Added database storage, updated the parameters obtained from LLM returns

app/routes/text_translator.py

@@ -1,5 +1,8 @@
 import os
 import gradio as gr
+from supabase import create_client, Client
+from dotenv import load_dotenv
+
 from utils.translate.translate_deepl import translate_by_deepl_api
 from utils.translate.translate_volcengine import translate_by_volcengine_api
 from utils.translate.translate_hkbu_chatgpt import translate_by_hkbu_chatgpt_api
@@ -7,10 +10,14 @@ from utils.translate.translate_openrouter import translate_by_openrouter_api
 from utils.translate.translate_google import translate_by_google_api
 from utils.translate.translate_baichuan import translate_by_baichuan_api
 from utils.translate.translate_zhipuai import translate_by_zhipuai_api
-from dotenv import load_dotenv
 
 load_dotenv()
 passcode_key = os.getenv("PASSCODE_KEY")
+supabase_url: str = os.environ.get("SUPABASE_URL")
+supabase_key: str = os.environ.get("SUPABASE_KEY")
+
+# Create a new Supabase client
+supabase: Client = create_client(supabase_url, supabase_key)
 
 # Model Dictionary for Translate by HKBU ChatGPT API
 model_dict_translate_by_hkbu_chatgpt_api = {
@@ -32,6 +39,13 @@ model_dict_translate_by_zhipuai_api = {
 
 
 def translate_text(source_language, target_language, original_text, tone_of_voice, industry, model, passcode):
+    translation_sample = None
+    rationale = None
+    translated_text = ""
+    res_content = None
+    translate_time = None
+    llm_time = None
+
     # Check if the passcode is correct
     if passcode != passcode_key:
         return "The passcode is incorrect. Please try again."
@@ -46,35 +60,52 @@ def translate_text(source_language, target_language, original_text, tone_of_voic
         return "The original text is too long. Please enter a text with less than 1000 characters."
 
     # Generate translated text
-    translated_text = ""
     if model == "DeepL":
-        translated_text = translate_by_deepl_api(source_language, target_language, original_text)
+        translated_text, translate_time = translate_by_deepl_api(source_language, target_language, original_text)
     elif model == "Volcengine":
-        translated_text = translate_by_volcengine_api(source_language, target_language, original_text)
+        translated_text, translate_time = translate_by_volcengine_api(source_language, target_language, original_text)
     elif model in model_dict_translate_by_hkbu_chatgpt_api:
-        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_hkbu_chatgpt_api(
+        translation_sample, rationale, translated_text, res_content, translate_time, llm_time = 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, rationale, translated_text, res_content, time_elapsed = translate_by_openrouter_api(
+        translation_sample, rationale, translated_text, res_content, translate_time, llm_time = 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, rationale, translated_text, res_content, time_elapsed = translate_by_google_api(
+        translation_sample, rationale, translated_text, res_content, translate_time, llm_time = translate_by_google_api(
             source_language, target_language, original_text, tone_of_voice, industry
         )
     elif model == "Baichuan AI (Baichuan2)":
-        translation_sample, rationale, translated_text, res_content, time_elapsed = translate_by_baichuan_api(
+        translation_sample, rationale, translated_text, res_content, translate_time, llm_time = 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, rationale, translated_text, res_content, time_elapsed = translate_by_zhipuai_api(
+        translation_sample, rationale, translated_text, res_content, translate_time, llm_time = translate_by_zhipuai_api(
             source_language, target_language, original_text, tone_of_voice, industry,
             model_dict_translate_by_zhipuai_api[model]
         )
 
+    # Insert the translation record into the database
+    supabase.table("translations").insert([
+        {
+            "source_language": source_language,
+            "target_language": target_language,
+            "original_text": original_text,
+            "tone_of_voice": tone_of_voice,
+            "industry": industry,
+            "model": model,
+            "translate_sample": translation_sample,
+            "rationale": rationale,
+            "translated_text": translated_text,
+            "res_content": res_content,
+            "translate_time": translate_time,
+            "llm_time": llm_time,
+        }
+    ]).execute()
+
     return translated_text
 
 

utils/prompts/translation_prompt.py

@@ -5,6 +5,9 @@ from utils.utils.other_utils import get_language_code
 
 # Translation prompt
 def generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry):
+    print("Generating translation prompt...")
+
+    # Languages that should use DeepL API
     languages_should_use_deepl = ["Chinese", "English (UK)", "English (US)", "French", "German", "Spanish",
                                   "Portuguese (Brazilian)", "Portuguese (European)", "Italian", "Dutch", "Polish",
                                   "Russian"]
@@ -13,11 +16,9 @@ def generate_translation_prompt(source_language, target_language, original_text,
     print(f"Target language: {target_language}, Language code: {get_language_code(target_language)}, Should use DeepL: {target_language in languages_should_use_deepl}")
     # Generate the translation sample
     if source_language in languages_should_use_deepl and target_language in languages_should_use_deepl:
-        print("Using DeepL API")
-        translation_sample = translate_by_deepl_api(source_language, target_language, original_text)
+        translation_sample, translate_time = translate_by_deepl_api(source_language, target_language, original_text)
     else:
-        print("Using Volcengine API")
-        translation_sample = translate_by_volcengine_api(source_language, target_language, original_text)
+        translation_sample, translate_time = translate_by_volcengine_api(source_language, target_language, original_text)
 
     # Generate the translation prompt
     translation_prompt = f"""{source_language}:
@@ -40,6 +41,7 @@ Your response should be in the following json format:
 }}
 ```"""
 
-    print(translation_prompt)
+    print("Translate Time:", translate_time, "seconds")
+    print("Translation Sample:", translation_sample)
 
-    return translation_sample, translation_prompt
+    return translation_sample, translation_prompt, translate_time

utils/translate/translate_baichuan.py

@@ -14,7 +14,7 @@ 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)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -28,10 +28,10 @@ def translate_by_baichuan_api(source_language, target_language, original_text, t
     res_content = res.content
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time

utils/translate/translate_deepl.py

@@ -1,4 +1,5 @@
 import os
+import time
 import deepl
 from dotenv import load_dotenv
 
@@ -9,8 +10,17 @@ deepl_api_key = os.environ.get("DEEPL_API_KEY")
 
 
 def translate_by_deepl_api(source_language, target_language, original_text):
+    print("Using DeepL API")
+
+    start_time = time.time()
+
     target_language_code = get_language_code(target_language).upper()
     deepl_client = deepl.Translator(deepl_api_key)
     translated_text = deepl_client.translate_text(original_text, target_lang=target_language_code)
 
-    return translated_text.text
+    end_time = time.time()
+    translate_time = end_time - start_time
+    print("Time Elapsed:", translate_time, "seconds")
+    print("Result content:", translated_text.text)
+
+    return translated_text.text, translate_time

utils/translate/translate_google.py

@@ -12,7 +12,7 @@ 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)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -22,10 +22,10 @@ def translate_by_google_api(source_language, target_language, original_text, ton
     res_content = res.content
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time

utils/translate/translate_hkbu_chatgpt.py

@@ -31,7 +31,7 @@ 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)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -51,10 +51,10 @@ def translate_by_hkbu_chatgpt_api(source_language, target_language, original_tex
         return res_content
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time

utils/translate/translate_openai.py

@@ -13,7 +13,7 @@ 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)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -27,10 +27,10 @@ def translate_by_openai_api(source_language, target_language, original_text, ton
     res_content = res.content
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time

utils/translate/translate_openrouter.py

@@ -40,7 +40,7 @@ def translate_by_openrouter_api(source_language, target_language, original_text,
     print("Use OpenRouter API")
 
     # Prompt to provide translation
-    translation_sample, translation_prompt = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -62,10 +62,10 @@ def translate_by_openrouter_api(source_language, target_language, original_text,
         res_content = 'Error:', e, res
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time

utils/translate/translate_volcengine.py

@@ -1,4 +1,5 @@
 import os
+import time
 import json
 from volcengine.ApiInfo import ApiInfo
 from volcengine.Credentials import Credentials
@@ -14,6 +15,10 @@ k_secret_key = os.environ.get("K_SECRET_KEY")
 
 
 def translate_by_volcengine_api(source_language, target_language, original_text):
+    print("Using Volcengine API")
+
+    start_time = time.time()
+
     source_language_code = get_language_code(source_language)
     target_language_code = get_language_code(target_language)
 
@@ -41,4 +46,9 @@ def translate_by_volcengine_api(source_language, target_language, original_text)
     translated_dict = json.loads(res)
     translated_text = translated_dict["TranslationList"][0]["Translation"]
 
-    return translated_text
+    end_time = time.time()
+    translate_time = end_time - start_time
+    print("Time Elapsed:", translate_time, "seconds")
+    print("Result content:", translated_text)
+
+    return translated_text, translate_time

utils/translate/translate_zhipuai.py

@@ -17,7 +17,7 @@ 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)
+    translation_sample, translation_prompt, translate_time = generate_translation_prompt(source_language, target_language, original_text, tone_of_voice, industry)
 
     start_time = time.time()
 
@@ -33,10 +33,10 @@ def translate_by_zhipuai_api(source_language, target_language, original_text, to
     res_content = res.choices[0].message.content
 
     end_time = time.time()
-    time_elapsed = end_time - start_time
-    print("Time Elapsed:", time_elapsed, "seconds")
+    llm_time = end_time - start_time
+    print("Time Elapsed:", llm_time, "seconds")
     print("Result content:", res_content)
 
     rationale, translated_text = extract_json_from_response(target_language, res_content)
 
-    return translation_sample, rationale, translated_text, res_content, time_elapsed
+    return translation_sample, rationale, translated_text, res_content, translate_time, llm_time