import gradio as gr
import os
import json
import time # We need this to wait
from dotenv import load_dotenv

# Your requested imports
from google import genai
from google.genai import types

# --- Configuration and Client Initialization ---
load_dotenv()

try:
    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.")

# --- Core Gradio Function ---

def analyze_device_condition(video_file_path):
    if not video_file_path:
        return "Please upload video", "", ""

    uploaded_file = None
    try:
        # 1. Upload the file
        print(f"Log: Uploading file: {video_file_path}...")
        uploaded_file = client.files.upload(file=video_file_path)
        print(f"Log: File upload initiated. File name: {uploaded_file.name}, State: {uploaded_file.state.name}")
        
        # 2. --- THIS IS THE CRITICAL POLLING LOOP ---
        #    Wait for the file to become ACTIVE.
        while uploaded_file.state.name == "PROCESSING":
            print("Log: File is processing, waiting 5 seconds...")
            time.sleep(5)
            # Get the latest status of the file.
            uploaded_file = client.files.get(name=uploaded_file.name)
            print(f"Log: Current file state: {uploaded_file.state.name}")

        # If the file failed processing, stop here.
        if uploaded_file.state.name != "ACTIVE":
            raise Exception(f"File processing failed. Final state: {uploaded_file.state.name}")
        # --- END OF CORRECTION ---
        
        print("Log: File is now ACTIVE and ready for use.")
        
        # 3. Prepare the prompt
        prompt = """
        Analyze the provided video. Respond ONLY with a valid JSON object with three keys:
        1. "device_type": A short string identifying the device.
        2. "condition": A single word: "Mint", "Excellent", "Good", "Fair", or "Poor".
        3. "reason": A brief string explaining the condition.
        """
        
        # 4. Use gemini-2.5-flash
        model_name = "gemini-2.5-flash"
        generate_content_config = types.GenerateContentConfig(
            temperature=0.2,
            response_mime_type="application/json"
        )
        
        # 5. Call the API with the now-active file
        contents = [uploaded_file, prompt]
        
        print(f"Log: Sending request to model: {model_name}...")
        response = client.models.generate_content(
            model=f"models/{model_name}",
            contents=contents,
            config=generate_content_config,
        )

        # 6. Parse the final JSON response
        parsed_json = json.loads(response.text)
        device_type = parsed_json.get("device_type", "N/A")
        condition = parsed_json.get("condition", "N/A")
        reason = parsed_json.get("reason", "N/A")

        return device_type, condition, reason

    except Exception as e:
        error_message = f"An error occurred: {e}"
        print(f"ERROR: {error_message}")
        return error_message, "", ""
    
    finally:
        # 7. Cleanup: Delete the file from Google's servers
        if uploaded_file:
            print(f"Log: Deleting uploaded file: {uploaded_file.name}")
            client.files.delete(name=uploaded_file.name)

# --- Gradio Interface ---
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 📱 Device Condition Analyzer")
    video_input = gr.Video(label="Upload or Record Video", sources=["upload", "webcam"], format="mp4")
    submit_button = gr.Button("Analyze Device", variant="primary")
    with gr.Row():
        device_type_output = gr.Textbox(label="Device Type")
        condition_output = gr.Textbox(label="Condition")
        reason_output = gr.Textbox(label="Reason / Details")

    submit_button.click(
        fn=analyze_device_condition,
        inputs=video_input,
        outputs=[device_type_output, condition_output, reason_output],
        show_progress='full'
    )

demo.launch(debug=True)