change to conditional kogpt trintiy project

app.py

@@ -47,12 +47,13 @@ def infer(input_ids, max_length, temperature, top_k, top_p):
 
 
 # prompts
-st.title("삼행시의 달인 KoGPT입니다 🦄")
-st.write("텍스트를 입력하고 CTRL+Enter(CMD+Enter)을 누르세요 🤗")
+st.title("주어진 감정에 맞게 문장을 만드는 KoGPT입니다 🦄")
+st.write("좌측에 감정상태의 변화를 줘보세요.")
+st.write("입력하고 나서 CTRL+Enter(CMD+Enter)를 누르세요 🤗")
 
 # text and sidebars
-default_value = "페르소나"
-sent = st.text_area("Text", default_value, max_chars=4, height=275)
+default_value = "수상한 밤들이 계속되던 날 언젠가부터 나는"
+sent = st.text_area("Text", default_value, max_chars=30, height=275)
 max_length = st.sidebar.slider("생성 문장 길이를 선택해주세요!", min_value=42, max_value=64)
 temperature = st.sidebar.slider(
     "Temperature", value=1.0, min_value=0.0, max_value=1.0, step=0.05
@@ -93,67 +94,25 @@ def infer_sentence(
     generated_sequence = output_sequences[0]
     print(generated_sequence)
 
-    # print(f"=== GENERATED SEQUENCE {generated_sequence_idx + 1} ===")
-    # generated_sequences = generated_sequence.tolist()
     # Decode text
     text = tokenizer.decode(generated_sequence, clean_up_tokenization_spaces=True)
     print(text)
-    # Remove all text after the stop token
+
+    # Remove all text after the pad token
     stop_token = tokenizer.pad_token
     print(stop_token)
     text = text[: text.find(stop_token) if stop_token else None]
     print(text)
-
+    
+    # Remove condition sentence
     condition_index = find_nth(text, "문장이다", 2)
     text = text[condition_index + 5 :]
     text = text.strip()
     return text
 
 
-def make_residual_conditional_samhaengshi(input_letter, condition_sentence):
-    # make letter string into
-    list_samhaengshi = []
-
-    # initializing text and index for iteration purpose
-    index = 0
-
-    # iterating over the input letter string
-    for index, letter_item in enumerate(input_letter):
-        # initializing the input_letter
-        if index == 0:
-            residual_text = letter_item
-            # print('residual_text:', residual_text)
-
-        # infer and add to the output
-        conditional_input = f"{condition_sentence} {residual_text}"
-        inferred_sentence = infer_sentence(conditional_input, tokenizer)
-        if index != 0:
-            # remove previous sentence from the output
-            print("inferred_sentence:", inferred_sentence)
-            inferred_sentence = inferred_sentence.replace(
-                list_samhaengshi[index - 1], ""
-            ).strip()
-        else:
-            pass
-        list_samhaengshi.append(inferred_sentence)
-
-        # until the end of the input_letter, give the previous residual_text to the next iteration
-        if index < len(input_letter) - 1:
-            residual_sentence = list_samhaengshi[index]
-            next_letter = input_letter[index + 1]
-            residual_text = (
-                f"{residual_sentence} {next_letter}"  #  previous sentence + next letter
-            )
-            print("residual_text", residual_text)
-
-        elif index == len(input_letter) - 1:  # end of the input_letter
-            # Concatenate strings in the list without intersection
-
-            return list_samhaengshi
-
-
-return_text = make_residual_conditional_samhaengshi(
-    input_letter=sent, condition_sentence=condition_sentence
+return_text = infer_sentence(
+    condition_plus_input=condition_plus_input, tokenizer=tokenizer
 )
 
 print(return_text)