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| # File: prompts.py | |
| DOCUMENT_OUTLINE_PROMPT_SYSTEM = """You are a document generator. Provide the outline of the document requested in <prompt></prompt> in JSON format. | |
| Include sections and subsections if required. Use the "Content" field to provide a specific prompt or instruction for generating content for that particular section or subsection. | |
| OUTPUT IN FOLLOWING JSON FORMAT enclosed in <output> tags | |
| <output> | |
| { | |
| "Document": { | |
| "Title": "Document Title", | |
| "Author": "Author Name", | |
| "Date": "YYYY-MM-DD", | |
| "Version": "1.0", | |
| "Sections": [ | |
| { | |
| "SectionNumber": "1", | |
| "Title": "Section Title", | |
| "Content": "Specific prompt or instruction for generating content for this section", | |
| "Subsections": [ | |
| { | |
| "SectionNumber": "1.1", | |
| "Title": "Subsection Title", | |
| "Content": "Specific prompt or instruction for generating content for this subsection" | |
| } | |
| ] | |
| } | |
| ] | |
| } | |
| } | |
| </output>""" | |
| DOCUMENT_OUTLINE_PROMPT_USER = """<prompt>{query}</prompt>""" | |
| DOCUMENT_SECTION_PROMPT_SYSTEM = """You are a document generator, You need to output only the content requested in the section in the prompt. | |
| FORMAT YOUR OUTPUT AS MARKDOWN ENCLOSED IN <response></response> tags | |
| <overall_objective>{overall_objective}</overall_objective> | |
| <document_layout>{document_layout}</document_layout>""" | |
| DOCUMENT_SECTION_PROMPT_USER = """<prompt>Output the content for the section "{section_or_subsection_title}" formatted as markdown. Follow this instruction: {content_instruction}</prompt>""" | |
| # File: app.py | |
| import os | |
| import json | |
| import re | |
| from typing import List, Dict, Optional, Any, Callable | |
| from openai import OpenAI | |
| import logging | |
| import functools | |
| from fastapi import APIRouter, HTTPException | |
| from pydantic import BaseModel | |
| #from prompts import * | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') | |
| logger = logging.getLogger(__name__) | |
| def log_execution(func: Callable) -> Callable: | |
| def wrapper(*args: Any, **kwargs: Any) -> Any: | |
| logger.info(f"Executing {func.__name__}") | |
| try: | |
| result = func(*args, **kwargs) | |
| logger.info(f"{func.__name__} completed successfully") | |
| return result | |
| except Exception as e: | |
| logger.error(f"Error in {func.__name__}: {e}") | |
| raise | |
| return wrapper | |
| class AIClient: | |
| def __init__(self): | |
| self.client = OpenAI( | |
| base_url="https://openrouter.ai/api/v1", | |
| api_key=os.environ['OPENROUTER_API_KEY'] | |
| ) | |
| def generate_response( | |
| self, | |
| messages: List[Dict[str, str]], | |
| model: str = "openai/gpt-4o-mini", | |
| max_tokens: int = 32000 | |
| ) -> Optional[str]: | |
| if not messages: | |
| return None | |
| response = self.client.chat.completions.create( | |
| model=model, | |
| messages=messages, | |
| max_tokens=max_tokens, | |
| stream=False | |
| ) | |
| return response.choices[0].message.content | |
| class DocumentGenerator: | |
| def __init__(self, ai_client: AIClient): | |
| self.ai_client = ai_client | |
| self.document_outline = None | |
| self.content_messages = [] | |
| def extract_between_tags(text: str, tag: str) -> str: | |
| pattern = f"<{tag}>(.*?)</{tag}>" | |
| match = re.search(pattern, text, re.DOTALL) | |
| return match.group(1).strip() if match else "" | |
| def remove_duplicate_title(content: str, title: str, section_number: str) -> str: | |
| patterns = [ | |
| rf"^#+\s*{re.escape(section_number)}(?:\s+|\s*:\s*|\.\s*){re.escape(title)}", | |
| rf"^#+\s*{re.escape(title)}", | |
| rf"^{re.escape(section_number)}(?:\s+|\s*:\s*|\.\s*){re.escape(title)}", | |
| rf"^{re.escape(title)}", | |
| ] | |
| for pattern in patterns: | |
| content = re.sub(pattern, "", content, flags=re.MULTILINE | re.IGNORECASE) | |
| return content.lstrip() | |
| def generate_document_outline(self, query: str, max_retries: int = 3) -> Optional[Dict]: | |
| messages = [ | |
| {"role": "system", "content": DOCUMENT_OUTLINE_PROMPT_SYSTEM}, | |
| {"role": "user", "content": DOCUMENT_OUTLINE_PROMPT_USER.format(query=query)} | |
| ] | |
| for attempt in range(max_retries): | |
| outline_response = self.ai_client.generate_response(messages, model="openai/gpt-4o") | |
| outline_json_text = self.extract_between_tags(outline_response, "output") | |
| try: | |
| self.document_outline = json.loads(outline_json_text) | |
| return self.document_outline | |
| except json.JSONDecodeError as e: | |
| if attempt < max_retries - 1: | |
| logger.warning(f"Failed to parse JSON (attempt {attempt + 1}): {e}") | |
| logger.info("Retrying...") | |
| else: | |
| logger.error(f"Failed to parse JSON after {max_retries} attempts: {e}") | |
| return None | |
| def generate_content(self, title: str, content_instruction: str, section_number: str) -> str: | |
| self.content_messages.append({ | |
| "role": "user", | |
| "content": DOCUMENT_SECTION_PROMPT_USER.format( | |
| section_or_subsection_title=title, | |
| content_instruction=content_instruction | |
| ) | |
| }) | |
| section_response = self.ai_client.generate_response(self.content_messages) | |
| content = self.extract_between_tags(section_response, "response") | |
| content = self.remove_duplicate_title(content, title, section_number) | |
| self.content_messages.append({ | |
| "role": "assistant", | |
| "content": section_response | |
| }) | |
| return content | |
| def generate_document(self, query: str) -> Dict: | |
| self.generate_document_outline(query) | |
| if self.document_outline is None: | |
| raise ValueError("Failed to generate a valid document outline") | |
| overall_objective = query | |
| document_layout = json.dumps(self.document_outline, indent=2) | |
| self.content_messages = [ | |
| { | |
| "role": "system", | |
| "content": DOCUMENT_SECTION_PROMPT_SYSTEM.format( | |
| overall_objective=overall_objective, | |
| document_layout=document_layout | |
| ) | |
| } | |
| ] | |
| for section in self.document_outline["Document"].get("Sections", []): | |
| section_title = section.get("Title", "") | |
| section_number = section.get("SectionNumber", "") | |
| content_instruction = section.get("Content", "") | |
| logger.info(f"Generating content for section: {section_title}") | |
| section["Content"] = self.generate_content(section_title, content_instruction, section_number) | |
| for subsection in section.get("Subsections", []): | |
| subsection_title = subsection.get("Title", "") | |
| subsection_number = subsection.get("SectionNumber", "") | |
| subsection_content_instruction = subsection.get("Content", "") | |
| logger.info(f"Generating content for subsection: {subsection_title}") | |
| subsection["Content"] = self.generate_content(subsection_title, subsection_content_instruction, subsection_number) | |
| return self.document_outline | |
| class MarkdownConverter: | |
| def slugify(text: str) -> str: | |
| return re.sub(r'\W+', '-', text.lower()) | |
| def generate_toc(cls, sections: List[Dict]) -> str: | |
| toc = "<div style='page-break-before: always;'></div>\n\n" | |
| toc += "<h2 style='color: #2c3e50; text-align: center;'>Table of Contents</h2>\n\n" | |
| toc += "<nav style='background-color: #f8f9fa; padding: 20px; border-radius: 5px; line-height: 1.6;'>\n\n" | |
| for section in sections: | |
| section_number = section['SectionNumber'] | |
| section_title = section['Title'] | |
| toc += f"<p><a href='#{cls.slugify(section_title)}' style='color: #3498db; text-decoration: none;'>{section_number}. {section_title}</a></p>\n\n" | |
| for subsection in section.get('Subsections', []): | |
| subsection_number = subsection['SectionNumber'] | |
| subsection_title = subsection['Title'] | |
| toc += f"<p style='margin-left: 20px;'><a href='#{cls.slugify(subsection_title)}' style='color: #2980b9; text-decoration: none;'>{subsection_number} {subsection_title}</a></p>\n\n" | |
| toc += "</nav>\n\n" | |
| return toc | |
| def convert_to_markdown(cls, document: Dict) -> str: | |
| # First page with centered content | |
| markdown = "<div style='text-align: center; padding-top: 33vh;'>\n\n" | |
| markdown += f"<h1 style='color: #2c3e50; border-bottom: 2px solid #3498db; padding-bottom: 10px; display: inline-block;'>{document['Title']}</h1>\n\n" | |
| markdown += f"<p style='color: #7f8c8d;'><em>By {document['Author']}</em></p>\n\n" | |
| markdown += f"<p style='color: #95a5a6;'>Version {document['Version']} | {document['Date']}</p>\n\n" | |
| markdown += "</div>\n\n" | |
| # Table of Contents on the second page | |
| markdown += cls.generate_toc(document['Sections']) | |
| # Main content | |
| markdown += "<div style='max-width: 800px; margin: 0 auto; font-family: \"Segoe UI\", Arial, sans-serif; line-height: 1.6;'>\n\n" | |
| for section in document['Sections']: | |
| markdown += "<div style='page-break-before: always;'></div>\n\n" | |
| section_number = section['SectionNumber'] | |
| section_title = section['Title'] | |
| markdown += f"<h2 id='{cls.slugify(section_title)}' style='color: #2c3e50; border-bottom: 1px solid #bdc3c7; padding-bottom: 5px;'>{section_number}. {section_title}</h2>\n\n" | |
| markdown += f"<div style='color: #34495e; margin-bottom: 20px;'>\n\n{section['Content']}\n\n</div>\n\n" | |
| for subsection in section.get('Subsections', []): | |
| subsection_number = subsection['SectionNumber'] | |
| subsection_title = subsection['Title'] | |
| markdown += f"<h3 id='{cls.slugify(subsection_title)}' style='color: #34495e;'>{subsection_number} {subsection_title}</h3>\n\n" | |
| markdown += f"<div style='color: #34495e; margin-bottom: 20px;'>\n\n{subsection['Content']}\n\n</div>\n\n" | |
| markdown += "</div>" | |
| return markdown | |
| router = APIRouter() | |
| class DocumentRequest(BaseModel): | |
| query: str | |
| class DocumentResponse(BaseModel): | |
| json_document: Dict | |
| markdown_document: str | |
| async def generate_document_endpoint(request: DocumentRequest): | |
| ai_client = AIClient() | |
| document_generator = DocumentGenerator(ai_client) | |
| try: | |
| # Generate the document | |
| json_document = document_generator.generate_document(request.query) | |
| # Convert to Markdown | |
| markdown_document = MarkdownConverter.convert_to_markdown(json_document["Document"]) | |
| return DocumentResponse( | |
| json_document=json_document, | |
| markdown_document=markdown_document | |
| ) | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) |