1) implement cmd+enter apply, 2) split system prompt and user prompt

translator/app.py

@@ -4,9 +4,8 @@
 # date  : 20250604
 
 import streamlit as st
-from langchain.chains import LLMChain
-from langchain.prompts import PromptTemplate
-from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain.prompts import ChatPromptTemplate
+from langchain_core.runnables import Runnable
 from langchain_ollama import ChatOllama
 from langchain_openai import ChatOpenAI
 from utils import parse_config
@@ -19,13 +18,14 @@ class TranslatorApp:
         self._config = parse_config(config_path)
         self._chain = self._prepare_chain()
 
-    def _prepare_chain(self) -> LLMChain:
+    def _prepare_chain(self) -> Runnable:
         """Prepare the chain for translation"""
-        template = (
-            '你是專業的翻譯人員，請判斷這段句子「{input_text}」的語言是否為{source_lang}，若非的'
-            '話則請回傳一模一樣的句子，若是的話則請將該句翻譯成{target_lang}，並且符合{description}'
-            '（僅回傳翻譯結果即可）。'
+        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}，'
+            '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。'
         )
+        user_template = '{input_text}'
+
         if self._config['app']['llm_mode'] == 'ollama':
             llm = ChatOllama(
                 base_url=self._config['app']['ollama']['url'],
@@ -45,10 +45,11 @@ class TranslatorApp:
             )
         else:
             raise ValueError(f'Unsupported llm model: {self._config['app']['llm_mode']}')
-        prompt = PromptTemplate(
-            input_variables=['input_text', 'source_lang', 'target_lang', 'description'],
-            template=template
-        )
+
+        prompt = ChatPromptTemplate.from_messages([
+            ('system', system_template),
+            ('human', user_template)
+        ])
         return prompt | llm
 
     def run(self) -> None:
@@ -67,32 +68,31 @@ class TranslatorApp:
             key='lang_choice',
             horizontal=True
         )
-
         input_text = st.text_area(
             label='輸入',
             placeholder='請輸入文字',
             key='input_text'
         )
-
+        translate_button = st.button('翻譯')
         output_container = st.empty()
 
-        if st.button('翻譯'):
+
+        if input_text or translate_button:
             if not input_text.strip():
                 st.warning("請輸入要翻譯的文字")
-                return
+            else:
+                with st.spinner('翻譯中...'):
 
-            with st.spinner('翻譯中...'):
+                    result = self._chain.stream({
+                        'input_text': input_text,
+                        'source_lang': self._config['app']['lang_directions'][direction]['source_lang'],
+                        'target_lang': self._config['app']['lang_directions'][direction]['target_lang'],
+                        'description': self._config['app']['lang_directions'][direction]['description']
+                    })
 
-                result = self._chain.stream({
-                    'input_text': input_text,
-                    'source_lang': self._config['app']['lang_directions'][direction]['source_lang'],
-                    'target_lang': self._config['app']['lang_directions'][direction]['target_lang'],
-                    'description': self._config['app']['lang_directions'][direction]['description']
-                })
-
-            output_container.write_stream(
-                stream=result
-            )
+                output_container.write_stream(
+                    stream=result
+                )
 
 
 if __name__ == '__main__':