Added app.py, Dockerfile and requirements files

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:3.10.9
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["gunicorn", "-b", "0.0.0.0:7860", "-w", "4", "--threads", "2", "app:app"]

app.py

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+from flask import jsonify, Flask, request
+from flasgger import Swagger
+from llmware.models import ModelCatalog
+
+app = Flask(__name__)
+swagger = Swagger(app, config={'specs_route': '/swagger-ui'}, merge=True)
+
+
+@app.route('/', methods=['GET'])
+def test_concurrency():
+    import random
+    random_numbers = [random.randint(0, 100000) for _ in range(100)]
+    total_sum = sum(random_numbers)
+    print(f'Sum: {total_sum}')
+    return jsonify({'message': 'Welcome'}), 200
+
+
+@app.route('/slim-ner', methods=['POST'])
+def llmware_model():
+    """
+    # llmware/slim-ner model to identify named entities such as people, organization, and place
+    ---
+    description: llmware/slim-ner model to identify named entities such as people, organization, and places
+    produces:
+      - application/json
+    parameters:
+      - in: body
+        name: body
+        description: Input data
+        schema:
+          $ref: '#/definitions/model'
+    definitions:
+      model:
+        type: object
+        properties:
+          params:
+            type: array
+            items:
+              type: string
+            collectionFormat: multi
+          input:
+            type: string
+        example: {"params":["people","organization","place"],"input":"Yesterday, in Redmond, Satya Nadella announced that Microsoft would be launching a new AI strategy."}
+    responses:
+      '200':
+        description: Success
+        schema:
+          type: object
+          example: {"person": ["Satya Nadella"], "organization": ["Microsoft"], "place": ["Redmond"]}
+    """
+    data = request.get_json()
+    text = data['input']
+    slim_model = ModelCatalog().load_model('llmware/slim-ner')
+    response = slim_model.function_call(text, function='classify', params=data['params'])
+    print(f'Input: {text} \nResponse: {response}')
+    return jsonify(response['llm_response']), 200
+
+
+if __name__ == '__main__':
+    app.run(debug=True, host='0.0.0.0', port=7860)

requirements.txt

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+Flask~=3.0.3
+flasgger~=0.9.7.1
+gunicorn~=22.0.0
+llmware==0.2.10