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Browse files- Dockerfile +18 -0
- app.py +21 -0
- model/.gitignore +0 -0
- model/resume_classifier.pkl +3 -0
- model/tfidf_vectorizer.pkl +3 -0
- requirements.txt +5 -0
- templates/index.html +17 -0
Dockerfile
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# Use official Python image
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FROM python:3.10-slim
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# Set working directory
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WORKDIR /app
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# Copy project files
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COPY . /app
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# Install dependencies
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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# Expose port 7860 (Hugging Face runs on this)
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EXPOSE 7860
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# Command to run your app
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CMD ["python", "app.py"]
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app.py
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from flask import Flask, render_template, request
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import joblib
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import os
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app = Flask(__name__)
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# Load models
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tfidf_vectorizer = joblib.load("model/tfidf_vectorizer.pkl")
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classifier = joblib.load("model/resume_classifier.pkl")
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@app.route("/", methods=["GET", "POST"])
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def home():
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prediction = None
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if request.method == "POST":
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resume_text = request.form["resume"]
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vectorized = tfidf_vectorizer.transform([resume_text])
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prediction = classifier.predict(vectorized)[0]
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return render_template("index.html", prediction=prediction)
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if __name__ == "__main__":
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app.run(host="0.0.0.0", port=7860)
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model/.gitignore
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File without changes
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model/resume_classifier.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:18c1a3c76533b101dd4957cc7f298193e71bc62022e63e3159fce64455718565
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size 1203647
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model/tfidf_vectorizer.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:adf8731a04beb2631164583d3ad5b56eaaadb7cc2905b386ccd7c50dfc14f387
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size 111516
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requirements.txt
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flask
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scikit-learn
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pandas
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joblib
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gunicorn
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templates/index.html
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<!DOCTYPE html>
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<html>
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<head>
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<title>ATS Resume Screening</title>
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</head>
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<body>
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<h2>ATS Resume Screening System</h2>
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<form method="post">
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<textarea name="resume" rows="10" cols="60" placeholder="Paste resume here"></textarea><br><br>
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<button type="submit">Predict Job Category</button>
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</form>
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{% if prediction %}
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<h3>Predicted Category: {{ prediction }}</h3>
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{% endif %}
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</body>
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</html>
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