Rename memory_sync.py.py to memory_sync.py

memory_sync.py

@@ -0,0 +1,114 @@
+#!/usr/bin/env python3
+"""
+OpenClaw 记忆同步脚本
+将本地记忆文件同步至 Hugging Face Dataset，并从 Dataset 恢复。
+"""
+
+import os
+import sys
+import time
+import logging
+from pathlib import Path
+from huggingface_hub import HfApi, hf_hub_download, upload_file, list_repo_files
+
+# 配置日志
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+class MemorySync:
+    def __init__(self):
+        self.hf_token = os.getenv('HF_TOKEN')
+        # 请将下面的 'your-username/openclaw-memory' 替换成你实际创建的 Dataset 名字
+        self.hf_dataset = os.getenv('HF_MEMORY_DATASET', 'a8926764/openclaw-memory')
+        # 确保这个路径和启动脚本中设置的 OPENCLAW_MEMORY_DIR 一致
+        self.local_memory_dir = Path(os.getenv('OPENCLAW_MEMORY_DIR', '/root/.openclaw/memory'))
+        self.api = HfApi(token=self.hf_token)
+
+    def ensure_memory_dir(self):
+        """确保本地记忆目录存在"""
+        self.local_memory_dir.mkdir(parents=True, exist_ok=True)
+        logger.info(f"Memory directory ensured: {self.local_memory_dir}")
+
+    def download_memory(self):
+        """从 Dataset 拉取所有记忆文件（.md 文件）"""
+        self.ensure_memory_dir()
+        try:
+            logger.info(f'开始从 Dataset 下载记忆文件: {self.hf_dataset}')
+            files = list_repo_files(repo_id=self.hf_dataset, repo_type="dataset")
+            downloaded_count = 0
+            for file_name in files:
+                if file_name.endswith('.md'):
+                    try:
+                        local_path = hf_hub_download(
+                            repo_id=self.hf_dataset,
+                            filename=file_name,
+                            repo_type="dataset",
+                            token=self.hf_token,
+                            local_dir=self.local_memory_dir
+                        )
+                        logger.info(f'已下载记忆文件: {file_name}')
+                        downloaded_count += 1
+                    except Exception as e:
+                        logger.error(f'下载文件 {file_name} 失败: {e}')
+                        continue
+            if downloaded_count == 0:
+                logger.info('Dataset 中未找到记忆文件，将使用新记忆。')
+            else:
+                logger.info(f'记忆文件下载完成，共下载 {downloaded_count} 个文件。')
+            return True
+        except Exception as e:
+            logger.error(f'从 Dataset 拉取记忆失败: {e}')
+            # 首次运行时 Dataset 可能为空，这不一定是错误，返回 True 允许流程继续
+            return True
+
+    def upload_memory(self):
+        """推送本地所有 .md 记忆文件到 Dataset"""
+        self.ensure_memory_dir()
+        try:
+            logger.info(f'开始推送记忆文件到 Dataset: {self.hf_dataset}')
+            memory_files = list(self.local_memory_dir.glob('*.md'))
+            if not memory_files:
+                logger.warning('本地没有找到 .md 格式的记忆文件，跳过上传。')
+                return False
+
+            uploaded_count = 0
+            for mem_file in memory_files:
+                try:
+                    upload_file(
+                        path_or_fileobj=str(mem_file),
+                        path_in_repo=mem_file.name,
+                        repo_id=self.hf_dataset,
+                        repo_type="dataset",
+                        token=self.hf_token,
+                        commit_message=f"自动同步记忆: {mem_file.name} - {time.strftime('%Y-%m-%d %H:%M:%S')}"
+                    )
+                    logger.info(f'已上传记忆文件: {mem_file.name}')
+                    uploaded_count += 1
+                except Exception as e:
+                    logger.error(f'上传文件 {mem_file.name} 失败: {e}')
+                    continue
+
+            logger.info(f'记忆文件上传完成，共上传 {uploaded_count} 个文件。')
+            return uploaded_count > 0
+        except Exception as e:
+            logger.error(f'推送记忆到 Dataset 失败: {e}')
+            return False
+
+def main():
+    """主函数，处理命令行参数"""
+    if len(sys.argv) != 2 or sys.argv[1] not in ['download', 'upload']:
+        print('用法: python memory_sync.py [download|upload]')
+        sys.exit(1)
+
+    sync = MemorySync()
+    mode = sys.argv[1]
+
+    if mode == 'download':
+        success = sync.download_memory()
+        sys.exit(0 if success else 1)
+    elif mode == 'upload':
+        success = sync.upload_memory()
+        sys.exit(0 if success else 1)
+
+if __name__ == '__main__':
+    main()

memory_sync.py.py

@@ -1,66 +0,0 @@
-# memory_sync.py
-import os
-import time
-import logging
-from pathlib import Path
-from huggingface_hub import HfApi, hf_hub_download, upload_file
-
-class MemorySync:
-    def __init__(self):
-        self.hf_token = os.getenv('HF_TOKEN')
-        # 使用专门存储记忆的Dataset
-        self.hf_dataset = os.getenv('HF_MEMORY_DATASET', 'a8926764/openclaw-memory')
-        # OpenClaw记忆存储的本地目录（关键！需要与配置一致）
-        self.local_memory_dir = Path(os.getenv('OPENCLAW_MEMORY_DIR', '/root/.openclaw/memory'))
-        self.api = HfApi(token=self.hf_token)
-
-    def ensure_memory_dir(self):
-        self.local_memory_dir.mkdir(parents=True, exist_ok=True)
-
-    def download_memory(self):
-        """从Dataset拉取所有记忆文件"""
-        self.ensure_memory_dir()
-        try:
-            # 这里需要根据你Dataset里文件的实际情况来获取文件列表
-            # 例如，假设所有.md文件都是记忆文件
-            from huggingface_hub import list_repo_files
-            files = list_repo_files(repo_id=self.hf_dataset, repo_type="dataset")
-            for file in files:
-                if file.endswith('.md'):  # 或其他记忆文件格式
-                    local_path = hf_hub_download(
-                        repo_id=self.hf_dataset,
-                        filename=file,
-                        repo_type="dataset",
-                        local_dir=self.local_memory_dir
-                    )
-                    print(f"Downloaded memory: {file}")
-            return True
-        except Exception as e:
-            print(f"Download memory failed: {e}")
-            return False
-
-    def upload_memory(self):
-        """推送所有记忆文件到Dataset"""
-        try:
-            memory_files = list(self.local_memory_dir.glob('*.md'))
-            for mem_file in memory_files:
-                upload_file(
-                    path_or_fileobj=str(mem_file),
-                    path_in_repo=mem_file.name,
-                    repo_id=self.hf_dataset,
-                    repo_type="dataset",
-                    commit_message=f"Update memory: {mem_file.name}"
-                )
-                print(f"Uploaded memory: {mem_file.name}")
-            return True
-        except Exception as e:
-            print(f"Upload memory failed: {e}")
-            return False
-
-if __name__ == '__main__':
-    import sys
-    sync = MemorySync()
-    if len(sys.argv) > 1 and sys.argv[1] == 'upload':
-        sync.upload_memory()
-    else:
-        sync.download_memory()