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from fastapi import FastAPI, HTTPException
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from models import CVExtracted, InsertedText, JobAndCV, ClassificationResult, InsertedLink
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import os
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from io import BytesIO
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import extractor
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from datetime import datetime
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from PyPDF2 import PdfReader
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import requests
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import classificator
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os.environ['TRANSFORMERS_CACHE'] = '/transformers_cache'
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os.environ['HF_HOME'] = '/transformers_cache'
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app = FastAPI()
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@app.get("/", response_model=dict[str, str])
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def getall():
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return {"hello":"world"}
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@app.post("/ext", response_model=CVExtracted)
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async def extract(text: InsertedText):
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dictresult = extractor.predict(text.text)
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return CVExtracted(**dictresult)
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@app.post("/classify", response_model=ClassificationResult)
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async def classify(body:JobAndCV ):
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mininmal_start = 0
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maximal_end = 0
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positions = []
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userMajors = []
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if len(body.cv.experiences) > 0:
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mininmal_start = datetime.strptime(body.cv.experiences[0]['start'], "%Y-%m-%d").date() if body.cv.experiences[0].get('start') != None else datetime.today().date()
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maximal_end = datetime.strptime(body.cv.experiences[0]['end'], "%Y-%m-%d").date()
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for exp in body.cv.experiences:
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positions.append(exp['position'])
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if exp.get('end') == None:
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exp['end'] = datetime.today().strftime("%Y-%m-%d")
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if datetime.strptime(exp['start'], "%Y-%m-%d").date() < mininmal_start:
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mininmal_start = datetime.strptime(exp['start'], "%Y-%m-%d").date()
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if datetime.strptime(exp['end'], "%Y-%m-%d").date() > maximal_end:
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maximal_end = datetime.strptime(exp['end'], "%Y-%m-%d").date()
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else:
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mininmal_start = 0
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maximal_end = 0
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for edu in body.cv.educations:
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userMajors.append(edu['major'])
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yoe = (maximal_end - mininmal_start).days//365
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cv = {
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"experiences": str(body.cv.experiences),
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"positions": str(positions),
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"userMajors": str(userMajors),
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"skills": str(body.cv.skills),
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"yoe": yoe
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}
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job = {
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"jobDesc": body.job.jobDesc,
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"role": body.job.role,
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"majors": str(body.job.majors),
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"skills": str(body.job.skills),
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"minYoE": body.job.minYoE
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}
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results = classificator.predict(cv, job)
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return ClassificationResult(**results)
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@app.post("/cv", response_model=CVExtracted)
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async def extract(link: InsertedLink):
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response = requests.get(link.link)
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if response.status_code == 200:
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pdf_reader = PdfReader(BytesIO(response.content))
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number_of_pages = len(pdf_reader.pages)
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page = pdf_reader.pages[0]
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text = page.extract_text()
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for i in range(1, number_of_pages):
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text+= '\n' + pdf_reader.pages[i].extract_text()
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else:
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raise HTTPException(status_code=response.status_code, detail="File server error")
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dictresult = extractor.predict(text)
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return CVExtracted(**dictresult) |
