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Create document-generator.py
Browse files- document-generator.py +279 -0
document-generator.py
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| 1 |
+
# File: prompts.py
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| 2 |
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| 3 |
+
DOCUMENT_OUTLINE_PROMPT_SYSTEM = """You are a document generator. Provide the outline of the document requested in <prompt></prompt> in JSON format.
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| 4 |
+
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.
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| 5 |
+
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| 6 |
+
OUTPUT IN FOLLOWING JSON FORMAT enclosed in <output> tags
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| 7 |
+
<output>
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| 8 |
+
{
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| 9 |
+
"Document": {
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| 10 |
+
"Title": "Document Title",
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| 11 |
+
"Author": "Author Name",
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| 12 |
+
"Date": "YYYY-MM-DD",
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| 13 |
+
"Version": "1.0",
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| 14 |
+
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| 15 |
+
"Sections": [
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| 16 |
+
{
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| 17 |
+
"SectionNumber": "1",
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| 18 |
+
"Title": "Section Title",
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| 19 |
+
"Content": "Specific prompt or instruction for generating content for this section",
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| 20 |
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"Subsections": [
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| 21 |
+
{
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| 22 |
+
"SectionNumber": "1.1",
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| 23 |
+
"Title": "Subsection Title",
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| 24 |
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"Content": "Specific prompt or instruction for generating content for this subsection"
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| 25 |
+
}
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| 26 |
+
]
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| 27 |
+
}
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| 28 |
+
]
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| 29 |
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}
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| 30 |
+
}
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| 31 |
+
</output>"""
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| 32 |
+
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| 33 |
+
DOCUMENT_OUTLINE_PROMPT_USER = """<prompt>{query}</prompt>"""
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| 34 |
+
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| 35 |
+
DOCUMENT_SECTION_PROMPT_SYSTEM = """You are a document generator, You need to output only the content requested in the section in the prompt.
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| 36 |
+
FORMAT YOUR OUTPUT AS MARKDOWN ENCLOSED IN <response></response> tags
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| 37 |
+
<overall_objective>{overall_objective}</overall_objective>
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| 38 |
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<document_layout>{document_layout}</document_layout>"""
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| 39 |
+
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| 40 |
+
DOCUMENT_SECTION_PROMPT_USER = """<prompt>Output the content for the section "{section_or_subsection_title}" formatted as markdown. Follow this instruction: {content_instruction}</prompt>"""
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| 41 |
+
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| 42 |
+
# File: app.py
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| 43 |
+
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| 44 |
+
import os
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| 45 |
+
import json
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| 46 |
+
import re
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| 47 |
+
from typing import List, Dict, Optional, Any, Callable
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| 48 |
+
from openai import OpenAI
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| 49 |
+
import logging
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| 50 |
+
import functools
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| 51 |
+
from fastapi import APIRouter, HTTPException
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| 52 |
+
from pydantic import BaseModel
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| 53 |
+
#from prompts import *
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| 54 |
+
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| 55 |
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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| 56 |
+
logger = logging.getLogger(__name__)
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| 57 |
+
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| 58 |
+
def log_execution(func: Callable) -> Callable:
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| 59 |
+
@functools.wraps(func)
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| 60 |
+
def wrapper(*args: Any, **kwargs: Any) -> Any:
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| 61 |
+
logger.info(f"Executing {func.__name__}")
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| 62 |
+
try:
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| 63 |
+
result = func(*args, **kwargs)
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| 64 |
+
logger.info(f"{func.__name__} completed successfully")
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| 65 |
+
return result
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| 66 |
+
except Exception as e:
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| 67 |
+
logger.error(f"Error in {func.__name__}: {e}")
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| 68 |
+
raise
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| 69 |
+
return wrapper
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| 70 |
+
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| 71 |
+
class AIClient:
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| 72 |
+
def __init__(self):
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| 73 |
+
self.client = OpenAI(
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| 74 |
+
base_url="https://openrouter.ai/api/v1",
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| 75 |
+
api_key=os.environ['OPENROUTER_API_KEY']
|
| 76 |
+
)
|
| 77 |
+
|
| 78 |
+
@log_execution
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| 79 |
+
def generate_response(
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| 80 |
+
self,
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| 81 |
+
messages: List[Dict[str, str]],
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| 82 |
+
model: str = "openai/gpt-4o-mini",
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| 83 |
+
max_tokens: int = 32000
|
| 84 |
+
) -> Optional[str]:
|
| 85 |
+
if not messages:
|
| 86 |
+
return None
|
| 87 |
+
response = self.client.chat.completions.create(
|
| 88 |
+
model=model,
|
| 89 |
+
messages=messages,
|
| 90 |
+
max_tokens=max_tokens,
|
| 91 |
+
stream=False
|
| 92 |
+
)
|
| 93 |
+
return response.choices[0].message.content
|
| 94 |
+
|
| 95 |
+
class DocumentGenerator:
|
| 96 |
+
def __init__(self, ai_client: AIClient):
|
| 97 |
+
self.ai_client = ai_client
|
| 98 |
+
self.document_outline = None
|
| 99 |
+
self.content_messages = []
|
| 100 |
+
|
| 101 |
+
@staticmethod
|
| 102 |
+
def extract_between_tags(text: str, tag: str) -> str:
|
| 103 |
+
pattern = f"<{tag}>(.*?)</{tag}>"
|
| 104 |
+
match = re.search(pattern, text, re.DOTALL)
|
| 105 |
+
return match.group(1).strip() if match else ""
|
| 106 |
+
|
| 107 |
+
@staticmethod
|
| 108 |
+
def remove_duplicate_title(content: str, title: str, section_number: str) -> str:
|
| 109 |
+
patterns = [
|
| 110 |
+
rf"^#+\s*{re.escape(section_number)}(?:\s+|\s*:\s*|\.\s*){re.escape(title)}",
|
| 111 |
+
rf"^#+\s*{re.escape(title)}",
|
| 112 |
+
rf"^{re.escape(section_number)}(?:\s+|\s*:\s*|\.\s*){re.escape(title)}",
|
| 113 |
+
rf"^{re.escape(title)}",
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| 114 |
+
]
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| 115 |
+
|
| 116 |
+
for pattern in patterns:
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| 117 |
+
content = re.sub(pattern, "", content, flags=re.MULTILINE | re.IGNORECASE)
|
| 118 |
+
|
| 119 |
+
return content.lstrip()
|
| 120 |
+
|
| 121 |
+
@log_execution
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| 122 |
+
def generate_document_outline(self, query: str, max_retries: int = 3) -> Optional[Dict]:
|
| 123 |
+
messages = [
|
| 124 |
+
{"role": "system", "content": DOCUMENT_OUTLINE_PROMPT_SYSTEM},
|
| 125 |
+
{"role": "user", "content": DOCUMENT_OUTLINE_PROMPT_USER.format(query=query)}
|
| 126 |
+
]
|
| 127 |
+
|
| 128 |
+
for attempt in range(max_retries):
|
| 129 |
+
outline_response = self.ai_client.generate_response(messages, model="openai/gpt-4o")
|
| 130 |
+
outline_json_text = self.extract_between_tags(outline_response, "output")
|
| 131 |
+
|
| 132 |
+
try:
|
| 133 |
+
self.document_outline = json.loads(outline_json_text)
|
| 134 |
+
return self.document_outline
|
| 135 |
+
except json.JSONDecodeError as e:
|
| 136 |
+
if attempt < max_retries - 1:
|
| 137 |
+
logger.warning(f"Failed to parse JSON (attempt {attempt + 1}): {e}")
|
| 138 |
+
logger.info("Retrying...")
|
| 139 |
+
else:
|
| 140 |
+
logger.error(f"Failed to parse JSON after {max_retries} attempts: {e}")
|
| 141 |
+
return None
|
| 142 |
+
|
| 143 |
+
@log_execution
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| 144 |
+
def generate_content(self, title: str, content_instruction: str, section_number: str) -> str:
|
| 145 |
+
self.content_messages.append({
|
| 146 |
+
"role": "user",
|
| 147 |
+
"content": DOCUMENT_SECTION_PROMPT_USER.format(
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| 148 |
+
section_or_subsection_title=title,
|
| 149 |
+
content_instruction=content_instruction
|
| 150 |
+
)
|
| 151 |
+
})
|
| 152 |
+
section_response = self.ai_client.generate_response(self.content_messages)
|
| 153 |
+
content = self.extract_between_tags(section_response, "response")
|
| 154 |
+
content = self.remove_duplicate_title(content, title, section_number)
|
| 155 |
+
self.content_messages.append({
|
| 156 |
+
"role": "assistant",
|
| 157 |
+
"content": section_response
|
| 158 |
+
})
|
| 159 |
+
return content
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| 160 |
+
|
| 161 |
+
@log_execution
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| 162 |
+
def generate_document(self, query: str) -> Dict:
|
| 163 |
+
self.generate_document_outline(query)
|
| 164 |
+
|
| 165 |
+
if self.document_outline is None:
|
| 166 |
+
raise ValueError("Failed to generate a valid document outline")
|
| 167 |
+
|
| 168 |
+
overall_objective = query
|
| 169 |
+
document_layout = json.dumps(self.document_outline, indent=2)
|
| 170 |
+
|
| 171 |
+
self.content_messages = [
|
| 172 |
+
{
|
| 173 |
+
"role": "system",
|
| 174 |
+
"content": DOCUMENT_SECTION_PROMPT_SYSTEM.format(
|
| 175 |
+
overall_objective=overall_objective,
|
| 176 |
+
document_layout=document_layout
|
| 177 |
+
)
|
| 178 |
+
}
|
| 179 |
+
]
|
| 180 |
+
|
| 181 |
+
for section in self.document_outline["Document"].get("Sections", []):
|
| 182 |
+
section_title = section.get("Title", "")
|
| 183 |
+
section_number = section.get("SectionNumber", "")
|
| 184 |
+
content_instruction = section.get("Content", "")
|
| 185 |
+
logger.info(f"Generating content for section: {section_title}")
|
| 186 |
+
section["Content"] = self.generate_content(section_title, content_instruction, section_number)
|
| 187 |
+
|
| 188 |
+
for subsection in section.get("Subsections", []):
|
| 189 |
+
subsection_title = subsection.get("Title", "")
|
| 190 |
+
subsection_number = subsection.get("SectionNumber", "")
|
| 191 |
+
subsection_content_instruction = subsection.get("Content", "")
|
| 192 |
+
logger.info(f"Generating content for subsection: {subsection_title}")
|
| 193 |
+
subsection["Content"] = self.generate_content(subsection_title, subsection_content_instruction, subsection_number)
|
| 194 |
+
|
| 195 |
+
return self.document_outline
|
| 196 |
+
|
| 197 |
+
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| 198 |
+
class MarkdownConverter:
|
| 199 |
+
@staticmethod
|
| 200 |
+
def slugify(text: str) -> str:
|
| 201 |
+
return re.sub(r'\W+', '-', text.lower())
|
| 202 |
+
|
| 203 |
+
@classmethod
|
| 204 |
+
def generate_toc(cls, sections: List[Dict]) -> str:
|
| 205 |
+
toc = "<div style='page-break-before: always;'></div>\n\n"
|
| 206 |
+
toc += "<h2 style='color: #2c3e50; text-align: center;'>Table of Contents</h2>\n\n"
|
| 207 |
+
toc += "<nav style='background-color: #f8f9fa; padding: 20px; border-radius: 5px; line-height: 1.6;'>\n\n"
|
| 208 |
+
for section in sections:
|
| 209 |
+
section_number = section['SectionNumber']
|
| 210 |
+
section_title = section['Title']
|
| 211 |
+
toc += f"<p><a href='#{cls.slugify(section_title)}' style='color: #3498db; text-decoration: none;'>{section_number}. {section_title}</a></p>\n\n"
|
| 212 |
+
|
| 213 |
+
for subsection in section.get('Subsections', []):
|
| 214 |
+
subsection_number = subsection['SectionNumber']
|
| 215 |
+
subsection_title = subsection['Title']
|
| 216 |
+
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"
|
| 217 |
+
|
| 218 |
+
toc += "</nav>\n\n"
|
| 219 |
+
return toc
|
| 220 |
+
|
| 221 |
+
@classmethod
|
| 222 |
+
def convert_to_markdown(cls, document: Dict) -> str:
|
| 223 |
+
# First page with centered content
|
| 224 |
+
markdown = "<div style='text-align: center; padding-top: 33vh;'>\n\n"
|
| 225 |
+
markdown += f"<h1 style='color: #2c3e50; border-bottom: 2px solid #3498db; padding-bottom: 10px; display: inline-block;'>{document['Title']}</h1>\n\n"
|
| 226 |
+
markdown += f"<p style='color: #7f8c8d;'><em>By {document['Author']}</em></p>\n\n"
|
| 227 |
+
markdown += f"<p style='color: #95a5a6;'>Version {document['Version']} | {document['Date']}</p>\n\n"
|
| 228 |
+
markdown += "</div>\n\n"
|
| 229 |
+
|
| 230 |
+
# Table of Contents on the second page
|
| 231 |
+
markdown += cls.generate_toc(document['Sections'])
|
| 232 |
+
|
| 233 |
+
# Main content
|
| 234 |
+
markdown += "<div style='max-width: 800px; margin: 0 auto; font-family: \"Segoe UI\", Arial, sans-serif; line-height: 1.6;'>\n\n"
|
| 235 |
+
|
| 236 |
+
for section in document['Sections']:
|
| 237 |
+
markdown += "<div style='page-break-before: always;'></div>\n\n"
|
| 238 |
+
section_number = section['SectionNumber']
|
| 239 |
+
section_title = section['Title']
|
| 240 |
+
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"
|
| 241 |
+
markdown += f"<div style='color: #34495e; margin-bottom: 20px;'>\n\n{section['Content']}\n\n</div>\n\n"
|
| 242 |
+
|
| 243 |
+
for subsection in section.get('Subsections', []):
|
| 244 |
+
subsection_number = subsection['SectionNumber']
|
| 245 |
+
subsection_title = subsection['Title']
|
| 246 |
+
markdown += f"<h3 id='{cls.slugify(subsection_title)}' style='color: #34495e;'>{subsection_number} {subsection_title}</h3>\n\n"
|
| 247 |
+
markdown += f"<div style='color: #34495e; margin-bottom: 20px;'>\n\n{subsection['Content']}\n\n</div>\n\n"
|
| 248 |
+
|
| 249 |
+
markdown += "</div>"
|
| 250 |
+
return markdown
|
| 251 |
+
|
| 252 |
+
|
| 253 |
+
router = APIRouter()
|
| 254 |
+
|
| 255 |
+
class DocumentRequest(BaseModel):
|
| 256 |
+
query: str
|
| 257 |
+
|
| 258 |
+
class DocumentResponse(BaseModel):
|
| 259 |
+
json_document: Dict
|
| 260 |
+
markdown_document: str
|
| 261 |
+
|
| 262 |
+
@router.post("/generate-document", response_model=DocumentResponse)
|
| 263 |
+
async def generate_document_endpoint(request: DocumentRequest):
|
| 264 |
+
ai_client = AIClient()
|
| 265 |
+
document_generator = DocumentGenerator(ai_client)
|
| 266 |
+
|
| 267 |
+
try:
|
| 268 |
+
# Generate the document
|
| 269 |
+
json_document = document_generator.generate_document(request.query)
|
| 270 |
+
|
| 271 |
+
# Convert to Markdown
|
| 272 |
+
markdown_document = MarkdownConverter.convert_to_markdown(json_document["Document"])
|
| 273 |
+
|
| 274 |
+
return DocumentResponse(
|
| 275 |
+
json_document=json_document,
|
| 276 |
+
markdown_document=markdown_document
|
| 277 |
+
)
|
| 278 |
+
except Exception as e:
|
| 279 |
+
raise HTTPException(status_code=500, detail=str(e))
|