Merge pull request #3 from msz136/main

config.example.yaml

@@ -61,11 +61,14 @@ decay:
 # --- Embedding / 向量化配置 ---
 # Uses embedding API for semantic similarity search
 # 通过 embedding API 实现语义相似度搜索
-# Reuses the same API key (OMBRE_API_KEY) and base_url from dehydration config
-# 复用脱水配置的 API key 和 base_url
+# You can configure embedding independently from dehydration.
+# If api_key is omitted, reuses the same API key (OMBRE_API_KEY) and base_url from dehydration config
+# 你可以把 embedding 独立配置；若 api_key 留空，复用脱水配置的 API key 和 base_url
 embedding:
   enabled: true                   # Enable embedding / 启用向量化
   model: "gemini-embedding-001"   # Embedding model / 向量化模型
+  # base_url: "https://generativelanguage.googleapis.com/v1beta/openai"
+  # api_key: ""                  
 
 # --- Scoring weights / 检索权重参数 ---
 # total = topic(×4) + emotion(×2) + time(×1.5) + importance(×1)

embedding_engine.py

@@ -34,8 +34,12 @@ class EmbeddingEngine:
         dehy_cfg = config.get("dehydration", {})
         embed_cfg = config.get("embedding", {})
 
-        self.api_key = dehy_cfg.get("api_key", "")
-        self.base_url = dehy_cfg.get("base_url", "https://generativelanguage.googleapis.com/v1beta/openai/")
+        self.api_key = (embed_cfg.get("api_key") or dehy_cfg.get("api_key") or "").strip()
+        self.base_url = (
+            (embed_cfg.get("base_url") or "").strip()
+            or (dehy_cfg.get("base_url") or "").strip()
+            or "https://generativelanguage.googleapis.com/v1beta/openai/"
+        )
         self.model = embed_cfg.get("model", "gemini-embedding-001")
         self.enabled = bool(self.api_key) and embed_cfg.get("enabled", True)