json

app.py

@@ -119,13 +119,14 @@ Give a score for the product. Format your response as a JSON object with \
 	print("***total_prompt:")
 	print(total_prompt)
 	response = get_completion(total_prompt)
-	gen_text = response["predictions"][0]["generated_text"]
-	return json.dumps(extract_json(gen_text, 3))
+	#gen_text = response["predictions"][0]["generated_text"]
+	#return json.dumps(extract_json(gen_text, 3))
+	return json.dumps(response)
 	#return json.dumps(response)
 
 #iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 #iface.launch()
 
 #iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Text to find entities", lines=2)], outputs=[gr.HighlightedText(label="Text with entities")], title="NER with dslim/bert-base-NER", description="Find entities using the `dslim/bert-base-NER` model under the hood!", allow_flagging="never", examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"])
-iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Elevator pitch", lines=3)], outputs="json")
+iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Elevator pitch", lines=3)], outputs="text")
 iface.launch()