app.py

 # app.py (runs on Hugging Face Spaces w/ Firebase Firestore)

import gradio as gr

from PIL import Image, ImageDraw, ImageFont

import hashlib

import requests

import firebase_admin

from firebase_admin import credentials, firestore

import os

from io import BytesIO



# 🔐 Firebase Setup (replace with your Firebase project credentials)

cred_json = {

  "type": "service_account",

  "project_id": "YOUR_PROJECT_ID",

  "private_key_id": "YOUR_KEY_ID",

  "private_key": "-----BEGIN PRIVATE KEY-----\\nYOUR_PRIVATE_KEY\\n-----END PRIVATE KEY-----\\n",

  "client_email": "[email protected]",

  "client_id": "your_client_id",

  "auth_uri": "https://accounts.google.com/o/oauth2/auth",

  "token_uri": "https://oauth2.googleapis.com/token",

  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",

  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/firebase-adminsdk-xxx%40your-project.iam.gserviceaccount.com"

}

if not firebase_admin._apps:

    cred = credentials.Certificate(cred_json)

    firebase_admin.initialize_app(cred)

db = firestore.client()



# 🤖 Hugging Face Emoji Gen

HF_TOKEN = os.getenv("HF_TOKEN", "")

HF_MODEL = "valhalla/emoji-diffusion"



def hf_generate_emoji(prompt):

    headers = {"Authorization": f"Bearer {HF_TOKEN}"}

    payload = {"inputs": prompt}

    response = requests.post(

        f"https://api-inference.huggingface.co/models/{HF_MODEL}",

        headers=headers,

        json=payload,

    )

    if response.status_code != 200:

        raise ValueError("Hugging Face API failed")

    return Image.open(BytesIO(response.content))



# 🎯 Fingerprint = hash of emoji image

def compute_fingerprint(img: Image.Image) -> str:

    gray = img.convert("L").resize((32, 32))

    return hashlib.sha256(gray.tobytes()).hexdigest()



# 🏷 Overlay micro-ad / sponsor

def embed_ad(img: Image.Image, tag: str) -> Image.Image:

    draw = ImageDraw.Draw(img)

    font = ImageFont.load_default()

    draw.text((img.width - 30, img.height - 12), tag[:3].upper(), fill="yellow", font=font)

    return img



# 🧠 Full pipeline: gen → fingerprint → save to Firestore

def process(prompt, sponsor=""):

    img = hf_generate_emoji(prompt).resize((128,128))

    if sponsor:

        img = embed_ad(img, sponsor)

    fingerprint = compute_fingerprint(img)



    doc_ref = db.collection("emojis").document(fingerprint)

    doc = doc_ref.get()

    if not doc.exists:

        doc_ref.set({

            "prompt": prompt,

            "sponsor": sponsor,

            "usage": 0,

        })



    return img, fingerprint



# 🔁 Increment emoji usage count

def use_emoji(fp):

    doc_ref = db.collection("emojis").document(fp)

    doc = doc_ref.get()

    if doc.exists:

        new_usage = doc.to_dict()["usage"] + 1

        doc_ref.update({"usage": new_usage})

        return f"Usage count updated: {new_usage}"

    return "Emoji not found"



# 🎛 Gradio App

with gr.Blocks() as demo:

    gr.Markdown("# 🧬 Emoji Factory: Generate, Track & Embed Micro-Ads")



    with gr.Row():

        prompt = gr.Textbox(label="Enter your idea prompt (e.g. pig vault rocket)")

        sponsor = gr.Textbox(label="Sponsor / Ad Tag (optional)")

    gen_btn = gr.Button("🚀 Generate Emoji")

    emoji_out = gr.Image(label="Generated Emoji")

    fp_out = gr.Textbox(label="Emoji Fingerprint")

    use_btn = gr.Button("🔁 Use Emoji")

    result = gr.Textbox(label="Usage Count / Message")



    gen_btn.click(fn=process, inputs=[prompt, sponsor], outputs=[emoji_out, fp_out])

    use_btn.click(fn=use_emoji, inputs=[fp_out], outputs=[result])



demo.launch()