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MarwanAshraf22
commited on
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4da3b8a
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Parent(s):
9063d8d
Update app.py
Browse files
app.py
CHANGED
@@ -6,6 +6,7 @@ from nltk.corpus import wordnet
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import nltk
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nltk.download('wordnet')
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def generate_text(prompt, temperature=0.7, top_k=50, repetition_penalty=1.2, max_length=None, min_length=10):
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text_model = "gpt2"
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tokenizer = AutoTokenizer.from_pretrained(text_model)
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@@ -80,37 +81,26 @@ try :
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new_image1 = generated_image1.resize((700, 500))
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st.image(new_image1, use_column_width=True)
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intro_text = generate_text(f'introduction about : {generated_text}', min_length=100, max_length=200)
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intro_text = intro_text.replace(f"introduction about : {generated_text}", "")
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st.write(intro_text.strip()) # Display the generated introduction text
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body_text1 = generate_text(f'article about : {generated_text}', min_length=100, max_length=150)
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body_text1 = body_text1.replace(f"article about : {generated_text}", "")
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st.write(body_text1.strip()) # Display the generated introduction text
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body_text2 = generate_text(f'article about : {generated_text}', min_length=200, max_length=300)
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body_text2 = body_text2.replace(f"{generated_text}", "")
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st.write(body_text2.strip()) # Display the generated introduction text
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conclusion_text = generate_text(f'conclusion about : {generated_text}', min_length=100, max_length=200)
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conclusion_text = conclusion_text.replace(f"conclusion about : {generated_text}", "")
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st.write(conclusion_text.strip()) # Display the generated introduction text
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st.subheader("Introduction")
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st.write(intro_text)
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modified_prompt = generated_text + 'bright'
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generated_image2 = generate_image(modified_prompt)
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new_image2 = generated_image2.resize((700, 300))
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st.image(new_image2, use_column_width=True)
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col1, col2 = st.columns(2)
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with col1:
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st.subheader("Body")
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with col2:
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modified_prompt2 = generated_text + 'shade'
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@@ -118,14 +108,22 @@ try :
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st.markdown("<br><br><br><br>", unsafe_allow_html=True)
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st.image(generated_image3, use_column_width=True)
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modified_prompt3 = generated_text + title
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generated_image4 = generate_image(modified_prompt3)
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new_image3 = generated_image4.resize((700, 300))
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st.image(new_image3, use_column_width=True)
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st.subheader("Conclusion")
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else:
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st.warning("Please input keywords to generate content.")
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import nltk
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nltk.download('wordnet')
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def generate_text(prompt, temperature=0.7, top_k=50, repetition_penalty=1.2, max_length=None, min_length=10):
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text_model = "gpt2"
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tokenizer = AutoTokenizer.from_pretrained(text_model)
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new_image1 = generated_image1.resize((700, 500))
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st.image(new_image1, use_column_width=True)
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# Introduction
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st.subheader("Introduction")
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intro_text = generate_text(f'introduction about : {generated_text}', min_length=100, max_length=200)
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intro_text = intro_text.replace(f"introduction about : {generated_text}", "")
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st.write(intro_text.strip()) # Display the generated introduction text
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modified_prompt = generated_text + 'bright'
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generated_image2 = generate_image(modified_prompt)
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new_image2 = generated_image2.resize((700, 300))
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st.image(new_image2, use_column_width=True)
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# Body 1
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col1, col2 = st.columns(2)
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with col1:
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st.subheader("Body")
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body_text1 = generate_text(f'article about : {generated_text}', min_length=100, max_length=150)
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body_text1 = body_text1.replace(f"article about : {generated_text}", "")
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st.write(body_text1.strip()) # Display the generated introduction text
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with col2:
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modified_prompt2 = generated_text + 'shade'
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st.markdown("<br><br><br><br>", unsafe_allow_html=True)
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st.image(generated_image3, use_column_width=True)
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# Body 2
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body_text2 = generate_text(f'article about : {generated_text}', min_length=200, max_length=300)
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body_text2 = body_text2.replace(f"{generated_text}", "")
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st.write(body_text2.strip()) # Display the generated introduction text
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modified_prompt3 = generated_text + title
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generated_image4 = generate_image(modified_prompt3)
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new_image3 = generated_image4.resize((700, 300))
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st.image(new_image3, use_column_width=True)
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# Conclusion
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st.subheader("Conclusion")
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conclusion_text = generate_text(f'conclusion about : {generated_text}', min_length=100, max_length=200)
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conclusion_text = conclusion_text.replace(f"conclusion about : {generated_text}", "")
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st.write(conclusion_text.strip()) # Display the generated introduction text
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else:
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st.warning("Please input keywords to generate content.")
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