import requests import io from PIL import Image import gradio as gr import os # Assuming you have your API tokens set in environment variables ZEPHYR_API_TOKEN = os.getenv("HF_API_TOKEN") SD_API_TOKEN = os.getenv("HF_API_TOKEN") if not ZEPHYR_API_TOKEN or not SD_API_TOKEN: raise ValueError("API tokens not found. Please set the ZEPHYR_API_TOKEN and HF_API_TOKEN environment variables.") ZEPHYR_API_URL = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta" SD_API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" def query_zephyr(prompt): headers = {"Authorization": f"Bearer {ZEPHYR_API_TOKEN}"} response = requests.post(ZEPHYR_API_URL, headers=headers, json={"inputs": prompt}) return response.json() def generate_image_from_prompt(prompt, guidance_scale=7.5, width=1024, height=768, num_inference_steps=30): headers = {"Authorization": f"Bearer {SD_API_TOKEN}"} payload = { "inputs": prompt, "parameters": { "guidance_scale": guidance_scale, "width": width, "height": height, "num_inference_steps": num_inference_steps, }, } response = requests.post(SD_API_URL, headers=headers, json=payload) image_bytes = response.content image = Image.open(io.BytesIO(image_bytes)) return image def generate_image_from_linkedin_text(linkedin_text): # Step 1: Generate a prompt from the LinkedIn text using Zephyr zephyr_output = query_zephyr(linkedin_text) generated_prompt = zephyr_output.get("generated_text", "") # Step 2: Use the generated prompt to create an image with Stable Diffusion if generated_prompt: return generate_image_from_prompt(generated_prompt) else: raise ValueError("Failed to generate a prompt from the LinkedIn text.") iface = gr.Interface( fn=generate_image_from_linkedin_text, inputs=[gr.Textbox(label="LinkedIn Message", placeholder="Enter LinkedIn message here...")], outputs=gr.Image(type="pil"), title="Generate Images from LinkedIn Messages", description="Enter a LinkedIn message to generate a creative prompt with Zephyr, which is then used to generate an image with Stable Diffusion." ) iface.launch()