AI PDF Generation with LLMs

import openai
import requests

openai_client = openai.OpenAI(api_key="your-openai-key")
FORMATEX_URL = "https://api.formatex.io/v1/compile/sync"
FORMATEX_API_KEY = "your-formatex-key"

SYSTEM_PROMPT = """You are a LaTeX expert. When asked to create a document,
respond ONLY with valid LaTeX source code. No markdown fences, no explanation.
Always include \\documentclass, a complete preamble, and
\\begin{document}...\\end{document}. Use standard packages only."""

def generate_latex(prompt: str) -> str:
    """Ask GPT-4 to write a complete LaTeX document."""
    response = openai_client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": SYSTEM_PROMPT},
            {"role": "user", "content": prompt},
        ],
        temperature=0.2,  # Low temperature for deterministic LaTeX output
    )
    return response.choices[0].message.content

def compile_to_pdf(latex_source: str, engine: str = "pdflatex") -> bytes:
    """Compile LaTeX source with FormaTeX and return PDF bytes."""
    response = requests.post(
        FORMATEX_URL,
        headers={
            "Authorization": f"Bearer {FORMATEX_API_KEY}",
            "Content-Type": "application/json",
        },
        json={"source": latex_source, "engine": engine},
        timeout=30,
    )
    response.raise_for_status()
    return response.content

def generate_pdf(prompt: str, output_path: str, engine: str = "pdflatex") -> None:
    """End-to-end: prompt → LaTeX → PDF saved to disk."""
    print(f"Generating LaTeX for: {prompt[:60]}...")
    latex_source = generate_latex(prompt)

    print("Compiling PDF with FormaTeX...")
    pdf_bytes = compile_to_pdf(latex_source, engine)

    with open(output_path, "wb") as f:
        f.write(pdf_bytes)
    print(f"PDF saved to {output_path} ({len(pdf_bytes):,} bytes)")


# Example usage
generate_pdf(
    prompt=(
        "Write a 3-page LaTeX technical report on transformer neural networks. "
        "Include an abstract, introduction, the scaled dot-product attention "
        "equation, a comparison table of model sizes, and a conclusion."
    ),
    output_path="transformer_report.pdf",
    engine="pdflatex",
)