Update app.py

app.py

@@ -1,5 +1,7 @@
-from fastapi import FastAPI, HTTPException, UploadFile, File
 import pandas as pd
+import tempfile
+import json
+import gradio as gr
 from resume_extractor import ResumeExtractor
 from job_description_extractor import JobDescriptionExtractor
 from model_trainer import ModelTrainer
@@ -11,8 +13,6 @@ from comparison_utils import (
 )
 from synthetic_data import create_synthetic_data
 
-app = FastAPI()
-
 def main(resume_text, job_description):
     openai_api_key = 'sk-proj-bC6H6QrP6DUqHkn5vOkYT3BlbkFJsSyvL4Bc9c3UEbHrsPMj'
     ner_model_name_or_path = "NLPclass/Named-entity-recognition"
@@ -59,17 +59,26 @@ def main(resume_text, job_description):
         "predicted_target": predicted_target[0]
     }
 
-@app.post("/extract")
-async def extract(resume_file: UploadFile = File(...), job_description_file: UploadFile = File(...)):
+def process_files(resume_file, job_description_file):
     try:
-        resume_text = await resume_file.read()
-        job_description = await job_description_file.read()
-        
-        # Convert bytes to string
-        resume_text = resume_text.decode('utf-8')
-        job_description = job_description.decode('utf-8')
+        resume_text = resume_file.read().decode('utf-8')
+        job_description = job_description_file.read().decode('utf-8')
         
         output = main(resume_text, job_description)
-        return output
+        
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".json", mode='w', encoding='utf-8') as tmp_file:
+            json.dump(output, tmp_file, ensure_ascii=False, indent=4)
+            return tmp_file.name
     except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
+        return {"error": str(e)}
+
+iface = gr.Interface(
+    fn=process_files,
+    inputs=[gr.File(label="رزومه (فایل .txt)"), gr.File(label="توضیحات شغل (فایل .txt)")],
+    outputs=gr.File(label="دانلود فایل JSON"),
+    title="پردازش رزومه و توضیحات شغلی",
+    description="این ابزار رزومه و توضیحات شغلی شما را پردازش کرده و امتیازات مشابهت را محاسبه می‌کند."
+)
+
+if __name__ == "__main__":
+    iface.launch()