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import os
import sys
import time
import base64
from io import BytesIO
from pathlib import Path
"""
Generate one AI illustration per slide concept using OpenAI Images API.
Outputs: docs/slide_illustrations/slide-1.png ... slide-5.png
Requires: OPENAI_API_KEY in environment and internet access.
"""
SLIDE_PROMPTS = [
(
1,
"Consistent Output Control",
(
"Minimalist flat-design infographic showing a flow from a user message to an agent "
"to a JSON schema validator producing a consistent structured JSON output. Use iconography only, no text. "
"Elements: speech bubble -> robot head -> curly-brace JSON icon with checkmark badge. "
"Style: clean, vector, blue/teal color palette, high contrast, centered composition."
),
),
(
2,
"Input Control via Missing Fields",
(
"Modern UI concept art of a form with several fields, where required fields are highlighted and missing fields are flagged. "
"An assistant bubble points to the missing fields to ask clarifying questions. No text labels. "
"Style: product illustration, rounded cards, subtle shadows, blue/orange highlights, vector."
),
),
(
3,
"Dynamic Input Schemas (KB & Internet)",
(
"Diagram of an agent deciding between two paths: a knowledge base database icon and an internet globe icon. "
"Branched arrows from the agent to each tool, then back to a combined result. Iconography only. "
"Style: sleek tech infographic, gradient accents, minimal lines, no words."
),
),
(
4,
"Multistep Execution & Delegation",
(
"An orchestrator node delegating tasks to multiple sub-agents in sequence. "
"Show numbered or visually ordered steps without using text: use small numbered badges or dots. "
"Style: systems diagram, monochrome with one accent color, clean vectors, no text."
),
),
(
5,
"API Calls (NCBI/Web Search)",
(
"Magnifying glass over a DNA helix icon next to a web globe, representing API calls to biomedical and web search. "
"Arrows indicate request and response. Iconography only, no text. "
"Style: scientific-tech aesthetic, cool tones, crisp vector illustration."
),
),
]
def ensure_api_key() -> str:
key = os.getenv("OPENAI_API_KEY")
if not key:
print("ERROR: OPENAI_API_KEY not set in environment. Set it and rerun.")
print("PowerShell example:")
print(" $Env:OPENAI_API_KEY = \"sk-...\"")
sys.exit(1)
return key
def main():
# Initialize OpenAI client if available
openai_enabled = False
openai_client = None
if os.getenv("OPENAI_API_KEY"):
try:
from openai import OpenAI # type: ignore
openai_client = OpenAI()
openai_enabled = True
except Exception as e:
print("WARNING: OpenAI client unavailable; will try Hugging Face fallback.")
print(f"Details: {e}\n")
# Initialize Hugging Face client if available
hf_enabled = False
hf_client = None
hf_model = os.getenv("HF_IMAGE_MODEL", "stabilityai/stable-diffusion-xl-base-1.0")
if os.getenv("HUGGINGFACE_API_TOKEN"):
try:
from huggingface_hub import InferenceClient # type: ignore
hf_client = InferenceClient(token=os.getenv("HUGGINGFACE_API_TOKEN"))
hf_enabled = True
except Exception as e:
print("WARNING: huggingface_hub not available. Install with: pip install huggingface_hub pillow")
print(f"Details: {e}\n")
project_root = Path(__file__).resolve().parents[1]
out_dir = project_root / "docs" / "slide_illustrations"
out_dir.mkdir(parents=True, exist_ok=True)
def enhance_prompt_with_gpt4(title: str, concept: str) -> str:
"""Use GPT-4o to expand the concept into a professional DALL-E 3 prompt."""
if not openai_enabled or openai_client is None:
return concept # fallback to original
try:
system_prompt = (
"You are an expert at writing DALL-E 3 prompts for professional technical illustrations. "
"Given a slide title and concept, expand it into a detailed, specific prompt that will produce "
"a high-quality, structured infographic-style illustration. Focus on: clean composition, professional "
"design, iconography without text labels, consistent color palette, and visual hierarchy. "
"Return ONLY the enhanced prompt, no explanations."
)
user_prompt = f"Slide title: {title}\n\nConcept: {concept}\n\nEnhanced DALL-E 3 prompt:"
resp = openai_client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
temperature=0.7,
max_tokens=300,
)
enhanced = resp.choices[0].message.content or concept
return enhanced.strip()
except Exception as e:
print(f" Prompt enhancement failed, using original: {e}")
return concept
def try_openai_responses_api(prompt: str):
"""Try gpt-image-1 via Responses API (newest, highest quality)."""
if not openai_enabled or openai_client is None:
return None
try:
response = openai_client.responses.create(
model="gpt-4.1-mini", # Use a model that supports image generation
input=prompt,
tools=[{"type": "image_generation"}],
)
# Extract image data from response
image_data = [
output.result
for output in response.output
if output.type == "image_generation_call"
]
if image_data:
return base64.b64decode(image_data[0])
return None
except Exception as e:
print(f" Responses API (gpt-image-1) failed: {e}")
return None
def try_openai(prompt: str):
"""Fallback: DALL-E 3 via Images API in landscape mode."""
if not openai_enabled or openai_client is None:
return None
try:
resp = openai_client.images.generate(
model="dall-e-3",
prompt=prompt,
size="1792x1024", # Landscape for slides
quality="hd",
response_format="b64_json",
)
b64 = resp.data[0].b64_json
if not b64:
return None
return base64.b64decode(b64)
except Exception as e:
print(f" DALL-E 3 generation failed: {e}")
return None
def try_hf(prompt: str):
if not hf_enabled or hf_client is None:
return None
try:
# text_to_image returns a PIL.Image.Image
img = hf_client.text_to_image(prompt=prompt, model=hf_model)
bio = BytesIO()
img = img.convert("RGB") # ensure 3-channel
img.save(bio, format="PNG")
return bio.getvalue()
except Exception as e:
print(f" Hugging Face generation failed: {e}")
return None
for idx, title, prompt in SLIDE_PROMPTS:
print(f"Generating slide {idx}: {title}")
# Step 1: Enhance prompt with GPT-4o (mimics ChatGPT's internal process)
print(f" Enhancing prompt with GPT-4o...")
enhanced_prompt = enhance_prompt_with_gpt4(title, prompt)
print(f" Enhanced prompt: {enhanced_prompt[:100]}...")
img_bytes = None
# Try newest model first (Responses API with gpt-image-1)
if openai_enabled:
img_bytes = try_openai_responses_api(enhanced_prompt)
# Fallback to DALL-E 3 landscape if Responses API unavailable
if img_bytes is None and openai_enabled:
print(" Falling back to DALL-E 3 (landscape)...")
img_bytes = try_openai(enhanced_prompt)
# Fallback to Hugging Face
if img_bytes is None and hf_enabled:
img_bytes = try_hf(enhanced_prompt)
if img_bytes is None:
print(
" Skipped: No image generated. Ensure either OPENAI_API_KEY (with access to gpt-image-1) "
"or HUGGINGFACE_API_TOKEN is set."
)
continue
out_path = out_dir / f"slide-{idx}.png"
with open(out_path, "wb") as f:
f.write(img_bytes)
print(f"Saved {out_path}")
time.sleep(0.75)
print(f"Done. Illustrations saved to: {out_dir}")
if not openai_enabled:
print("Note: OPENAI_API_KEY not set or OpenAI client unavailable.")
if not hf_enabled:
print("Note: HUGGINGFACE_API_TOKEN not set or huggingface_hub unavailable.")
if __name__ == "__main__":
main()
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