app.py

import google.generativeai as genai
from pathlib import Path
import gradio as gr
from dotenv import load_dotenv
import os

# Load environment variables from a .env file
load_dotenv()

# Configure the GenerativeAI API key using the loaded environment variable
genai.configure(api_key=os.getenv("AIzaSyCsoOchC3kjG_N_A03VFN0IQ1pGuXC18Hw"))

# Set up the model configuration for text generation
generation_config = {
    "temperature": 0.4,
    "top_p": 1,
    "top_k": 32,
    "max_output_tokens": 4096,
}

# Define safety settings for content generation
safety_settings = [
    {"category": f"HARM_CATEGORY_{category}",
        "threshold": "BLOCK_MEDIUM_AND_ABOVE"}
    for category in ["HARASSMENT", "HATE_SPEECH", "SEXUALLY_EXPLICIT", "DANGEROUS_CONTENT"]
]

# Initialize the GenerativeModel with the specified model name, configuration, and safety settings
model = genai.GenerativeModel(
    model_name="gemini-pro-vision",
    generation_config=generation_config,
    safety_settings=safety_settings,
)
# Function to read image data from a file path


def read_image_data(file_path):
    image_path = Path(file_path)
    if not image_path.exists():
        raise FileNotFoundError(f"Could not find image: {image_path}")
    return {"mime_type": "image/jpeg", "data": image_path.read_bytes()}

# Function to generate a response based on a prompt and an image path


def generate_gemini_response(prompt, image_path):
    image_data = read_image_data(image_path)
    response = model.generate_content([prompt, image_data])
    return response.text


# Initial input prompt for the plant pathologist
input_prompt = """
As a highly skilled human orthopedic specialist, your expertise is indispensable in finding what the X-ray image says. You will be provided with information or X-ray samples, and your role involves conducting a detailed analysis to identify the specific issues, propose solutions, and offer recommendations.

**Analysis Guidelines:**

1. **Disease Identification:** Examine the provided information or samples to identify and characterize.

2. **Detailed Findings:** Provide in-depth findings on the nature, including affected parts, and potential causes.

3. **Next Steps:** Outline the recommended course of action for managing and controlling the identified defect. This may involve treatment options, preventive measures, or further investigations.

4. **Recommendations:** Offer informed recommendations for maintaining bone health, preventing future bone problems, and optimizing overall bone well-being.


**Disclaimer:**
*"Please note that the information provided is based on X- ray image and data analysis and should not replace professional doctor advice. Consult with qualified experts before implementing any strategies or treatments."*

Your role is pivotal in ensuring the health and productivity of humans. Proceed to analyze the provided information or samples, adhering to the structured 
"""

# Function to process uploaded files and generate a response


def process_uploaded_files(files):
    file_path = files[0].name if files else None
    response = generate_gemini_response(
        input_prompt, file_path) if file_path else None
    return file_path, response


# Gradio interface setup
with gr.Blocks() as demo:
    file_output = gr.Textbox()
    image_output = gr.Image()
    combined_output = [image_output, file_output]

    # Upload button for user to provide images
    upload_button = gr.UploadButton(
        "Click to Upload an Image",
        file_types=["image"],
        file_count="multiple",
    )
    # Set up the upload button to trigger the processing function
    upload_button.upload(process_uploaded_files,
                         upload_button, combined_output)

# Launch the Gradio interface with debug mode enabled
demo.launch(debug=True)