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import gradio as gr
import os
import sys
sys.path.append("/home/user/app") # Ensures Hugging Face looks in the correct place
from HuggingFaceHelper import HuggingFaceHelper
from AICoreAGIX_with_TB import AICoreAGIX
# Initialize AI Core for TB analysis
ai_core = AICoreAGIX()
# Initialize Hugging Face training helper
helper = HuggingFaceHelper(model_path="./merged_model")
def diagnose_tb(image_file, audio_file):
user_id = 1 # Placeholder user ID
result = ai_core.run_tb_diagnostics(image_file.name, audio_file.name, user_id)
return (
f"**TB Risk Level:** {result['tb_risk']}\n\n"
f"**Image Result:** {result['image_analysis']['result']} "
f"(Confidence: {result['image_analysis']['confidence']:.2f})\n\n"
f"**Audio Result:** {result['audio_analysis']['result']} "
f"(Confidence: {result['audio_analysis']['confidence']:.2f})\n\n"
f"**Ethical Analysis:** {result['ethical_analysis']}\n\n"
f"**Explanation:** {result['explanation']}\n\n"
f"**Shareable Link:** {result['shareable_link']}"
)
def upload_and_finetune(jsonl_file):
save_path = f"./training_data/{jsonl_file.name}"
os.makedirs("training_data", exist_ok=True)
with open(save_path, "wb") as f:
f.write(jsonl_file.read())
# Trigger fine-tuning
helper.dataset_path = save_path
helper.fine_tune(output_dir="./codette_finetuned")
return f"â
Fine-tuning complete! Model updated and stored."
def get_latest_model():
return "Download the latest fine-tuned Codriao model here: https://huggingface.co/Raiff1982/codriao-finetuned"
# Gradio UI
demo = gr.TabbedInterface(
[
gr.Interface(
fn=diagnose_tb,
inputs=[
gr.File(label="Upload TB Saliva Image"),
gr.File(label="Upload Cough Audio File (.wav)")
],
outputs="text",
title="Codriao TB Risk Analyzer",
description="Upload a microscopy image and cough audio to analyze TB risk with compassionate AI support."
),
gr.Interface(
fn=upload_and_finetune,
inputs=[gr.File(label="Upload JSONL Training Data")],
outputs="text",
title="Codriao Fine-Tuning Trainer",
description="Upload JSONL files to teach Codriao new knowledge."
),
gr.Interface(
fn=get_latest_model,
inputs=[],
outputs="text",
title="Download Codriao's Fine-Tuned Model"
)
],
title="Codriao AI System",
description="Train Codriao, run TB diagnostics, and download updated models."
)
if __name__ == "__main__":
demo.launch()
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