initial implementation for all questions

.gitignore

@@ -0,0 +1,2 @@
+venv/
+venv

app.py

@@ -0,0 +1,29 @@
+import gradio as gr
+from transformers import pipeline
+
+model = pipeline("question-answering", model="Eitanli/distilbert-qa-checkpoint-v3")
+
+
+questions = ['which ingredients are mentioned?',
+             'what is the amount of ingredient mentioned?',
+             'what are the special instructions mentioned?']
+
+
+def predict(context, topk, answer_threshold):
+    output = {}
+    for question in questions:
+        output['Question'] = question
+        answers = model(question=question, context=context, topk=topk)
+        output['Answer'] = '\n'.join([ans['answer'] for ans in answers if ans['score'] > answer_threshold])
+    return output
+
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Textbox(label="Recipe line"),
+        gr.Slider(0, 0.99, step=0.01, value=0.8, label="answer_threshold", info="Select a threshold in [0, 0.99]"),
+        gr.Slider(1, 5, step=1.0, value=2, label="top k", info="Choose between 1 and 5")],
+    outputs=gr.Textbox(label='Questions and answers')
+)
+iface.launch()

requirements.txt

@@ -0,0 +1,2 @@
+transformers==4.30.2
+torch>=2.0