Merge branch 'main' into main

embedding_adapters.py

@@ -188,42 +188,42 @@ class GeminiEmbeddingAdapter(BaseEmbeddingAdapter):
             return []
 
 class SiliconFlowEmbeddingAdapter(BaseEmbeddingAdapter):
-     """
-     基于 SiliconFlow 的 embedding 适配器
-     """
-     def __init__(self, api_key: str, base_url: str, model_name: str):
-         # 自动为 base_url 添加 scheme（如果缺失）
-         if not base_url.startswith("http://") and not base_url.startswith("https://"):
-             base_url = "https://" + base_url
-         self.url = base_url if base_url else "https://api.siliconflow.cn/v1/embeddings"
+    """
+    基于 SiliconFlow 的 embedding 适配器
+    """
+    def __init__(self, api_key: str, base_url: str, model_name: str):
+        # 自动为 base_url 添加 scheme（如果缺失）
+        if not base_url.startswith("http://") and not base_url.startswith("https://"):
+            base_url = "https://" + base_url
+        self.url = base_url if base_url else "https://api.siliconflow.cn/v1/embeddings"
 
-         self.payload = {
-             "model": model_name,
-             "input": "Silicon flow embedding online: fast, affordable, and high-quality embedding services. come try it out!",
-             "encoding_format": "float"
-         }
-         self.headers = {
-             "Authorization": "Bearer {api_key}".format(api_key=api_key),
-             "Content-Type": "application/json"
-         }
+        self.payload = {
+            "model": model_name,
+            "input": "Silicon flow embedding online: fast, affordable, and high-quality embedding services. come try it out!",
+            "encoding_format": "float"
+        }
+        self.headers = {
+            "Authorization": "Bearer {api_key}".format(api_key=api_key),
+            "Content-Type": "application/json"
+        }
 
-     def embed_documents(self, texts: List[str]) -> List[List[float]]:
-         embeddings = []
-         for text in texts:
-             self.payload["input"] = text
-             response = requests.post(self.url, json=self.payload, headers=self.headers)
-             result = response.json()
-             # 从返回数据中提取第一个 embedding
-             emb = result.get("data", [{}])[0].get("embedding", [])
-             embeddings.append(emb)
-         return embeddings
+    def embed_documents(self, texts: List[str]) -> List[List[float]]:
+        embeddings = []
+        for text in texts:
+            self.payload["input"] = text
+            response = requests.post(self.url, json=self.payload, headers=self.headers)
+            result = response.json()
+            # 从返回数据中提取第一个 embedding
+            emb = result.get("data", [{}])[0].get("embedding", [])
+            embeddings.append(emb)
+        return embeddings
 
-     def embed_query(self, query: str) -> List[float]:
-         self.payload["input"] = query
-         # print('SiliconFlowEmbeddingAdapter发送',self.payload)
-         response = requests.post(self.url, json=self.payload, headers=self.headers)
-         result = response.json()
-         return result.get("data", [{}])[0].get("embedding", [])
+    def embed_query(self, query: str) -> List[float]:
+        self.payload["input"] = query
+        # print('SiliconFlowEmbeddingAdapter发送',self.payload)
+        response = requests.post(self.url, json=self.payload, headers=self.headers)
+        result = response.json()
+        return result.get("data", [{}])[0].get("embedding", [])
 
 def create_embedding_adapter(
     interface_format: str,
@@ -246,6 +246,6 @@ def create_embedding_adapter(
     elif fmt == "gemini":
         return GeminiEmbeddingAdapter(api_key, model_name, base_url)
     elif fmt == "siliconflow":
-         return SiliconFlowEmbeddingAdapter(api_key, base_url, model_name)    
+        return SiliconFlowEmbeddingAdapter(api_key, base_url, model_name)
     else:
         raise ValueError(f"Unknown embedding interface_format: {interface_format}")

ui/config_tab.py

@@ -184,10 +184,9 @@ def build_embeddings_config_tab(self):
             elif new_value == "Gemini":
                 self.embedding_url_var.set("https://generativelanguage.googleapis.com/v1beta/")
                 self.embedding_model_name_var.set("models/text-embedding-004")
-            elif new_value == "硅基流动":
-                 self.embedding_url_var.set("https://api.siliconflow.cn/v1/embeddings")
-                 self.embedding_model_name_var.set("BAAI/bge-m3")
-
+            elif new_value == "SiliconFlow":
+                self.embedding_url_var.set("https://api.siliconflow.cn/v1/embeddings")
+                self.embedding_model_name_var.set("BAAI/bge-m3")
 
     for i in range(5):
         self.embeddings_config_tab.grid_rowconfigure(i, weight=0)
@@ -202,7 +201,9 @@ def build_embeddings_config_tab(self):
 
     # 2) Embedding 接口格式
     create_label_with_help(self, parent=self.embeddings_config_tab, label_text="Embedding 接口格式:", tooltip_key="embedding_interface_format", row=1, column=0, font=("Microsoft YaHei", 12))
-    emb_interface_options = ["DeepSeek", "OpenAI", "Azure OpenAI", "Gemini", "Ollama", "ML Studio","硅基流动"]
+
+    emb_interface_options = ["DeepSeek", "OpenAI", "Azure OpenAI", "Gemini", "Ollama", "ML Studio","SiliconFlow"]
+
     emb_interface_dropdown = ctk.CTkOptionMenu(self.embeddings_config_tab, values=emb_interface_options, variable=self.embedding_interface_format_var, command=on_embedding_interface_changed, font=("Microsoft YaHei", 12))
     emb_interface_dropdown.grid(row=1, column=1, padx=5, pady=5, sticky="nsew")
 

ui/novel_params_tab.py

@@ -4,7 +4,6 @@ import customtkinter as ctk
 from tkinter import filedialog, messagebox
 from ui.context_menu import TextWidgetContextMenu
 from tooltips import tooltips
-from tooltips import tooltips
 
 def build_novel_params_area(self, start_row=1):
     self.params_frame = ctk.CTkScrollableFrame(self.right_frame, orientation="vertical")