1) replace gpt4.1 to gpt5.4, 2) accelerate loading speed

tests/test_config.toml

@@ -0,0 +1,3 @@
+[test]
+key1 = "value1"
+key2 = "value2"

tests/test_config.yaml

@@ -1,3 +0,0 @@
-test:
-  key1: value1
-  key2: value2

tests/test_utils.py

@@ -8,7 +8,7 @@ from translator.utils import parse_config
 
 class TestUtils:
     def test_parse_config(self) -> None:
-        config = parse_config('tests/test_config.yaml')
+        config = parse_config('tests/test_config.toml')
         assert isinstance(config, dict)
         assert 'test' in config
         assert 'key1' in config['test']

translator/app.py

@@ -3,56 +3,69 @@
 # author: deng
 # date  : 20250604
 
+import threading
+
 import streamlit as st
-from langchain.prompts import ChatPromptTemplate
-from langchain_ollama import ChatOllama
-from langchain_openai import ChatOpenAI
 from utils import parse_config
 
 
 class TranslatorApp:
     """Streamlit App for Language Translation"""
 
-    def __init__(self, config_path: str = 'config.yaml'):
+    def __init__(self, config_path: str = 'assets/config.toml'):
         self._config = parse_config(config_path)
         self._chain = None
 
-    def _prepare_chain(self) -> None:
+        # Start pre-warming imports and LLM client in a background thread
-        """Prepare the chain for translation"""
+        self._lock = threading.Lock()
+        threading.Thread(target=self.prepare_chain, daemon=True).start()
+
+    def prepare_chain(self) -> None:
+        """Prepare the chain for translation.
+        Thread-safe: safe to call from both background thread and main thread.
+        """
         if self._chain is not None:
             return
 
-        system_template = (
+        with self._lock:
-            '你是專業的翻譯人員，請判斷接下來句子的語言是否為{source_lang}，若是的話則請將該句翻譯成{target_lang}，'
+            if self._chain is not None:
-            '並且符合{description}（僅回傳翻譯結果即可），若非的話則請回傳一模一樣的句子。'
+                return
-        )
-        user_template = '{input_text}'
 
-        if self._config['app']['llm_mode'] == 'ollama':
+            from langchain.prompts import ChatPromptTemplate
-            llm = ChatOllama(
-                base_url=self._config['app']['ollama']['url'],
-                model=self._config['app']['ollama']['model_name'],
-                temperature=self._config['app']['ollama']['temperature'],
-                max_tokens=self._config['app']['ollama']['max_tokens'],
-                top_p=self._config['app']['ollama']['top_p'],
-                keep_alive=self._config['app']['ollama']['keep_alive'],
-                stop=None
-            )
-        elif self._config['app']['llm_mode'] == 'openai':
-            llm = ChatOpenAI(
-                model=self._config['app']['openai']['model_name'],
-                temperature=self._config['app']['openai']['temperature'],
-                max_tokens=self._config['app']['openai']['max_tokens'],
-                top_p=self._config['app']['openai']['top_p']
-            )
-        else:
-            raise ValueError(f'Unsupported llm model: {self._config['app']['llm_mode']}')
 
-        prompt = ChatPromptTemplate.from_messages([
+            system_template = (
-            ('system', system_template),
+                '你是專業的翻譯人員，請判斷接下來句子的語言是否為{source_lang}，若是的話則請將該句翻譯成{target_lang}，'
-            ('human', user_template)
+                '並且符合{description}（僅回傳翻譯結果即可），若非的話則請回傳一模一樣的句子。'
-        ])
+            )
-        self._chain = prompt | llm
+            user_template = '{input_text}'
+
+            if self._config['app']['llm_mode'] == 'ollama':
+                from langchain_ollama import ChatOllama
+                llm = ChatOllama(
+                    base_url=self._config['app']['ollama']['url'],
+                    model=self._config['app']['ollama']['model_name'],
+                    temperature=self._config['app']['ollama']['temperature'],
+                    max_tokens=self._config['app']['ollama']['max_tokens'],
+                    top_p=self._config['app']['ollama']['top_p'],
+                    keep_alive=self._config['app']['ollama']['keep_alive'],
+                    stop=None
+                )
+            elif self._config['app']['llm_mode'] == 'openai':
+                from langchain_openai import ChatOpenAI
+                llm = ChatOpenAI(
+                    model=self._config['app']['openai']['model_name'],
+                    temperature=self._config['app']['openai']['temperature'],
+                    max_tokens=self._config['app']['openai']['max_tokens'],
+                    top_p=self._config['app']['openai']['top_p']
+                )
+            else:
+                raise ValueError(f"Unsupported llm model: {self._config['app']['llm_mode']}")
+
+            prompt = ChatPromptTemplate.from_messages([
+                ('system', system_template),
+                ('human', user_template)
+            ])
+            self._chain = prompt | llm
 
     def run(self) -> None:
         """ Run the Streamlit app """
@@ -79,14 +92,12 @@ class TranslatorApp:
         translate_button = st.button('翻譯')
         output_container = st.empty()
 
-        # Prepare chain
-        self._prepare_chain()
-        
         # Action
         if input_text or translate_button:
             if not input_text.strip():
-                st.warning("請輸入要翻譯的文字")
+                st.warning('請輸入要翻譯的文字')
             else:
+                self.prepare_chain()
                 with st.spinner('翻譯中...'):
                     result = self._chain.stream({
                         'input_text': input_text,
@@ -99,6 +110,11 @@ class TranslatorApp:
                 )
 
 
+@st.cache_resource(show_spinner=False, max_entries=1)
+def get_app_instance() -> TranslatorApp:
+    return TranslatorApp()
+
+
 if __name__ == '__main__':
-    app = TranslatorApp()
+    app = get_app_instance()
     app.run()

translator/assets/config.toml

@@ -0,0 +1,28 @@
+[app]
+page_title = "橫渡語言的黑水溝"
+page_favicon_path = "./assets/favicon.png"
+llm_mode = "openai"
+
+[app.ollama]
+url = "http://localhost:11434"
+model_name = "gemma3:12b-it-qat"
+max_tokens = 512
+temperature = 0.2
+top_p = 0.9
+keep_alive = "2m"
+
+[app.openai]
+model_name = "gpt-5.4-nano"
+max_tokens = 1024
+temperature = 0.2
+top_p = 0.9
+
+[app.lang_directions."英->中"]
+source_lang = "英文"
+target_lang = "正體中文"
+description = "台灣地區用語"
+
+[app.lang_directions."中->英"]
+source_lang = "中文"
+target_lang = "英文"
+description = "自然通順"

translator/config.yaml

@@ -1,25 +0,0 @@
-app:
-  page_title: 橫渡語言的黑水溝
-  page_favicon_path: ./assets/favicon.png
-  llm_mode: openai
-  ollama:
-    url: http://localhost:11434
-    model_name: gemma3:12b-it-qat
-    max_tokens: 512
-    temperature: 0.2
-    top_p: 0.9
-    keep_alive: 2m
-  openai:
-    model_name: gpt-4.1-nano
-    max_tokens: 1024
-    temperature: 0.2
-    top_p: 0.9
-  lang_directions:
-    '英->中':
-      source_lang: '英文'
-      target_lang: '正體中文'
-      description: '台灣地區用語'
-    '中->英':
-      source_lang: '中文'
-      target_lang: '英文'
-      description: '自然通順'

translator/utils.py

@@ -3,18 +3,18 @@
 # author: deng
 # date  : 20250604
 
-import yaml
+import tomllib
 
 
 def parse_config(config_path: str) -> dict:
     """Config parser
 
     Args:
-        config_path (str): path of config yaml.
+        config_path (str): path of config toml.
 
     Returns:
         dict: configuration dictionary
     """
-    with open(config_path, 'r', encoding='utf-8') as file:
+    with open(config_path, 'rb') as file:
-        config = yaml.safe_load(file)
+        config = tomllib.load(file)
     return config