Update app.py

app.py

@@ -10,7 +10,6 @@ import asyncio
 
 # Download NLTK data
 download('punkt')
-download('punkt_tab')
 
 # Configure Gemini API using environment variable
 api_key = os.environ.get("GEMINI_API_KEY")
@@ -19,54 +18,29 @@ if not api_key:
 
 genai.configure(api_key=api_key)
 
-# Use gemini-1.5-flash for faster and more accessible text analysis
-try:
-    model = genai.GenerativeModel('gemini-1.5-flash')
-except Exception as e:
-    # Fallback: List available models if the specified model is not found
-    print(f"Error initializing model: {str(e)}")
-    print("Available models:")
-    for m in genai.list_models():
-        print(m.name)
-    raise ValueError("Failed to initialize gemini-1.5-flash. Check available models above and update the model name.")
-
-# Prompt for Gemini to analyze text with specified output format
+model = genai.GenerativeModel('gemini-1.5-flash')
+
 PROMPT = """
 You are an AI content reviewer. Analyze the provided text for the following:
 1. *Grammar Issues*: Identify and suggest corrections for grammatical errors.
 2. *Legal Policy Violations*: Flag content that may violate common legal policies (e.g., copyright infringement, defamation, incitement to violence).
 3. *Crude/Abusive Language*: Detect crude, offensive, or abusive language.
 4. *Sensitive Topics*: Identify content related to sensitive topics such as racism, gender bias, or other forms of discrimination.
-
 Return the results in the following markdown format:
 # Blog Review Report
-
 ## Grammar Corrections
 1. [Heading of issue]
    - CONTENT: [Exact line or part of text with the issue]
    - SUGGESTION: [Suggested correction]
    - ISSUE: [Description of the issue]
-
-2. [Heading of next issue]
-   - CONTENT: [Exact line or part of text with the issue]
-   - SUGGESTION: [Suggested correction]
-   - ISSUE: [Description of the issue]
-
-[Continue numbering for additional issues or state "None detected"]
-
 ## Legal Policy Violations
 - CONTENT: [Exact line or part of text with the issue]
   SUGGESTION: [Suggested action or correction]
   ISSUE: [Description of the legal violation]
-[Or state "None detected"]
-
 ## Crude/Abusive Language
 - [List instances of crude or abusive language or "None detected"]
-
 ## Sensitive Topics
 - [List instances of sensitive topics or "None detected"]
-
-For each issue, provide the exact text, a suggested correction or action, and a concise explanation. Be precise and ensure the output strictly follows the specified format.
 """
 
 async def fetch_url_content(url):
@@ -74,161 +48,94 @@ async def fetch_url_content(url):
         response = requests.get(url, timeout=10)
         response.raise_for_status()
         soup = BeautifulSoup(response.text, 'html.parser')
-        # Extract text from common content tags
         content = ' '.join([p.get_text(strip=True) for p in soup.find_all(['p', 'article', 'div'])])
         return content if content else "No readable content found on the page."
     except Exception as e:
         return f"Error fetching URL: {str(e)}"
 
 async def review_blog(text_input, url_input):
-    # Start loading effect immediately
-    button_text = "Processing..."
-
-    # Determine input type based on which field is populated
     if text_input and not url_input:
-        input_type = "Text"
         input_text = text_input
     elif url_input and not text_input:
-        input_type = "URL"
-        input_text = url_input
+        input_text = await fetch_url_content(url_input)
+        if input_text.startswith("Error"):
+            return "Review Blog", input_text, gr.update(visible=False), ""
     else:
-        return "Review Blog", "Error: Please provide input in either the Text or URL tab, but not both.", gr.update(visible=False)
-
-    # Handle empty input
-    if not input_text:
-        return "Review Blog", "Error: No input provided.", gr.update(visible=False)
+        return "Review Blog", "Error: Please provide input in either the Text or URL tab, but not both.", gr.update(visible=False), ""
 
     try:
-        async with asyncio.timeout(30):  # 30-second timeout for entire process
-            # Handle URL input
-            if input_type == "URL":
-                button_text = "Fetching content..."
-                input_text = await fetch_url_content(input_text)
-                if input_text.startswith("Error"):
-                    return "Review Blog", input_text, gr.update(visible=False)
-
-            # Tokenize input for analysis
-            sentences = sent_tokenize(input_text)
-            analysis_text = "\n".join(sentences)
-
-            # Update button for API call
-            button_text = "Generating report..."
-            try:
-                response = await asyncio.to_thread(model.generate_content, PROMPT + "\n\nText to analyze:\n" + analysis_text)
-                report = response.text.strip()
-                # Ensure the response is markdown by removing any code fences
-                report = re.sub(r'^markdown\n|$', '', report, flags=re.MULTILINE)
-            except Exception as e:
-                report = f"Error analyzing content with Gemini: {str(e)}. Please check your API key, network connection, or model availability."
-                # Fallback: List available models for debugging
-                print("Available models:")
-                for m in genai.list_models():
-                    print(m.name)
-                return "Review Blog", report, gr.update(visible=False)
-
-            # Create a temporary file to store the report
-            try:
-                with tempfile.NamedTemporaryFile(mode='w', suffix='.md', delete=False, encoding='utf-8') as temp_file:
-                    temp_file.write(report)
-                    temp_file_path = temp_file.name
-                # Add note to scroll to report
-                report = f"**Report generated, please scroll down to view.**\n\n{report}"
-                return "Review Blog", report, gr.update(visible=True, value=temp_file_path)
-            except Exception as e:
-                return "Review Blog", f"Error creating temporary file: {str(e)}", gr.update(visible=False)
-
+        sentences = sent_tokenize(input_text)
+        analysis_text = "\n".join(sentences)
+        response = await asyncio.to_thread(model.generate_content, PROMPT + "\n\nText to analyze:\n" + analysis_text)
+        report = response.text.strip()
+
+        suggestions = re.findall(r'- CONTENT: (.*?)\n\s*SUGGESTION: (.*?)\n\s*ISSUE: (.*?)\n', report, re.DOTALL)
+        highlighted = input_text
+        for content, suggestion, issue in suggestions:
+            highlighted = highlighted.replace(content, f'<span style="background-color: #ffcccc;" title="{issue} | Suggested: {suggestion}">{content}</span>')
+
+        with tempfile.NamedTemporaryFile(mode='w', suffix='.md', delete=False, encoding='utf-8') as temp_file:
+            temp_file.write(report)
+            temp_file_path = temp_file.name
+
+        report = f"**Report generated, please scroll down to view.**\n\n{report}"
+        return "Review Blog", report, gr.update(visible=True, value=temp_file_path), highlighted
     except asyncio.TimeoutError:
-        return "Timeout", "Error: Process timed out after 30 seconds.", gr.update(visible=False)
+        return "Timeout", "Error: Process timed out after 30 seconds.", gr.update(visible=False), ""
 
-# Custom CSS for hover effect, loading state, and Inter font
 custom_css = """
-@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap');
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
 .gradio-container {
     font-family: 'Inter', sans-serif !important;
-    background-color: #f9f9f9;
 }
 .review-btn {
     transition: all 0.3s ease;
-    font-weight: 600;
-    font-size: 16px;
-    background-color: #1f2937;
+    font-weight: 500;
+    background-color: #2c3e50;
     color: white;
-    border-radius: 12px;
-    padding: 12px 24px;
-    margin-top: 10px;
+    border-radius: 8px;
+    padding: 10px 20px;
+    position: relative;
 }
 .review-btn:hover {
-    background-color: #10b981;
-    transform: scale(1.03);
+    background-color: #4CAF50;
+    color: white;
+    transform: scale(1.05);
 }
 .review-btn:disabled {
-    opacity: 0.6;
+    opacity: 0.7;
     cursor: not-allowed;
 }
-.review-btn:disabled::before {
-    content: '';
-    display: inline-block;
-    width: 16px;
-    height: 16px;
-    border: 3px solid #fff;
-    border-radius: 50%;
-    border-top-color: transparent;
-    animation: spin 1s linear infinite;
-    margin-right: 8px;
-    vertical-align: middle;
-}
-@keyframes spin {
-    0% { transform: rotate(0deg); }
-    100% { transform: rotate(360deg); }
+.tab-nav button {
+    font-family: 'Inter', sans-serif;
+    font-weight: 500;
 }
 input, textarea {
     font-family: 'Inter', sans-serif;
-    font-size: 15px;
-    padding: 10px;
-    border-radius: 8px;
 }
 """
 
-with gr.Blocks(theme=gr.themes.Base(), css=custom_css) as demo:
-    gr.Markdown("## 📝 AI Blog Reviewer", elem_id="title")
-    gr.Markdown(
-        """
-        <div style="font-size: 16px; color: #444; line-height: 1.6;">
-        📌 Enter your blog text or a blog URL below.<br>
-        ✅ The AI will check for grammar, legal issues, crude language, and sensitive content.<br>
-        🧾 A detailed report will be shown and available to download.
-        </div>
-        """,
-        elem_id="description"
-    )
+with gr.Blocks(theme=gr.themes.Monochrome(), css=custom_css) as demo:
+    gr.Markdown("# 📝 AI Blog Reviewer")
+    gr.Markdown("Enter blog text or a URL to review. Issues will be highlighted in the content and summarized in a downloadable report.")
 
     with gr.Tabs():
-        with gr.TabItem("✍️ Text Input"):
-            text_input = gr.Textbox(
-                lines=10,
-                label="Your Blog Content",
-                placeholder="Paste your blog text here...",
-                show_label=True
-            )
-        with gr.TabItem("🌐 URL Input"):
-            url_input = gr.Textbox(
-                lines=1,
-                label="Blog URL",
-                placeholder="Enter the blog URL here...",
-                show_label=True
-            )
-
-    status_button = gr.Button(value="🚀 Review Blog", elem_classes=["review-btn"])
+        with gr.TabItem("Text"):
+            text_input = gr.Textbox(lines=8, label="Blog Content", placeholder="Paste your blog text here...")
+        with gr.TabItem("URL"):
+            url_input = gr.Textbox(lines=1, label="Blog URL", placeholder="Enter the blog URL here...")
 
+    status_button = gr.Button(value="Review Blog", elem_classes=["review-btn"])
     gr.Markdown("### 📄 Review Report")
-    report_output = gr.Markdown(elem_id="report-markdown")
-    download_btn = gr.File(label="📥 Download Markdown Report", visible=False)
+    report_output = gr.Markdown()
+    download_btn = gr.File(label="Download Report", visible=False)
+    gr.Markdown("### 🔍 Highlighted Blog Content")
+    highlighted_text = gr.HTML()
 
-    # Bind button click
     status_button.click(
         fn=review_blog,
         inputs=[text_input, url_input],
-        outputs=[status_button, report_output, download_btn]
+        outputs=[status_button, report_output, download_btn, highlighted_text]
     )
 
-demo.launch()
+demo.launch()