main.py

import os
from uuid import uuid4
import uvicorn
from fastapi import FastAPI, UploadFile, File
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware
import aiofiles
import PyPDF2
from langchain_openai import ChatOpenAI
from langchain.schema import HumanMessage
import json
from fastapi.responses import FileResponse
from docx import Document

UPLOAD_FOLDER = "uploads"
os.makedirs(UPLOAD_FOLDER, exist_ok=True)

app = FastAPI()

# Enable CORS (you can restrict origins later)
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


llm = ChatOpenAI(
    model_name="gpt-4o-mini",  # Use a valid model name like "gpt-4o" or "gpt-4-turbo"
    temperature=0,
    openai_api_key=os.getenv("OPENAI_API_KEY")
)
    
def parse_resume_text(text: str) -> dict:
    prompt = f"""
    Extract structured information from this resume text and return the result in strict JSON format with the following keys:
    - basics: {{first_name, last_name, gender, emails, phone_numbers, address, total_experience_in_years, profession, summary, skills, has_driving_license}}
    - educations
    - professional_experiences
    - trainings_and_certifications
    - languages
    - awards
    - references
    - cv_text: {text}
    - cv_language: "en"
    Resume:
    {text}
    Return ONLY valid JSON, no text, no explanation.
    """
    result = llm([HumanMessage(content=prompt)])
    #return result.content
    raw_string = str(result.content).replace("```json\n", "").replace("\n```", "")
    final_data = json.loads(raw_string)
    return (json.dumps(final_data, indent=2))



# ✅ Save uploaded file asynchronously
async def save_file(file: UploadFile) -> str:
    filename = f"{uuid4()}_{file.filename}"
    file_path = os.path.join(UPLOAD_FOLDER, filename)
    async with aiofiles.open(file_path, 'wb') as out_file:
        content = await file.read()
        await out_file.write(content)
    return file_path

# ✅ Extract text from DOCX
def extract_text_from_docx(docx_path: str) -> str:
    try:
        doc = Document(docx_path)
        text = "\n".join([para.text for para in doc.paragraphs])
        return text.strip()
    except Exception as e:
        return f"Error extracting text from DOCX: {str(e)}"

# ✅ Extract text from PDF using PyPDF2
def extract_text_from_pdf(pdf_path: str) -> str:
    text = ""
    try:
        with open(pdf_path, "rb") as file:
            pdf_reader = PyPDF2.PdfReader(file)
            for page in pdf_reader.pages:
                page_text = page.extract_text()
                if page_text:
                    text += page_text + "\n"
        return text.strip()
    except Exception as e:
        return f"Error extracting text: {str(e)}"
        
@app.post("/parse-resume")
async def parse_resume(file: UploadFile = File(...)):
    try:
        print("🔄 Saving file...")
        path = await save_file(file)
        print(f"✅ File saved at {path}")

        print("📄 Extracting text...")
        ext = os.path.splitext(path)[-1].lower()
        if ext == ".pdf":
            text = extract_text_from_pdf(path)
        elif ext in [".docx", ".doc"]:
            text = extract_text_from_docx(path)
        else:
            os.remove(path)
            return JSONResponse(status_code=400, content={"error": "Unsupported file type"})

        print("✅ Text extracted.")
        json_result = parse_resume_text(text)
        
        os.remove(path)
        print("🧹 File removed.")

        filename = "cleaned_resume.json"
        file_path = os.path.join(UPLOAD_FOLDER, filename)
        with open(file_path, "w") as f:
            f.write(json_result)

        return FileResponse( path=file_path, filename=filename, media_type="application/json")
    
    except Exception as e:
        import traceback
        print("❌ Exception occurred:\n", traceback.format_exc())
        return JSONResponse(status_code=500, content={"error": str(e)})


@app.get("/")
async def root():
    return {"message": "Resume PDF Text Extractor is running 🎯"}

if __name__ == "__main__":
    uvicorn.run("main:app", host="0.0.0.0", port=7860, reload=True)