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Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+RUN wget https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf/resolve/main/Phi-3-mini-4k-instruct-q4.gguf
+
+Run git clone "https://huggingface.co/sentence-transformers/paraphrase-TinyBERT-L6-v2"
+
+RUN mkdir /.cache
+
+RUN chmod 777 /.cache
+
+# RUN mkdir /.cache/huggingface
+
+# RUN mkdir /.cache/huggingface/hub
+
+# RUN mkdir /.cache/huggingface/hub/models--sentence-transformers--paraphrase-TinyBERT-L6-v2
+
+# RUN mkdir /.cache/huggingface/hub/models--sentence-transformers--paraphrase-TinyBERT-L6-v2/blobs
+
+# RUN mkdir /.cache/huggingface/hub/models--sentence-transformers--paraphrase-TinyBERT-L6-v2/snapshots
+
+COPY . .
+
+CMD ["gunicorn", "-b", "0.0.0.0:7860", "--timeout", "300", "main:app"]

README.md

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+---
+title: Cv
+emoji: 🚀
+colorFrom: blue
+colorTo: red
+sdk: docker
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

gitattributes

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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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main.py

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+from flask import Flask, request, jsonify
+from langchain_community.llms import LlamaCpp
+from sentence_transformers import SentenceTransformer
+from transformers import AutoModel
+import torch
+from torch.nn.functional import cosine_similarity
+import os 
+
+app = Flask(__name__)
+
+n_gpu_layers = 0
+n_batch = 1024
+
+llm = LlamaCpp(
+    model_path="Phi-3-mini-4k-instruct-q4.gguf",  # path to GGUF file
+    temperature=0.1,
+    n_gpu_layers=n_gpu_layers,
+    n_batch=n_batch,
+    verbose=True,
+    n_ctx=4096
+)
+model0 = AutoModel.from_pretrained('sentence-transformers/paraphrase-TinyBERT-L6-v2')
+
+model = SentenceTransformer('sentence-transformers/paraphrase-TinyBERT-L6-v2')
+
+file_size = os.stat('Phi-3-mini-4k-instruct-q4.gguf')
+print("model size ====> :", file_size.st_size, "bytes")
+
+
+@app.route('/cv', methods=['POST'])
+def get_skills():
+    cv_body = request.json.get('cv_body')
+
+    # Simple inference example
+    output = llm(
+        f"<|user|>\n{cv_body}<|end|>\n<|assistant|>Can you list the skills mentioned in the CV?<|end|>",
+        max_tokens=256,  # Generate up to 256 tokens
+        stop=["<|end|>"], 
+        echo=True,  # Whether to echo the prompt
+    )
+
+    return jsonify({'skills': output})
+
+@app.get('/')
+def health():
+    return jsonify({'status': 'Worked'})
+
+@app.route('/compare', methods=['POST'])
+def compare():
+    employee_skills = request.json.get('employee_skills')
+    jobs_skills = request.json.get('jobs_skills')
+
+    # Validation
+    if not isinstance(jobs_skills, list) or not all(isinstance(skill, str) for skill in jobs_skills):
+        raise ValueError("jobs_skills must be a list of strings")
+
+    # Encoding skills into embeddings
+    job_embeddings = model.encode(jobs_skills)
+    employee_embeddings = model.encode(employee_skills)
+
+    # Computing cosine similarity between employee skills and each job
+    similarity_scores = []
+    employee_embeddings_tensor = torch.from_numpy(employee_embeddings).unsqueeze(0)
+
+    for i, job_e in enumerate(job_embeddings):
+        job_e_tensor = torch.from_numpy(job_e).unsqueeze(0)
+        similarity_score = cosine_similarity(employee_embeddings_tensor, job_e_tensor, dim=1)
+        similarity_scores.append({"job": jobs_skills[i], "similarity_score": similarity_score.item()})
+
+    return jsonify(similarity_scores)
+
+
+if __name__ == '__main__':
+    app.run()

main.yml

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+name: Python application
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python 3.x
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.x'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: Run the app
+      run: python app.py

requirements.txt

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+flask
+langchain
+matplotlib
+numpy
+gensim
+scikit-learn
+llama-cpp-python
+huggingface_hub==0.23.0
+langchain
+langchain-experimental
+scipy==1.10.1
+gunicorn
+langchain-community
+sentence-transformers
+torch
+transformers