Update app.py

app.py

@@ -1,24 +1,23 @@
-import torch
 import streamlit as st
+import torch
 from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
 from diffusers import StableDiffusionPipeline
-from PIL import Image
+from nltk.corpus import wordnet
 
-text_model = "gpt2"
-tokenizer = AutoTokenizer.from_pretrained(text_model)
-model = AutoModelForCausalLM.from_pretrained(text_model)
 
-image_model = "runwayml/stable-diffusion-v1-5"
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-generator = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    device=0 if torch.cuda.is_available() else -1
-)
 
 def generate_text(prompt, temperature=0.7, top_k=50, repetition_penalty=1.2, max_length=None, min_length=10):
+    text_model = "gpt2"
+    tokenizer = AutoTokenizer.from_pretrained(text_model)
+    model = AutoModelForCausalLM.from_pretrained(text_model)
+
+    generator = pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer,
+        device=0 if torch.cuda.is_available() else -1
+    )
+
     return generator(
         prompt,
         max_length=max_length,
@@ -32,71 +31,111 @@ def generate_text(prompt, temperature=0.7, top_k=50, repetition_penalty=1.2, max
     )[0]["generated_text"]
 
 def generate_image(prompt):
+    image_model = "runwayml/stable-diffusion-v1-5"
+    device = "cuda" if torch.cuda.is_available() else "cpu"
     pipe = StableDiffusionPipeline.from_pretrained(image_model, torch_dtype=torch.float32)
     pipe = pipe.to(device)
     image = pipe(prompt).images[0]
     return image
 
-st.title("AI-Generated Blog Post")
+def get_synonyms(word):
+    synonyms = set()
+    for syn in wordnet.synsets(word):
+        for lemma in syn.lemmas():
+            synonyms.add(lemma.name().replace('_', ' '))
+    return list(synonyms)
+
+st.title(":black[_AI-Generated Blog Post_]")
 
 title = st.text_input("Topic of the Article")
-keywords_input = st.text_input("Enter Some Keywords About The Topic (Separate keywords with commas)")
-keywords = [word.strip() for word in keywords_input.split(',')]
-keywords.append(title)
 
-if st.button('Generate Article'):
-    if keywords:
-        generated_text = " ".join(keywords)
 
-        formatted_title = title.capitalize()
+keywords_selection = st.selectbox('Do you want to select Keywords Manually or Automatic',['','Manually','Automatic'])
+
+if keywords_selection == 'Manually' :
+    keywords_input = st.text_input("Enter Some Keywords About The Topic (Separate keywords with commas)")
+    keywords = [word.strip() for word in keywords_input.split(',')]
+    keywords.append(title)
+
+if keywords_selection == 'Automatic' :
+    keywords = get_synonyms(title)
+    st.write(f'Your keywords Are {keywords}')
+
+try :
+    if st.button('Generate Article'):
+        if keywords:
+            generated_text = " ".join(keywords)
+            formatted_title = title.capitalize()
+
+            st.markdown(
+                f"<h1 style='text-align: center; color: blue; font-size: 70px;'>{formatted_title}</h1>",
+                unsafe_allow_html=True
+            )
+
+
+
+            col1, col2, col3 = st.columns([1, 2, 1])
+            with col2:
+                generated_image1 = generate_image(generated_text)
+                new_image1 = generated_image1.resize((700, 500))
+                st.image(new_image1, use_column_width=True)
+
+            intro_text = generate_text(f'introduction about : {generated_text}', min_length=100, max_length=200)
+            intro_text = intro_text.replace(f"introduction about : {generated_text}", "")
+            st.write(intro_text.strip())  # Display the generated introduction text
+
+            body_text1 = generate_text(f'article about : {generated_text}', min_length=100, max_length=150)
+            body_text1 = body_text1.replace(f"article about : {generated_text}", "")
+            st.write(body_text1.strip())  # Display the generated introduction text
+
+            body_text2 = generate_text(f'article about : {generated_text}', min_length=200, max_length=300)
+            body_text2 = body_text2.replace(f"{generated_text}", "")
+            st.write(body_text2.strip())  # Display the generated introduction text
+
+            conclusion_text = generate_text(f'conclusion about : {generated_text}', min_length=100, max_length=200)
+            conclusion_text = conclusion_text.replace(f"conclusion about : {generated_text}", "")
+            st.write(conclusion_text.strip())  # Display the generated introduction text
 
-        st.markdown(
-            f"<h1 style='text-align: center; color: blue; font-size: 70px;'>{formatted_title}</h1>",
-            unsafe_allow_html=True
-        )
 
-        generated_image1 = generate_image(generated_text)
 
-        col1, col2, col3 = st.columns([1, 2, 1])
-        with col2:
-            new_image1 = generated_image1.resize((700, 300))  # Resize the image here
-            st.image(new_image1, use_column_width=True)
+            st.subheader("Introduction")
+            st.write(intro_text)
+            modified_prompt = generated_text + 'bright'
+            generated_image2 = generate_image(modified_prompt)
 
-        intro_text = generate_text(generated_text, min_length=100, max_length=200)
-        body_text1 = generate_text(generated_text, min_length=200, max_length=250)
-        body_text2 = generate_text(generated_text, min_length=300, max_length=400)
-        conclusion_text = generate_text(generated_text, min_length=100, max_length=200)
+            new_image2 = generated_image2.resize((700, 300))
+            st.image(new_image2, use_column_width=True)
 
-        st.header("Introduction")
-        st.write(intro_text)
-        modified_prompt = generated_text + ' bright'
-        generated_image2 = generate_image(modified_prompt)
 
-        new_image2 = generated_image1.resize((700, 300))  # Resize the image here
-        st.image(new_image2, use_column_width=True)
+            col1, col2 = st.columns(2)
+            with col1:
+                st.subheader("Body")
+                st.write(body_text1)
 
+            with col2:
+                modified_prompt2 = generated_text + 'shade'
+                generated_image3 = generate_image(modified_prompt2)
+                st.markdown("<br><br><br><br>", unsafe_allow_html=True)
+                st.image(generated_image3, use_column_width=True)
 
-        col1, col2 = st.columns(2)
-        with col1:
-            st.header("Body")
-            st.write(body_text1)
+            st.write(body_text2)
+            modified_prompt3 = generated_text + title
+            generated_image4 = generate_image(modified_prompt3)
+            new_image3 = generated_image4.resize((700, 300))
+            st.image(new_image3, use_column_width=True)
 
-        with col2:
-            modified_prompt2 = generated_text + ' shade'
-            generated_image3 = generate_image(modified_prompt2)
-            st.markdown("<br><br><br><br>", unsafe_allow_html=True)  # Add vertical space
-            st.image(generated_image3, use_column_width=True)
+            st.subheader("Conclusion")
+            st.write(conclusion_text)
+        else:
+            st.warning("Please input keywords to generate content.")
 
-        st.write(body_text2)
+except :
+    st.warning('Please Enter Title and Keywords')
 
-        st.header("Conclusion")
-        st.write(conclusion_text)
-    else:
-        st.warning("Please input keywords to generate content.")
 
 st.sidebar.title("Instructions")
 st.sidebar.write(
-    "1. Enter keywords related to the topic you want to generate content about."
+    "1. Enter title and keywords related to the topic you want to generate content about."
     "\n2. Click 'Generate Article' to create the AI-generated blog post."
     "\n3. Explore the Introduction, Body, and Conclusion sections of the generated content."
 )