Create app.py

app.py

@@ -0,0 +1,137 @@
+from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi.responses import JSONResponse
+from fastapi.middleware.cors import CORSMiddleware 
+from fastapi import Request
+import joblib
+import PyPDF2
+import re
+import logging
+import tempfile
+import os
+
+app = FastAPI()
+
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+logging.basicConfig(level=logging.INFO)
+
+try:
+    model = joblib.load("react_classifier.joblib")
+except Exception as e:
+    logging.error(f"Erro ao carregar o modelo: {e}")
+    raise
+
+def clean_text(text):
+    text = text.lower()
+    text = re.sub(r'[^\w\s]', ' ', text)
+    text = re.sub(r'\s+', ' ', text)
+    return text.strip()
+
+def extract_text_from_pdf(file_path):
+    text = ""
+    try:
+        with open(file_path, 'rb') as f:
+            reader = PyPDF2.PdfReader(f)
+            for page in reader.pages:
+                page_text = page.extract_text()
+                if page_text:
+                    text += page_text + "\n"
+    except Exception as e:
+        raise Exception(f"Erro ao extrair texto do PDF: {e}")
+    return text
+
+def avaliar_candidato(
+    anosEstudoTecnologia: int,
+    tempoDesenvolvedor: int,
+    tempoExperiencia: int,
+    nivelIngles: int,
+    graduacao: int
+) -> dict:
+    score_estudo = anosEstudoTecnologia / 6
+    score_desenvolv = tempoDesenvolvedor / 6
+    score_experiencia = tempoExperiencia / 6
+    score_ingles = nivelIngles / 4
+    score_graduacao = graduacao / 7
+
+    peso_estudo = 0.15
+    peso_desenvolv = 0.2
+    peso_experiencia = 0.3
+    peso_ingles = 0.25
+    peso_graduacao = 0.1
+
+    score_final = (
+        score_estudo * peso_estudo +
+        score_desenvolv * peso_desenvolv +
+        score_experiencia * peso_experiencia +
+        score_ingles * peso_ingles +
+        score_graduacao * peso_graduacao
+    )
+
+    score_percentual = round(score_final * 100, 2)
+    aprovado = score_percentual >= 70.0
+
+    return {
+        "score": score_percentual,
+        "aprovado": aprovado
+    }
+
+
+@app.post("/classify")
+async def classify_resume(file: UploadFile = File(...)):
+    try:
+        suffix = os.path.splitext(file.filename)[-1]
+        with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp:
+            temp.write(await file.read())
+            temp_path = temp.name
+
+        raw_text = extract_text_from_pdf(temp_path)
+        cleaned = clean_text(raw_text)
+
+        proba = model.predict_proba([cleaned])[0]
+        prediction = model.predict([cleaned])[0]
+
+        result = {
+            "classificacao": "React Developer" if prediction == 1 else "Outra Área",
+            "probabilidade": f"{proba[1]*100:.2f}%",
+            "trecho_texto": cleaned[:500] + "..." if len(cleaned) > 500 else cleaned
+        }
+
+        return JSONResponse(content=result)
+
+    except Exception as e:
+        logging.error(f"Erro no processamento: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+    finally:
+        if 'temp_path' in locals() and os.path.exists(temp_path):
+            os.remove(temp_path)
+
+@app.post("/avaliar")
+async def avaliar_formulario(request: Request):
+    try:
+        data = await request.json()
+
+        resultado = avaliar_candidato(
+            anosEstudoTecnologia=int(data.get("anosEstudoTecnologia", 0)),
+            tempoDesenvolvedor=int(data.get("tempoDesenvolvedor", 0)),
+            tempoExperiencia=int(data.get("tempoExperiencia", 0)),
+            nivelIngles=int(data.get("nivelIngles", 0)),
+            graduacao=int(data.get("graduacao", 0))
+        )
+
+        return JSONResponse(
+            status_code=200,
+            content={
+                "avaliacao": "Aprovado" if resultado["aprovado"] else "Reprovado",
+                "score": resultado["score"]
+            }
+        )
+    except Exception as e:
+        logging.error(f"Erro na avaliação do formulário: {e}")
+        raise HTTPException(status_code=500, detail="Erro ao processar os dados.")