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from fastapi import FastAPI, File, UploadFile
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
from typing import List
from langchain_community.chat_models import ChatOpenAI
from utils import process_file_with_dedoc, extract_text_from_all_levels, generate_formatted_resume, \
generate_json_structured_resume
import shutil
import os
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
ALLOWED_EXTENSIONS = {"jpg", "jpeg", "png", "docx", "pdf", "html", "doc"}
def allowed_file(filename):
return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
@app.post("/parse_resume/")
async def parse_resume(files: List[UploadFile] = File(...)):
parsed_resumes = []
for uploaded_file in files:
if allowed_file(uploaded_file.filename):
chat_llm_text = ChatOpenAI(model='gpt-3.5-turbo', temperature=0.0)
chat_llm_json = ChatOpenAI(model='gpt-3.5-turbo', temperature=0.4)
if not os.path.exists("temp"):
os.makedirs("temp")
file_path = f"temp/{uploaded_file.filename}"
# Process the uploaded file asynchronously
text = await process_file_with_dedoc(uploaded_file)
text_f = await extract_text_from_all_levels(text)
# Generate parsed resume and parsed JSON resume asynchronously
parsed_resume = generate_formatted_resume(text_f, chat_llm_text)
parsed_json_resume = None
while parsed_json_resume is None:
# Execute your code to generate parsed_json_resume
parsed_json_resume = generate_json_structured_resume(text_f, chat_llm_json)
parsed_resumes.append({
"file_name": uploaded_file.filename,
"parsed_resume": parsed_resume,
"parsed_json_resume": parsed_json_resume
})
else:
return JSONResponse(status_code=400, content={
"message": "Invalid file type. Allowed file types are: jpg, jpeg, png, docx, pdf, html, doc"})
return parsed_resumes
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000) |