From 2bf1123647a727aecca21a8c2a4c61f9e92db641 Mon Sep 17 00:00:00 2001 From: wayyoungboy <1017761807@qq.com> Date: Thu, 8 Jan 2026 23:52:19 +0800 Subject: [PATCH] =?UTF-8?q?=E9=83=A8=E5=88=86=E9=85=8D=E7=BD=AEkey?= =?UTF-8?q?=E4=BF=AE=E6=AD=A3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docs/powermem-integration.md | 42 +++++--- main/xiaozhi-server/config.yaml | 8 +- .../providers/memory/powermem/powermem.py | 101 +++++++++++------- 3 files changed, 97 insertions(+), 54 deletions(-) diff --git a/docs/powermem-integration.md b/docs/powermem-integration.md index 818e65ed..5b194106 100644 --- a/docs/powermem-integration.md +++ b/docs/powermem-integration.md @@ -59,7 +59,9 @@ Memory: llm_model: qwen-plus # 嵌入模型配置 embedding_api_key: 你的嵌入模型API密钥 - embedding_model: text-embedding-v3 + embedding_model: text-embedding-v4 + # 可选：自定义嵌入服务地址（OpenAI兼容模式） + # embedding_openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 ``` ### 配置参数详解 @@ -72,10 +74,21 @@ Memory: | `embedding_provider` | 嵌入模型提供商 | `qwen` | `qwen`, `zhipu`, `openai`, 等 | | `llm_api_key` | LLM API 密钥 | - | - | | `llm_model` | LLM 模型名称 | - | 根据提供商选择 | -| `llm_base_url` | LLM API 地址（可选） | - | - | +| `llm_base_url` | LLM API 地址（可选） | - | 根据provider自动选择参数名 | | `embedding_api_key` | 嵌入模型 API 密钥 | - | - | | `embedding_model` | 嵌入模型名称 | - | 根据提供商选择 | -| `embedding_base_url` | 嵌入模型 API 地址（可选） | - | - | +| `embedding_base_url` | 嵌入模型 API 地址（可选） | - | 通用配置，根据provider自动选择 | +| `embedding_openai_base_url` | OpenAI兼容的嵌入服务地址（可选） | - | 优先级高于 embedding_base_url | +| `embedding_dashscope_base_url` | 阿里云灵积嵌入服务地址（可选） | - | 优先级高于 embedding_base_url | + +#### Base URL 配置优先级 + +| 配置项 | 优先级 | 适用 Provider | +|--------|--------|---------------| +| `embedding_openai_base_url` | 最高 | openai | +| `embedding_dashscope_base_url` | 最高 | qwen | +| `embedding_base_url` | 中 | 通用，根据 provider 自动选择 | +| 默认值 | 最低 | 使用 provider 的默认服务地址 | ### 记忆模式说明 @@ -102,7 +115,9 @@ Memory: llm_api_key: sk-xxxxxxxxxxxxxxxx llm_model: qwen-plus embedding_api_key: sk-xxxxxxxxxxxxxxxx - embedding_model: text-embedding-v3 + embedding_model: text-embedding-v4 + # 可选：使用 OpenAI 兼容模式的服务地址 + embedding_openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 ``` ### 使用智谱免费 LLM（完全免费方案） @@ -118,14 +133,14 @@ Memory: powermem: type: powermem database_provider: sqlite - llm_provider: zhipu - embedding_provider: zhipu + llm_provider: openai # 使用 openai 兼容模式 + embedding_provider: openai # 使用 openai 兼容模式 llm_api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx llm_model: glm-4-flash llm_base_url: https://open.bigmodel.cn/api/paas/v4/ embedding_api_key: xxxxxxxxxxxxxxxx.xxxxxxxxxxxxxxxx embedding_model: embedding-3 - embedding_base_url: https://open.bigmodel.cn/api/paas/v4/ + embedding_openai_base_url: https://open.bigmodel.cn/api/paas/v4/ ``` ### 使用 OpenAI @@ -142,7 +157,7 @@ Memory: llm_base_url: https://api.openai.com/v1 embedding_api_key: sk-xxxxxxxxxxxxxxxx embedding_model: text-embedding-3-small - embedding_base_url: https://api.openai.com/v1 + embedding_openai_base_url: https://api.openai.com/v1 ``` ### 使用 OceanBase（最佳性能方案） @@ -164,7 +179,8 @@ Memory: llm_api_key: sk-xxxxxxxxxxxxxxxx llm_model: qwen-plus embedding_api_key: sk-xxxxxxxxxxxxxxxx - embedding_model: text-embedding-v3 + embedding_model: text-embedding-v4 + embedding_openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 # OceanBase 数据库连接配置 vector_store: provider: oceanbase @@ -198,10 +214,11 @@ Memory: model: qwen-plus # 嵌入模型配置 embedder: - provider: qwen + provider: openai # 使用 OpenAI 兼容模式 config: api_key: sk-xxxxxxxxxxxxxxxx - model: text-embedding-v3 + model: text-embedding-v4 + openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 ``` ## 设备记忆隔离 @@ -231,7 +248,8 @@ Memory: llm_api_key: sk-xxxxxxxxxxxxxxxx llm_model: qwen-plus embedding_api_key: sk-xxxxxxxxxxxxxxxx - embedding_model: text-embedding-v3 + embedding_model: text-embedding-v4 + embedding_openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 # OceanBase 数据库连接配置 vector_store: provider: oceanbase diff --git a/main/xiaozhi-server/config.yaml b/main/xiaozhi-server/config.yaml index e5420b2c..324fb972 100644 --- a/main/xiaozhi-server/config.yaml +++ b/main/xiaozhi-server/config.yaml @@ -301,9 +301,15 @@ Memory: # 智谱AI(免费): https://bigmodel.cn/usercenter/proj-mgmt/apikeys llm_api_key: 你的LLM API密钥 llm_model: qwen-plus + # llm_base_url: https://dashscope.aliyuncs.com/api/v1 # 可选，自定义LLM服务地址 # 嵌入模型配置 (使用通义千问为例) embedding_api_key: 你的嵌入模型API密钥 - embedding_model: text-embedding-v3 + embedding_model: text-embedding-v4 + embedding_openai_base_url: https://dashscope.aliyuncs.com/compatible-mode/v1 # OpenAI兼容的嵌入服务地址 + # embedding_base_url: https://dashscope.aliyuncs.com/api/v1 # 可选，自定义嵌入模型服务地址 + # 或使用独立的base_url配置（优先级更高）: + # embedding_openai_base_url: https://api.openai.com/v1 # OpenAI兼容的嵌入服务地址 + # embedding_dashscope_base_url: https://dashscope.aliyuncs.com/api/v1 # 阿里云灵积嵌入服务地址 nomem: # 不想使用记忆功能，可以使用nomem type: nomem diff --git a/main/xiaozhi-server/core/providers/memory/powermem/powermem.py b/main/xiaozhi-server/core/providers/memory/powermem/powermem.py index c1891932..fc883c68 100644 --- a/main/xiaozhi-server/core/providers/memory/powermem/powermem.py +++ b/main/xiaozhi-server/core/providers/memory/powermem/powermem.py @@ -21,13 +21,13 @@ TAG = __name__ class MemoryProvider(MemoryProviderBase): """ PowerMem memory provider implementation. - + PowerMem is an open-source agent memory component that provides efficient memory management for AI agents. - + Supports multiple storage backends (sqlite, oceanbase, postgres), LLM providers (qwen, openai, etc.) and embedding providers. - + Config options: - enable_user_profile: bool - Enable UserMemory for user profiling (requires OceanBase) - database_provider: str - Storage backend (sqlite, oceanbase, postgres) @@ -40,16 +40,16 @@ class MemoryProvider(MemoryProviderBase): self.use_powermem = False self.memory_client = None self.enable_user_profile = False - + try: # Check if user profile mode is enabled self.enable_user_profile = config.get("enable_user_profile", False) - + # Get configuration parameters database_provider = config.get("database_provider", "sqlite") llm_provider = config.get("llm_provider", "qwen") embedding_provider = config.get("embedding_provider", "qwen") - + # UserMemory requires OceanBase if self.enable_user_profile and database_provider not in ["oceanbase"]: logger.bind(tag=TAG).warning( @@ -57,13 +57,13 @@ class MemoryProvider(MemoryProviderBase): "Falling back to AsyncMemory mode." ) self.enable_user_profile = False - + # Build powermem configuration dict # PowerMem supports two config styles: # 1. powermem style: database, llm, embedding # 2. mem0 style: vector_store, llm, embedder powermem_config = {} - + # Configure vector store / database if "vector_store" in config: powermem_config["vector_store"] = config["vector_store"] @@ -74,7 +74,7 @@ class MemoryProvider(MemoryProviderBase): "provider": database_provider, "config": {} } - + # Configure LLM if "llm" in config: powermem_config["llm"] = config["llm"] @@ -84,13 +84,23 @@ class MemoryProvider(MemoryProviderBase): llm_config["api_key"] = config["llm_api_key"] if "llm_model" in config: llm_config["model"] = config["llm_model"] + # Handle base_url based on provider type + # - qwen provider uses dashscope_base_url + # - openai provider uses openai_base_url if "llm_base_url" in config: - llm_config["base_url"] = config["llm_base_url"] + if llm_provider == "qwen": + llm_config["dashscope_base_url"] = config["llm_base_url"] + else: + llm_config["openai_base_url"] = config["llm_base_url"] + if "openai_base_url" in config: + llm_config["openai_base_url"] = config["openai_base_url"] + if "dashscope_base_url" in config: + llm_config["dashscope_base_url"] = config["dashscope_base_url"] powermem_config["llm"] = { "provider": llm_provider, "config": llm_config } - + # Configure embedder if "embedder" in config: powermem_config["embedder"] = config["embedder"] @@ -100,13 +110,25 @@ class MemoryProvider(MemoryProviderBase): embedder_config["api_key"] = config["embedding_api_key"] if "embedding_model" in config: embedder_config["model"] = config["embedding_model"] + # Handle base_url based on provider type + # - qwen provider uses dashscope_base_url + # - openai provider uses openai_base_url + # Priority: embedding_xxx_base_url > embedding_base_url > xxx_base_url if "embedding_base_url" in config: - embedder_config["base_url"] = config["embedding_base_url"] + if embedding_provider == "qwen": + embedder_config["dashscope_base_url"] = config["embedding_base_url"] + else: + embedder_config["openai_base_url"] = config["embedding_base_url"] + # Embedding-specific base_url (higher priority) + if "embedding_openai_base_url" in config: + embedder_config["openai_base_url"] = config["embedding_openai_base_url"] + if "embedding_dashscope_base_url" in config: + embedder_config["dashscope_base_url"] = config["embedding_dashscope_base_url"] powermem_config["embedder"] = { "provider": embedding_provider, "config": embedder_config } - + # Initialize memory client based on mode if self.enable_user_profile: from powermem import UserMemory @@ -116,14 +138,14 @@ class MemoryProvider(MemoryProviderBase): from powermem import AsyncMemory self.memory_client = AsyncMemory(config=powermem_config) memory_mode = "AsyncMemory (普通记忆模式)" - + self.use_powermem = True - + logger.bind(tag=TAG).info( f"PowerMem initialized successfully: mode={memory_mode}, " f"database={database_provider}, llm={llm_provider}, embedding={embedding_provider}" ) - + except ImportError as e: logger.bind(tag=TAG).error( f"PowerMem not installed. Please install with: pip install powermem. Error: {e}" @@ -137,17 +159,17 @@ class MemoryProvider(MemoryProviderBase): async def save_memory(self, msgs): """ Save conversation messages to PowerMem. - + Args: msgs: List of message objects with 'role' and 'content' attributes - + Returns: Result from PowerMem API or None if failed """ if not self.use_powermem or self.memory_client is None: logger.bind(tag=TAG).warning("PowerMem is not available, skipping save_memory") return None - + if len(msgs) < 2: logger.bind(tag=TAG).debug("Not enough messages to save (need at least 2)") return None @@ -159,16 +181,16 @@ class MemoryProvider(MemoryProviderBase): for message in msgs if message.role != "system" ] - + # Add memory using PowerMem SDK result = await self.memory_client.add( messages=messages, user_id=self.role_id ) - + logger.bind(tag=TAG).debug(f"Save memory result: {result}") return result - + except Exception as e: logger.bind(tag=TAG).error(f"Error saving memory: {str(e)}") logger.bind(tag=TAG).debug(f"Detailed error: {traceback.format_exc()}") @@ -177,24 +199,24 @@ class MemoryProvider(MemoryProviderBase): async def query_memory(self, query: str) -> str: """ Query memories from PowerMem based on similarity search. - + Args: query: The search query string - + Returns: Formatted string of relevant memories or empty string if none found """ if not self.use_powermem or self.memory_client is None: logger.bind(tag=TAG).warning("PowerMem is not available, skipping query_memory") return "" - + try: if not getattr(self, "role_id", None): logger.bind(tag=TAG).debug("No role_id set, returning empty memory") return "" result_parts = [] - + # If user profile mode is enabled, include user profile in results if self.enable_user_profile: profile = await self.get_user_profile() @@ -207,7 +229,7 @@ class MemoryProvider(MemoryProviderBase): user_id=self.role_id, limit=30 ) - + if results and "results" in results: # Format each memory entry with its update time memories = [] @@ -218,7 +240,7 @@ class MemoryProvider(MemoryProviderBase): timestamp = str(entry["updated_at"]) elif "created_at" in entry and entry["created_at"]: timestamp = str(entry["created_at"]) - + if timestamp: try: # Parse and reformat the timestamp (remove milliseconds if present) @@ -231,7 +253,7 @@ class MemoryProvider(MemoryProviderBase): formatted_time = timestamp else: formatted_time = "" - + memory = entry.get("memory", "") or entry.get("content", "") if memory: if formatted_time: @@ -251,7 +273,7 @@ class MemoryProvider(MemoryProviderBase): final_result = "\n\n".join(result_parts) logger.bind(tag=TAG).debug(f"Query results: {final_result}") return final_result - + except Exception as e: logger.bind(tag=TAG).error(f"Error querying memory: {str(e)}") logger.bind(tag=TAG).debug(f"Detailed error: {traceback.format_exc()}") @@ -260,40 +282,37 @@ class MemoryProvider(MemoryProviderBase): async def get_user_profile(self) -> str: """ Get user profile from PowerMem (only available in UserMemory mode). - + Returns: Formatted user profile string or empty string if not available """ if not self.use_powermem or self.memory_client is None: return "" - + if not self.enable_user_profile: logger.bind(tag=TAG).debug("User profile mode is not enabled") return "" - + try: if not getattr(self, "role_id", None): return "" - + # Get user profile using UserMemory SDK profile = await self.memory_client.get_profile(user_id=self.role_id) - + if not profile: return "" - + # Format profile as readable string profile_parts = [] for key, value in profile.items(): if value: profile_parts.append(f"- {key}: {value}") - + return "\n".join(profile_parts) - + except Exception as e: logger.bind(tag=TAG).error(f"Error getting user profile: {str(e)}") logger.bind(tag=TAG).debug(f"Detailed error: {traceback.format_exc()}") return "" - -# Register the memory provider instance -powermem = MemoryProvider({})