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| import openai | |
| import gradio as gr | |
| from typing import Dict, List | |
| import re | |
| from humanize import paraphrase_text | |
| from ai_generate import generate | |
| import requests | |
| from gptzero_free import GPT2PPL | |
| def clean_text(text: str) -> str: | |
| paragraphs = text.split('\n\n') | |
| cleaned_paragraphs = [] | |
| for paragraph in paragraphs: | |
| cleaned = re.sub(r'\s+', ' ', paragraph).strip() | |
| cleaned = re.sub(r'(?<=\.) ([a-z])', lambda x: x.group(1).upper(), cleaned) | |
| cleaned_paragraphs.append(cleaned) | |
| return '\n'.join(cleaned_paragraphs) | |
| def format_and_correct(text: str) -> str: | |
| """Correct formatting and grammar without changing content significantly.""" | |
| prompt = f""" | |
| Please correct the formatting, grammar, and spelling errors in the following text without changing its content significantly. Ensure proper paragraph breaks and maintain the original content: | |
| {text} | |
| """ | |
| corrected_text = generate(prompt, "Groq", None) | |
| return clean_text(corrected_text) | |
| def generate_prompt(settings: Dict[str, str]) -> str: | |
| """Generate a detailed prompt based on user settings.""" | |
| prompt = f""" | |
| Write a {settings['article_length']} {settings['format']} on {settings['topic']}. | |
| Style and Tone: | |
| - Writing style: {settings['writing_style']} | |
| - Tone: {settings['tone']} | |
| - Target audience: {settings['user_category']} | |
| Content: | |
| - Depth: {settings['depth_of_content']} | |
| - Structure: {', '.join(settings['structure'])} | |
| Keywords to incorporate: | |
| {', '.join(settings['keywords'])} | |
| Additional requirements: | |
| - Include {settings['num_examples']} relevant examples or case studies | |
| - Incorporate data or statistics from {', '.join(settings['references'])} | |
| - End with a {settings['conclusion_type']} conclusion | |
| - Add a "References" section at the end with at least 3 credible sources, formatted as [1], [2], etc. | |
| - Do not make any headline, title bold. | |
| Ensure proper paragraph breaks for better readability. | |
| Avoid any references to artificial intelligence, language models, or the fact that this is generated by an AI, and do not mention something like here is the article etc. | |
| """ | |
| return prompt | |
| def generate_article( | |
| topic: str, | |
| keywords: str, | |
| article_length: str, | |
| format: str, | |
| writing_style: str, | |
| tone: str, | |
| user_category: str, | |
| depth_of_content: str, | |
| structure: str, | |
| references: str, | |
| num_examples: str, | |
| conclusion_type: str, | |
| ai_model: str, | |
| api_key: str = None | |
| ) -> str: | |
| """Generate an article based on user-defined settings.""" | |
| settings = { | |
| "topic": topic, | |
| "keywords": [k.strip() for k in keywords.split(',')], | |
| "article_length": article_length, | |
| "format": format, | |
| "writing_style": writing_style, | |
| "tone": tone, | |
| "user_category": user_category, | |
| "depth_of_content": depth_of_content, | |
| "structure": [s.strip() for s in structure.split(',')], | |
| "references": [r.strip() for r in references.split(',')], | |
| "num_examples": num_examples, | |
| "conclusion_type": conclusion_type | |
| } | |
| prompt = generate_prompt(settings) | |
| if ai_model in ['OpenAI GPT 3.5', 'OpenAI GPT 4']: | |
| response = openai.ChatCompletion.create( | |
| model="gpt-4" if ai_model == 'OpenAI GPT 4' else "gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "system", "content": "You are a professional content writer with expertise in various fields."}, | |
| {"role": "user", "content": prompt} | |
| ], | |
| max_tokens=3000, | |
| n=1, | |
| stop=None, | |
| temperature=0.7, | |
| ) | |
| article = response.choices[0].message.content.strip() | |
| else: | |
| article = generate(prompt, ai_model, api_key) | |
| return clean_text(article) | |
| def humanize( | |
| text: str, | |
| model: str, | |
| temperature: float = 1.2, | |
| repetition_penalty: float = 1, | |
| top_k: int = 50, | |
| length_penalty: float = 1 | |
| ) -> str: | |
| result = paraphrase_text( | |
| text=text, | |
| model_name=model, | |
| temperature=temperature, | |
| repetition_penalty=repetition_penalty, | |
| top_k=top_k, | |
| length_penalty=length_penalty, | |
| ) | |
| return format_and_correct(result) | |
| ai_check_options = [ | |
| "Polygraf AI", | |
| # "Sapling AI", | |
| "GPTZero" | |
| ] | |
| def ai_generated_test_polygraf(text: str) -> Dict: | |
| url = "http://34.66.10.188/ai-vs-human" | |
| access_key = "6mcemwsFycVVgVjMFwKXki3zJka1r7N4u$Z0Y|x$gecC$hdNtpQf-SpL0+=k;u%BZ" | |
| headers = { | |
| "ACCESS_KEY": access_key | |
| } | |
| data = { | |
| "text" : f"{text}" | |
| } | |
| response = requests.post(url, headers=headers, json=data) | |
| return response.json() | |
| def ai_generated_test_sapling(text: str) -> Dict: | |
| response = requests.post( | |
| "https://api.sapling.ai/api/v1/aidetect", | |
| json={ | |
| "key": "60L9BPSVPIIOEZM0CD1DQWRBPJIUR7SB", | |
| "text": f"{text}" | |
| } | |
| ) | |
| return { "AI" : response.json()['score'], "HUMAN" : 1 - response.json()['score']} | |
| def ai_generated_test_gptzero(text): | |
| gptzero_model = GPT2PPL() | |
| result = gptzero_model(text) | |
| print(result) | |
| return result | |
| def ai_check(text: str, option: str) -> Dict: | |
| if option == 'Polygraf AI': | |
| return ai_generated_test_polygraf(text) | |
| elif option == 'Sapling AI': | |
| return ai_generated_test_sapling(text) | |
| elif option == "GPTZero": | |
| return ai_generated_test_gptzero(text) | |
| else: | |
| return ai_generated_test_polygraf(text) | |
| def update_visibility_api(model: str): | |
| if model in ['OpenAI GPT 3.5', 'OpenAI GPT 4']: | |
| return gr.update(visible=True) | |
| else: | |
| return gr.update(visible=False) | |
| def format_references(text: str) -> str: | |
| """Extract and format references from the generated text.""" | |
| lines = text.split('\n') | |
| references = [] | |
| article_text = [] | |
| in_references = False | |
| for line in lines: | |
| if line.strip().lower() == "references": | |
| in_references = True | |
| continue | |
| if in_references: | |
| references.append(line.strip()) | |
| else: | |
| article_text.append(line) | |
| formatted_refs = [] | |
| for i, ref in enumerate(references, 1): | |
| formatted_refs.append(f"[{i}] {ref}\n") | |
| return "\n\n".join(article_text) + "\n\nReferences:\n" + "\n".join(formatted_refs) | |
| def generate_and_format( | |
| topic, keywords, article_length, format, writing_style, tone, user_category, | |
| depth_of_content, structure, references, num_examples, conclusion_type, ai_model, api_key | |
| ): | |
| article = generate_article( | |
| topic, keywords, article_length, format, writing_style, tone, user_category, | |
| depth_of_content, structure, references, num_examples, conclusion_type, ai_model, api_key | |
| ) | |
| return format_references(article) | |
| def copy_to_input(text): | |
| return text | |
| def create_interface(): | |
| with gr.Blocks(theme=gr.themes.Default( | |
| primary_hue=gr.themes.colors.pink, | |
| secondary_hue=gr.themes.colors.yellow, | |
| neutral_hue=gr.themes.colors.gray | |
| )) as demo: | |
| gr.Markdown("# Polygraf AI Content Writer", elem_classes="text-center text-3xl mb-6") | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| with gr.Group(): | |
| gr.Markdown("## Article Configuration", elem_classes="text-xl mb-4") | |
| input_topic = gr.Textbox(label="Topic", placeholder="Enter the main topic of your article", elem_classes="input-highlight-pink") | |
| input_keywords = gr.Textbox(label="Keywords", placeholder="Enter comma-separated keywords", elem_classes="input-highlight-yellow") | |
| with gr.Row(): | |
| input_format = gr.Dropdown( | |
| choices=['Article', 'Essay', 'Blog post', 'Report', 'Research paper', 'News article', 'White paper'], | |
| value='Article', | |
| label="Format", | |
| elem_classes="input-highlight-turquoise" | |
| ) | |
| input_length = gr.Dropdown( | |
| choices=["Short (500 words)", "Medium (1000 words)", "Long (2000+ words)", "Very Long (3000+ words)"], | |
| value="Medium (1000 words)", | |
| label="Article Length", | |
| elem_classes="input-highlight-pink" | |
| ) | |
| with gr.Row(): | |
| input_writing_style = gr.Dropdown( | |
| choices=["Formal", "Informal", "Technical", "Conversational", "Journalistic", "Academic", "Creative"], | |
| value="Formal", | |
| label="Writing Style", | |
| elem_classes="input-highlight-yellow" | |
| ) | |
| input_tone = gr.Dropdown( | |
| choices=["Friendly", "Professional", "Neutral", "Enthusiastic", "Skeptical", "Humorous"], | |
| value="Professional", | |
| label="Tone", | |
| elem_classes="input-highlight-turquoise" | |
| ) | |
| input_user_category = gr.Dropdown( | |
| choices=["Students", "Professionals", "Researchers", "General Public", "Policymakers", "Entrepreneurs"], | |
| value="General Public", | |
| label="Target Audience", | |
| elem_classes="input-highlight-pink" | |
| ) | |
| input_depth = gr.Dropdown( | |
| choices=["Surface-level overview", "Moderate analysis", "In-depth research", "Comprehensive study"], | |
| value="Moderate analysis", | |
| label="Depth of Content", | |
| elem_classes="input-highlight-yellow" | |
| ) | |
| input_structure = gr.Dropdown( | |
| choices=[ | |
| "Introduction, Body, Conclusion", | |
| "Abstract, Introduction, Methods, Results, Discussion, Conclusion", | |
| "Executive Summary, Problem Statement, Analysis, Recommendations, Conclusion", | |
| "Introduction, Literature Review, Methodology, Findings, Analysis, Conclusion" | |
| ], | |
| value="Introduction, Body, Conclusion", | |
| label="Structure", | |
| elem_classes="input-highlight-turquoise" | |
| ) | |
| input_references = gr.Dropdown( | |
| choices=["Academic journals", "Industry reports", "Government publications", "News outlets", "Expert interviews", "Case studies"], | |
| value="News outlets", | |
| label="References", | |
| elem_classes="input-highlight-pink" | |
| ) | |
| input_num_examples = gr.Dropdown( | |
| choices=["1-2", "3-4", "5+"], | |
| value="1-2", | |
| label="Number of Examples/Case Studies", | |
| elem_classes="input-highlight-yellow" | |
| ) | |
| input_conclusion = gr.Dropdown( | |
| choices=["Summary", "Call to Action", "Future Outlook", "Thought-provoking Question"], | |
| value="Summary", | |
| label="Conclusion Type", | |
| elem_classes="input-highlight-turquoise" | |
| ) | |
| with gr.Group(): | |
| gr.Markdown("## AI Model Configuration", elem_classes="text-xl mb-4") | |
| ai_generator = gr.Dropdown( | |
| choices=['Llama 3', 'Groq', 'Mistral', 'Gemma', 'OpenAI GPT 3.5', 'OpenAI GPT 4'], | |
| value='Llama 3', | |
| label="AI Model", | |
| elem_classes="input-highlight-pink" | |
| ) | |
| input_api = gr.Textbox(label="API Key", visible=False) | |
| ai_generator.change(update_visibility_api, ai_generator, input_api) | |
| generate_btn = gr.Button("Generate Article", variant="primary") | |
| with gr.Column(scale=3): | |
| output_article = gr.Textbox(label="Generated Article", lines=20) | |
| with gr.Row(): | |
| with gr.Column(): | |
| ai_detector_dropdown = gr.Radio( | |
| choices=ai_check_options, label="Select AI Detector", value="Polygraf AI") | |
| ai_check_btn = gr.Button("AI Check") | |
| ai_check_result = gr.Label(label="AI Check Result") | |
| humanize_btn = gr.Button("Humanize") | |
| humanized_output = gr.Textbox(label="Humanized Article", lines=20) | |
| copy_to_input_btn = gr.Button("Copy to Input for AI Check") | |
| with gr.Accordion("Advanced Humanizer Settings", open=False): | |
| with gr.Row(): | |
| model_dropdown = gr.Radio( | |
| choices=[ | |
| "Base Model", | |
| "Large Model", | |
| "XL Model", | |
| # "XL Law Model", | |
| # "XL Marketing Model", | |
| # "XL Child Style Model", | |
| ], | |
| value="Large Model", | |
| label="Humanizer Model Version" | |
| ) | |
| with gr.Row(): | |
| temperature_slider = gr.Slider(minimum=0.5, maximum=2.0, step=0.1, value=1.2, label="Temperature") | |
| top_k_slider = gr.Slider(minimum=0, maximum=300, step=25, value=50, label="Top k") | |
| with gr.Row(): | |
| repetition_penalty_slider = gr.Slider(minimum=1.0, maximum=2.0, step=0.1, value=1, label="Repetition Penalty") | |
| length_penalty_slider = gr.Slider(minimum=0.0, maximum=2.0, step=0.1, value=1.0, label="Length Penalty") | |
| generate_btn.click( | |
| fn=generate_and_format, | |
| inputs=[ | |
| input_topic, | |
| input_keywords, | |
| input_length, | |
| input_format, | |
| input_writing_style, | |
| input_tone, | |
| input_user_category, | |
| input_depth, | |
| input_structure, | |
| input_references, | |
| input_num_examples, | |
| input_conclusion, | |
| ai_generator, | |
| input_api | |
| ], | |
| outputs=[output_article], | |
| ) | |
| ai_check_btn.click( | |
| fn=ai_check, | |
| inputs=[output_article, ai_detector_dropdown], | |
| outputs=[ai_check_result], | |
| ) | |
| humanize_btn.click( | |
| fn=humanize, | |
| inputs=[ | |
| output_article, | |
| model_dropdown, | |
| temperature_slider, | |
| repetition_penalty_slider, | |
| top_k_slider, | |
| length_penalty_slider, | |
| ], | |
| outputs=[humanized_output], | |
| ) | |
| copy_to_input_btn.click( | |
| fn=copy_to_input, | |
| inputs=[humanized_output], | |
| outputs=[output_article], | |
| ) | |
| return demo | |
| if __name__ == "__main__": | |
| demo = create_interface() | |
| demo.launch(server_name="0.0.0.0", share=True) |