clean code

app.py

@@ -17,101 +17,21 @@ client = OpenAI(
   api_key=os.getenv('OPENAI_API_KEY')
 )
 
-# hugging face setup
-#model_name = "mmnga/ELYZA-japanese-Llama-2-7b-instruct-gguf"
-API_URL = f"https://api-inference.huggingface.co/models/"
-#API_URL = f"https://api-inference.huggingface.co/models/{model_name}"
-headers = {"Authorization": f"Bearer {HF_TOKEN}"}
-
 # Global variable to control debug printing
 DEBUG_MODE = True
 
 
-
-
 def debug_print(*args, **kwargs):
     if DEBUG_MODE:
         print(*args, **kwargs)
 
-
-
-def translate_openai(input_text):
-
-    prompt = "Translate the following text into Japanese language: " + input_text
-
-    response = client.chat.completions.create( # get translation from GPT
-        messages=[
-            {
-                "role": "user",
-                "content": prompt,
-            }
-        ],
-        model="gpt-3.5-turbo",
-        temperature=0 # should be the same translation every time
-      )
-    translation = response.choices[0].message.content
-    debug_print("GPT translation:", translation)
-
-    return translation
-
-def assess(original_japanese, student_translation):
-
-    try:
-      # get the English translation
-      generated_translation = translate_hf(original_japanese)
-      debug_print("Generated translation:", generated_translation)
-    except Exception as e:
-      return "Error in processing translation.", str(e)
- 
-    try:
-      prompt = (f"Evaluate the student's English translation of Japanese for accuracy and naturalness. "
-            f"Original: {original_japanese}, "
-            f"Reference Translation: {generated_translation}, "
-            f"Student Translation: {student_translation}. "
-            "Highlight errors, suggest improvements, and note any nuances. Provide concise and very simple feedback for an English language learner aimed at improving their translation skills. Where possible, give concrete examples.")
-
-      debug_print(prompt)
-
-      # Evaluating the student's translation attempt
-      response = client.chat.completions.create(
-        messages=[
-            {
-                "role": "user",
-                "content": prompt,
-            }
-        ],
-        model="gpt-3.5-turbo",
-      )
-
-      debug_print("Full GPT response:", response)
-
-      debug_print("Generated translation:", generated_translation)
-                  
-      evaluation_feedback = response.choices[0].message.content
-      
-      return generated_translation, evaluation_feedback
-    except Exception as e:
-      return "Error in processing evaluation.", str(e)
-
-
-
 def generate_questions(input_prompt):
     """
     Generates EFL questions based on the input text using OpenAI's GPT-3.
     """
-    # response = openai.Completion.create(
-    #   engine="text-davinci-003",  # or another suitable engine
-    #   prompt=f"Generate 5 EFL (English as a Foreign Language) comprehension questions based on the following text:\n\n{text}",
-    #   temperature=0.5,
-    #   max_tokens=150,
-    #   top_p=1.0,
-    #   frequency_penalty=0.0,
-    #   presence_penalty=0.0
-    # )
-    # return response.choices[0].text.strip()
-
-
-    prompt=f"Generate 5 EFL (English as a Foreign Language) simple questions based on the following topic: {input_prompt}."
+   
+
+    prompt=f"Generate 5 simple questions for an EFL (English as a Foreign Language) based on the following topic: {input_prompt}"
 
     response = client.chat.completions.create(