any]] = []
+        for candidate in candidates[:8]:
+            nodes.append(
+                {
+                    "name": candidate,
+                    "labels": ["Entity", fallback_type],
+                    "summary": candidate,
+                    "attributes": {},
+                }
+            )
+        return nodes
+
+    def _heuristic_extract_edges(
+        self,
+        chunk: str,
+        nodes: Sequence[Dict[str, Any]],
+        ontology: Dict[str, Any],
+    ) -> List[Dict[str, Any]]:
+        relation_types = [e.get("name", "RELATED_TO") for e in ontology.get("edge_types", []) if isinstance(e, dict)]
+        relation_name = relation_types[0] if relation_types else "RELATED_TO"
+        node_names = [str(node.get("name", "")).strip() for node in nodes if str(node.get("name", "")).strip()]
+        if len(node_names) < 2:
+            return []
+
+        # Split on sentence boundaries first; fall back to whole chunk if needed.
+        sentences = [part.strip() for part in re.split(r"[\.!?。！？\n]+", chunk) if part.strip()]
+        if not sentences:
+            sentences = [chunk.strip()]
+
+        edges: List[Dict[str, Any]] = []
+        seen_pairs = set()
+
+        for sentence in sentences:
+            matched: List[str] = []
+            lower_sentence = sentence.lower()
+            for name in node_names:
+                needle = name.lower()
+                if needle and needle in lower_sentence and name not in matched:
+                    matched.append(name)
+            if len(matched) < 2:
+                continue
+            for source_name, target_name in zip(matched, matched[1:]):
+                pair_key = (source_name.lower(), target_name.lower(), sentence.lower())
+                if pair_key in seen_pairs:
+                    continue
+                seen_pairs.add(pair_key)
+                edges.append(
+                    {
+                        "name": relation_name,
+                        "fact": sentence.strip() or f"{source_name} {relation_name} {target_name}",
+                        "source_node_name": source_name,
+                        "target_node_name": target_name,
+                        "attributes": {},
+                        "fact_type": relation_name,
+                    }
+                )
+
+        if not edges:
+            for source_name, target_name in zip(node_names, node_names[1:]):
+                pair_key = (source_name.lower(), target_name.lower(), "fallback")
+                if pair_key in seen_pairs:
+                    continue
+                seen_pairs.add(pair_key)
+                edges.append(
+                    {
+                        "name": relation_name,
+                        "fact": f"{source_name} {relation_name} {target_name}",
+                        "source_node_name": source_name,
+                        "target_node_name": target_name,
+                        "attributes": {},
+                        "fact_type": relation_name,
+                    }
+                )
+
+        return edges
+
+    def _guess_entities(self, text: str) -> List[str]:
+        # Simple fallback: quoted names, title-case words, and long nouns.
+        candidates: List[str] = []
+        for match in re.findall(r"[A-Z][A-Za-z0-9&_-]*(?:\s+[A-Z][A-Za-z0-9&_-]*){0,3}", text):
+            match = match.strip().strip("'\"“”‘’,，。.!?；;:：")
+            if len(match) > 2:
+                candidates.append(match)
+        for match in re.findall(r"[\u4e00-\u9fff]{2,10}", text):
+            match = match.strip()
+            if len(match) > 2:
+                candidates.append(match)
+        seen = set()
+        result = []
+        for item in candidates:
+            key = item.lower()
+            if key not in seen:
+                seen.add(key)
+                result.append(item)
+        return result
+
+    def _store_extracted_chunk(
+        self,
+        graph_id: str,
+        extracted: ExtractedChunk,
+        episode_uuid: str,
+        existing_nodes: Dict[str, Dict[str, Any]],
+    ) -> Dict[str, Dict[str, Any]]:
+        ontology = self.get_graph(graph_id) or {}
+        new_nodes: Dict[str, Dict[str, Any]] = {}
+        node_uuid_by_name: Dict[str, str] = {}
+
+        # First, upsert nodes.
+        for node in extracted.nodes:
+            if not isinstance(node, dict):
+                continue
+            name = str(node.get("name", "")).strip()
+            if not name:
+                continue
+            labels = node.get("labels") or ["Entity", "Entity"]
+            if isinstance(labels, str):
+                labels = [labels]
+            summary = str(node.get("summary", ""))
+            attributes = node.get("attributes") or {}
+            entity_type = next((label for label in labels if label not in ["Entity", "Node"]), "Entity")
+            node_uuid = node.get("uuid") or _stable_uuid(graph_id, "node", entity_type, name)
+            self.upsert_node(graph_id, name, labels, summary=summary, attributes=attributes, node_uuid=node_uuid)
+            node_uuid_by_name[name.lower()] = node_uuid
+            node_uuid_by_name.setdefault(name.strip().lower(), node_uuid)
+            new_nodes[name.lower()] = {
+                "uuid": node_uuid,
+                "name": name,
+                "labels": list(labels),
+                "summary": summary,
+                "attributes": attributes,
+            }
+
+        # Resolve existing names too.
+        for name, node in existing_nodes.items():
+            node_uuid_by_name.setdefault(name, node.get("uuid", ""))
+
+        # Now upsert edges.
+        for edge in extracted.edges:
+            if not isinstance(edge, dict):
+                continue
+            name = str(edge.get("name", "RELATED_TO")).strip() or "RELATED_TO"
+            fact = str(edge.get("fact", "")).strip()
+            source_name = str(edge.get("source_node_name", "")).strip()
+            target_name = str(edge.get("target_node_name", "")).strip()
+            if not source_name or not target_name:
+                continue
+            source_uuid = node_uuid_by_name.get(source_name.lower()) or existing_nodes.get(source_name.lower(), {}).get("uuid")
+            target_uuid = node_uuid_by_name.get(target_name.lower()) or existing_nodes.get(target_name.lower(), {}).get("uuid")
+            if not source_uuid:
+                source_uuid = self.upsert_node(graph_id, source_name, ["Entity", "Entity"], summary=source_name)
+                node_uuid_by_name[source_name.lower()] = source_uuid
+            if not target_uuid:
+                target_uuid = self.upsert_node(graph_id, target_name, ["Entity", "Entity"], summary=target_name)
+                node_uuid_by_name[target_name.lower()] = target_uuid
+            self.upsert_edge(
+                graph_id=graph_id,
+                name=name,
+                fact=fact or f"{source_name} {name} {target_name}",
+                source_node_uuid=source_uuid,
+                target_node_uuid=target_uuid,
+                source_node_name=source_name,
+                target_node_name=target_name,
+                attributes=edge.get("attributes") or {},
+                episodes=[episode_uuid],
+                fact_type=str(edge.get("fact_type", name) or name),
+                edge_uuid=edge.get("uuid"),
+            )
+
+        return new_nodes
+
+    def _row_to_node(self, row: Optional[sqlite3.Row]) -> Dict[str, Any]:
+        if row is None:
+            return {}
+        return {
+            "uuid": row["uuid"],
+            "name": row["name"],
+            "labels": _json_loads(row["labels_json"], []),
+            "summary": row["summary"],
+            "attributes": _json_loads(row["attributes_json"], {}),
+            "created_at": row["created_at"],
+        }
+
+    def _row_to_edge(self, row: Optional[sqlite3.Row]) -> Dict[str, Any]:
+        if row is None:
+            return {}
+        return {
+            "uuid": row["uuid"],
+            "name": row["name"],
+            "fact": row["fact"],
+            "fact_type": row["fact_type"],
+            "source_node_uuid": row["source_node_uuid"],
+            "target_node_uuid": row["target_node_uuid"],
+            "source_node_name": row["source_node_name"],
+            "target_node_name": row["target_node_name"],
+            "attributes": _json_loads(row["attributes_json"], {}),
+            "created_at": row["created_at"],
+            "valid_at": row["valid_at"],
+            "invalid_at": row["invalid_at"],
+            "expired_at": row["expired_at"],
+            "episodes": _json_loads(row["episodes_json"], []),
+        }

backend/app/services/zep_entity_reader.py

@@ -12,6 +12,7 @@ from zep_cloud.client import Zep
 from ..config import Config
 from ..utils.logger import get_logger
 from ..utils.zep_paging import fetch_all_nodes, fetch_all_edges
+from .local_graph_store import LocalGraphStore
 
 logger = get_logger('mirofish.zep_entity_reader')
 
@@ -80,6 +81,13 @@ class ZepEntityReader:
     
     def __init__(self, api_key: Optional[str] = None):
         self.api_key = api_key or Config.ZEP_API_KEY
+        self.use_local_storage = Config.GRAPH_STORAGE_BACKEND == 'sqlite' or not self.api_key
+        self.local_store = LocalGraphStore() if self.use_local_storage else None
+
+        if self.use_local_storage:
+            self.client = None
+            return
+
         if not self.api_key:
             raise ValueError("ZEP_API_KEY 未配置")
         
@@ -136,6 +144,11 @@ class ZepEntityReader:
         """
         logger.info(f"获取图谱 {graph_id} 的所有节点...")
 
+        if self.use_local_storage:
+            nodes_data = self.local_store.list_nodes(graph_id)
+            logger.info(f"共获取 {len(nodes_data)} 个节点")
+            return nodes_data
+
         nodes = fetch_all_nodes(self.client, graph_id)
 
         nodes_data = []
@@ -163,6 +176,11 @@ class ZepEntityReader:
         """
         logger.info(f"获取图谱 {graph_id} 的所有边...")
 
+        if self.use_local_storage:
+            edges_data = self.local_store.list_edges(graph_id)
+            logger.info(f"共获取 {len(edges_data)} 条边")
+            return edges_data
+
         edges = fetch_all_edges(self.client, graph_id)
 
         edges_data = []
@@ -190,6 +208,9 @@ class ZepEntityReader:
             边列表
         """
         try:
+            if self.use_local_storage:
+                return self.local_store.get_edges_for_node_any(node_uuid)
+
             # 使用重试机制调用Zep API
             edges = self._call_with_retry(
                 func=lambda: self.client.graph.node.get_entity_edges(node_uuid=node_uuid),
@@ -346,11 +367,13 @@ class ZepEntityReader:
             EntityNode或None
         """
         try:
-            # 使用重试机制获取节点
-            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 self.use_local_storage:
+                node = self.local_store.get_node(graph_id, entity_uuid)
+            else:
+                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
@@ -396,6 +419,17 @@ class ZepEntityReader:
                         "summary": related_node.get("summary", ""),
                     })
             
+            if self.use_local_storage:
+                return EntityNode(
+                    uuid=node["uuid"],
+                    name=node["name"],
+                    labels=node["labels"],
+                    summary=node["summary"],
+                    attributes=node["attributes"],
+                    related_edges=related_edges,
+                    related_nodes=related_nodes,
+                )
+
             return EntityNode(
                 uuid=getattr(node, 'uuid_', None) or getattr(node, 'uuid', ''),
                 name=node.name or "",

backend/app/services/zep_graph_memory_updater.py

@@ -17,6 +17,7 @@ from zep_cloud.client import Zep
 from ..config import Config
 from ..utils.logger import get_logger
 from ..utils.locale import get_locale, set_locale
+from .local_graph_store import LocalGraphStore
 
 logger = get_logger('mirofish.zep_graph_memory_updater')
 
@@ -239,11 +240,13 @@ class ZepGraphMemoryUpdater:
         """
         self.graph_id = graph_id
         self.api_key = api_key or Config.ZEP_API_KEY
+        self.use_local_storage = Config.GRAPH_STORAGE_BACKEND == 'sqlite' or not self.api_key
+        self.local_store = LocalGraphStore() if self.use_local_storage else None
         
-        if not self.api_key:
+        if not self.use_local_storage and not self.api_key:
             raise ValueError("ZEP_API_KEY未配置")
         
-        self.client = Zep(api_key=self.api_key)
+        self.client = None if self.use_local_storage else Zep(api_key=self.api_key)
         
         # 活动队列
         self._activity_queue: Queue = Queue()
@@ -403,6 +406,21 @@ class ZepGraphMemoryUpdater:
         """
         if not activities:
             return
+
+        if self.use_local_storage:
+            store = self.local_store
+            assert store is not None
+            combined_text = "\n".join(activity.to_episode_text() for activity in activities)
+            store.append_activity(self.graph_id, {
+                "platform": platform,
+                "activities": [activity.__dict__ for activity in activities],
+                "combined_text": combined_text,
+            })
+            self._total_sent += 1
+            self._total_items_sent += len(activities)
+            display_name = self._get_platform_display_name(platform)
+            logger.info(f"本地模式已记录 {len(activities)} 条{display_name}活动到 SQLite 图谱 {self.graph_id}")
+            return
         
         # 将多条活动合并为一条文本，用换行分隔
         episode_texts = [activity.to_episode_text() for activity in activities]