app.py

import gradio as gr
import os
import json
import time
from dotenv import load_dotenv

from google import genai
from google.genai import types

# Import the optimized DINO functions
from dino_processor import load_dino_model, process_video_with_dino

# --- Configuration and Initialization ---
load_dotenv()
try:
    GEMINI_CLIENT = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
except KeyError:
    raise gr.Error("FATAL: GEMINI_API_KEY not found. Please set it in your Hugging Face Space secrets.")

DINO_MODEL, DINO_DEVICE = load_dino_model()

# --- Main Gradio Generator Function ---
def full_analysis(video_file_path, user_observations):
    if not video_file_path:
        yield "Please upload a video first.", "", "", None
        return

    # Stage 1: Gemini Analysis
    print("--- Starting Device Analysis ---")
    device_type, condition, reason = "Processing...", "Processing...", "Processing..."
    yield device_type, condition, reason, None

    uploaded_file = None
    try:
        uploaded_file = GEMINI_CLIENT.files.upload(file=video_file_path)
        while uploaded_file.state.name == "PROCESSING":
            time.sleep(5)
            uploaded_file = GEMINI_CLIENT.files.get(name=uploaded_file.name)
        if uploaded_file.state.name != "ACTIVE":
            raise Exception(f"File processing failed for Gemini. State: {uploaded_file.state.name}")
        
        prompt = f"""
        Analyze the provided video and user observations. Respond ONLY with a valid JSON object.
        User Observations: "{user_observations if user_observations else 'None'}"
        Logic:
        1. Is the object an electronic device or white good?
        2. If YES: respond with JSON keys "device_type", "condition" (from "unusable", "poor", "functional", "good", "excellent"), and "reason".
        3. If NO: respond with JSON key "device_type" starting with "Invalid: ".
        """
        model_name = "gemini-1.5-flash-latest" # Using a reliable public model
        config = types.GenerateContentConfig(temperature=0.2, response_mime_type="application/json")
        contents = [uploaded_file, prompt]
        response = GEMINI_CLIENT.models.generate_content(model=f"models/{model_name}", contents=contents, config=config)
        parsed_json = json.loads(response.text)
        device_type = parsed_json.get("device_type", "N/A")
        if "Invalid:" in device_type:
            condition, reason = "N/A", "Object is not a valid device."
        else:
            condition, reason = parsed_json.get("condition", "N/A"), parsed_json.get("reason", "N/A")
        print("--- Device Analysis Complete ---")
    except Exception as e:
        print(f"ERROR during Gemini processing: {e}")
        device_type, condition, reason = f"Error in Gemini processing: {e}", "", ""
    finally:
        if uploaded_file:
            GEMINI_CLIENT.files.delete(name=uploaded_file.name)

    yield device_type, condition, reason, None

    # Stage 2: DINO Analysis
    print("--- Starting DINO Analysis ---")
    try:
        # OPTIMIZATION: This now returns a simple list of overlay image paths
        overlay_images = process_video_with_dino(video_file_path, DINO_MODEL, DINO_DEVICE)
        print("--- DINO Analysis Complete ---")
    except Exception as e:
        print(f"ERROR during DINO processing: {e}")
        reason += f" | DINO Error: {e}"
        overlay_images = None

    # OPTIMIZATION: Final yield with only 4 items
    yield device_type, condition, reason, overlay_images

# --- Gradio Interface (Simplified) ---
theme = gr.themes.Soft(
    primary_hue="green", secondary_hue="emerald"
).set(
    body_background_fill="#E0F2F1", block_background_fill="white",
    block_border_width="1px", block_shadow="*shadow_drop_lg",
    button_primary_background_fill="*primary_500", button_primary_text_color="white",
)

with gr.Blocks(theme=theme) as demo:
    gr.Markdown("# 🧊 KIKERP: AI Assessment Tool")
    gr.Markdown("Upload a video of a device or white good for a complete visual and AI-driven analysis.")
    
    with gr.Row():
        with gr.Column(scale=1):
            video_input = gr.Video(label="Upload or Record Video", sources=["upload", "webcam"], format="mp4")
            observations_input = gr.Textbox(label="Optional: User Observations", placeholder="e.g., Device overheats...")
            submit_button = gr.Button("Run Full Analysis", variant="primary")
        
        with gr.Column(scale=2):
            gr.Markdown("## Device Condition Analysis")
            with gr.Row():
                device_type_output = gr.Textbox(label="Device Type", interactive=False)
                condition_output = gr.Textbox(label="Condition", interactive=False)
                reason_output = gr.Textbox(label="Reason / Details", interactive=False)
    
    gr.Markdown("---")
    
    # OPTIMIZATION: Simplified DINO output section
    gr.Markdown("## Overlayed Heatmaps on Key Frames")
    overlay_gallery = gr.Gallery(label="Overlayed Heatmaps", elem_id="gallery", columns=3)

    submit_button.click(
        fn=full_analysis,
        inputs=[video_input, observations_input],
        # OPTIMIZATION: Updated outputs list to have only 4 items
        outputs=[
            device_type_output, 
            condition_output, 
            reason_output, 
            overlay_gallery
        ],
        show_progress='full'
    )

demo.launch(debug=True)