Update app.py

app.py

@@ -6,106 +6,216 @@ import google.generativeai as genai
 import os
 import re
 import tempfile
+import asyncio
 
-# Download NLTK tokenizer data
+# Download NLTK data
 download('punkt')
+download('punkt_tab')
 
-# Set your Gemini API key
+# Configure Gemini API using environment variable
 api_key = os.environ.get("GEMINI_API_KEY")
 if not api_key:
-    raise ValueError("GEMINI_API_KEY not found in environment variables")
+    raise ValueError("GEMINI_API_KEY not found in environment variables. Please set it in your environment.")
 
 genai.configure(api_key=api_key)
-model = genai.GenerativeModel("gemini-pro")
 
-# Helper functions
-def extract_text_from_url(url):
+# 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
+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):
     try:
         response = requests.get(url, timeout=10)
-        soup = BeautifulSoup(response.text, "html.parser")
-
-        for script in soup(["script", "style", "header", "footer", "nav"]):
-            script.decompose()
-
-        paragraphs = soup.find_all("p")
-        blog_text = "\n".join(p.get_text() for p in paragraphs if len(p.get_text()) > 40)
-
-        return blog_text.strip()
+        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 extracting content: {str(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
+    else:
+        return "Review Blog", "Error: Please provide input in either the Text or URL tab, but not both.", gr.update(visible=False)
 
-def review_blog(blog_text):
-    prompt = f"""
-You are a professional AI blog reviewer and sensitive content analyst.
+    # Handle empty input
+    if not input_text:
+        return "Review Blog", "Error: No input provided.", gr.update(visible=False)
 
-Carefully analyze the following blog content for:
-1. Grammar, spelling, and clarity improvements
-2. Crude, harsh, or unprofessional language
-3. Sensitive, biased, offensive, or policy-violating content
+    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)
+
+    except asyncio.TimeoutError:
+        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;500;600;700&display=swap');
+.gradio-container {
+    font-family: 'Inter', sans-serif !important;
+}
+.review-btn {
+    transition: all 0.3s ease;
+    font-weight: 500;
+    background-color: #2c3e50;
+    color: white;
+    border-radius: 8px;
+    padding: 10px 20px;
+    position: relative;
+}
+.review-btn:hover {
+    background-color: #4CAF50;
+    color: white;
+    transform: scale(1.05);
+}
+.review-btn:disabled {
+    opacity: 0.7;
+    cursor: not-allowed;
+}
+.review-btn:disabled::before {
+    content: '';
+    display: inline-block;
+    width: 16px;
+    height: 16px;
+    border: 2px 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;
+}
+"""
 
-Provide detailed suggestions and highlight what should be improved.
+# Gradio UI with Tabs
+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 for grammar, legal issues, crude language, and sensitive topics. The report is generated in markdown format.")
 
-BLOG:
-\"\"\"
-{blog_text}
-\"\"\"
-"""
-    response = model.generate_content(prompt)
-    return response.text
+    with gr.Tabs():
+        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...")
 
-def process_input(text_input, url_input):
-    if url_input:
-        blog_content = extract_text_from_url(url_input)
-    else:
-        blog_content = text_input
-
-    if not blog_content or blog_content.strip() == "":
-        return "Please provide blog content or a valid URL.", None
-
-    analysis = review_blog(blog_content)
-
-    # Create a temporary file with the markdown review
-    with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".md") as tmp_file:
-        tmp_file.write(analysis)
-        file_path = tmp_file.name
-
-    return analysis, file_path
-
-# Gradio UI
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🧠 AI Blog Reviewer")
-    gr.Markdown("Review blogs for grammar, clarity, and policy issues using Gemini AI.")
-
-    with gr.Row(equal_height=True):
-        with gr.Column(scale=3):
-            with gr.Tabs():
-                with gr.TabItem("✍️ Text Input"):
-                    text_input = gr.Textbox(
-                        label="Paste Your Blog Content",
-                        placeholder="Write or paste your blog text here...",
-                        lines=12
-                    )
-                with gr.TabItem("🔗 URL Input"):
-                    url_input = gr.Textbox(
-                        label="Enter Blog URL",
-                        placeholder="https://example.com/blog"
-                    )
-        with gr.Column(scale=2):
-            gr.Markdown("""
-### 🚀 How It Works
-1. **Input**: Paste your blog text or provide a blog URL  
-2. **Analysis**: Gemini AI checks for grammar, legal violations, and sensitive content  
-3. **Report**: Instantly download a structured Markdown review
-            """)
-            status_button = gr.Button("🧠 Review Blog")
-
-    output_text = gr.Textbox(label="Review Summary", lines=20)
-    download_button = gr.File(label="Download Markdown Review")
+    status_button = gr.Button(value="Review Blog", elem_classes=["review-btn"])
 
+    gr.Markdown("### 📄 Review Report")
+    report_output = gr.Markdown()
+    download_btn = gr.File(label="Download Report", visible=False)
+
+    # Bind the review button to process inputs
     status_button.click(
-        fn=process_input,
+        fn=review_blog,
         inputs=[text_input, url_input],
-        outputs=[output_text, download_button]
+        outputs=[status_button, report_output, download_btn]
     )
 
 demo.launch()
+
+
+Explain me line by  line
+Literally line by line 
+Think I'm s beginner,, new to ai, coding n all n explain