feat: 添加阿里百炼重排序模型适配器

astrbot/core/config/default.py

@@ -1308,6 +1308,19 @@
                         "timeout": 20,
                         "launch_model_if_not_running": False,
                     },
+                    "阿里云百炼重排序": {
+                        "id": "bailian_rerank",
+                        "type": "bailian_rerank",
+                        "provider": "bailian",
+                        "provider_type": "rerank",
+                        "enable": True,
+                        "rerank_api_key": "",
+                        "rerank_api_base": "https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank",
+                        "rerank_model": "qwen3-rerank",
+                        "timeout": 30,
+                        "return_documents": False,
+                        "instruct": "",
+                    },
                     "Xinference STT": {
                         "id": "xinference_stt",
                         "type": "xinference_stt",
@@ -1342,6 +1355,16 @@
                         "description": "重排序模型名称",
                         "type": "string",
                     },
+                    "return_documents": {
+                        "description": "是否在排序结果中返回文档原文",
+                        "type": "bool",
+                        "hint": "默认值false，以减少网络传输开销。",
+                    },
+                    "instruct": {
+                        "description": "自定义排序任务类型说明",
+                        "type": "string",
+                        "hint": "仅在使用 qwen3-rerank 模型时生效。建议使用英文撰写。",
+                    },
                     "launch_model_if_not_running": {
                         "description": "模型未运行时自动启动",
                         "type": "bool",

astrbot/core/provider/manager.py

@@ -331,6 +331,10 @@ async def load_provider(self, provider_config: dict):
                     from .sources.xinference_rerank_source import (
                         XinferenceRerankProvider as XinferenceRerankProvider,
                     )
+                case "bailian_rerank":
+                    from .sources.bailian_rerank_source import (
+                        BailianRerankProvider as BailianRerankProvider,
+                    )
         except (ImportError, ModuleNotFoundError) as e:
             logger.critical(
                 f"加载 {provider_config['type']}({provider_config['id']}) 提供商适配器失败：{e}。可能是因为有未安装的依赖。",

astrbot/core/provider/sources/bailian_rerank_source.py

@@ -0,0 +1,236 @@
+import os
+
+import aiohttp
+
+from astrbot import logger
+
+from ..entities import ProviderType, RerankResult
+from ..provider import RerankProvider
+from ..register import register_provider_adapter
+
+
+class BailianRerankError(Exception):
+    """百炼重排序服务异常基类"""
+
+    pass
+
+
+class BailianAPIError(BailianRerankError):
+    """百炼API返回错误"""
+
+    pass
+
+
+class BailianNetworkError(BailianRerankError):
+    """百炼网络请求错误"""
+
+    pass
+
+
+@register_provider_adapter(
+    "bailian_rerank", "阿里云百炼文本排序适配器", provider_type=ProviderType.RERANK
+)
+class BailianRerankProvider(RerankProvider):
+    """阿里云百炼文本重排序适配器."""
+
+    def __init__(self, provider_config: dict, provider_settings: dict) -> None:
+        super().__init__(provider_config, provider_settings)
+        self.provider_config = provider_config
+        self.provider_settings = provider_settings
+
+        # API配置
+        self.api_key = provider_config.get("rerank_api_key") or os.getenv(
+            "DASHSCOPE_API_KEY", ""
+        )
+        if not self.api_key:
+            raise ValueError("阿里云百炼 API Key 不能为空。")
+
+        self.model = provider_config.get("rerank_model", "qwen3-rerank")
+        self.timeout = provider_config.get("timeout", 30)
+        self.return_documents = provider_config.get("return_documents", False)
+        self.instruct = provider_config.get("instruct", "")
+
+        self.base_url = provider_config.get(
+            "rerank_api_base",
+            "https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank",
+        )
+
+        # 设置HTTP客户端
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        self.client = aiohttp.ClientSession(
+            headers=headers, timeout=aiohttp.ClientTimeout(total=self.timeout)
+        )
+
+        # 设置模型名称
+        self.set_model(self.model)
+
+        logger.info(f"AstrBot 百炼 Rerank 初始化完成。模型: {self.model}")
+
+    def _build_payload(
+        self, query: str, documents: list[str], top_n: int | None
+    ) -> dict:
+        """构建请求载荷
+
+        Args:
+            query: 查询文本
+            documents: 文档列表
+            top_n: 返回前N个结果，如果为None则返回所有结果
+
+        Returns:
+            请求载荷字典
+        """
+        base = {"model": self.model, "input": {"query": query, "documents": documents}}
+
+        params = {
+            k: v
+            for k, v in [
+                ("top_n", top_n if top_n is not None and top_n > 0 else None),
+                ("return_documents", True if self.return_documents else None),
+                (
+                    "instruct",
+                    self.instruct
+                    if self.instruct and self.model == "qwen3-rerank"
+                    else None,
+                ),
+            ]
+            if v is not None
+        }
+
+        if params:
+            base["parameters"] = params
+
+        return base
+
+    def _parse_results(self, data: dict) -> list[RerankResult]:
+        """解析API响应结果
+
+        Args:
+            data: API响应数据
+
+        Returns:
+            重排序结果列表
+
+        Raises:
+            BailianAPIError: API返回错误
+            KeyError: 结果缺少必要字段
+        """
+        # 检查响应状态
+        if data.get("code", "200") != "200":
+            raise BailianAPIError(
+                f"百炼 API 错误: {data.get('code')} – {data.get('message', '')}"
+            )
+
+        results = data.get("output", {}).get("results", [])
+        if not results:
+            logger.warning(f"百炼 Rerank 返回空结果: {data}")
+            return []
+
+        # 转换为RerankResult对象，使用.get()避免KeyError
+        rerank_results = []
+        for idx, result in enumerate(results):
+            try:
+                index = result.get("index", idx)
+                relevance_score = result.get("relevance_score", 0.0)
+
+                if relevance_score is None:
+                    logger.warning(f"结果 {idx} 缺少 relevance_score，使用默认值 0.0")
+                    relevance_score = 0.0
+
+                rerank_result = RerankResult(
+                    index=index, relevance_score=relevance_score
+                )
+                rerank_results.append(rerank_result)
+            except Exception as e:
+                logger.warning(f"解析结果 {idx} 时出错: {e}, result={result}")
+                continue
+
+        return rerank_results
+
+    def _log_usage(self, data: dict) -> None:
+        """记录使用量信息
+
+        Args:
+            data: API响应数据
+        """
+        tokens = data.get("usage", {}).get("total_tokens", 0)
+        if tokens > 0:
+            logger.debug(f"百炼 Rerank 消耗 Token: {tokens}")
+
+    async def rerank(
+        self,
+        query: str,
+        documents: list[str],
+        top_n: int | None = None,
+    ) -> list[RerankResult]:
+        """
+        对文档进行重排序
+
+        Args:
+            query: 查询文本
+            documents: 待排序的文档列表
+            top_n: 返回前N个结果，如果为None则使用配置中的默认值
+
+        Returns:
+            重排序结果列表
+        """
+        if not documents:
+            logger.warning("文档列表为空，返回空结果")
+            return []
+
+        if not query.strip():
+            logger.warning("查询文本为空，返回空结果")
+            return []
+
+        # 检查限制
+        if len(documents) > 500:
+            logger.warning(
+                f"文档数量({len(documents)})超过限制(500)，将截断前500个文档"
+            )
+            documents = documents[:500]
+
+        try:
+            # 构建请求载荷，如果top_n为None则返回所有重排序结果
+            payload = self._build_payload(query, documents, top_n)
+
+            logger.debug(
+                f"百炼 Rerank 请求: query='{query[:50]}...', 文档数量={len(documents)}"
+            )
+
+            # 发送请求
+            async with self.client.post(self.base_url, json=payload) as response:
+                response.raise_for_status()
+                response_data = await response.json()
+
+                # 解析结果并记录使用量
+                results = self._parse_results(response_data)
+                self._log_usage(response_data)
+
+                logger.debug(f"百炼 Rerank 成功返回 {len(results)} 个结果")
+
+                return results
+
+        except aiohttp.ClientError as e:
+            error_msg = f"网络请求失败: {e}"
+            logger.error(f"百炼 Rerank 网络请求失败: {e}")
+            raise BailianNetworkError(error_msg) from e
+        except BailianRerankError:
+            raise
+        except Exception as e:
+            error_msg = f"重排序失败: {e}"
+            logger.error(f"百炼 Rerank 处理失败: {e}")
+            raise BailianRerankError(error_msg) from e
+
+    async def terminate(self) -> None:
+        """关闭HTTP客户端会话."""
+        if self.client:
+            logger.info("关闭 百炼 Rerank 客户端会话")
+            try:
+                await self.client.close()
+            except Exception as e:
+                logger.error(f"关闭 百炼 Rerank 客户端时出错: {e}")
+            finally:
+                self.client = None