From a7bfab14751aaebbc2891d719c3320b815735074 Mon Sep 17 00:00:00 2001 From: fawney19 Date: Mon, 15 Dec 2025 18:52:34 +0800 Subject: [PATCH] debug: add logging for model support checking and refactor cache resolution priority MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - 在 aware_scheduler.py 中添加调试日志，用于跟踪模型支持检查过程 - 重构 model_cache.py 的别名解析逻辑：调整优先级为 alias > provider_model_name > direct_match - 优化缓存命中路径，将直接匹配逻辑移到别名匹配失败后执行 --- src/services/cache/aware_scheduler.py | 5 + src/services/cache/model_cache.py | 144 ++++++++++++++------------ 2 files changed, 84 insertions(+), 65 deletions(-) diff --git a/src/services/cache/aware_scheduler.py b/src/services/cache/aware_scheduler.py index 134d1d3..f4b3a0b 100644 --- a/src/services/cache/aware_scheduler.py +++ b/src/services/cache/aware_scheduler.py @@ -802,6 +802,11 @@ class CacheAwareScheduler: # 查询该 Provider 是否有实现这个 GlobalModel for model in provider.models: if model.global_model_id == global_model.id and model.is_active: + logger.debug( + f"[_check_model_support_for_global_model] Provider={provider.name}, " + f"GlobalModel={global_model.name}, " + f"provider_model_name={model.provider_model_name}" + ) # 检查流式支持 if is_stream: supports_streaming = model.get_effective_supports_streaming() diff --git a/src/services/cache/model_cache.py b/src/services/cache/model_cache.py index f3a21f9..239759c 100644 --- a/src/services/cache/model_cache.py +++ b/src/services/cache/model_cache.py @@ -273,24 +273,7 @@ class ModelCacheService: logger.debug(f"GlobalModel 缓存命中(别名解析): {normalized_name}") return ModelCacheService._dict_to_global_model(cached_data) - # 2. 直接通过 GlobalModel.name 查找 - global_model = ( - db.query(GlobalModel) - .filter(GlobalModel.name == normalized_name, GlobalModel.is_active == True) - .first() - ) - - if global_model: - resolution_method = "direct_match" - # 缓存结果 - global_model_dict = ModelCacheService._global_model_to_dict(global_model) - await CacheService.set( - cache_key, global_model_dict, ttl_seconds=ModelCacheService.CACHE_TTL - ) - logger.debug(f"GlobalModel 已缓存(别名解析-直接匹配): {normalized_name}") - return global_model - - # 3. 通过别名匹配（优化：精确查询，避免加载所有 Model） + # 2. 优先通过 provider_model_name 和别名匹配（Provider 配置的别名优先级最高） from sqlalchemy import or_ from src.models.database import Provider @@ -337,72 +320,103 @@ class ModelCacheService: .all() ) - # 用于检测别名冲突 - matched_global_models = [] + # 用于存储匹配结果：{(model_id, global_model_id): (GlobalModel, match_type, priority)} + # 使用字典去重，同一个 Model 只保留优先级最高的匹配 + matched_models_dict = {} # 遍历查询结果进行匹配 for model, gm in models_with_global: - # 检查 provider_model_name 是否匹配 - if model.provider_model_name == normalized_name: - matched_global_models.append((gm, "provider_model_name")) - logger.debug( - f"模型名称 '{normalized_name}' 通过 provider_model_name 匹配到 " - f"GlobalModel: {gm.name}" - ) + key = (model.id, gm.id) - # 检查 provider_model_aliases 是否匹配 + # 检查 provider_model_aliases 是否匹配（优先级更高） if model.provider_model_aliases: for alias_entry in model.provider_model_aliases: if isinstance(alias_entry, dict): alias_name = alias_entry.get("name", "").strip() if alias_name == normalized_name: - matched_global_models.append((gm, "alias")) + # alias 优先级为 0（最高），覆盖任何已存在的匹配 + matched_models_dict[key] = (gm, "alias", 0) logger.debug( f"模型名称 '{normalized_name}' 通过别名匹配到 " - f"GlobalModel: {gm.name}" + f"GlobalModel: {gm.name} (Model: {model.id[:8]}...)" ) break - # 处理匹配结果 - if not matched_global_models: - resolution_method = "not_found" - # 未找到匹配，缓存负结果 - await CacheService.set( - cache_key, "NOT_FOUND", ttl_seconds=ModelCacheService.CACHE_TTL - ) - logger.debug(f"GlobalModel 未找到(别名解析): {normalized_name}") - return None + # 如果还没有匹配（或只有 provider_model_name 匹配），检查 provider_model_name + if key not in matched_models_dict or matched_models_dict[key][1] != "alias": + if model.provider_model_name == normalized_name: + # provider_model_name 优先级为 1（兜底），只在没有 alias 匹配时使用 + if key not in matched_models_dict: + matched_models_dict[key] = (gm, "provider_model_name", 1) + logger.debug( + f"模型名称 '{normalized_name}' 通过 provider_model_name 匹配到 " + f"GlobalModel: {gm.name} (Model: {model.id[:8]}...)" + ) - # 优先使用 provider_model_name 的直接匹配，其次才是 aliases；同级别按名称排序保证确定性 - matched_global_models.sort( - key=lambda item: (0 if item[1] == "provider_model_name" else 1, item[0].name) - ) - - # 记录解析方式 - resolution_method = matched_global_models[0][1] - - if len(matched_global_models) > 1: - # 检测到别名冲突 - unique_models = {gm.id: gm for gm, _ in matched_global_models} - if len(unique_models) > 1: - model_names = [gm.name for gm in unique_models.values()] - logger.warning( - f"别名冲突: 模型名称 '{normalized_name}' 匹配到多个不同的 GlobalModel: " - f"{', '.join(model_names)}，使用第一个匹配结果" + # 如果通过 provider_model_name/alias 找到了，直接返回 + if matched_models_dict: + # 转换为列表并排序：按 priority（alias=0 优先）、然后按 GlobalModel.name + matched_global_models = [ + (gm, match_type) for gm, match_type, priority in matched_models_dict.values() + ] + matched_global_models.sort( + key=lambda item: ( + 0 if item[1] == "alias" else 1, # alias 优先 + item[0].name # 同优先级按名称排序（确定性） ) - # 记录别名冲突指标 - model_alias_conflict_total.inc() + ) - # 返回第一个匹配的 GlobalModel - result_global_model: GlobalModel = matched_global_models[0][0] - global_model_dict = ModelCacheService._global_model_to_dict(result_global_model) + # 记录解析方式 + resolution_method = matched_global_models[0][1] + + if len(matched_global_models) > 1: + # 检测到冲突 + unique_models = {gm.id: gm for gm, _ in matched_global_models} + if len(unique_models) > 1: + model_names = [gm.name for gm in unique_models.values()] + logger.warning( + f"模型冲突: 名称 '{normalized_name}' 匹配到多个不同的 GlobalModel: " + f"{', '.join(model_names)}，使用第一个匹配结果（别名优先）" + ) + # 记录冲突指标 + model_alias_conflict_total.inc() + + # 返回第一个匹配的 GlobalModel + result_global_model: GlobalModel = matched_global_models[0][0] + global_model_dict = ModelCacheService._global_model_to_dict(result_global_model) + await CacheService.set( + cache_key, global_model_dict, ttl_seconds=ModelCacheService.CACHE_TTL + ) + logger.debug( + f"GlobalModel 已缓存(别名解析-{resolution_method}): {normalized_name} -> {result_global_model.name}" + ) + return result_global_model + + # 3. 如果通过 provider 别名没找到，最后尝试直接通过 GlobalModel.name 查找 + global_model = ( + db.query(GlobalModel) + .filter(GlobalModel.name == normalized_name, GlobalModel.is_active == True) + .first() + ) + + if global_model: + resolution_method = "direct_match" + # 缓存结果 + global_model_dict = ModelCacheService._global_model_to_dict(global_model) + await CacheService.set( + cache_key, global_model_dict, ttl_seconds=ModelCacheService.CACHE_TTL + ) + logger.debug(f"GlobalModel 已缓存(别名解析-直接匹配): {normalized_name}") + return global_model + + # 4. 完全未找到 + resolution_method = "not_found" + # 未找到匹配，缓存负结果 await CacheService.set( - cache_key, global_model_dict, ttl_seconds=ModelCacheService.CACHE_TTL + cache_key, "NOT_FOUND", ttl_seconds=ModelCacheService.CACHE_TTL ) - logger.debug( - f"GlobalModel 已缓存(别名解析): {normalized_name} -> {result_global_model.name}" - ) - return result_global_model + logger.debug(f"GlobalModel 未找到(别名解析): {normalized_name}") + return None finally: # 记录监控指标