Added count time_elapsed, and return more parameters

app/routes/text_translator.py

@@ -52,25 +52,25 @@ def translate_text(source_language, target_language, original_text, tone_of_voic
     elif model == "Volcengine":
         translated_text = translate_by_volcengine_api(source_language, target_language, original_text)
     elif model in model_dict_translate_by_hkbu_chatgpt_api:
-        translation_sample, translated_text = translate_by_hkbu_chatgpt_api(
+        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_hkbu_chatgpt_api(
             source_language, target_language, original_text, tone_of_voice, industry,
             model_dict_translate_by_hkbu_chatgpt_api[model]
         )
     elif model in model_dict_translate_by_openrouter_api:
-        translation_sample, translated_text = translate_by_openrouter_api(
+        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_openrouter_api(
             source_language, target_language, original_text, tone_of_voice, industry,
             model_dict_translate_by_openrouter_api[model]
         )
     elif model == "Google Gemini (gemini-pro)":
-        translation_sample, translated_text = translate_by_google_api(
+        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_google_api(
             source_language, target_language, original_text, tone_of_voice, industry
         )
     elif model == "Baichuan AI (Baichuan2)":
-        translation_sample, translated_text = translate_by_baichuan_api(
+        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_baichuan_api(
             source_language, target_language, original_text, tone_of_voice, industry
         )
     elif model in model_dict_translate_by_zhipuai_api:
-        translation_sample, translated_text = translate_by_zhipuai_api(
+        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_zhipuai_api(
             source_language, target_language, original_text, tone_of_voice, industry,
             model_dict_translate_by_zhipuai_api[model]
         )

utils/translate/translate_baichuan.py

@@ -1,4 +1,5 @@
 import os
+import time
 from langchain_community.chat_models import ChatBaichuan
 from langchain.schema import HumanMessage
 from dotenv import load_dotenv
@@ -14,6 +15,9 @@ baichuan_secret_key = os.environ.get("BAICHUAN_SECRET_KEY")
 def translate_by_baichuan_api(source_language, target_language, original_text, tone_of_voice, industry):
     # Prompt to provide translation
     translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+
+    start_time = time.time()
+
     # Translate by accessing Baichuan API
     chat = ChatBaichuan(temperature=0.7, baichuan_api_key=baichuan_api_key, baichuan_secret_key=baichuan_secret_key, model='Baichuan2')
     res = chat(
@@ -22,7 +26,12 @@ def translate_by_baichuan_api(source_language, target_language, original_text, t
         ]
     )
     res_content = res.content
-    print(res_content)
+
+    end_time = time.time()
+    time_elapsed = end_time - start_time
+    print("Time Elapsed:", time_elapsed, "seconds")
+    print("Result content:", res_content)
+
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed

utils/translate/translate_google.py

@@ -1,4 +1,5 @@
 import os
+import time
 from langchain_google_genai import ChatGoogleGenerativeAI
 from dotenv import load_dotenv
 
@@ -12,11 +13,19 @@ google_api_key = os.environ.get("GOOGLE_API_KEY")
 def translate_by_google_api(source_language, target_language, original_text, tone_of_voice, industry):
     # Prompt to provide translation
     translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+
+    start_time = time.time()
+
     # Translate by accessing Google API
     chat = ChatGoogleGenerativeAI(temperature=0.7, model="gemini-pro")
     res = chat.invoke(translation_prompt)
     res_content = res.content
-    print(res_content)
+
+    end_time = time.time()
+    time_elapsed = end_time - start_time
+    print("Time Elapsed:", time_elapsed, "seconds")
+    print("Result content:", res_content)
+
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed

utils/translate/translate_hkbu_chatgpt.py

@@ -1,4 +1,5 @@
 import os
+import time
 from dotenv import load_dotenv
 import requests
 
@@ -31,6 +32,9 @@ def call_hkbu_chatgpt_api(conversation_list, model_name="gpt-35-turbo", temperat
 def translate_by_hkbu_chatgpt_api(source_language, target_language, original_text, tone_of_voice, industry, model_name="gpt-35-turbo-16k"):
     # Prompt to provide translation
     translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+
+    start_time = time.time()
+
     res = ""
     try:
         # Translate by accessing HKBU ChatGPT API
@@ -46,7 +50,11 @@ def translate_by_hkbu_chatgpt_api(source_language, target_language, original_tex
         res_content = 'Error:', e, res
         return res_content
 
-    print(res_content)
+    end_time = time.time()
+    time_elapsed = end_time - start_time
+    print("Time Elapsed:", time_elapsed, "seconds")
+    print("Result content:", res_content)
+
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed

utils/translate/translate_openai.py

@@ -1,4 +1,5 @@
 import os
+import time
 from langchain_community.chat_models import ChatOpenAI
 from langchain.schema import HumanMessage
 from dotenv import load_dotenv
@@ -13,6 +14,9 @@ openai_api_key = os.environ.get("OPENAI_API_KEY")
 def translate_by_openai_api(source_language, target_language, original_text, tone_of_voice, industry, model_name="gpt-3.5-turbo-1106"):
     # Prompt to provide translation
     translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+
+    start_time = time.time()
+
     # Translate by accessing OpenAI API
     chat = ChatOpenAI(temperature=0.7, openai_api_key=openai_api_key, model_name=model_name)
     res = chat(
@@ -21,7 +25,12 @@ def translate_by_openai_api(source_language, target_language, original_text, ton
         ]
     )
     res_content = res.content
-    print(res_content)
+
+    end_time = time.time()
+    time_elapsed = end_time - start_time
+    print("Time Elapsed:", time_elapsed, "seconds")
+    print("Result content:", res_content)
+
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed

utils/translate/translate_openrouter.py

@@ -55,17 +55,17 @@ def translate_by_openrouter_api(source_language, target_language, original_text,
             temperature=0.7
         )
         if isinstance(res, tuple) and res[0] == 'Error':
-            chat_response = res
+            res_content = res
         else:
-            chat_response = res["choices"][0]["message"]["content"]
+            res_content = res["choices"][0]["message"]["content"]
     except Exception as e:
-        chat_response = 'Error:', e, res
+        res_content = 'Error:', e, res
 
     end_time = time.time()
     time_elapsed = end_time - start_time
     print("Time Elapsed:", time_elapsed, "seconds")
-    print("Chat Response:", chat_response)
+    print("Result content:", res_content)
 
-    rationale, translated_text = extract_json_from_response(target_language, chat_response)
+    rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed

utils/translate/translate_zhipuai.py

@@ -1,4 +1,5 @@
 import os
+import time
 from zhipuai import ZhipuAI
 from dotenv import load_dotenv
 
@@ -17,6 +18,9 @@ zhipuai_api_key = os.environ.get("ZHIPUAI_API_KEY")
 def translate_by_zhipuai_api(source_language, target_language, original_text, tone_of_voice, industry, model_name="glm-3-turbo"):
     # Prompt to provide translation
     translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+
+    start_time = time.time()
+
     # Translate by accessing ZhipuAI API
     chat = ZhipuAI(api_key=zhipuai_api_key)
     res = chat.chat.completions.create(
@@ -27,7 +31,12 @@ def translate_by_zhipuai_api(source_language, target_language, original_text, to
         temperature=0.7
     )
     res_content = res.choices[0].message.content
-    print(res_content)
+
+    end_time = time.time()
+    time_elapsed = end_time - start_time
+    print("Time Elapsed:", time_elapsed, "seconds")
+    print("Result content:", res_content)
+
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, translated_text
+    return translation_sample, rationale, translated_text, res_content, time_elapsed