app.py

import gradio as gr
import os
import base64
from groq import Groq
from PIL import Image
import io

# 1. Setup Groq Client (Ensure GROQ_API_KEY is in Space Secrets)
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))

# 2. Function to convert PIL image to Base64
def encode_image(image):
    buffered = io.BytesIO()
    image.save(buffered, format="JPEG")
    return base64.b64encode(buffered.getvalue()).decode('utf-8')

# 3. Load and encode fixed reference images from the local folder
REF_PATHS = ["references/reference_1.jpeg", "references/reference_2.jpeg"]
FIXED_BASE64 = []
for path in REF_PATHS:
    if os.path.exists(path):
        img = Image.open(path).convert("RGB")
        FIXED_BASE64.append(encode_image(img))

def detect_covering(query_image):
    if query_image is None:
        return "Please upload an image."

    # Encode the user's query image
    query_b64 = encode_image(query_image)

    # Build the multi-image message content
    content = [{"type": "text", "text": "First two reference images show a green pole around the tree. Determine if the LAST image contains the SAME type of green pole. Answer ONLY YES or NO."}]
    
    # Add reference images to content
    for b64 in FIXED_BASE64:
        content.append({
            "type": "image_url",
            "image_url": {"url": f"data:image/jpeg;base64,{b64}"}
        })

    # Add the final query image
    content.append({
        "type": "image_url",
        "image_url": {"url": f"data:image/jpeg;base64,{query_b64}"}
    })

    # Call Groq API (Llama 3.2 Vision supports up to 5 images per request)
    completion = client.chat.completions.create(
        model="meta-llama/llama-4-scout-17b-16e-instruct",
        messages=[{"role": "user", "content": content}],
        temperature=0.0, # Keep output consistent
        max_tokens=10
    )
    
    return completion.choices[0].message.content.strip().upper()

# Gradio Interface
demo = gr.Interface(
    fn=detect_covering,
    inputs=gr.Image(type="pil", label="Upload Query Image"),
    outputs="text",
    title="Tree Guard Detector",
    description="Uses pre-set reference images from the repo to detect tree guards via Groq."
)

demo.launch()