application

Makefile

@@ -0,0 +1,22 @@
+install:
+	pip install --upgrade pip &&\
+		pip install -r requirements.txt
+
+test:
+	python -m pytest -vv --cov=main --cov=mylib test_*.py
+
+format:	
+	black *.py 
+
+lint:
+	pylint --disable=R,C --ignore-patterns=test_.*?py *.py mylib/*.py
+
+container-lint:
+	docker run --rm -i hadolint/hadolint < Dockerfile
+
+refactor: format lint
+
+deploy:
+	#deploy goes here
+		
+all: install lint test format deploy

README.md

@@ -1 +1,3 @@
-# MLOps-Practice-Repo-1
+# MLOps-Practice-Repo-1
+
+source ~/.venv/bin/activate

app.py

@@ -0,0 +1,15 @@
+from transformers import pipeline
+import gradio as gr
+
+model = pipeline("summarization")
+
+def predict(prompt):
+    summary = model(prompt)[0]['summary_text']
+    return summary
+
+with gr.Blocks() as demo:
+    textbox = gr.Textbox(placeholder="Enter text block to summarize", lines=4)
+
+output = gr.Interface(fn=predict, inputs=textbox, outputs="text", title="Text Summarizartion Demo with MLOps Techniques",)
+
+output.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+transformers
+tensorflow