cover generator removed

README.md

@@ -1,5 +1,5 @@
 ---
-title: AI Blog Post Generator
+title: Blog Post Generator
 emoji: 📝
 colorFrom: blue
 colorTo: green

app.py

@@ -1,66 +1,81 @@
 import gradio as gr
 import torch
 from transformers import pipeline
-from diffusers import StableDiffusionPipeline
+import logging
+
+# Set up logging
+logging.basicConfig(
+    level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
+)
 
 ARTICLE_GENERATOR_MODEL = "gpt2"
 SUMMARIZER_MODEL = "Falconsai/text_summarization"
 TITLE_GENERATOR_MODEL = "czearing/article-title-generator"
-IMAGE_GENERATOR_MODEL = "prompthero/openjourney-v4"
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"{DEVICE = }")
+logging.info(f"Using device: {DEVICE}")
 
+logging.info("Initializing models...")
 text_generator = pipeline(
     "text-generation", model=ARTICLE_GENERATOR_MODEL, device=DEVICE
 )
 summarizer = pipeline("summarization", model=SUMMARIZER_MODEL, device=DEVICE)
 title_generator = pipeline(
-    "text2text-generation",
-    model=TITLE_GENERATOR_MODEL,
-    device=DEVICE,
+    "text2text-generation", model=TITLE_GENERATOR_MODEL, device=DEVICE
 )
-image_generator = StableDiffusionPipeline.from_pretrained(
-    IMAGE_GENERATOR_MODEL,
-    torch_dtype=torch.float16 if DEVICE == "cuda" else torch.float32,
-)
-image_generator = image_generator.to(DEVICE)
+logging.info("Models initialized successfully")
 
 
-def generate_blog_post(query, article_length, title_length, summary_length):
-    print("Generating article.")
-    article = text_generator(query, max_length=article_length, num_return_sequences=1)[
-        0
-    ]["generated_text"]
-    print(f"{article = }")
+def generate_article(query, max_new_tokens):
+    logging.info(f"Generating article for query: {query}")
+    article = text_generator(
+        query,
+        max_new_tokens=max_new_tokens,
+        num_return_sequences=1,
+    )[0]["generated_text"]
+    logging.debug(f"Generated article: {article[:100]}...")
+    return article
+
+
+def generate_title(article):
+    logging.info("Generating title")
+    title = title_generator(article, num_return_sequences=1)[0]["generated_text"]
+    logging.debug(f"Generated title: {title}")
+    return title
 
-    print("Generating the title.")
-    title = title_generator(article, max_length=title_length, num_return_sequences=1)[
-        0
-    ]["generated_text"]
-    print(f"{title = }")
 
-    print("Generating the summary.")
+def generate_summary(article):
+    logging.info("Generating summary")
     summary = summarizer(
         article,
-        max_length=summary_length,
-        min_length=min(30, summary_length),
         do_sample=False,
-    )[0]["summary_text"]
-    print(f"{summary = }")
+    )[
+        0
+    ]["summary_text"]
+    logging.debug(f"Generated summary: {summary}")
+    return summary
+
+
+def generate_blog_post(query, max_new_tokens):
+    logging.info("Starting blog post generation")
 
-    print("Generating the cover image.")
-    image = image_generator(
-        summary, num_inference_steps=40, guidance_scale=7.5, width=512, height=512
-    ).images[0]
+    logging.info("Generating article")
+    article = generate_article(query, max_new_tokens)
 
-    return title, summary, article, image
+    logging.info("Generating title")
+    title = generate_title(article)
+
+    logging.info("Generating summary")
+    summary = generate_summary(article)
+
+    logging.info("Blog post generation completed")
+    return title, summary, article
 
 
 with gr.Blocks() as iface:
     gr.Markdown("# Blog Post Generator")
     gr.Markdown(
-        "Enter a topic, and I'll generate a blog post with a title, cover image, and optional summary!"
+        "Enter a topic, and I'll generate a blog post with a title and summary!"
     )
 
     with gr.Row():
@@ -69,56 +84,44 @@ with gr.Blocks() as iface:
     with gr.Row():
         generate_button = gr.Button("Generate Blog Post", size="sm")
 
+    gr.Examples(
+        examples=[
+            "The future of artificial intelligence in healthcare",
+            "Top 10 travel destinations for nature lovers",
+            "How to start a successful online business in 2024",
+            "The impact of climate change on global food security",
+        ],
+        inputs=input_prompt,
+    )
+
     with gr.Row():
         with gr.Column(scale=2):
             with gr.Blocks() as title_block:
                 gr.Markdown("## Title")
-
-                with gr.Accordion("Options", open=False):
-                    title_length = gr.Slider(
-                        minimum=10, maximum=50, value=30, step=5, label="Title Length"
-                    )
                 title_output = gr.Textbox(label="Title")
 
             with gr.Blocks() as body_block:
                 gr.Markdown("## Body")
-
+                article_output = gr.Textbox(label="Article", lines=30)
                 with gr.Accordion("Options", open=False):
-                    article_length = gr.Slider(
-                        minimum=100,
-                        maximum=1000,
+                    max_new_tokens = gr.Slider(
+                        minimum=20,
+                        maximum=500,
                         value=500,
-                        step=50,
-                        label="Article Length",
+                        step=10,
+                        label="Max New Tokens",
                     )
-                article_output = gr.Textbox(label="Article", lines=10)
 
         with gr.Column(scale=1):
-            with gr.Blocks() as image_block:
-                gr.Markdown("## Cover Image")
-                image_output = gr.Image(label="Cover Image")
-
             with gr.Blocks() as summary_block:
                 gr.Markdown("## Summary")
-                with gr.Accordion("Options", open=False):
-                    summary_length = gr.Slider(
-                        minimum=30,
-                        maximum=200,
-                        value=100,
-                        step=10,
-                        label="Summary Length",
-                    )
                 summary_output = gr.Textbox(label="Summary", lines=5)
 
-    job = generate_button.click(
+    generate_button.click(
         generate_blog_post,
-        inputs=[
-            input_prompt,
-            article_length,
-            title_length,
-            summary_length,
-        ],
-        outputs=[title_output, summary_output, article_output, image_output],
+        inputs=[input_prompt, max_new_tokens],
+        outputs=[title_output, summary_output, article_output],
     )
 
-iface.launch()
+logging.info("Launching Gradio interface")
+iface.queue().launch()