Update app.py

app.py

@@ -5,47 +5,72 @@ from nltk import download, sent_tokenize
 import google.generativeai as genai
 import os
 import re
+import tempfile
+import asyncio
+import time
 
 # Download NLTK data
 download('punkt')
 download('punkt_tab')
 
-# Configure Gemini API using Hugging Face Spaces secrets
+# 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. Please set it in Hugging Face Spaces secrets.")
+    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-2.5')
 
-# Prompt for Gemini to analyze text
+# 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.
+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:
-```markdown
 # Blog Review Report
 
 ## Grammar Corrections
-- [List grammar issues and suggested 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
-- [List any potential legal violations or "None detected"]
+- 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 original sentence, the issue, and the suggested correction or explanation. Be precise and concise.
+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.
 """
 
-def fetch_url_content(url):
+async def fetch_url_content(url):
     try:
         response = requests.get(url, timeout=10)
         response.raise_for_status()
@@ -56,50 +81,132 @@ def fetch_url_content(url):
     except Exception as e:
         return f"Error fetching URL: {str(e)}"
 
-def review_blog(input_text, input_type):
-    # Handle input type
+async def review_blog(text_input, url_input, progress=gr.Progress()):
+    # 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)
+
+    # Handle empty input
+    if not input_text:
+        return "Review Blog", "Error: No input provided.", gr.update(visible=False)
+
+    # Handle URL input
     if input_type == "URL":
-        input_text = fetch_url_content(input_text)
+        progress(0, desc="Fetching content...")
+        input_text = await fetch_url_content(input_text)
         if input_text.startswith("Error"):
-            return input_text, None
+            return "Review Blog", input_text, gr.update(visible=False)
 
     # Tokenize input for analysis
     sentences = sent_tokenize(input_text)
     analysis_text = "\n".join(sentences)
 
+    # Simulate progress for API call
+    progress(0, desc="Generating report...")
+    start_time = time.time()
+    for i in range(1, 10):
+        await asyncio.sleep(1)  # Simulate progress every second
+        progress(i / 10, desc=f"Generating report... ({int(i * 10)}%)")
+        if time.time() - start_time > 30:  # Timeout after 30 seconds
+            return "Review Blog", "Error: API request timed out after 30 seconds.", gr.update(visible=False)
+
     # Query Gemini with the prompt
     try:
-        response = model.generate_content(PROMPT + "\n\nText to analyze:\n" + analysis_text)
+        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|```$', '', report, flags=re.MULTILINE)
+        report = re.sub(r'^markdown\n|$', '', report, flags=re.MULTILINE)
     except Exception as e:
         report = f"Error analyzing content with Gemini: {str(e)}"
+        # 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)
 
-    return report, report
+    # 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
+        progress(1.0, desc="Report generated!")
+        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)
+
+# 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;
+}
+.review-btn:hover {
+    background-color: #4CAF50;
+    color: white;
+    transform: scale(1.05);
+}
+.review-btn:disabled {
+    opacity: 0.7;
+    cursor: not-allowed;
+}
+.review-btn:disabled::after {
+    content: ' ⏳';
+}
+.tab-nav button {
+    font-family: 'Inter', sans-serif;
+    font-weight: 500;
+}
+input, textarea {
+    font-family: 'Inter', sans-serif;
+}
+.gr-progress {
+    background-color: #e0e0e0;
+    border-radius: 8px;
+    overflow: hidden;
+}
+.gr-progress > div {
+    background-color: #4CAF50;
+    height: 20px;
+    transition: width 0.3s ease;
+}
+"""
 
-# Gradio UI
-with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
+# 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.")
 
-    input_type = gr.Radio(["Text", "URL"], label="Input Type", value="Text")
-    blog_input = gr.Textbox(lines=8, label="Blog Content or URL", placeholder="Paste your blog text or URL here...")
-    review_btn = gr.Button("Review Blog")
+    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...")
+
+    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)
 
-    def handle_review_output(report, file_report):
-        if file_report and not file_report.startswith("Error"):
-            return report, gr.update(visible=True, value={"content": file_report, "filename": "blog_review_report.md"})
-        return report, gr.update(visible=False)
-
-    review_btn.click(
-        review_blog,
-        inputs=[blog_input, input_type],
-        outputs=[report_output, download_btn]
+    # Bind the review button to process inputs
+    status_button.click(
+        fn=review_blog,
+        inputs=[text_input, url_input],
+        outputs=[status_button, report_output, download_btn]
     )
 
 demo.launch()