Add application file

Dockerfile

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+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9-slim
+
+# Install system dependencies
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+    pandoc \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create and switch to user
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+ENV PYTHONPATH=/app
+
+# Set up working directory
+WORKDIR /app
+
+# Install Python dependencies
+COPY --chown=user requirements.txt .
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir --upgrade -r requirements.txt && \
+    pip install --no-cache-dir --upgrade g4f[all]
+
+# Copy application code
+COPY --chown=user . .
+
+# Expose port
+EXPOSE 7860
+
+# Run the application
+CMD ["gunicorn", "--bind", "0.0.0.0:7860", "--workers", "4", "--threads", "2", "app:app"]

a.py

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+import g4f
+import os
+import subprocess
+from datetime import datetime
+from tqdm import tqdm
+from typing import List, Tuple
+
+def get_available_models() -> List[str]:
+    """Get list of available models from g4f"""
+    try:
+        # New way to get available models in recent g4f versions
+        return sorted(g4f.models._all_models)
+    except Exception as e:
+        print(f"Warning: Could not fetch models from g4f. Using default models. Error: {e}")
+        return [
+            'gpt-4',
+            'gpt-3.5-turbo',
+            'llama2-70b',
+            'claude-2'
+        ]
+
+def get_user_choice(prompt: str, options: List[str]) -> str:
+    """Get user choice from a list of options"""
+    print(prompt)
+    for i, option in enumerate(options, 1):
+        print(f"{i}. {option}")
+    while True:
+        try:
+            choice = int(input("Enter your choice: "))
+            if 1 <= choice <= len(options):
+                return options[choice-1]
+            print(f"Please enter a number between 1 and {len(options)}")
+        except ValueError:
+            print("Please enter a valid number")
+
+def create_output_directory() -> None:
+    """Create output directory if it doesn't exist"""
+    if not os.path.exists("output"):
+        os.makedirs("output")
+
+def generate_filename() -> Tuple[str, str]:
+    """Generate filenames with timestamp"""
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    md_filename = f"output/research_paper_{timestamp}.md"
+    docx_filename = f"output/research_paper_{timestamp}.docx"
+    return md_filename, docx_filename
+
+def generate_index_content(model: str, research_subject: str, manual_chapters: List[str] = None) -> str:
+    """Generate index content for the research paper"""
+    try:
+        if manual_chapters:
+            prompt = f"Generate a detailed index/table of contents for a research paper about {research_subject} with these chapters: " + \
+                    ", ".join(manual_chapters) + ". Include section headings in markdown format."
+        else:
+            prompt = f"Generate a detailed index/table of contents for a research paper about {research_subject}. Include chapter titles and section headings in markdown format."
+        
+        response = g4f.ChatCompletion.create(
+            model=model,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        # Ensure we get string output
+        return str(response) if response else "[Empty response from model]"
+    except Exception as e:
+        raise Exception(f"Failed to generate index: {str(e)}")
+
+def extract_chapters(index_content: str) -> List[str]:
+    """Extract chapter titles from index content"""
+    chapters = []
+    for line in index_content.split('\n'):
+        if line.strip().startswith('## '):  # Chapter level headings
+            chapter_title = line.strip()[3:].strip()
+            if chapter_title.lower() not in ['introduction', 'conclusion', 'references']:
+                chapters.append(chapter_title)
+    return chapters if chapters else ["Literature Review", "Methodology", "Results and Discussion"]
+
+def generate_automatic_sections(model: str, research_subject: str) -> List[Tuple[str, str]]:
+    """Generate sections automatically based on AI-generated index"""
+    try:
+        with tqdm(total=1, desc="Generating Index") as pbar:
+            index_content = generate_index_content(model, research_subject)
+            pbar.update(1)
+            
+            chapters = extract_chapters(index_content)
+            
+            sections = [
+                ("Index", index_content),
+                ("Introduction", f"Write a comprehensive introduction for a research paper about {research_subject}. Include background information, research objectives, and significance of the study.")
+            ]
+            
+            for i, chapter in enumerate(chapters, 1):
+                sections.append(
+                    (f"Chapter {i}: {chapter}", 
+                     f"Write a detailed chapter about '{chapter}' for a research paper about {research_subject}. "
+                     f"Provide comprehensive coverage of this aspect, including relevant theories, examples, and analysis.")
+                )
+            
+            sections.append(
+                ("Conclusion", f"Write a conclusion section for a research paper about {research_subject}. Summarize key findings, discuss implications, and suggest future research directions.")
+            )
+            
+            return sections
+    except Exception as e:
+        raise Exception(f"Failed to generate automatic structure: {str(e)}")
+
+def get_manual_sections(research_subject: str) -> List[Tuple[str, str]]:
+    """Get predefined manual sections"""
+    return [
+        ("Index", "[Index will be generated first]"),
+        ("Introduction", f"Write a comprehensive introduction for a research paper about {research_subject}."),
+        ("Chapter 1: Literature Review", f"Create a detailed literature review chapter about {research_subject}."),
+        ("Chapter 2: Methodology", f"Describe the research methodology for a study about {research_subject}."),
+        ("Chapter 3: Results and Discussion", f"Present hypothetical results and discussion for a research paper about {research_subject}. Analyze findings and compare with existing literature."),
+        ("Conclusion", f"Write a conclusion section for a research paper about {research_subject}.")
+    ]
+
+def generate_section_content(model: str, prompt: str) -> str:
+    """Generate content for a single section"""
+    try:
+        response = g4f.ChatCompletion.create(
+            model=model,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        return str(response) if response else "[Empty response from model]"
+    except Exception as e:
+        raise Exception(f"Failed to generate section content: {str(e)}")
+
+def write_research_paper(md_filename: str, research_subject: str, sections: List[Tuple[str, str]], model: str) -> None:
+    """Write the research paper to a markdown file"""
+    with open(md_filename, "w", encoding="utf-8") as f:
+        f.write(f"# Research Paper: {research_subject}\n\n")
+        
+        for section_title, prompt in tqdm(sections, desc="Generating Paper Sections"):
+            try:
+                if isinstance(prompt, str) and (prompt.startswith("##") or prompt.startswith("#")):
+                    # Pre-generated content (like index)
+                    content = f"{prompt}\n\n"
+                else:
+                    # Generate new content
+                    response = generate_section_content(model, prompt)
+                    content = f"## {section_title}\n\n{response}\n\n"
+                
+                f.write(content)
+            except Exception as e:
+                print(f"Error generating {section_title}: {str(e)}")
+                f.write(f"## {section_title}\n\n[Error generating this section]\n\n")
+
+def convert_to_word(md_filename: str, docx_filename: str) -> None:
+    """Convert markdown file to Word document using Pandoc"""
+    try:
+        with tqdm(total=1, desc="Converting to Word") as pbar:
+            # Build the command list
+            command = [
+                "pandoc", md_filename,
+                "-o", docx_filename,
+                "--standalone",  # Include header and footer
+                "--table-of-contents",  # Add table of contents
+                "--toc-depth=3"  # Include up to level 3 headings in TOC
+            ]
+            
+            # Only add reference-doc if it exists
+            if os.path.exists("reference.docx"):
+                command.extend(["--reference-doc", "reference.docx"])
+            
+            # Run the command
+            subprocess.run(command, check=True)
+            pbar.update(1)
+        print(f"Word document generated as {docx_filename}")
+    except subprocess.CalledProcessError as e:
+        raise Exception(f"Error converting to Word document: {str(e)}")
+    except FileNotFoundError:
+        raise Exception("Pandoc not found. Please install Pandoc to convert to Word document.")
+
+def main():
+    """Main function to generate research paper"""
+    try:
+        # Get configuration
+        available_models = get_available_models()
+        research_subject = input("Enter your research subject: ")
+        selected_model = get_user_choice("\nSelect AI model:", available_models)
+        
+        structure_choice = get_user_choice(
+            "\nSelect paper structure generation method:",
+            ["Automatic (from AI-generated index)", "Manual (predefined structure)"]
+        )
+        
+        # Setup files and directories
+        create_output_directory()
+        md_filename, docx_filename = generate_filename()
+
+        # Generate sections
+        sections = []
+        if structure_choice.startswith("Automatic"):
+            try:
+                sections = generate_automatic_sections(selected_model, research_subject)
+            except Exception as e:
+                print(f"\nError: {str(e)}")
+                print("Falling back to manual structure...")
+                sections = get_manual_sections(research_subject)
+                # Generate index for manual structure
+                manual_chapters = [section[0] for section in sections[1:]]
+                try:
+                    index_content = generate_index_content(selected_model, research_subject, manual_chapters)
+                    sections[0] = ("Index", index_content)
+                except Exception as e:
+                    print(f"Error generating index: {str(e)}")
+                    sections[0] = ("Index", "[Error generating index]")
+        else:
+            sections = get_manual_sections(research_subject)
+            # Generate index for manual structure
+            manual_chapters = [section[0] for section in sections[1:]]
+            try:
+                index_content = generate_index_content(selected_model, research_subject, manual_chapters)
+                sections[0] = ("Index", index_content)
+            except Exception as e:
+                print(f"Error generating index: {str(e)}")
+                sections[0] = ("Index", "[Error generating index]")
+
+        # Generate paper content
+        write_research_paper(md_filename, research_subject, sections, selected_model)
+        print(f"\nResearch paper saved as {md_filename}")
+
+        # Convert to Word
+        try:
+            convert_to_word(md_filename, docx_filename)
+        except Exception as e:
+            print(f"Warning: {str(e)}")
+
+    except Exception as e:
+        print(f"\nFatal error occurred: {str(e)}")
+        exit(1)
+
+if __name__ == "__main__":
+    try:
+        import g4f
+        main()
+    except ImportError:
+        print("Error: g4f package not installed. Please install it with:")
+        print("pip install -U g4f[all]")
+        exit(1)

app.py

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+# app.py
+from flask import Flask, render_template, request, jsonify, send_from_directory
+import g4f
+import os
+import subprocess
+from datetime import datetime
+from typing import List, Tuple
+import uuid
+from werkzeug.utils import secure_filename
+
+app = Flask(__name__)
+app.config['UPLOAD_FOLDER'] = 'output'
+
+# Initialize output directory
+os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
+
+def get_available_models() -> List[str]:
+    """Get list of available models from g4f"""
+    try:
+        return sorted(g4f.models._all_models)
+    except Exception:
+        return ['gpt-4', 'gpt-3.5-turbo', 'llama2-70b', 'claude-2']
+
+def generate_filename() -> Tuple[str, str]:
+    """Generate filenames with unique ID"""
+    unique_id = str(uuid.uuid4())[:8]
+    md_filename = f"research_paper_{unique_id}.md"
+    docx_filename = f"research_paper_{unique_id}.docx"
+    return md_filename, docx_filename
+
+def generate_index_content(model: str, research_subject: str, manual_chapters: List[str] = None) -> str:
+    """Generate index content for the research paper"""
+    try:
+        if manual_chapters:
+            prompt = f"Generate a detailed index/table of contents for a research paper about {research_subject} with these chapters: " + \
+                    ", ".join(manual_chapters) + ". Include section headings in markdown format."
+        else:
+            prompt = f"Generate a detailed index/table of contents for a research paper about {research_subject}. Include chapter titles and section headings in markdown format."
+        
+        response = g4f.ChatCompletion.create(
+            model=model,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        return str(response) if response else "[Empty response from model]"
+    except Exception as e:
+        raise Exception(f"Failed to generate index: {str(e)}")
+
+def extract_chapters(index_content: str) -> List[str]:
+    """Extract chapter titles from index content"""
+    chapters = []
+    for line in index_content.split('\n'):
+        if line.strip().startswith('## '):
+            chapter_title = line.strip()[3:].strip()
+            if chapter_title.lower() not in ['introduction', 'conclusion', 'references']:
+                chapters.append(chapter_title)
+    return chapters if chapters else ["Literature Review", "Methodology", "Results and Discussion"]
+
+def generate_automatic_sections(model: str, research_subject: str) -> List[Tuple[str, str]]:
+    """Generate sections automatically based on AI-generated index"""
+    try:
+        index_content = generate_index_content(model, research_subject)
+        chapters = extract_chapters(index_content)
+        
+        sections = [
+            ("Index", index_content),
+            ("Introduction", f"Write a comprehensive introduction for a research paper about {research_subject}. Include background information, research objectives, and significance of the study.")
+        ]
+        
+        for i, chapter in enumerate(chapters, 1):
+            sections.append(
+                (f"Chapter {i}: {chapter}", 
+                 f"Write a detailed chapter about '{chapter}' for a research paper about {research_subject}. "
+                 f"Provide comprehensive coverage of this aspect, including relevant theories, examples, and analysis.")
+            )
+        
+        sections.append(
+            ("Conclusion", f"Write a conclusion section for a research paper about {research_subject}. Summarize key findings, discuss implications, and suggest future research directions.")
+        )
+        
+        return sections
+    except Exception as e:
+        raise Exception(f"Failed to generate automatic structure: {str(e)}")
+
+def get_manual_sections(research_subject: str) -> List[Tuple[str, str]]:
+    """Get predefined manual sections"""
+    return [
+        ("Index", "[Index will be generated first]"),
+        ("Introduction", f"Write a comprehensive introduction for a research paper about {research_subject}."),
+        ("Chapter 1: Literature Review", f"Create a detailed literature review chapter about {research_subject}."),
+        ("Chapter 2: Methodology", f"Describe the research methodology for a study about {research_subject}."),
+        ("Chapter 3: Results and Discussion", f"Present hypothetical results and discussion for a research paper about {research_subject}. Analyze findings and compare with existing literature."),
+        ("Conclusion", f"Write a conclusion section for a research paper about {research_subject}.")
+    ]
+
+def generate_section_content(model: str, prompt: str) -> str:
+    """Generate content for a single section"""
+    try:
+        response = g4f.ChatCompletion.create(
+            model=model,
+            messages=[{"role": "user", "content": prompt}],
+        )
+        return str(response) if response else "[Empty response from model]"
+    except Exception as e:
+        raise Exception(f"Failed to generate section content: {str(e)}")
+
+def write_research_paper(md_filename: str, research_subject: str, sections: List[Tuple[str, str]], model: str) -> None:
+    """Write the research paper to a markdown file"""
+    full_path = os.path.join(app.config['UPLOAD_FOLDER'], md_filename)
+    with open(full_path, "w", encoding="utf-8") as f:
+        f.write(f"# Research Paper: {research_subject}\n\n")
+        
+        for section_title, prompt in sections:
+            try:
+                if isinstance(prompt, str) and (prompt.startswith("##") or prompt.startswith("#")):
+                    content = f"{prompt}\n\n"
+                else:
+                    response = generate_section_content(model, prompt)
+                    content = f"## {section_title}\n\n{response}\n\n"
+                f.write(content)
+            except Exception as e:
+                f.write(f"## {section_title}\n\n[Error generating this section: {str(e)}]\n\n")
+
+def convert_to_word(md_filename: str, docx_filename: str) -> None:
+    """Convert markdown file to Word document using Pandoc"""
+    md_path = os.path.join(app.config['UPLOAD_FOLDER'], md_filename)
+    docx_path = os.path.join(app.config['UPLOAD_FOLDER'], docx_filename)
+    
+    command = [
+        "pandoc", md_path,
+        "-o", docx_path,
+        "--standalone",
+        "--table-of-contents",
+        "--toc-depth=3"
+    ]
+    
+    if os.path.exists("reference.docx"):
+        command.extend(["--reference-doc", "reference.docx"])
+    
+    subprocess.run(command, check=True)
+
+@app.route('/')
+def index():
+    models = get_available_models()
+    return render_template('index.html', models=models)
+
+@app.route('/generate', methods=['POST'])
+def generate():
+    data = request.json
+    research_subject = data.get('subject', '').strip()
+    selected_model = data.get('model', 'gpt-4')
+    structure_type = data.get('structure', 'automatic')
+    
+    if not research_subject:
+        return jsonify({'error': 'Research subject is required'}), 400
+    
+    try:
+        # Generate filenames
+        md_filename, docx_filename = generate_filename()
+        
+        # Generate sections based on structure type
+        if structure_type == 'automatic':
+            try:
+                sections = generate_automatic_sections(selected_model, research_subject)
+            except Exception:
+                sections = get_manual_sections(research_subject)
+                index_content = generate_index_content(selected_model, research_subject, [s[0] for s in sections[1:]])
+                sections[0] = ("Index", index_content)
+        else:
+            sections = get_manual_sections(research_subject)
+            index_content = generate_index_content(selected_model, research_subject, [s[0] for s in sections[1:]])
+            sections[0] = ("Index", index_content)
+        
+        # Generate the paper
+        write_research_paper(md_filename, research_subject, sections, selected_model)
+        
+        # Convert to Word
+        try:
+            convert_to_word(md_filename, docx_filename)
+        except Exception as e:
+            return jsonify({
+                'status': 'partial_success',
+                'message': f'Paper generated but Word conversion failed: {str(e)}',
+                'md_file': md_filename
+            })
+        
+        return jsonify({
+            'status': 'success',
+            'docx_file': docx_filename,
+            'md_file': md_filename
+        })
+        
+    except Exception as e:
+        return jsonify({'error': f'Failed to generate paper: {str(e)}'}), 500
+
+@app.route('/download/<filename>')
+def download(filename):
+    safe_filename = secure_filename(filename)
+    return send_from_directory(
+        app.config['UPLOAD_FOLDER'],
+        safe_filename,
+        as_attachment=True
+    )
+
+if __name__ == '__main__':
+    app.run(debug=True)

d.cmd

@@ -0,0 +1,3 @@
+git add .
+git commit -m "Add application file"
+git push

har_and_cookies/auth_OpenaiChat.json

@@ -0,0 +1 @@
+{"api_key": null, "cookies": {"_dd_s": "rum=0&expire=1744328288966&logs=1&id=a148f952-1aeb-404e-b346-222e9ceff98f&created=1744327388966", "oai-sc": "0gAAAAABn-FLgF7j4QQAAB46feL-KF_EgdrI7AC2CR-8BMKvd55AmgokL3NGl-MKTYlLJMw2ccFD1r6f7XGD9r-HbM0CYvns9juFmjubg6mbl4imHg7Q8vZee1TBrht73tL-8eAAHEa3bR4DiRGR4-Z3mG65OxfYXgXk_Y-dSr9L1rystTeLu2Ymlhuo_kEEnXn2lX9IWnNTnXJR9ll-L21leSmdC2YS1ulloBCFTz9krt9Oh_vcYBxI", "cf_clearance": "4tihdc7vg7IT29uwN7w2xFtVrS6ZL7.5pRJOzZzJCzk-1744327389-1.2.1.1-DUnJs2Rc._f3t9UeP8aL8P0qbfJjglZnJvzfauCXNps31hWNTSUpQDdtP4SSpwkKEhZLiMNkrgcvXue6XVDDKv6I9cGgQesp1jnRn3.yiy6Y0BTg.MkjhktYi8x43OvXARvKPBUVaf03YLelG9mtzA5.HupQo9odc2sLIhHl6AeEzIEe54EeGRsMhEgoY41fSW_tuzEAvLuxz.Z_Rv2d9GkM.GHlCDG0VVoxbCHFQLXakzN6bUrJueXW4MqIWyz6k3nSEWVnnq3fPMXPKdvZdkgtS6xVWXSA6t7XVX7VsARUTZet8V2VAZq5TK0xEm2IAzeGUPJRgBder.yeid__b2TdWn9GjAKWNo2byArrHwI", "__cflb": "0H28vzvP5FJafnkHxj4UT4q3DSGqRYN2PgVfGD42o1D", "_cfuvid": "2AXajlsJCkqL6C7RiZr8UEXoHlEgxO7fc2NM1EbV6fk-1744327386278-0.0.1.1-604800000", "__Host-next-auth.csrf-token": "a57f875f5a6c9e2417a3ec87fbb631857f8c20d277a9dadb11348ab992d47dd1%7C37e7bd65b00f393844395f1248a5e44e1e6a64046ad4e2fa28a8b0875430fbc6", "__cf_bm": "uwro6GZ2FmV9cyr8IA1AfEr7UpRpXiYuFtIyw3KKMTM-1744327386-1.0.1.1-YZPH_ZobjntjzOXG9s_gmr0KYQ1jwE39o10caQzkERtvW4qZv6PWU90Q.f3A8ME_u66VbxhogXtxyl9T84RWKBNsVaR2XMpm5cvPHP4nWFM", "oai-did": "ace63a11-36f3-4681-a00d-3a6e4ca41c0b", "__Secure-next-auth.callback-url": "https%3A%2F%2Fchatgpt.com"}, "headers": {"upgrade-insecure-requests": "1", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36", "sec-ch-ua": "\"Google Chrome\";v=\"135\", \"Not-A.Brand\";v=\"8\", \"Chromium\";v=\"135\"", "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": "\"Windows\"", "cookie": "_dd_s=rum=0&expire=1744328288966&logs=1&id=a148f952-1aeb-404e-b346-222e9ceff98f&created=1744327388966; oai-sc=0gAAAAABn-FLgF7j4QQAAB46feL-KF_EgdrI7AC2CR-8BMKvd55AmgokL3NGl-MKTYlLJMw2ccFD1r6f7XGD9r-HbM0CYvns9juFmjubg6mbl4imHg7Q8vZee1TBrht73tL-8eAAHEa3bR4DiRGR4-Z3mG65OxfYXgXk_Y-dSr9L1rystTeLu2Ymlhuo_kEEnXn2lX9IWnNTnXJR9ll-L21leSmdC2YS1ulloBCFTz9krt9Oh_vcYBxI; cf_clearance=4tihdc7vg7IT29uwN7w2xFtVrS6ZL7.5pRJOzZzJCzk-1744327389-1.2.1.1-DUnJs2Rc._f3t9UeP8aL8P0qbfJjglZnJvzfauCXNps31hWNTSUpQDdtP4SSpwkKEhZLiMNkrgcvXue6XVDDKv6I9cGgQesp1jnRn3.yiy6Y0BTg.MkjhktYi8x43OvXARvKPBUVaf03YLelG9mtzA5.HupQo9odc2sLIhHl6AeEzIEe54EeGRsMhEgoY41fSW_tuzEAvLuxz.Z_Rv2d9GkM.GHlCDG0VVoxbCHFQLXakzN6bUrJueXW4MqIWyz6k3nSEWVnnq3fPMXPKdvZdkgtS6xVWXSA6t7XVX7VsARUTZet8V2VAZq5TK0xEm2IAzeGUPJRgBder.yeid__b2TdWn9GjAKWNo2byArrHwI; __cflb=0H28vzvP5FJafnkHxj4UT4q3DSGqRYN2PgVfGD42o1D; _cfuvid=2AXajlsJCkqL6C7RiZr8UEXoHlEgxO7fc2NM1EbV6fk-1744327386278-0.0.1.1-604800000; __Host-next-auth.csrf-token=a57f875f5a6c9e2417a3ec87fbb631857f8c20d277a9dadb11348ab992d47dd1%7C37e7bd65b00f393844395f1248a5e44e1e6a64046ad4e2fa28a8b0875430fbc6; __cf_bm=uwro6GZ2FmV9cyr8IA1AfEr7UpRpXiYuFtIyw3KKMTM-1744327386-1.0.1.1-YZPH_ZobjntjzOXG9s_gmr0KYQ1jwE39o10caQzkERtvW4qZv6PWU90Q.f3A8ME_u66VbxhogXtxyl9T84RWKBNsVaR2XMpm5cvPHP4nWFM; oai-did=ace63a11-36f3-4681-a00d-3a6e4ca41c0b; __Secure-next-auth.callback-url=https%3A%2F%2Fchatgpt.com"}, "expires": null, "proof_token": [2134, "Fri Apr 11 2025 02:23:10 GMT+0300 (Arabian Standard Time)", 2248146944, 21, "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36", null, "prod-e900b9b3b43b17d1d2e0655bc3b78309ac4bd4c6", "en-US", "en-US,en", 179, "sendBeacon\u2212function sendBeacon() { [native code] }", "location", "webkitRequestFileSystem", 6295.699999999255, "5aa516a5-5969-420c-b633-a2e45fd581da", "", 4, 1744327384310.3], "turnstile_token": "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"}

har_and_cookies/blackbox.json

@@ -0,0 +1 @@
+{"validated_value": "00f37b34-a166-4efb-bce5-1312d87f2f94"}

requirements.txt

@@ -0,0 +1,6 @@
+flask
+g4f
+pypandoc
+python-dotenv
+werkzeug
+uvicorn

templates/index.html

@@ -0,0 +1,259 @@
+<!-- templates/index.html -->
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Research Paper Generator</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
+</head>
+<body class="bg-gray-50 min-h-screen">
+    <div class="container mx-auto px-4 py-8">
+        <div class="max-w-3xl mx-auto bg-white rounded-xl shadow-md overflow-hidden p-6">
+            <div class="text-center mb-8">
+                <h1 class="text-3xl font-bold text-indigo-700 mb-2">
+                    <i class="fas fa-file-alt mr-2"></i>Research Paper Generator
+                </h1>
+                <p class="text-gray-600">Generate complete research papers with AI</p>
+            </div>
+
+            <form id="paperForm" class="space-y-6">
+                <div>
+                    <label for="subject" class="block text-sm font-medium text-gray-700 mb-1">
+                        <i class="fas fa-book mr-2"></i>Research Subject
+                    </label>
+                    <input type="text" id="subject" name="subject" required
+                        class="w-full px-4 py-2 border border-gray-300 rounded-md focus:ring-indigo-500 focus:border-indigo-500"
+                        placeholder="Enter your research topic">
+                </div>
+
+                <div>
+                    <label for="model" class="block text-sm font-medium text-gray-700 mb-1">
+                        <i class="fas fa-brain mr-2"></i>AI Model
+                    </label>
+                    <select id="model" name="model"
+                        class="w-full px-4 py-2 border border-gray-300 rounded-md focus:ring-indigo-500 focus:border-indigo-500">
+                        {% for model in models %}
+                        <option value="{{ model }}">{{ model }}</option>
+                        {% endfor %}
+                    </select>
+                </div>
+
+                <div>
+                    <label class="block text-sm font-medium text-gray-700 mb-2">
+                        <i class="fas fa-layer-group mr-2"></i>Paper Structure
+                    </label>
+                    <div class="flex space-x-4">
+                        <label class="inline-flex items-center">
+                            <input type="radio" name="structure" value="automatic" checked
+                                class="h-4 w-4 text-indigo-600 focus:ring-indigo-500">
+                            <span class="ml-2 text-gray-700">Automatic</span>
+                        </label>
+                        <label class="inline-flex items-center">
+                            <input type="radio" name="structure" value="manual"
+                                class="h-4 w-4 text-indigo-600 focus:ring-indigo-500">
+                            <span class="ml-2 text-gray-700">Manual</span>
+                        </label>
+                    </div>
+                </div>
+
+                <div class="pt-4">
+                    <button type="submit" id="generateBtn"
+                        class="w-full flex justify-center items-center py-3 px-4 border border-transparent rounded-md shadow-sm text-sm font-medium text-white bg-indigo-600 hover:bg-indigo-700 focus:outline-none focus:ring-2 focus:ring-offset-2 focus:ring-indigo-500 disabled:opacity-50 disabled:cursor-not-allowed">
+                        <i class="fas fa-magic mr-2"></i> Generate Paper
+                    </button>
+                </div>
+            </form>
+
+            <div id="progressContainer" class="mt-8 hidden">
+                <h3 class="text-lg font-medium text-gray-900 mb-4">
+                    <i class="fas fa-tasks mr-2"></i>Generation Progress
+                </h3>
+                <div class="space-y-4">
+                    <div id="progressSteps" class="space-y-3"></div>
+                    <div class="relative pt-1">
+                        <div class="flex items-center justify-between">
+                            <div>
+                                <span id="progressText" class="text-xs font-semibold inline-block text-indigo-600">
+                                    0%
+                                </span>
+                            </div>
+                        </div>
+                        <div class="overflow-hidden h-2 mb-4 text-xs flex rounded bg-indigo-200">
+                            <div id="progressBar" style="width:0%"
+                                class="shadow-none flex flex-col text-center whitespace-nowrap text-white justify-center bg-indigo-500 transition-all duration-300"></div>
+                        </div>
+                    </div>
+                </div>
+            </div>
+
+            <div id="resultContainer" class="mt-8 hidden">
+                <h3 class="text-lg font-medium text-gray-900 mb-4">
+                    <i class="fas fa-check-circle mr-2 text-green-500"></i>Generation Complete
+                </h3>
+                <div class="flex space-x-4">
+                    <a id="downloadDocx" href="#"
+                        class="inline-flex items-center px-4 py-2 border border-transparent text-sm font-medium rounded-md shadow-sm text-white bg-green-600 hover:bg-green-700">
+                        <i class="fas fa-file-word mr-2"></i> Download Word
+                    </a>
+                    <a id="downloadMd" href="#"
+                        class="inline-flex items-center px-4 py-2 border border-gray-300 text-sm font-medium rounded-md text-gray-700 bg-white hover:bg-gray-50">
+                        <i class="fas fa-file-code mr-2"></i> Download Markdown
+                    </a>
+                </div>
+            </div>
+
+            <div id="errorContainer" class="mt-8 hidden">
+                <div class="bg-red-50 border-l-4 border-red-400 p-4">
+                    <div class="flex">
+                        <div class="flex-shrink-0">
+                            <i class="fas fa-exclamation-circle text-red-400"></i>
+                        </div>
+                        <div class="ml-3">
+                            <p id="errorMessage" class="text-sm text-red-700"></p>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+    <script>
+        document.getElementById('paperForm').addEventListener('submit', function(e) {
+            e.preventDefault();
+            
+            const form = e.target;
+            const generateBtn = document.getElementById('generateBtn');
+            const progressContainer = document.getElementById('progressContainer');
+            const resultContainer = document.getElementById('resultContainer');
+            const errorContainer = document.getElementById('errorContainer');
+            const progressSteps = document.getElementById('progressSteps');
+            const progressBar = document.getElementById('progressBar');
+            const progressText = document.getElementById('progressText');
+            
+            // Reset UI
+            generateBtn.disabled = true;
+            progressContainer.classList.remove('hidden');
+            resultContainer.classList.add('hidden');
+            errorContainer.classList.add('hidden');
+            progressSteps.innerHTML = '';
+            progressBar.style.width = '0%';
+            progressText.textContent = '0%';
+            
+            // Show initial progress steps
+            const steps = [
+                'Preparing document structure...',
+                'Generating index/table of contents...',
+                'Writing introduction...',
+                'Generating chapters...',
+                'Creating conclusion...',
+                'Finalizing document...',
+                'Converting to Word format...'
+            ];
+            
+            steps.forEach((step, index) => {
+                const stepElement = document.createElement('div');
+                stepElement.className = 'flex items-center';
+                stepElement.innerHTML = `
+                    <div class="flex-shrink-0 h-5 w-5 text-gray-400">
+                        <i class="far fa-circle"></i>
+                    </div>
+                    <div class="ml-3">
+                        <p class="text-sm font-medium text-gray-700">${step}</p>
+                    </div>
+                `;
+                stepElement.id = `step-${index}`;
+                progressSteps.appendChild(stepElement);
+            });
+            
+            // Get form data
+            const formData = {
+                subject: form.subject.value,
+                model: form.model.value,
+                structure: form.structure.value
+            };
+            
+            // Simulate progress updates (in a real app, you'd use SSE or websockets)
+            const totalSteps = steps.length;
+            let currentStep = 0;
+            
+            const updateProgress = () => {
+                const progress = Math.min(100, Math.round((currentStep / totalSteps) * 100));
+                progressBar.style.width = `${progress}%`;
+                progressText.textContent = `${progress}%`;
+                
+                // Update step icons
+                if (currentStep > 0) {
+                    const prevStepElement = document.getElementById(`step-${currentStep-1}`);
+                    if (prevStepElement) {
+                        prevStepElement.querySelector('i').className = 'fas fa-check-circle text-green-500';
+                    }
+                }
+                
+                if (currentStep < totalSteps) {
+                    const currentStepElement = document.getElementById(`step-${currentStep}`);
+                    if (currentStepElement) {
+                        currentStepElement.querySelector('i').className = 'fas fa-spinner fa-spin text-indigo-500';
+                    }
+                }
+            };
+            
+            const interval = setInterval(() => {
+                currentStep++;
+                updateProgress();
+                
+                if (currentStep >= totalSteps) {
+                    clearInterval(interval);
+                }
+            }, 1000);
+            
+            // Send request to server
+            fetch('/generate', {
+                method: 'POST',
+                headers: {
+                    'Content-Type': 'application/json',
+                },
+                body: JSON.stringify(formData)
+            })
+            .then(response => response.json())
+            .then(data => {
+                clearInterval(interval);
+                updateProgress();
+                
+                if (data.error) {
+                    throw new Error(data.error);
+                }
+                
+                // Show download links
+                if (data.docx_file) {
+                    document.getElementById('downloadDocx').href = `/download/${data.docx_file}`;
+                }
+                if (data.md_file) {
+                    document.getElementById('downloadMd').href = `/download/${data.md_file}`;
+                }
+                
+                // Mark all steps as complete
+                for (let i = 0; i < steps.length; i++) {
+                    const stepElement = document.getElementById(`step-${i}`);
+                    if (stepElement) {
+                        stepElement.querySelector('i').className = 'fas fa-check-circle text-green-500';
+                    }
+                }
+                
+                progressBar.style.width = '100%';
+                progressText.textContent = '100%';
+                resultContainer.classList.remove('hidden');
+            })
+            .catch(error => {
+                clearInterval(interval);
+                document.getElementById('errorMessage').textContent = error.message;
+                errorContainer.classList.remove('hidden');
+            })
+            .finally(() => {
+                generateBtn.disabled = false;
+            });
+        });
+    </script>
+</body>
+</html>